PETER N.ROSENWEG BA, Grad Dip Couns
DISSERTATION
Evaluation of a self-regulating skill
for rapid attention recovery (rART).
Submitted to Swinburne Higher Degree Research
In fulfillment of the requirements for the degree of
Doctor of Philosophy
Swinburne University of Technology
Faculty of Science, Engineering and Technology
August 2018
Men ought to know that from the brain and from
the brain only arise our pleasures, joys,
laughter, and jests as well as our sorrows pains
griefs and tears.
It is the same thing which makes us mad or
delirious, inspires us with dread and fear,
whether by night or by day, brings
sleeplessness, inopportune mistakes, aimless
anxieties, absent mindedness and acts that are
contrary to habit.
Hippocrates (c. 400 B.C) The Sacred Disease
Declaration
I declare that no material has been included herein that has been accepted for the award of any
other degree or diploma, except where due reference is made in the text of the examinable
outcome.
To the best of my knowledge the submitted thesis contains no material previously published or
written by another person except where due reference is made in the text of the examinable
outcome.
This thesis is not work based on joint research or publications or that of other authors.
Peter N.Rosenweg
Acknowledgements
With much appreciation for their endless effort and insight by
Dr Mark Schier
Dr Peter Higgins
Group Captain Doug Edwards RAAF (Ret)
Dr Janice Langan-Fox
Table of Contents
Declaration ................................................................................................... iii
Acknowledgements .......................................................................................iv
Tables: .............................................................................................................i
Abbreviations & Glossary ........................................................................... vii
ABSTRACT ..................................................................................................................... I
OUTLINE OF THE THESIS ......................................................................................... I
LIST OF CHAPTERS ....................................................................................................II
1. INTRODUCTION ....................................................................................................... 1
Where is the risk? ........................................................................................... 1
1.2 The extent of human error ........................................................................ 2
2. ATTENTION & SELF REGULATION ................................................................. 10
2.1 Introduction to Attention ........................................................................ 10
2.2 Models and limitations of attention ........................................................ 10
2.3 Capacity Models: .................................................................................... 11
2.4 Bottleneck models: ................................................................................. 12
2.5 Attentional Networks. ............................................................................. 13
2.6 Arousal and performance........................................................................ 14
2.7 Attention switching and multitasking ..................................................... 18
2.8 Brain State and Mental State .................................................................. 19
2.9 Mental State and Unsafe Behaviour ....................................................... 21
2.10 Cognitive resilience and mental state ................................................... 23
2.11 Cognitive resilience and performance .................................................. 24
2.12 Cognitive resilience and prospective memory...................................... 25
2.13 Attention in situation awareness ........................................................... 26
2.14 Self-regulation Absent in NOTECH Training ...................................... 28
2.15 Self-regulation Absent in Simulator Training ...................................... 31
2.16 Self-regulation Absent in Profiling ...................................................... 31
2.17 Is it Possible to Measure the Right Stuff? ............................................ 32
2.18 NEO Personality Profile & the PCI ...................................................... 34
2.19 Capability and mental state .................................................................. 35
2.20 The Pilot’s Perception of cognitive demand......................................... 37
2.21 Cognitive Load and Experience ........................................................... 39
2.22 Complacency and awareness ................................................................ 40
2.23 Automation a Reverse Problem ............................................................ 41
2.24 Necessity to manage the self ................................................................ 43
2.25 Summary of Need for self-regulation training ..................................... 46
2.26 Aim of the Study .................................................................................. 47
3. SELF-REGULATION TRAINING ......................................................................... 48
3.1 Self-Regulation and Self Control ........................................................... 48
3.2 Behavioural markers of Self-Regulation ................................................ 51
3.3 Methodological Issues in Evaluating Self-Regulation ........................... 51
3.4 Comparison of Effect Size by Training Methods ................................... 53
3.5 Conventional Training Approaches ........................................................ 53
3.6 Behavioural Operant and Cued Techniques ........................................... 55
3.7 Metacognitive Self-Regulation Techniques ........................................... 56
3.8 Cognitive Behavioural methods ............................................................. 57
3.9 Self-regulation through Mindfulness ...................................................... 59
3.10 CB Methods and Counselling ............................................................... 60
3.11 Self-Regulation Techniques ................................................................. 61
4. PSYCHOPHYSIOLOGY OF ATTENTION .......................................................... 63
4.1 Introduction ............................................................................................ 63
4.2 Energy and Mental Effort ....................................................................... 64
4.3 Mental Energy & Fatigue ....................................................................... 66
4.4 Methods of Arousal ................................................................................ 67
4.5 Nasal olfactory action and the sniff ........................................................ 70
4.6 The Sniff as an Analogy of the Startle ................................................... 71
4.7 The Role of the Amygdala in Rapidly Cued Attention .......................... 72
4.8 The Breathing mechanism ...................................................................... 74
4.9 Measured Breathing and Mental State ................................................... 75
4.10 Operant Learning .................................................................................. 77
5.0 METHODOLOGY .................................................................................................. 79
5.1 Introduction ............................................................................................ 79
5.2 Research Design ..................................................................................... 79
5.3 A Technique to Achieve Attention Recovery......................................... 80
5.4 Issues in Delivering Online Training...................................................... 81
5.5 Unsupervised Baseline Testing .............................................................. 83
5.6 The Research Hypothesis ....................................................................... 85
Hypothesis 1 ................................................................................................. 85
Hypothesis 2 ................................................................................................. 85
Hypothesis 3 ................................................................................................. 85
Hypothesis 4 ................................................................................................. 85
5.7 Overall Structure of the Study ................................................................ 85
5.8 The Study Development Group .............................................................. 86
5.9 Criteria and Development of the Test Instruments ................................. 87
5.10 Baseline test development .................................................................... 87
5.11 Development of the baseline test .......................................................... 90
5.12 The Attention Recovery Demonstration Video .................................... 91
5.13 The Aviation Student Groups ............................................................... 91
5.14 The Rapid Attention Recovery Instruction Set..................................... 93
5.15 Data Collection ..................................................................................... 94
5.16 Statistical procedures. ........................................................................... 95
6. RESULTS ................................................................................................................... 97
6.1 Introduction ............................................................................................ 97
6.2 Hypothesis .............................................................................................. 98
6.3 Demographics of the baseline test development group .......................... 98
6.4 Overview of Experimental Group Study Participation......................... 100
6.5 Experimental Group - Enrolment, Retention & Performance .............. 103
6.6 Experimental Group Compliance with Instructions ............................. 104
6.7 Perception of Workload Strain ............................................................. 108
6.8 Experimental group baseline test performance by Gender ................... 111
6.9 Sample Bias and Generalisability of results ......................................... 113
6.10 Results for Hypothesis 1. Fatigue affects Behaviour ........................ 113
6.11 Results for Hypothesis 2 - Self-regulation predicts rART usage ...... 116
6.12 Results for Hypothesis 3. Self-regulation predicts course completion .................................................................................................................... 120
6.13 Results for Hypothesis 4 - More aviation students complete the course .................................................................................................................... 122
Analysis of variance for mental alertness. .................................................. 124
6.14 Contribution of Gender to the study. .................................................. 127
6.15 Gender bias in task completion .......................................................... 132
6.16 Efficacy of the rapid ART Technique by gender ............................... 132
7. DISCUSSION ........................................................................................................... 133
Introduction ................................................................................................ 133
Study Objectives ......................................................................................... 133
The Study Background ............................................................................... 134
What difference was sought ....................................................................... 137
Study Outcomes .......................................................................................... 138
Control Group ............................................................................................. 138
Participant behaviour .................................................................................. 141
Study methodology and issues ................................................................... 143
Future Directions ........................................................................................ 145
8.0.0 REFERENCES .................................................................................................. 146
APPENDICES .............................................................................................................. 164
Appendix A: Test Development Statistics ................................................ 164
Appendix B. Detail of the Online Questionnaire ....................................... 167
Appendix C: Rapid ART Instruction ......................................................... 175
Appendix D. Ethics Clearance................................................................. 176
Appendix E. Call for Volunteers ................................................................ 177
Tables:
Table 1.1. Ratio of fatalities per incidents by industry ........................................................ 12
Table 2.1 Executive functions and self-regulatory mechanisms .......................................... 21
Table 2.2 Incident types classified in the SA model ............................................................ 27
Table 3.1 Comparison of mean effect size by training methods .......................................... 48
Table 3.2 Utility of four self-regulation training methods ................................................... 55
Table 5.1 Scale Measures Associated with Behavioural markers ........................................ 78
Table 5.1 Scale Measures Derived for Behavioural markers ........................................... 79.
Table 5.3 Development group baseline test statistics .......................................................... 80
Table 5.2 Baseline test scale definitions ..................................................................................
Table 6.1 Aviation experience development group benchmark test .................................... 88
Table 6.2 Initial development group baseline test statistics ............................................... 89
Table 6.3 Re-test performance development group baseline test ........................................ 89
Table. 6.4. Demographics by study completion and departure rates ................................... 90
Table 6.5 Aviation experience by age and gender completing the study ............................. 91
Table 6.6 Demographics of early terminations experimental group .................................... 92
Table 6. 7 Time and days on course by age and completion status ..................................... 93
Table. 6.8 Hours elapsed between log-ins and sessions - all participants ........................... 94
Table 6.9 Source of Perceived Workload Strain (PWS) by total sample ............................. 96
Table 6.10 Perceived workload strain for the completion group ......................................... 96
Table 6.11 Perceived Workload Strain one-sample test ...................................................... 97
Table 6.12 Experimental group baseline test means by Gender .......................................... 99
Table 6.13 VIF for Mental Alertness and Fatigue Management ....................................... 100
Table 6.14 Regression predicting Fatigue Management on Mental Alertness and Perceived
Workload Strain ......................................................................................................... 101
Table 6.15 VIF for Mental Alertness and Management of Fatigue ................................... 102
Table 6.16 Regression predicting Perceived rART Efficacy on Mental Alertness and Fatigue
Management ............................................................................................................... 103
Table 6.17 VIF for Mental Alertness and Fatigue Management ....................................... 104
Table 6.18 Regression predicting Perceived Ease of rART Method on Mental Alertness and
Fatigue Management .................................................................................................. 105
Table 6.19 VIF for Mental Alertness and Fatigue Management ....................................... 106
Table 6.20 Regression predicting Completion by Mental Alertness and Fatigue Management
.................................................................................................................................... 107
Table 6.20 Independent Samples t-Test for pilot experience by completion ..................... 108
Table 6.21 Analysis of Variance for Fatigue Management by Flying Experience ............ 110
Table 6.22 Descriptive statistics for Mental Alertness by Pilot Experience ...................... 110
Table 6.23 Analysis of variance for Fatigue Management by Pilot Experience ................ 111
Table 6.24 Descriptive statistics Fatigue Management by Pilot Experience .................. 111
Table 6.24 VIF for Gender, Mental Alertness, Workload Strain and Fatigue Management
.................................................................................................................................... 112
Table 6.25 Regression predicting Completion on Gender, Mental Alertness, and Fatigue
Management ....................................................................................................................... 113
Table 6.26 VIF for Gender, Mental Alertness, Fatigue Management, and Perceived
Workload Strain ......................................................................................................... 114
Table 6.27 Regression predicting Cognitive Performance on Gender, Mental Alertness,
Fatigue Management, and Perceived Workload Strain. ............................................. 115
Table A1. Statistics - Baseline test-retest administration ................................................. 145
Table A2. Comparison of development group baseline retest scores time 2 with time 1 . 145
Table A3 Summary - Development group baseline test scale reliabilities and item statistics
.................................................................................................................................... 145
Table. A6. Study completion rates, age & gender by session for 221 enrolled participants
.................................................................................................................................... 146
Table B1. Online questionnaire and presentation order ..................................................... 147
Table B.2 Preliminary literacy Test conducted at start of the baseline survey .................. 152
Table B2. Study Survey Reading Grade .......................................................................... 152
Table B3. Flesch-Kincaid Formulae Grade Levels ........................................................... 152
Table B3 Perception of stress and coping with the TLX ................................................... 153
Table B.4 Fatigue Management & Alertness Baseline Questions ..................................... 154
Table B.5 Functional performance test questions. ............................................................. 155
Table of Figures
Figure 1.1 The Swiss Cheese Model by Reason .................................................................. 10
Figure: 1.2 From technical to human causes Source: .......................................................... 11
Figure 2.1 Yerkes-Dodson Law of arousal and performance .............................................. 14
Figure 2.2 Capacity model for attention .............................................................................. 15
Figure 2.3 Wickens model of attention. ............................................................................... 16
Figure 2.3 Tang et al, 2015 process of mindfulness meditation .......................................... 23
Figure 2.4 Relationship of cognitive failure to incident rates .............................................. 24
Figure 3.1 Hierarchy of Performance dependencies and behaviours ................................... 47
Figure 4.1 Behavioural dependencies and identified attributes ........................................... 56
Figure 4.2 The Olfactory Pathway ....................................................................................... 62
Figure 4.3 Path of Nasal Air ................................................................................................ 64
Figure 4.4 Proposed Cued recall of mental state to improve attention ................................ 68
Figure 5.1 The Rapid Attention Recovery Instruction Set ................................................... 82
Figure 6.1 Study login times by course completion status. .................................................. 93
Figure 6.2 Comparison of elapsed log-in times between sessions. ...................................... 94
Figure 6.3 Perceived source of workload strain – completion group .................................. 97
Figure 6.4 Gender by coping with perceived workload strain ............................................. 98
Figure 6.5 Experimental Group total test results by gender ................................................. 99
Figure 6.6 Q-Q scatterplot for normality for Mental Alertness and Perceived Workload
Strain predicting Fatigue Management. ..................................................................... 101
Figure 6.7 Residuals scatterplot for homoscedasticity of Mental Alertness and Perceived
Workload Strain predicting Fatigue Management. .................................................... 101
Figure 6.8 Q-Q scatterplot for normality for Mental Alertness and Fatigue Management
predicting Perceived rART Efficacy .......................................................................... 103
Figure 6.9. Residuals scatterplot for homoscedasticity for Mental Alertness and Management
of Fatigue predicting Perceived rART Efficacy ......................................................... 103
Figure 6.10 Q-Q scatterplot for normality for Mental Alertness and Fatigue Management
predicting Perceived Ease of rART Method .............................................................. 105
Figure 6.11 Residuals scatterplot for homoscedasticity for Mental Alertness and Fatigue
Management predicting Perceived Ease of rART Method ........................................ 105
Figure 6.12 Q-Q scatterplot for normality for Mental Alertness and Fatigue Management
predicting Rate of Completion ................................................................................... 107
Figure 6.13 Residuals scatterplot for homoscedasticity for Mental Alertness and Fatigue
Management predicting Rate of Completion ............................................................. 107
Figure 6.14 Means of Rate of Completion by Pilot Experience. ....................................... 109
Figure 6.15 Q-Q scatterplot for normality for Gender, Mental Alertness, Perceived Workload
Strain, and Fatigue Management predicting Rate of Completion .............................. 112
Figure 6.16 Residuals scatterplot for homoscedasticity for Gender, Mental Alertness,
Perceived Workload Strain, and Fatigue Management predicting Rate of Completion
.................................................................................................................................... 112
Figure 6.17. Q-Q scatterplot for normality for Gender, Mental Alertness, Fatigue
Management, and Perceived Workload Strain predicting Overall Cognitive
Performance ............................................................................................................... 114
Figure 6.18. Residuals scatterplot for homoscedasticity for Gender, Mental Alertness,
Fatigue Management, and Perceived Workload Strain predicting Overall Cognitive
Performance ............................................................................................................... 114
Figure: 6.19 Total Group Report of RART Efficacy ......................................................... 115
Figure: 6.20 Efficacy of rART by Gender ......................................................................... 116
Figure C0.1. Video: Actor with voice over demonstrating the 4-step rapid ART technique
.................................................................................................................................... 156
Figure C1. Online demonstration of the 4-step procedure ................................................. 156
Abbreviations & Glossary
:
ABS Australian Bureau of Statistics ART Attention Restoration Technique AST Attention state training AT Attention training CB Cognitive Behavioural methods (therapy & training) CPL Commercial pilot license CR Cognitive Resilience CRM Crew Resource Management DSMIV Diagnostic & Statistical Manual of Mental Disorders 4th Ed GA General aviation HF Human Factors ICAO International Civil Aviation Organisation IMT Integrated mindfulness training IRR Inter rater reliability IST MBSR
Item Sum Total method Mindfulness Based Stress Reduction
MPL Multicrew Pilot license MT Mindfulness training NOTECH Non-technical skills PPL Private pilot license PTSD Post-traumatic stress disorder PWS Perceived workload strain rART Rapid attention recovery technique SA Situational awareness SAGAT Situation Awareness Global Assessment Technique SR Self-regulation STOM Strategic task overload model TCIF Applied Task Analysis and Task Complexity in Flight’ TEM Threat and error management TLX Task Load Index NASA TLX
ABSTRACT
Loss of attention, perception and judgement is frequently cited as contributing to deficient
performance and adverse incidents in safety-critical industries, such as aviation, transport,
healthcare and in the formative domains of education and training. External cueing,
instructional, chemical, cognitive behavioural and mindfulness techniques have been
extensively researched to improve performance of attention through self-regulation of mental
state. However, there has been no research to date into a context independent, self-initiated,
rapid attention recovery technique (rART), to augment self-regulating skills that can be
invoked to recover attention at the instant of demand. Undergraduate students from an
Australian University volunteered to learn an efficient mental enhancement technique in an
unsupervised online tuition of a self-regulating skill. After completing the self-regulation
baseline test participants were instructed to log in online and complete a 10-minute video-
assisted exercise each night immediately prior to sleep, for ten sessions. Outcome measures
of retention and compliance were the evidence for success. A final self-report of the
utilisation of the rART technique outside of the study provided a qualitative dimension to the
data. Attrition of the 220 enrolled participants resulted in 32% (n=70) completing the
benchmark measures with 46 completing the whole course. Results included Self reports of
the efficacy of the rART for those completing the course with a mean of 65%, slightly higher
for females than males, but found to be overall independent of the baseline test in predicting
success. The contrasting groups of aviation and general students were near equal on course
retention and on self-reports of perceived efficacy of the rART method. A significant
difference was found in measured indicators of self-regulating behaviours between aviation
and general student groups with respect to mental-state (alertness) and fatigue management.
Results showed that participant self-regulation of mental alertness and management of
fatigue correlated with reports of coping with workload strain. However, neither measure
predicted completion of the online course. Completion of the course together with reported
efficacy outside of the nightly course suggests the completion group had effectively utilised
the rART in the study. Compliance with study protocols was found to be consistent with
requirements whereas the partially completed respondents were widely inconsistent in their
application. Due to the negation of the control group the rART training and effect was not
clearly established in this study.
Keywords: Attention, resilience, self-regulation, situation awareness, performance, cognitive failure, respiration, human
factors, cued recall, fatigue countermeasures, startle reflex, mental state, coping skills, aviation, healthcare.
i
Outline of the thesis
This research explores a self-regulating skill involving a rapid attention recovery
mechanism evolving from the compelling need for the maintenance of alertness and
responsiveness that confront individuals in safety critical industries. Secondly, this
experiment involved the online delivery and assessment of the rART technique as a self-
regulating skill for attention recovery with a sample of aviation student pilots and non-
aviation students.
The pursuit of an understanding of how to improve cognition under stress continues to
generate vigorous research and debate into almost all facets of attention and self-regulation.
Tang and Posner (2009) had emphasised the differences between attention training (AT)
obtained with mental exercises and attention state training (AST) achieved by mindfulness,
which addresses and coordinates a much wider range of self-regulating elements involving
both the central and autonomic nervous system. However, the utility of present AST
methods is problematic in occupations in which action and response are time critical and
subject to uncertainty of retrieval of the preferred mental-state under competing demands.
There is an absence of research focused on self-initiated, context independent mechanisms to
instantly recover and free mental resources when overloaded, disturbed or emotionally sensitive
for those with a pre-existing condition, when under threat, fatigue or increased mental load. The
speed of automatic behaviours surrounding natural defensive responses such as the ‘startle
response’ prompted the adaptation of an existing ‘normal psychophysiological mechanism’ as
a technique to recover attention and full cognitive functioning at the instant of demand when no
anticipation or preparation time is possible.
ii
List of Chapters
Chapter 1 INTRODUCTION
details the contribution and size of the risk that human errors and non-compliance have in
perpetuating adverse events in safety critical industries and driving the search for a rapid
universal remedy. Student pilots were chosen as the critical occupational model.
Chapter 2 ATTENTION & SELF-REGULATION discusses attention in the context of self-
regulation, differentiates mental-state and brain-state on mental and task switching, fatigue
and resilience. Assembles and synthesises behavioural markers that address hazardous
performance and mental states,
Chapter 3 SELF-REGULATION TRAINING Discusses models of attention as the basis for
self-regulation. Compares the efficacy of conventional and metacognitive methods for the
temporary recovery from fatigue and degrade of cognitive performance through four
mainstream options to training in the achievement of self-regulating behaviours.
Chapter 4 PSYCHOPHYSIOLOGY OF ATTENTION Discusses the psychophysiological
connection between the olfactory sniff and attention. Outlines the respiratory process and
probable neurological sequences that activate changes in mental state.
Chapter 5 METHODOLOGY discusses the recruitment of participants, research design, and
online training delivery methodology. The construction of the initial benchmark test with
an independent development depicting behavioural self-regulation measures for the study
baseline test. The scripting and filming of the training component is discussed, and the
resulting statistical analysis of results outlined.
Chapter 6 RESULTS An analysis is presented of the stated hypothesis, the statistical results and
participant compliance with the study protocols. A comparison is made of the usability and
efficacy of the online process against participant results and demographics.
Chapter 7 DISCUSSION reviews the study objectives, background of the study and participant
controls designed for the unsupervised delivery. The hypothesis are discussed in the light
of limitations and participant behaviour. Further suggestion is made of research to expand
the concept and neurophysiological basis of the action
1
1. INTRODUCTION
Where is the risk?
Individual performance is sensitive to mental state and the ability to continue to function when
fatigued, overloaded or distracted. Attention to the task is the essential criterion for
performance, reinforced by adaptive and learned skills embedded in self-regulating behaviours.
This study identifies and evaluates an attention recovery technique as a self-regulating skill
utilising an online delivery method with a student sample. Chapter one illustrates the magnitude
of the risk that makes this an imperative study from both scientific and social perspectives.
Pilots are a group that have a repeated ‘attention critical task’ at both take-off and landing.
Their tasks require extensive technical training and the development of self-regulating skills to
maintain their flying skills; attributes which are not necessarily present in the novice pilot but
developed over time. To accommodate the large numbers of new pilots needed, governments
and aviation regulators worldwide have modified training standards to expedite the more rapid
placement of novice pilots into airlines. (ICAO, 2007; (CASA, 2015). Demand for pilots has
increased with Boeing and Airbus as well as some 1700 other jet airliner manufacturers and
major airlines globally projecting a continued 6% growth annually in air travel over the next
15 years. Growth due to fleet expansion and attrition due to retirements require an estimated
558,000 new pilots to be trained to ensure maximum utilisation of more than 70,850 aircraft
on the order books presently (Tinseth, 2015) (Leahy, 2015). The training and development of
large numbers of young pilots to operate in a hazardous environment makes the evaluation and
training of self-regulating behaviours in trainee’s imperative. The outcome of poor attention,
anticipation and the likelihood of cognitive failure when stressed would inevitably escalate the
risk of human error on the flight deck.
2
Human error continues to dominate incidents in safety critical industries such as aviation,
transport and healthcare. Human error resulting from loss of attention and situation awareness
(SA) (Endsley, 1995) has been widely researched. It is apparent that when the quality of
attention as the essential interface between human perception, cognition and response is
affected, then cognitive functioning is also affected (Kahneman, 1973)(Wickens, 1992)
(Posner, Rothbart, Sheese, & Voelker, 2014). Increased stress has been shown to vary attention,
narrowing and slowing thought processes to increase errors (Eysenck, Derakshan, Santos, &
Calvo, 2007; Eysenck, Payne, S., & Derakshan, N., 2005). The need for the ability to return to
a fully functioning mental state after disruption has been viewed as enabled by the individual’s
cognitive resilience (CR) (Staal, Boulton, Yaroush, & Bourne Jr, 2008), or ‘mental toughness’
in being able to bounce back after disruption.
1.2 The extent of human error Endsley’s (1995) widely-used Situational Awareness (SA) construct, views the potential for
error management and competent functioning, through the cognitive elements of perception,
comprehension and projection (judgement) about a current situation. SA is thus fundamentally
dependent on attention state training to facilitate perception in the model (Tang & Posner,
2009). The SA construct has been extensively used in describing and measuring the necessary
cognitive attributes and performance of pilots (Campbell, Castaneda, & Pulos, 2009; Carretta
et al., 2014) and air traffic controllers (Chappelle, Thompson, Goodman, Bryan, & Reardon,
2015; Pecena et al., 2013). Attributes similarly required for mobile equipment operators,
surgeons and nurses, chemical plant operators and police officers. Incident investigations
across industries as detailed in chapter two (Table 2.2) have shown that human error has
featured in 80% or more of incidents (ATSB, 2004; Endsley, 1995) with overall loss of
attention and perception directly associated in 76% of cases (Endsley & Garland, 2000; Jones
& Endsley, 1996; Shook, Bandiero, Coello, Garland, & Endsley, 2000) (O’Hare, 2006;
3
Sneddon, Mearns & Flin, 2006). The universal nature of human error and specifically loss of
SA has also been implicated as a key factor in investigations of preventable adverse events in
ospitals due to incorrect medication, misidentified patients, poor hygiene compliance and
deferred or forgotten intentions (Levin et al., 2011).
The magnitude of the problem of human error encompasses all industries. Pilot error rates
continue to be successively reported at 75-80% for Australia (CASA 2014; ATSB 2007; ATSB
2014) and 80% for the US (FAA, 2010) and similarly for global aviation (ICAO, 2015). The
figures and overall approach to pilot error and human error in general, have been challenged
by several authors, generally critical of the non-inclusion of antecedent organisational factors
(Dekker, 2011; van Winsen, Henriqson, Schuler, & Dekker, 2014). The authors arguing that
organisational factors in the culture, system of work and even non-work related events have a
greater role and impact on safe behaviour. Equipment usability studies have been employed by
combining behavioural and engineering concepts, to minimise risk and improve fail-safe
operation at the human-system interface. For example, to program pre-failure warning systems
and automatic stops, or as in one historical example, a simple change to the shape of an aircraft
undercarriage lever. The solution being replacement of the grip with a tyre-like knob to prevent
inadvertent error in selection during the highest workload, the last 20% of the landing phase
by the pilot. Typically, when the pilot’s vision and concentration is out of the window and less
so looking down to find the lever in the gloom of a buttons and instrument rich cockpit.
Similarly, the 'Positive Deviance Program' was implemented in some hospitals, by engineering
interactive behaviours through training to achieve compliance with infection control. (Lloyd,
Buscell, & Lindberg, 2008), the person being recognised as the last line of defence with the
ultimate discretion to prevent adverse incidents.
The global healthcare industry is the source of most preventable fatalities and adverse incidents
in the workplace. Progressive quarterly figures are published (HHA, 2015) on compliance rates
4
with protocols show the difficulties in the measurement of non-compliance, pointing to the
problematic nature of subjectively influenced and inevitably biased self-reporting assessments
(Cohen & Sherman, 2014; O'Brien & O'Hare, 2007). The measures have tended to display
inflated rates, masking the true situation when compared with covert observation methods
(Skinner, 1953, van de Mortel, Apostolopoulou, & Petrikkos, 2010). However, even when
using more objective electronic methods of assessing compliance to avoid observer bias, true
measures were confounded by what has been mistakenly understood to be the classic
‘Hawthorne effect’ (Adair, 1984); insofar that nurses mindful of being observed increased their
compliance then later decreased it when unobserved (Edmonds, Brown, White, & Kirk, 2013).
Observed non-compliance with hygiene protocols, as a key behavioural marker to infection
and fatality rates, vary worldwide, reportedly hovering at around 20-25% in Australia (HHA,
2015), but when covertly observed, non-compliance rose to more than 60% of the time. The
standard hospital responses to non-compliance have been more training, raising consciousness
through abundant signage and placement of hand gel bottles within reach of every work site.
An implicit recognition of the human factor operating through fatigue and inevitable
distractions in the hospital system of work.
Education and simulated practice will raise the threshold of vulnerability at which an individual
is likely to lose situation awareness and responsiveness to circumstances (Koglbauer, Kallus,
Braunsting, & Boucsein, 2011). However, conventional training does not necessarily address
the intrinsic attributes or mental state of the nurse, pilot, driver or operator and have proved
insufficient to ensure compliance under pressure or defend against expedient decisions under
stress (Goodman, 1999; Orasanu & Martin, 1998). Reinforcing conclusions derived from the
global research on safety that the unaddressed human factor provides the most potential for
loss. Dismukes, investigating the extent of problems due to remembering intentions
(prospective memory) at NASA discussed the inherent variability of human performance and
5
in the frailty of prospective memory amongst medical and aviation personnel concluding that
trained and conscientious people routinely make mistakes and that just trying hard would not
eliminate errors. A theory that was further expanded by him in his reference to the statistical
inevitability of failure in remembering intentions or prospective memory. By contrast James
Reason, in his ‘Swiss Cheese’ model (fig 1.1) had advanced the argument that even if the
preconditions for a failure were present in a situation, failure would not result until or unless
all conditions had lined up to deliver a domino-like effect, but that the human in the sequence
could intervene and prevent a problem developing in timely manner (Reason, 2000).
(Adapted from Reason, J. Human Error: Models and Measurement 2000)
Fault free performance in this context thus suggests the need for constant alertness and attention
to the task and an active anticipation of threat and error. In addressing that issue (Dodhia &
Dismukes, 2009) had proposed a cognitive solution involving pausing at an interruption to
firmly re-encode an intention, utilise salient cues as reminders and pause further to mentally
restate both the intention and the task objective when changes have occurred. While this
unquestionably decreases prospective memory lapses and unintentional error due to forgotten
and interrupted intentions, in a less time urgent context where a pattern or ‘primed’ response,
based on previous learning could be given (Ross, Klein, Thunholm, Schmitt, & Baxter, 2004)),
rapid temporal changes in a stressful situation would likely mean an increase in cognitive error
Figure 1.1 The Swiss Cheese Model by Reason
6
rates as decision times shorten. Starcke et al in a review had shown that both decision speed
and risk taking increased with stress (Starcke and Brand, 2012). Mechanisms such as
checklists, cues, memory techniques and speed of recall, are themselves vulnerable to the same
human factors of distraction, deferments, interruptions, violations and fatigue.
It is just as easy to forget to use the reminder as it is to forget to execute an intention. so then
the solution must lie more closely to cognitive task switching and the capacity to ‘unload’ any
mental preoccupation or stress (Wickens, 2014), to function as required at the instant of
demand. From technical to human causes, the contribution of pilot error in incidents recorded
by the transport regulator for the Australian aviation sample has hovered around 75% or more
over the last ten years despite the vastly increased emphasis on human error, in training
programs (ATSB, 2007; ATSB, 2014).
While Australian regular public transport airline operations represent a volume that is
magnitudes less than those of the USA, Middle East, Asia and Europe, the rate of incidents due
to pilot error is reported as proportionally similar across regions and airlines, at around 80-90%
of all fatal incidents.The figures indicate that the human factor risks amongst highly trained
pilots and maintenance engineers have not been fully addressed (Fig 1.2).
Figure 1.2 From technical to human causes Source: (Boeing, 2007)
7
The question arose as to whether the aviation case was the same as that of other industries. A
simple comparison of the severity of risk and the crucial need for solutions was assessed for
various industries (table 1.1). The ratios of fatalities to incidents were calculated as indicated
in (Table 1.1) from fatalities per ‘serious’ investigated workplace incidents, across aviation,
Industrial, hospital and transport industries.
No industries were found where incidents did not occur. Analysing the rates of fatalities and
survivability for each industry revealed that while there were inevitable differences in skills,
motivation and culture, the increase in severity of risk was relative to the system of work, the
task and the impact of human error. That is, whether the risk just affected the nurse or operator
or flowed on to deliver harm to another person, the patient, the bystander, or another driver
(Wiegmann & Shappell, 2001). At the higher severity ratios (Table 1.1), the predominant
technology in the workplace is likely to be more sophisticated, the complexity of defensive
skills and the training needed to manage the risk and the impact on others may be more
complex, task errors may impact others more than the self. For example, in nursing, patients
are more at risk than nurses from the procedures and equipment used to heal them. Similarly,
in aviation, aircraft systems and weather collectively increase passengers and crew risk but
Table 1.1. Ratio of fatalities per incidents by industry
Industry Ratio Frequency of adverse events Source
Hospital patients 1:57 200,000 infections & 3480
fatalities (ACSQHC, 2014. p44)
Transport Drivers 1:100 6500 crashes & 65 fatalities ABS, 2015. BITRE,
2015
Aviation 1:150 5683 serious incidents, 38
fatalities ATSB, 2015 Quick
Counts
General industrial 1:2859 531,800 incidents, 186 fatalities Safe Work Australia,
2013, p22
8
leave the maintenance technician unscathed. Inspection of the calculated severity ratios
suggests that the risk level increases as the combination of the complexity of operator tasks,
the urgency and the potential for distraction and inattention increases (Yu, 2016). Nurses
working shifts in a hospital operating rooms and emergency departments are expected to be
able to deal with a succession of rapid and frequently interrupted events while involved in
complex tasks (Antoniadis, Passauer-Baierl, Baschnegger, & Weigl, 2014). The hospital or
nursing context in a public hospital represents a systematic process of rendering attention to
patients, the management of materials and equipment and the often voluminous and detailed
documentation of patient medical notes and reports, overlain by sudden demands and ad hoc
interruptions (Cohen & Sherman, 2014). Access to patients, pateient records and equipment
means that nurses need to constantly walk from one location to another in a ward. Contributing
to daily fatigue, accumulated further over the span of the shift (Barker & Nussbaum, 2011) to
erode mental energy and attention (Linden, Keijsers, Eling, & Schaijk, 2005), The increase in
physical fatigue potentially inhibits motivation to comply with the moment-by-moment
hygiene controls (Huis et al., 2013). The heavy road transport statistics reflect the
circumstances of road transport drivers and mobile equipment operators. Truck drivers are
often at the mercy of other road users in cars, occasionally needing to defensively manage
heavy articulated vehicles, road trains or tankers to stay on the road or stop suddenly. Rail and
long-range road transport includes extended periods of drivers sitting in a cab, subject to the
monotony of long unrelieved distances, risking complacency (Prinzel III, DeVries, Freeman,
& Mikulka, 2001). Low task stimulus, spasmodic cognitive demands, coupled with fatigue
induced by noise, heat and vibration have a performance and safety effect on drivers. Critical
competencies such as visual perception and motor control (Conway, Szalma, & Hancock, 2007;
Frissen & Guastavino, 2014) are affected and combine to lessen driver alertness and
responsiveness. Evidence from claims-based incidents show that mobile equipment operators
9
of all kinds (forklift, cranes, trucks) are more than four times at greater risk of traumatic injuries
and fatalities than all other types of industrial work in Australia (Safe_Work., 2015). The
aviation groups in the risk ratio comparison table (Table 1.1.) mainly represent pilots but the
risk of ‘deficient performance’ equally extends to maintenance personnel because of their
critical role in ensuring that aircraft can fly safely. The general industrial context (Table 1.1)
represents the greatest number of incidents in the cross-industry comparison of severity, mostly
of a high frequency and low severity such as ‘slips, trips and falls, made more serious when
being struck by falling objects, falls from height and exposure to uncontained energy. The
largest employer is the general industrial sector which is also lesser supervised by comparison.
The large numbers of small to medium companies as employers - provide the greatest
opportunity for incidents covering more than half of the Australian workforce (Australian
Bureau of Statistics, 2015). Improved techniques and analysis in the last 50 years have
progressively shifted the emphasis from technical factors as the cause of adverse events to be
largely replaced by human factors (fig 1.2), serving to bring error management and
performance through self-regulation (SR) into sharper focus. Research into attention recovery
as a key aspect of SR has become imperative given the rate of growth in the need for services
that are subject to the variability in the human factor. The emphasis on traditional education
and training now increasingly includes consideration of performance and the way people self-
regulate to achieve their objectives. While fatigue and the systems of work that impact SR and
performance, continue to be widely researched topics, the means and mechanisms to enhance
SR has had a consistent but slower growth, dependent as it is on a better understanding of the
way brain-state and mental-state influence each other. The path to reducing the risk and
decreasing incidents is through a better understanding of the human factors in workplaces.
10
2. ATTENTION & SELF REGULATION
2.1 Introduction to Attention Attention and error are intertwined in human performance, a failure in one frequently leading
to the other. The need for an understanding of attention and the means to recover it when lost
is universal and critical in all roles associated with cognitively challenging, time-critical or
hazard-prone decisions. Attention to the task is one of the most frequently addressed topics in
psychology attracting a wide range of theoretical, functional and metaphysical contributions.
Relevant to attention recovery are perspectives that have evolved from capacity models by
Kahneman (1973) (fig 2.2), Structural models by Wickens (1992) (fig 2.3) and Posner’s neural
network theory (Petersen & Posner, 2012) (Fan, McCandliss, Fossella, Flombaum, & Posner,
2005; Posner & Boies, 1971; Posner et al., 2014).
2.2 Models and limitations of attention That limitations exist in both structural and capacity models of attention is evidence of the
complexity in the relationship linking attention and performance. The decline of performance,
as is commonly attributed with arousal, in the Yerkes, R. M & Dodson, J. D 1908 law, suggests
that performance quality beyond an optimal point becomes inversely related to arousal (fig
2.1). The apparent reversal in performance has been central in several perspectives and theories
to suggest either capacity or structural limitations in attentional models. In comparison, in both
capacity and structural models, as load, contention, time pressure and arousal increase beyond
individual ability, error rates increase, effort decreases and performance, diminishes.
Kahneman had pointed out that an important aspect of effort and attention was the dependency
n the task-load and the time pressure imposed on short-term memory (Kahneman, 1973, pp27).
11
2.3 Capacity Models: A major difference in the models is in the way the they are said to handle specific contention
and overload, for parallel events. In Kahneman’s model (fig 2.2) that task falls to management
of capacity and the allocation policy in which arousal has the potential to reallocate and activate
a temporary reserve increasing capacity or to re-prioritise concurrent tasks. Whereas in the
Figure 2.1 Yerkes-Dodson Law of arousal and performance
(Adapted from Kahneman 1973)
Figure 2.2 Kahneman’s Capacity model for attention (Adapted from Kahneman 1973
12
structural model as described in Wickens model (fig 2.3), concurrent processing is not available
and similar demands made on the facility face the problem of being blocked as overload.
Human activity in general and safety critical roles often operate with a need to manage
concurrent streams of attention. How the streams are allocated and apportioned when in
conflict or overload is important in identifying functional constraints. Kahneman’s (1973)
model (fig 2.2) depicts a linear process from arousal to response. The model see attention as
having a limited capacity necessarily managed by a feedback and allocation policy.
For example in ‘capacity’ models (Kahneman, 1973), attention is more discretionary or
competitive in allocating capacity for various needs but remains a limited commodity, highly
dependent on mental effort (Shenhav et al., 2017), while allowing for some simultaneous
processing, easily disrupted or reduced. The capacity model of attention implies limitations but
helps, in part, to explain degraded attention with task overload. In the capacity model, attention
is difficult to maintain over extended periods and easily degraded by normal competing
distractors and influences such as age, task load and emotional states ( Eysenck et al., 2007).
2.4 Bottleneck models: Bottleneck models as in the Wickens, (1992) (Fig.2.3), extend the capacity model to
accommodate the number of processing channels available. Commencing with attention as the
input, the structural or ‘bottleneck’ approach as depicted in Wickens model. Perception,
judgement, memory and response, as well as sensory stimuli, have a direct input. A position at
the person-stimulus or signal interface gives the attention receptor a preeminent position as it
directly accesses other cognitive functions in Wickens model. However, it is not sufficient to
just have receptors, the capacity to engage, absorb and respond to external needs and
circumstances depends on the person’s ability to select, adapt or switch attention. A change in
13
mental-state can be a common human response in coping with stress. Avoiding thinking about
an issue, taking a deep breath to relax, or taking direct action to eliminate the problem
Figure 2.3 Wickens model of attention. (Adapted from Wickens (1992)
is often automatic and unconscious in reducing discomfort (Monet & Lazarus 1977. p145).
While discomfort serves as immediate motivation to seek change, the intensity of the need may
compel more conscious and deliberate action or drugs to effect change. Recovery when
clinically or chronically stressed is commonly facilitated by cognitive behavioural counselling
or specific training in changing mental-states as in meditation and mindfulness training (MT).
2.5 Attentional Networks. Posner & Boies (1971) advanced a network theory of attention, moving away from attention
as a uniform concept encapsulated by the linear models of Kahneman and Wickens. Posner’s
Attention Network Theory (ANT) provided an anatomical as well as a functional picture of
attention, defined as anatomically separate from other processing systems that are affected by
14
attention. (Petersen & Posner, 2012). The ANT theory distinguishes between attention and
processing networks in a potentially duplicated three-network model comprising the
components of alerting as the arousal system, orienting focused on prioritising sensory inputs
and the executive managing conflict in the network. While functional networks are named their
action is distributed across brain regions. A significant aspect of the theory has been the
practical use of the model for attention training (AT), with application in the improvement of
cognitive test results and specific clinical interventions (Raz & Buhle, 2006). Development of
the attention model has seen the utilisation of (MT) which Tang & Posner (2009) refer to as
‘attention state training’ (AST) to effect change through specific networks. The meditation-like
practice in the concept is the means to act on the network to change mental-state. The effect of
which generalises across the cognitive domain to influence other domains of behaviour and
contrasts with attention training, a task specific skill for a procedure requiring direct executive
control.
2.6 Arousal and performance How attention is initiated must necessarily look to arousal and orientation. Kahneman (1973)
had viewed arousal and effort as the same thing. Arousal for attention is generally associated
with being a more energised state, different from just paying attention which represents a more
passive state. Posner et al, (1971) had suggested that attention, was not limited to just meaning
‘awareness’ but also had the properties of selectivity - as focused and divided attention, and
intensity - as alertness and sustained attention (Posner & Boies, 1971). Sturm et al, (2001)
added to more emphasis to arousal by dividing attention into components of intrinsic and phasic
alertness, where intrinsic alertness represented arousal and phasic alertness, representing the
ability to modulate the level of receptivity to an arousing stimulus (Sturm & Willmes, 2001).
The phrase, “a maximum state of arousal”, suggests there are no remaining resources available
to deal with other demands. The Yerkes-Dodson 1908 law (fig 2.1) states that performance is
15
an inverse function of arousal level at a point (Kahneman, 1973, pp.49). The ability to switch
attention from divided to being focused and to sustain alertness for a greater period infers the
supply of energy for cognitive effort. At the extremes, where arousal is lowest or absent, a lack
of mental energy and inclination to cognitive effort, can present as apathy as seen in various
mood disorders (DSMIV, 1994). While physical exercise has been seen to increase mental
arousal and effort up to a state of exhaustion, a subsequent attempt to increase it further results
in a conscious inability to stimulate or increase it further, despite the desire to do so.
The bi-directional relationship between exercise and mental effort had shown that sustained
physical activity decreased with increased mental fatigue (Marcora, Staiano, & Manning,
2009), while a decrease in mental effort was reflected in poorer cognitive test performance
(Storbeck et al. 2015; Cockshell & Mathias, 2012; Wright, 2014; Jackson et al. 1999). Mental
state was a found to be a further limiting factor, with cognitive-affective variables such as
anxiety highly predictive of disruption of mental effort and performance in sports (Allen, Jones,
McCarthy, Sheehan-Mansfield & Sheffield, 2013). An anxious arousal resulting in a decline in
performance, consistent with the Yerkes-Dodson law (fig 2.1).
Kahneman’s suggested that optimal performance could be most easily achieved where the
perceived threat was low and where the energy required to manage it was low. Also, where
arousal was not excessively high, where a broad attention state was experienced and where
attentional stability prevailed together with improved memory recall and physical coordination.
In summary, a prescription that closely resembles a stable low anxiety mental state.
The allocation of mental effort is most often seen in the context of task demands, for example,
as in driving in traffic, but can also be discretionary and strongly mediated by trait-based
persistence and conscientiousness in determining the time on task. After which it could be
relinquished for something more comfortable and desirable as an alternative (Wickens et al.,
16
2015). The ANT by Posner et al, sees allocation of resources as a network task managed by the
executive in the model.
At the behavioural level, mental-switching could also be due to a ‘seductive attractor’.
Described as the situation where the target attractor represents a particular interest with a
hedonic valence, that is likely to result in gratification and a lower mental workload (Bearman,
Paletz, & Orasanu, 2009).
Kahneman’s (1973) model (Fig 2.3) articulated the arousal-attention relationship by expanding
on outcomes of low and high arousal to reveal dependencies in the model. Arousal was depicted
early in the model and fatigue later accounting for the erosion of attention. The inclusion of an
‘evaluation and allocation’ policy in the model suggested executive based cognitions and
decisions that also involved motivation and intentions; an aspect mentioned later in this section
by Wickens et al (2015) in discussing task retention and attention switching using the Strategic
task overload model (STOM).
At the psychological level, Lazarus and Folkman (1984), in differentiating the two mental
states in their model of coping as ‘intrapsychic’ and ‘direct action' implied that effort was
required for coping and mental energy. They used the two terms when referring to mental state
to mean to adjust, confront, regulate feelings, to detach the self, and make the effort to ‘make
things work’ (Lazarus & Folkman, 1984). In this context effort in coping means actively
maintaining an unencumbered alert, emotionally calm mental state, conducive to greater
cognitive effort and attention.
The association between attention and mental effort was investigated from several
perspectives, framed by whether it emanates from a physiological or psychological perspective.
For example, Oken, et al (2006) described the physiology of arousal, vigilance alertness and
attention as activation states of the cerebral cortex (Oken, Salinsky, & Elsas, 2006). Gomez-
Pinilla extensively examined the central role of nutrition to cognitive functioning, showing
17
energy metabolism and neural plasticity important in learning and that mental effort was
directly affected by diet (Gomez-Pinilla, 2008). Limits to arousal, in turn, were described by
Tanaka, et al, (2014), showing that continuous activation of the prefrontal cortex increased
sleepiness and the frequency of beta brain waves (Tanaka, Ishii, & Watanabe, 2014). The
changes in brain-state indicating that where arousal was high, depleted energy or fatigue at
some point could overwhelm both arousal and motivation.
In addition to the common effect of fatigue acting to reduce mental effort on most tasks (Engle-
Friedman, 2014; Murata, Uetake, & Takasawa, 2005); other common strong influences on
mental effort include depressed moods that moderate motivation to act (Capa, Audiffren, &
Ragot, 2008; Smith, 2012) and the effect of fatigue-inducing anxiety on performance (M. W.
Eysenck et al., 2007). At the biological level, Fairclough & Houston (2004) found direct
correlation with changes of blood glucose levels on mental effort (Fairclough & Houston,
2004) and also significantly, the effect of type of diet on alertness and mental effort (Allen,
Jones, McCarthy, Sheehan-Mansfield, & Sheffield, 2013). The latter finding support in the
work on pilots and diets where protein, carbohydrate and fat weighted diets were compared
(Lindseth. G., Lindseth. P, Jensen, Petros, Helland & Fossum, 2011). Lindseth et al found that
high carbohydrate and fat diets resulted in significantly better and more consistent performance
in flight simulator trials than others, with correspondingly higher scores on cognitive abilities
tests. The findings suggesting that mental as well as physical energy were diet dependent and
could be reflected in test scores; that high protein diets delivered better reaction times compared
to others. The size of the ‘lunch’ was also of importance when the de-energised postprandial
mental dip associated with a state of sleepiness was analysed. The effect being a low energy
state probably due to the activity of the parasympathetic nervous system in response to food in
the digestive tract. Further reinforcing that attention depends on both the availability of mental
effort, an energy source and an absence of cognitive-affective interference.
18
2.7 Attention switching and multitasking
Attention switching, and multitasking are two forms of dealing with apparently simultaneous
events. An investigation of a mathematical model of multi-tasking and task switching decisions
in the STOM with a meta-analytic integration of 31 experiments analysed choices based on
ease and attractiveness of the alternative task (Wickens, Gutzwiller and Santamaria, 2015).
Where multitasking may be said to occur, it would follow that attention as a neural resource is
rapidly reassigned at each change or slice of time. The enemy of multitasking and of being able
to switch rapidly from one thing to another is fixation, or cognitive tunneling, representing a
state of unconscious disregard of external signals, or a conscious reluctance to share attention.
Many activities are done concurrently by sharing attentional resources (Wickens et al., 2015),
with cognitive resources allocated on a priority basis to the more complex and least automatic
task. Wickens et al. pointed out further limitations of the STOM including the additional risks
of neglect, of choice and avoidance and in the prioritisation of attention to less demanding
activities. That there were temporal limitations in multitasking when engaged in a continuously
demanding task were also found in testing for reaction time using a standard test for pilot
assessment (Carretta, 2011; Carretta et al., 2014), with the finding that errors increased as the
time for recall and execution shortened. Emphasising that time on task is a significant
consideration in the application of attention (Kahneman, 1973)(Dismukes, 2006) (Wickens et
al, 2015). Loss of interest due to boredom or typically uneventful execution can leave a task
unfinished or poorly executed. The focus is thus firmly on the pilot’s limitations of how well,
how long and how flexible their attention to cockpit tasks can be. Focusing on the pilot
reinforces the need for a mechanism that can address all the elements of the STOM by enabling
the pilot to rapidly relinquish preoccupation and fixation to self-regulate their attentional state.
Merging Hofmann’s Self-regulation mechanisms (Table 2.1) with Endsley’s (1997) taxonomy
19
of situational awareness and behavioural requirements, suggests the following: eight
(unordered) behavioural markers as key competencies.
(Hofmann, Schmeichel, & Baddeley, 2012)
2.8 Brain State and Mental State A distinction is made for clarity of the difference between mental-state and brain-state when
discussing attention. While not exclusively so, mental-state can be diverse and changeable,
easily influenced by the situation, environment, mood, motivation and agenda of the person,
subject to both endogenous and exogenous inputs. Brain-state is limited here to the
neurobiological expression of mental-state. Note that mental-state and brain-state will clearly
influence each other. Hence any arousal which precedes overt thought such as the startle
response is treated here as associated with brain-state. Arousal, orientation and attention
resulting from a subjective input could then be ascribed to mental-state, while understanding
that brain systems have an underlying role in their expression. When mental-state is the
executive, and the stimulus occurs due to a thought, perception, anticipation or association, it
could inform brain-state in determining the level of arousal, intensity and selectivity of
attention required. (Tang, Rothbart, & Posner, 2012). Primal reflexes such as the startle
response responding to exogenous stimuli and occurring without apparent or overt thought is
1. Can deliver the necessary mental effort 2. Find it easy to remember despite interruption 3. Can switch attention rapidly between demands 4. Can see things others may miss 5. Can anticipate sudden changes 6. Less vulnerable to emotional preoccupation 7. Ability to avoid becoming fixated 8. Remembers procedures, rules and exceptions
Table 2.1 Executive functions and self-regulatory mechanism
20
an example of a reversal where brain-state affects mental-state, likely trading thoughtfulness
for speed of response; albeit at the risk of increased errors as speed of application increases
(Dismukes, 2006).
Tang et al (2012) in reviewing the relationship between mental state and brain state, concluded
that a voluntary and preferred mental state could be achieved by modulating brain states with
integrated MT (IMT). The evidence showing that resultant changes were a good predictor of
subsequent improved cognitive performance. The ability to switch between mental-states was
considered by Tang et al, as “vital” for SR. However, some involuntary mental-switches can
result in undesirable outcomes, where for example, a dysfunctional mental-state is triggered,
by recognition or recall, and the person’s self-regulating defensive mental-switch fails.
PTSD is a mental-state that has a long-term effect on brain-state. Experienced as chronic
fatigue, poor concentration, difficulty in making decisions and subjective feelings of depressed
hopelessness. It frequently includes symptoms such as cued hyperarousal (Heesink et al.,
2017)(APA DSMIV, 1994) while others experience extreme disassociation (Cortese, Leslie, &
Uhde, 2015; Lanius, Bluhm, Lanius, & Pain, 2006). Perpetuation of cognitive impairment is
also seen in typical chronic fatigue, depression and anxiety, emphasising the cross-modal effect
of mental-state and brain-state (Reppermund et al., 2007).
The management of mental-state has long been a preoccupation amongst philosophers.
Humphries (1971) in discussing a Buddhist variant of MT, the Zen technique, related that in
the teaching ‘Satori’ or enlightenment was said to be experienced, rather than something that
is known, implying Satori to be a mental-state rather than knowledge. In Zen the achievement
of Satori is achieved by disciplining the mind to pay attention to the event rather than as is
common the noise in the mental environment.
One mechanism, practiced in the Zen method is redirection of thinking away from the mental
‘noise’; such as the use of contemplation of rationally impossible propositions, such as ‘the
21
sound of one hand clapping’ called ‘Koans’ (Humphries, 1971, pp116). The practical effect of
struggling mentally with an irrational proposition to achieve a less encumbered mental-state,
is the displacement of emotionally laden self-preoccupation and ruminative anxiety. Continued
meditation maintains the preferred mental-state, to control impulse and Freud’s primitive or
hedonic ‘id’ (O'Bryan, 2011). Evidence of the corresponding benefits of MT cited by Tang et
al, (2015), as found in different studies of MT, included improved attention span, measured by
a reduced attentional blink, in others improved conflict monitoring and enhanced attentional
orienting. The process of meditation involving focused contemplation over longer periods of
time was also said by Tang et al, to help in ‘cultivating’ attention with repetition. Thus attention
control is the starting point for emotion regulation, self-awareness and subsequently effortful
doing, mind wandering control and to ultimately achieve ‘effortless being’, which could also
Adapted from Tang, Y. Y., Holzel, B. K., & Posner, M. I. (2015).
2.9 Mental State and Unsafe Behaviour be interpreted as a lack of self-consciousness and preoccupation (fig 2.3) (Tang, Holzel, &
Posner, 2015). Variations of the MT approach with application to stress management,
Mindfulness Based Stress Reduction (MBSR), were reported by Jha, et al, (2007) in a
comparison to differentiate MBSR with MT and a control. Jha et al., found mindfulness training
Figure 2.3 Tang et al, 2015 process of mindfulness meditation
22
as important for attention behaviours through the sub-components of the attention network and
other subsequent cognitive processes of attention, orientation and conflict resolution (Jha,
Krompinger, & Baime, 2007), demonstrating that MT can influence brain state through the
attentional networks.
The psychological literature has extensively referenced how a person’s mental state and coping
style directly influences behaviour. The earlier work on coping styles by Monat and Lazarus
(1977, p150), (Folkman, Lazarus, Dunkel-Schetter, DeLongis, & Gruen, 1986), had shown that
superior performance was more consistent with what they called an externally focused ‘direct
action’ style than an internally focused ‘intrapsychic’ style. A person’s coping style and mental
state, whether it was internally or externally focused, could thus be seen to be a strong indicator
of the ability to respond adequately to situations. A failure in perception and cognitive
processing predicts poorer performance outcomes. The behaviour based assessment of
propensity to human error, as achieved in the development of the ‘Cognitive Failure
Questionnaire’ (CFQ) (Broadbent, 1982), effectively translated observed behaviours into
mental-state (Wallace & Chen, 2005). Observable mistakes and errors in the Broadbent filter
model of attention, associated cognitive impairment with physiological states, such as fatigue
and illness. The model allowed for functional variance in behaviour in contrast to the use of
intentions and attitudes in predicting behavioural outcomes, as in the theory of planned
behaviour (Madden, Ellen & Ajzen, 1992).
Taken together, the three perspectives of coping style and mental state (Lazarus,1976), when
added to cognitive failure (Broadbent et al. 1992) and Endsley’s situation awareness (Endsley,
1995), suggest a natural convergence and sequence with cognitive failure leading to unsafe
behaviours and incidents (fig 2.4).
23
(Broadbent, 1982),
2.10 Cognitive resilience and mental state This study, further detailed in chapter five, centres on students but the need for resiliency in
behaviour applies equally to all personnel engaged in complex tasks and when under increased
mental load or threat. Staal et al., (2008) referred to resilience as the capacity to recover and
overcome adverse situations and the effect of stress on cognitive function (M. A. Staal,
Boulton, Yaroush, & Bourne Jr, 2008). A degree of cognitive resilience is required in those
circumstances to disengage from other preoccupations, attend to the situation and act on the
presenting problem. Mogg et al., (2008) found evidence showing that high anxiety was
associated with a greater bias in shifting attention to threats and slowness in disengaging from
those threats, a state resembling fixation (Mogg, Holmes, Garner, & Bradley, 2008). Once
perceived, a difference or change as in either slowing or increasing the speed of response to a
threat suggests a post-perception evaluation and change in the strategy for dealing with that
threat. The Mogg et al., (2008) study provided support for the tendency to fixation and
cognitive slowing evident in anxious individuals (Eysenck et al, 2004). An observation also
Figure 2.4 Relationship of cognitive failure to incident rates
24
consistent with the theoretical models and outcomes in the Lazarus & Folkman accounts in
which defensive behaviours are characterised by self-preoccupation, anxiety, withdrawal and
inevitable loss of external awareness (Lazarus, 1976. p74), which they called intrapsychic
versus direct action coping. The intrapsychic form involving functional losses in memory,
attention and decision skills consistent with cognitive failure in the Broadbent et al., model
(Wallace & Chen, 2005) and reflected in the Mogg et al., finding. In adverse situations,
recovery to full functioning is dependent on the person’s psychological resilience, which
Lazarus refers to as the capacity for cognitive appraisal in adapting and enabling the return to
a stable mental state (Monet & Lazarus 1977. p145), consistent with a Self-Regulated state.
There are a range of psychopathologies classified as personality disorders (DSMIV) that only
tend to be revealed when triggered by an adverse situation and surface when feeling
undervalued, anxious and depressed (Presniak, Olson, & Macgregor, 2010)(APA DSMIV,
1994). The perspective taken in this study follows the Monet et al model in that cognitive
resilience is the ability to adapt, relinquish or clear mental impediments to full cognitive
functioning. Impediments which would otherwise and variously block functional abilities such
as concentration inhibit mental effort, rapid task switching, prospective memory, the speed of
memory recall and vigilance. Abilities that are essential and interdependent for optimal
problem-solving performance (Rockstroh & Schweizer, 2001; Christopher D Wickens, 2008;
C. M. Wickens, Toplak, & Wiesenthal, 2008).
2.11 Cognitive resilience and performance Performance is an output dependent on resilience and the individual’s capacity to monitor their
mental-state. Easterbrook’s work in 1959, pointed to the effects of stress on perception and
performance referring to the ‘tunnel hypothesis’, a narrowing of the perceptual field with
behaviour restricted and oriented to the object of threat (Dirken, 1983). An aspect that Kohn
25
had previously noted in 1954 as having the potential to increase in severity with ‘emotional
intensity’ of negative self-evaluation (M. A. Staal, 2004). Eysenck et al (2007), pointed
implicitly to SR as a key factor of their ‘Attentional Control Theory’. Their theory proposed
that the ability to pay attention was dependent on the person’s capacity to regulate their mental
state and recover from cognitive-affective interferences, such as anxiety, emotional
preoccupation, distraction or fatigue when under cognitive load (Eysenck, Derakshan, Santos
& Calvo, 2007).
2.12 Cognitive resilience and prospective memory The extent of the disability from these factors in time critical events and processes had
encouraged experimentation with pharmacological agents to increase performance.
Dextroamphetamine (Dexedrine) as an example was used to maintain arousal and as a
countermeasure to fatigue, finding that their use could reverse decrements in performance.
However, the psychological side-effects from the prolonged use of Dexedrine subsequently
shifted the focus to Modafinil, a less injurious drug. The experience had shown that arousal by
the drug did not flow on to benefit all aspects of attention and that ultimately, perception,
orientation and executive functions could all be distorted by the drugs. (Estrada, Kelley, Webb,
Athy, & Crowley, 2012).
Dismukes (2006) in a review of 27 major (USA) airline incidents listed in the NTSB database
highlighted a specific limitation of the human attention management system. Finding that most
incidents, amongst high-experience airline pilots, were due to errors of omission which he
called lapses of prospective memory, due to inadequate information encoding and cueing when
experiencing competing demands and interruptions. Dismukes had approached the
comprehensive assessment of pilots’ behaviour from three different views. Including
ethnographic, incident analysis and laboratory reports; and five types of situations involving
(1) remembering tasks (prospective), (2) unusual events (episodic), (3) typical tasks, (4)
26
interrupted tasks and (5) simultaneous and multitasking (interleaving tasks). The results
supported a prior investigation by Dodhia and Dismukes (2005) that had demonstrated a failure
of attention, missed cues and a lack of explicit encoding of intentions occurring where failure
to perform tasks had progressively deteriorated as time spans shortened. Predictively, where
pilots had longer time to retrieve an intention, the failure rate decreased (Dodhia & Dismukes,
2009). An apparent loss of memory that is not due to a drug or traumatic event and which could
otherwise be prompted and quickly retrieved, suggests a blocking or masking rather than a loss
of the memory. Thus, a loss of prospective memory or forgetting what needs to be done could
be understood to be an example of the limitations involved in the reallocation of priorities as
depicted in Kahneman’s capacity model (fig 2.2) or blocking from overload in Wickens (fig
2.3) model.
Cross-cultural support in that memory recall and loss of attention represent universal
vulnerabilities, was also reported in a more general study of Russian military pilots by Dolgova
et al, (2013), in which they had concluded that the pilot’s resilience and ability to manage
cognitive loads in responding adequately to tasks were important in maintaining performance
under stress (Dolgova, Ivaniuk, & Tukayev, 2013).
2.13 Attention in situation awareness Because perception is logically dependent on attention, a loss of perception of what it is to be
attended to also primarily means loss or reduced attention. Studies utilising Endsley’s (1995)
taxonomy and subsequent evaluation by Jones and Endsley (1996) (Table 2.2), have suggested
that the most frequent cause (at around 76.3%) were level 1 errors of inattention or perception,
including a loss of either mental (i.e., cognitive failure) or visual perception (i.e., attentional
blindness). Subsequent confirmation was obtained from the classification of incidents from a
diverse range of hazardous industries (O’Hare, 2006; Sneddon et al. 2006; Shook et al. 2000).
The ability of the individual to respond safely and promptly to hazardous circumstances, with
27
adequate SA is the ability to perceive, understand and project the likely outcomes in
surrounding events Hence a block in attention will likely block all executive functions,
comparable to Wickens (1992) model of perception being dependent on attention. SA at the
entry point is firstly “the perception of the elements in the environment within a volume of
time and space, secondly the comprehension of their meaning, and thirdly the projection of
their status in the near future” (Endsley, 1995). Investigations across aviation and industrial
domains found support for the utility of the Endsley model (Table 2.2) and in emphasising
The predictive capacity of the Endsley (1995) construct of SA had earlier been suggested by
Endsley and Bolstad (1994) to be due to differences in abilities such as short-term memory,
speed of perception, ability to see the connection between events or objects, attention-switching
and multi-tasking. Stanton, Chambers & Piggott (2001) debating the usefulness of SA reviewed
three similar constructs and found a divergence of opinion as to whether Endsley’s model
Table 2.2 Incident types classified in the SA model by Endsley (1995)
28
applied to process or product, but that the concept of SA was based on inherited psychological
principles. Stanton et al., concluded that irrespective of the differences the SA model had
concurred with the primary psychological constructs of attention, perception, understanding,
projection and in some cases memory. Further practical evidence was found by O'Brien &
O’Hare (2007) for SA as an ability, finding it to be a better predictor of performance than either
cognitive skills training or planning behaviour.
The risk of fatigue induced loss of SA and responsiveness due to personal fitness was
extensively investigated from various perspectives, but primarily with respect to emotional
recovery and positive affect mediating mental-state (Gomez-Pinilla, 2008; Bernstein &
McNally, 2017; Feuerhahn, Sonnentag, & Woll, 2012). Personal training was found to augment
the pilot’s ability to withstand the stress of sudden urgent demands and fatigue in flight.
Mentoring and coaching from experienced pilots, expands and models flying skills, which
include crew management and tighter rules, procedures and regulations, in a way that
classrooms cannot do, because as suggested by Wiggins (1997) that it was often difficult to
characterise the cognitive expertise involved. Other more traditional approaches to cognitive
improvement programmes have involved traditional attention skills training (AT) to improve
agility, spatial memory and verbal memory (Adams, 1993).
2.14 Self-regulation Absent in NOTECH Training Addressing the preponderance of pilot error in aviation incidents, the aviation industry has
adopted further advances in training techniques. Achievement by aircrew of satisfactory self-
management and preparation skills are presently embodied in airline threat and error
management (TEM), human factors (HF) and crew resource management (CRM) courses,
typically not fully available to the novice until recruited as an airline pilot. CASA, the civil
aviation regulator has added non-technical skills (NOTECH) competencies to the training
syllabus in recognition of the importance of pilot capacity to maintain effectiveness under
29
stress, even though the problem of measuring those in training has been problematic and as
Wiggins (1997) had previously pointed out, difficult to assess. Student progress is subject to
inter-rater reliability (IRR) between instructors and examiners, providing the opportunity for
vulnerabilities to be missed, given the likelihood of a student having several different
instructors in rapid succession. The potential of that inconsistency has led some researchers to
pursue alternative assessment methods. Roth and Mavin (2013) proposed using a ‘fuzzy logic’
approach, moving away from a precise measurement score denoting skill attainment level to
one of categorisation where the variability in performance becomes the focus. It was proposed
by Roth et al, that an understanding of the type, consistency and magnitude of error made would
result in more purposeful and effective intervention, than that obtained from the instructor
simply making a judgement of proximity to a functional criterion score on a checklist. The
Roth et al approach running counter to the prevailing interest in direct measurement techniques
(Mulqueen, Baker, & Dismukes, 2002). However, irrespective of the NOTECH course
components it remains the case that training in SR and personal recovery techniques are not
yet available to assess novices on those skills. Positive SR development through exposure to
actual in-flight risk (as in stress inoculation) has been reassigned from actual airborne flight to
that of ground-based simulator experience and incorporated into the ‘fast track’ multi-crew
license (MPL) for novices, as equivalent experience. Although, some flying activities that
depend on high alertness and responsiveness by the pilot for safety; such as aircraft stall
recovery where flying speed is lost and the risk of crashing is imminent, are now returning to
the syllabus, retitled as ‘upset recovery’ (CASA MOS, 2015). The regulator’s manual of
standards specifies rostered fatigue management, threat and error, human factors and crew
resource management training (CASA, 2015). However, aviation training programmes have
still yet to provide a trainable means to deal with hazardous loss of awareness, with a technique
for the immediate recovery of attention, that is independent of the pilot’s mental-state, so as to
30
function better at the critical moment. Few opportunities for training in self-regulation of
emotions exist for novices in aviation.
Implicit recognition of the impact of degraded attention has seen developments in
ergonomically designed and simplified cockpit layouts and instrumentation to decrease the
pilots’ mental load and the ambiguity of decision information. Improvements in simulator-
based skill development have made it possible to practice skills more often where mistakes can
be corrected (Dahlström, 2008). Fatigue management is addressed through systems (Cicek &
Serres, 2014; Gander et al., 2014) and procedural rules, task planning and shift rostering as
countermeasures (Dawson, Chapman, & Thomas, 2012). The ‘in-flight’ nap over long oceanic
distances was implemented for the purpose of enabling the crew to provide peak attention to
the critical landing phase of the flight. To manage growing mental fatigue due to intensive
episodes of concurrent and multiple tasks and recover from the gradual somnolence induced
by a lack of stimulus or activity en route (Warm, Parasuraman, & Matthews, 2008). A better
understanding of the capability needed by pilots has resulted in more systematic selection
procedures (Gaydos, Curry, & Bushby, 2013).
In civilian pilot selection, a candidate’s capacity to recover from loss of awareness, distraction
and cognitive fatigue, is often identified through normative self-report questionnaires.
Supporting test evidence from computerised hand-eye coordination, tracking and multitasking
exercises complete the assessment; after which cognitive resilience is observed and assessed
by instructors via simulators and flying sorties, as a development objective (Damos, 2014). In
military settings, the measure of capacity for adequate cognitive resilience occurs earlier and
more rigorously assessed in the context of continuous high-stress operations, similarly
identified at the start with abilities tests (Carretta, 2011) to be subsequently verified in a series
of high-intensity practical flying exercises. A lack of cognitive resilience or inability to cope
with the demand resulting in multiple uncorrected errors as described by King would most
31
often stream the candidate to a different specialty (King, 2014). The civil aviation regulator in
Australia (CASA) prescribes the training standards and competencies required for the various
licences. While no specific technique or recovery skill is suggested, the training courses for
commercial pilots contained in the ‘CASA Part 61 Manual of Standards’ (CASA, 2015)
provides guidelines regarding common behavioural risks in piloting.
2.15 Self-regulation Absent in Simulator Training The demands made on pilots go beyond the mere control of the aircraft. The means to identify
those less capable has moved to obtaining practical evidence through simulators of varying
kinds. The simulator operating as an objective “show me” type of test by delivering some form
of relevant task complexity or mission profile, makes the test an immediately valid criterion
referenced performance measure (Roscoe, Corl, & LaRoche, 2001). When combined with a
battery of cognitive performance tests, the overall results deliver a valid correlation of
prediction of success in training but not in operations (Carretta, 2011; King et al., 2013).
Simulators such as that of the desktop simulators ‘Wombat’ and its Australian variant the
‘Ausbat’ had also provided coordination and attention testing (Roscoe et al., 2001). Predictive
as they were, they represent point-in-time assessments with candidates well prepared for their
testing session. It is not possible to replicate real life-threatening stress while in a simulator.
The simulator can help with inoculating against the stress of task overload but cannot replicate
the emotional experience of a real emergency. This makes it uncertain that the pilot’s arousal
level has been reached sufficiently to replicate or reveal any tendency to habitual or confused
behaviours when stressed.
2.16 Self-regulation Absent in Profiling Self-regulation, specifically with respect to attention management is not mentioned or
measured in any personality profile. It must be assumed that the attribute is inferred in general
underlying facets such as emotional stability and conscientious behaviour. Popular instruments
32
in pilot selection include the NEO-PI-R five factor model, a more sophisticated development
to that of similar instruments such as Cattell's 16PF (Cattell & Mead, 2008), and Eysenck’s
EPI Extraversion, Neuroticism, Psychoticism model (Bartram, 1995; Sato, 2005). A more
recent test, is the PCI by Helmreich (Musson, 2004). Since the instruments were not developed
as criterion-referenced competency assessments of SR for selection purposes, or to elicit
attention and perception ability as defined in the Endsley model of situation awareness
(Endsley, 1995), or correspond with the task-switching need defined in the Wickens model of
attention (Wickens et al, 2015) makes their use difficult for the assessor looking for direct
measures of that attribute. Descriptions of broad constructs like the popular ‘Five Factor’
Model (NEO) typically delivered without the benefit of a task analysis to specify criteria and
performance validated cut-scores. As expected, without criteria and by relying on normative
grading, predictive validities of the NEO were found to be marginal by Tett et al (1991) in the
five factors (r = 0.16 - 0.33). Adding to the long-standing problem that low validities tend to
denote low effect size, making any skilled interpretation difficult when working without a
benchmark to match attributes with tasks. Pursuing the reliability-validity issue of personality
profiles, Tett et al (1991) had been able to improve the validity of the NEO by criterion
referencing the NEO results, thereby obtaining a slightly higher overall mean validity (r = 0.38)
of outcomes with that instrument (Tett, Jackson & Rothstein, 1991).
2.17 Is it Possible to Measure the Right Stuff? Identifying and measuring “The right stuff” (Wolfe, 1979) seems reasonable, pilots need to be
assessed for their strengths and weaknesses to ensure they have the ability required for the role.
Measuring personality with self-report tests of lists of attributes, values attitudes, beliefs and
behaviours to identify the potentially competent ‘error free’ pilot candidate has endured despite
the difficulties of such prediction using trait based psychological profiling techniques. Pilot
33
performance and personality may be linked but clear identification and prediction remain, for
the present, less than conclusive for selection purposes, despite the use of multiple tests for
confirmation of attributes (Rose, Helmreich & McFadden, 1994). Research and development
of selection tests in the American military, specifically testing of pilots beyond that of skills
and abilities was relegated to post-hire evaluation (King et al 2014), for reasons that included
the requirement to adhere to the ADA Act (1990). The act had defined psychological tests as a
medical assessment contravening the principle of no discrimination in employment based on
medical grounds. Nevertheless, investigations seeking to identify the personality profile for the
competent pilot with appropriate leadership skills, have included recently developed
instruments. Helmreich’s Personal Characteristic Inventory (PCI) (Musson et al, 2004)
measures frequently occurring clusters of traits to arrive at either “The Right Stuff, The Wrong
stuff or No Stuff”; a phrase made famous in the novel about the Mercury astronaut selection
(Wolfe, 1979). In Helmreich’s model, findings were essentially a replication of the earlier study
by Rose et al (1994) the right stuff was characterised by higher instrumentality and expressivity
along with lower interpersonal aggressiveness’, while the ‘wrong stuff’ featured low
achievement orientation and higher levels of passive aggressive tendencies. Exploring and
comparing the basis for an identifiable pilot personality Fitzgibbons, Schutte, & Davis (2000)
used the NEO-PI-R five-factor model developed by Costa & McCrae (1995) in a study of 93
commercial pilots to identify the type on five major dimensions and 30 facet scales. Fitzgibbon
et al concluded from their study, that a pilot personality does exist and that pilots could be
defined as one of three types and by a particular set of traits, which they listed as “An
emotionally stable individual, low in anxiety, vulnerability, anger, hostility, impulsiveness and
depression. Typically with a high degree of (belief in their) conscientiousness, striving,
assertiveness and dutifulness. Additionally, they were active, trusting and assertive”;
replicating previous results (Hormann & Maschke, 1996; Picano, 1991) and characteristics that
34
had been noted much earlier by Armstrong (1936) discussing various forms of post-traumatic
stress disorder amongst aging WW1 aviators.
Since the purpose of such personality testing is differentiation in selection, a question arises as
to how self-report personality profiles, where weak linear relationships are found together with
unavoidable statistical error, could be improved (Tett, Jackson, & Rothstein, 1991). The
uncertainty of ‘profiling’ tests is an especially important deficit since their purpose is to gauge
pilot reaction and capability when it matters, under stress; in addition to trainability and their
leadership potential.
2.18 NEO Personality Profile & the PCI As an example, in comparing three types of tests quite different results were found using the
Millon Clinical Multiaxial Inventory (MCMI) to those obtained in the NEO-PI-R (Costa &
McCrea,1995) and the PCI (Helmreich, 2004) studies.
A key consideration in evaluating the different results is that the tests were not all delivering
the same construct with the same normative or criterion evaluation, but based on population
norms and rankings, except for the MCMI which had used the criterion of within-groups norms
from clinical populations.
Campbell et al, (2009) examined 350 USAF undergraduates in pilot training using the MCMI
(Melon, 1983), finding that in the “Right Stuff” category, the sample were highly aggressive,
dominant, exhibitionistic, impulsive and playful, in addition to being narcissistic and histrionic
(Campbell, Moore, Poythress, & Kennedy, 2009). While in the NEO-PI-R study of 93
commercial pilots by Fitzgibbons et al (2000), the “Right Stuff” category described
emotionally stable individuals, low in anxiety, vulnerability, anger, hostility, impulsiveness
and depression, with a high degree of (belief in their) conscientiousness, striving, assertiveness
and dutifulness (Fitzgibbons, Schutte, & Davis, 2000). In the third instrument, (Musson et al,
35
2004) using the PCI by Helmreich in evaluating 259 astronaut candidates most of whom had
been military pilots or were mission specialists such as scientists etc, found that the right stuff
was similarly characterised as in the NEO model by higher instrumentality and expressivity
along with lower interpersonal aggressiveness (Musson, Sandal & Helmreich, 2004).
A promising direction leading to a measure of the ideal candidate may be the research on
identifying the cognitive behavioural attributes and error inducing, internal and external
performance shaping factors that influence the person (O'Hare 2006; CASA 2015; Wiegmann
& Shappell, 2001, Hart & Staveland, 1988). Behavioural attributes and cognitive abilities were
compared in a correlational study, finding cognitive ability to be the best predictor of pilot
training performance. In the same study neuroticism showed a marginally significant
correlation at r = .25, p<.01 for the failure group (Carretta, Teachout, Ree, Barto, King, &
Michaels, 2014). The results replicating an earlier study by Carretta & Ree, (2003) of a
correlation of r = .53, p<.01 in the relation of flying performance to cognitive ability, aviation
job knowledge/experience, and psychomotor ability. p<.01 in the relation of flying
performance to cognitive ability, aviation job knowledge/experience, and psychomotor ability.
2.19 Capability and mental state The capacity to function under extreme duress has been explored with projective assessment
techniques such as the Defensive Measures Test (DMT) (Civelli & Stoll, 1990; Cooper &
Kline, 1986)(Olff, Godaert, & Ursin, 1990) to explore specific coping or SR tendencies, such
instruments are suggested as tests for resilience. Projective measures have proved to be valid,
albeit difficult to administer and require an experienced administrator to extract the necessary
data, particularly when considering the DMT. The DMT provides the opportunity to utilise a
different method than the traditional paper and pencil list of adjectives or behaviours, through
situationally based assessment like the story completion by picture cards of the Thematic
Apperception Test by Murray (1943).
36
The successful identification of neo Freudian ‘defensive measures’ amongst recruits was
demonstrated in the significantly decreased rate of pilot fatalities and aircraft crashes in the
military of several countries, including Australia. Ejections are universally the most critical
decision a pilot can make in single pilot fast jet operations and represent a situation when all
the facets of stress and the need for instant decision making are present for the pilot (Miles,
2015). The history of which shows that even in the most rigorously selected and highly
experienced pilot group, despite specific instruction, there was still a tendency in 55% of such
cases to hesitation and indecision, risking injury or death. The analysis is consistent with the
findings of retarded decision making in failed ejections (Goodman, 1999), as inattention or
distraction, indecision and delay (Nakamura, 2007), factors suggesting cognitive failure at the
moment of greatest demand.
King (2014) reinforcing the importance of mental state, conducted a practical retrospective
study using empirically derived psychiatric criteria with 12,548 student pilots in the USAF
(King, 2014). King found that those who had terminated before completing the course had
symptoms of personality disorders and had been diagnosed with clinically significant
depression or were more neurotically anxious as defined by the DSMIV (1994). In comparison,
a parsimony of effort could be achieved in the highly predictive Cognitive Failures
Questionnaire (CFQ), an instrument based on the Broadbent model to achieve greater certainty
of prediction (Broadbent, Cooper, FitzGerald, Parkes, 1982). Bridger et al were able to
correctly classify 76.8% of the sample as experiencing future strain using the CFQ in a
prospective study with navy personnel (Bridger, Johnsen, & Brasher, 2013). The CFQ
measuring specific behaviours and failures in memory, attention and action that impacted
mental alertness had shown that in a two year follow up and at an odds ratio of 2.05, those with
high CFQ scores were twice as likely to experience and succumb to ‘strain’. Bridger’s modified
workplace form of the questionnaire (Wallace & Chen, 2005) sought answers to specific
37
behaviours and frequency of actions, such as ‘forgets things, switches the wrong thing off ‘etc.
Behavioural measures, such as those have greater face validity for the end-user and tend to
build a more accurate picture of the person and what they did or do through correlation with a
standard when compared with benchmarked performance criteria. With this method,
respondents can be compared against established cut-off scores for a role to provide greater
confidence in achieving a required standard of performance, thereby ultimately reducing error
potential and safety risks.
2.20 The Pilot’s Perception of cognitive demand Being airborne constrains behaviour and decisions, inevitably made more urgent by limited
fuel, weather and landing options. Pilots operate in a continuum, ‘making decisions literally
on the fly’, without the familiar luxury of ‘pausing or pulling over’ to assess a problem on the
road. In the critical take-off and landing phases of flight pilots need to apply and switch
attention rapidly to multiple demands in setting and maintaining a specific flight path, maintain
vigilance and look out for other aircraft which may be on a conflicting trajectory,
communicating with air traffic controllers, preparing the landing parameters, to set aircraft
landing configurations, finally coordinating manual control of the aircraft for touch-down;
aspects made more hazardous by simultaneous take-offs and landings at major airports.
Thus, managing a technologically advanced $350m airliner, subject to a range of possibly
adverse circumstances in flight, requires a clear understanding of the functional and
behavioural criteria and limits for effective performance. Since the issue of stress and the divide
between performance and failure begins with what is in the ‘eye of the beholder’, Hart and
Staveland (1988) approached assessment of need from a subjective point of view in developing
the NASA Task Load Index (TLX). The resultant instrument derived 10 workload factors from
16 different experiments to provide a reliable multidimensional subjective rating scale of six
workload factors. The final dimensions of the instrument included subjective estimates of
38
mental demand, physical demand, the pace of work, performance, effort and frustration
experienced in the role and tasks as in the following extractions.
The instrument was designed to be used by the pilot or by an assessor, as a rapid and reliable
low bias indexed score of the salient dimensions of operator perception of the workload.
The NASA Subjective Task Load Index (Binder & Desai, 2011; G. Young, Zavelina, &
Hooper, 2008) has provided a well validated subjective framework for both task analysis and
accident investigation (Belland, Olsen, & Lawry, 2010).
A more objective analysis to inform the performance needs and attributes required of the pilot
has utilised ‘Cognitive task analysis’ (CTA), and its derivative, ‘Applied Task Analysis and
Task Complexity in Flight’ (TCIF) (Zheng, Lu, Wang, Huang, & Fu, 2015). Both CTA and
TCIF measure combinations and relationships between physical tasks and cognitive strategies
such as goal identification, decision making, and the judgements needed to accomplish goals.
These have been augmented as necessary by neuropsychological tests establishing criterion-
based measures analogous of piloting competencies (Carretta, 2011; Carretta et al., 2014).
Examples of the practical application of CTA occurred with the use by Endsley, Farley, Jones,
How stressful do you find the mental effort required to do this job (e.g. thinking, deciding, calculating, remembering, looking, searching, etc.)? Do you find the job/task easy or demanding, simple or complex, exacting or forgiving?
How exhausting do you find the physical activities that are required to do this job/task (e.g. pushing, pulling, turning, controlling, activating, etc.)? Is the job/task easy or demanding, slow or brisk, slack or strenuous, restful or laborious?
How much time pressure is there due to the rate or pace at which the job/tasks or task must be done? Is the pace slow and leisurely or rapid and frantic?
How successful can you be in doing this job/task in achieving the goals of this role as required? Consider if there are any problems in the way the work is done or the way the organisation supports it?
How hard do you have to work (both mentally and physically) to accomplish the required level of performance for this role?
How insecure, discouraged, irritated, stressed and annoyed versus secure, gratified, content, relaxed or complacent do you feel and does the system of work and typical outcomes in the role affect you?
39
Midkiff, & Hansman (1998), Strater and Endsley (2000) in conjunction with experienced
commercial pilots in the development of the Situation Awareness Global Assessment
Technique (SAGAT)(Strater & Endsley, 2000) assessing pilot awareness of their situation,
surroundings and elements operating in the same operational space. The advantage as detailed
by Endsley of SAGAT over the hierarchically oriented CTA with complex relations and
abstractions was the greater focus on simulation and the opportunity to introduce and assess
error inducing parameters into the study. Endsley claimed that the effect of observation in ‘real
time’ assisted in the reduction of statistical measurement error and to reveal hitherto hidden
anomalies through direct observation of task execution. In their model, the simulation would
be paused and the pilot questioned regarding the situation. Strater and Endsley (1995) utilised
the concept of situation awareness as involving perception, comprehension and projection of
the flight elements, as the basis for classification.
2.21 Cognitive Load and Experience Prince and Salas (1998) explored the nature of the effect of experience on cognitive load
comparing the behaviours of general aviation pilots with respect to their levels of experience
(variously with 700, 6000 and 12000 hours of flying time), finding that the gradient of
experience from high to low also reflected the extent to which pilots were respectively either
proactive or apparently passive in their flight preparations. In cognitive-behavioural terms, the
most highly experienced check captains spent more time projecting the potential of the
elements in the coming flight, whereas the least experienced were most concerned with
accessing the minimal information needed for the flight. An aspect which could be interpreted
as low time pilots needing to engage more mental resources to manage the information load in
the flight preparation stage, possibly with an elevated level of concern at not acquiring the
necessary detail. Effective threat and error management defined as anticipation or looking
beyond the immediate circumstances by the experienced pilots was deemed to be a
40
differentiating competency. Another differentiating factor noted by (Eldar & Bar-Haim, 2010;
Todd & Thomas, 2013) in a review of low and high time pilots in three Australian airlines was
the lesser situation awareness of low time pilots when compared with their more senior
colleagues. Reflecting an increased mental load when trying to be competent very consciously.
Experienced pilots, by contrast, operating with less self-preoccupation, in an unconsciously
competent way made greater use of their mental resources. The extent of the difference between
novices and the experienced pilot was also evident in a further study of pilot decision making
in simulator-based weather-related decision exercises. The study showed that experienced
pilots managed their cognitive load so as to be less engrossed in evaluating data, by utilising
heuristics and generalisations in problem-solving more than novices (Wiggins & O’Hare,
1995). A finding replicated in a later study where pilots managed their cognitive load by the
greater use of cues that require fewer cognitive resources and anticipation, by dealing with a
few ‘chunks’ of information rather than grappling with a mass of detail (Wiggins, Azar,
Hawken, Loveday & Newman, 2014). Self-confidence gained by experience allowed the
greater use of cues and heuristics; an example of natural self-regulation of mental resources
under load. The role of ‘ego’ in pilot behaviour has featured as being at the core of numerous
incidents. From indecision to eject and crash a multimillion dollar aircraft for fear of losing
flying status, overriding critical information from others due to own seniority, to engaging in
risky and unnecessary behaviours with fatal potential simply to impress others. More typically,
avoiding responsibility for poor decisions and not reporting deficits or flight disqualifying
ailments. The strength of identity amongst pilots, with most seeing it as a life-long profession
increases sensitivity and reluctance to be measured or grounded due to errors (Ashcraft, 2005;
Fraher & Gabriel, 2014).
2.22 Complacency and awareness
41
Aircraft systems are complex but still need a pilot. While the need to remove ‘pilot error’, as
the leading cause of incidents has encouraged the trend to full automation, relegating control
of various technical processes to a self-managing system with an electronic monitoring device
in the cockpit has delivered the potential for yet another type of problem. Prolonged exposure
and reliance on automation have been shown to induce complacency and loss of anticipatory
attention risking poor decision and response to emerging risks (Prinzel III et al., 2001). The
second most frequent of these types of incidents emanating from over-reliance on automation,
being controlled flight into terrain (CFIT) (Richardson & Lang, 2005), typically where critical
weather-related decisions were required in transitioning from a visual to instrument
meteorological conditions, described by Wiggins as an over-reliance on the technology despite
apparent cues and conditions to the contrary (Wiggins, 2007). Pope and Bogart (1992) coined
the phrase “hazardous state of awareness” in their study examining psychophysiological
predispositions associated with the passive monitoring state. Complacency includes rumination
a deactivation of alertness and vigilance produced by low stimulus of feedback, experienced in
monitoring tasks where no response is necessary by the console operator. A common feature
identified as a significant hazard in high-reliability air traffic control, petrochemical process
plants and road traffic grid-control systems where the task involves monitoring without input
(Prinzel III et al., 2001).
2.23 Automation a Reverse Problem
Most training in aviation continues to be about the technology, the engineering and control of
an aircraft in the air and in returning it safely to the ground. Training typically involves the
rehearsal of combinations of specific aircraft management procedures designed for specific
situations. Training on particular types of aircraft (ie, time on type) and rehearsing problem
scenarios has been seen to benefit the development of fluent and fault-free execution of
procedures (Casner et al., 2012); but has also risked ‘automaticity’ an unthinking response with
42
a similar action or sometimes no action at all. Automaticity represents habit formed errors in
the rapid transfer of skills to a different or new and less familiar cockpit environment evident
in incident reports as activation of the wrong control. A familiar parallel sometimes seen when
driving a different make of car, with the inadvertent activation of the wiper blades instead of
the turning signals. Rehearsal and practice in simulators resembles the older techniques of rote
learning, doing it until it is done correctly, so that with constant correct application incorrect
procedures are inhibited or extinguished, and correct procedures are reinforced to be more
likely to occur in a crisis.
Increased automation of the flight deck seeks to alleviate cognitive demand by presenting
information via synthetic displays viewed as flat panel computer screens, referred to as 'glass
cockpits' rather than a mass of analog dials. Unquestionably these have made a significant
impact on pilot workload and error management but still requires that cockpit data be delivered
as a moving collective or summary for anticipatory and pre-emptive action, by projection of
the outcome of the displayed data. Ideally emulating Endsley’s (1995) SA, with the aircraft
system detecting, analysing and projecting outcomes as choices for the pilot. Improved design
for safety and efficiency has changed the functional nature of the pilot’s task but not the
capacity to cope with stress and pressure to maintain attention (Casner, 2009). Meanwhile,
individuals continue to forget procedures, become complacent and rely on the system data
presented ‘after the fact’ for decision and action.
At the low end of the stress spectrum, the elegance of the technology may encourage trust in
the system and add further to another problem, that of ‘reliability-induced complacency’
(Casner & Schooler, 2015). At the upper end of the stress spectrum, the unpredictable and
chaotic nature of crisis, with the potential to surprise, overwhelm and disrupt the pilot, can
exacerbate and expose a vulnerability to cognitive failure and an inability to think, act safely
and accurately (Broadbent, 1982). Despite the added training, numerous structural and
43
procedural changes made in aviation, ‘pilot error’ continues to feature at the core variously
quoted as 70-90% of aviation incidents, highlighting the complexity of the system and
vulnerability of the pilot.
2.24 Necessity to manage the self A pilots’ priorities are to “aviate, navigate, communicate,” to aviate meaning (maintain aircraft
control), navigate (maintain track to destination) and communicate (inform intentions to others
in the airspace). The complexity of flying an aircraft is increased with the added need to manage
multiple systems (involving visual information displays, pressurisation, backup facilities for
undercarriage, engine fire, flaps, fuel transfers, electrical power, etc.). Beyond these functional
tasks, the pilot’s capacity to manage themselves, to make decisions and operate competently in
a timely way, according to numerous procedures, has been investigated by researchers focusing
on pilot behaviour and cognitive processes. Adams (1993) writing on how ‘expert’ pilots think,
(Adams, 1993) had concluded that speed and accuracy coupled with good memory
distinguished the expert pilot. Cognitive competence in Adams findings corresponded with the
notion of a mind ‘unfettered’ by cyclic worry thinking, fixation and preoccupation, providing
the maximum of attentional resources to the task.
In ‘Attentional control theory’ (M. W. Eysenck et al., 2007), suggested the first thing to be
forgotten when stressed was likely to be the recommended procedure, even in the proximity of
checklists (Dismukes & Berman, 2010). Despite this common experience, there has been no
formal behavioural training or technique that a pilot, controller, driver or operator can invoke
to clear the mind and overcome defensive ‘mental blocks’ or some other worrying
preoccupation at the stressful moment. The threshold at which an individual may succumb at
the extreme to defensive ‘freezing or panicking’ varies and in addition to the magnitude of the
mental load has been found to be dependent on moderating factors such as self-efficacy and
self-esteem. Reinterpreting risk or threat (Zeigler-Hill, Chadha, & Osterman, 2008) through
44
experience as manageable or survivable helps to overcome adverse mental states resulting from
defensive retreat and denial styles of coping (Monat & Lazarus, 1977, p152; Folkman et al.,
1986). Traditional means of raising the coping threshold have involved reinforcement through
exposure-based inoculation and desensitisation, development of successful management of
similar events or formal training (Boucher, 2011; Staal et al., 2008). The sudden and
unexpected nature of emergencies makes the development of self-efficacy critically important
in managing later stress (Rochat, Billieux, & Van der Linden, 2012). The ability to switch from
intrapsychic or self-focused thinking style to an externally directed one (Broverman & Lazarus,
1958) is an essential competency. The current fast track training syllabus for the Multi-Crew
Pilot License (CASA, 2015) introduced to expedite novice pilot training discusses self-
management but provides no specific behavioural training that builds self-regulating
competencies for new pilots.
Pilots need to be able to function expertly when suddenly confronted with a life-threatening
potential, such as imminent collision trajectories, engine or structural failure, jammed controls,
invisible wind shear, fuel loss and onboard systems failure (Casner, Geven, & Williams, 2012).
While systems issues have lethal possibilities, so do those that act on the executive in the mental
loop through visual and physical disorientation, fatigue and confusion. For example, inability
to comprehend rapidly changing cockpit instruments in an uncontrolled descent will inevitably
cause flight into terrain (CFIT) under any condition.
Cognitive Resilience (CR), the ability to deliver mental performance in the face of sudden or
prolonged psychological loads as described by Staal et al., (2008), is generally viewed as
‘bounce back’ the positive ability to adapt, improvise and recover from adverse situations and
mental states, rather than freeze, ignore or panic in those situations. CR is implicitly defined as
involving hardiness and a positive coping style with constructive defensive mechanisms or
compensatory measures that enable cognitive performance despite adversity.
45
Eysenck et al., (2005) cited the impact of affective states and Dornic (1980) reported on the
interfering effect of anxiety on performance, finding that the affective state of anxiety required
the supply of significant mental effort to overcome a crisis. Consistent with the view that
anxiety impacts the working memory system to disrupt attention and inhibit processing (
Eysenck, Payne & Derakshan, 2005). The extent of a person’s cognitive resilience thus being
dependent on their defensive repertoire or how well reactions are regulated when demanded.
Cognitive resilience is invoked to avoid cognitive paralysis when threats demand a response
(Leach, 2004). CR could be a defence to basic emotionally generated survival responses and
inhibitions that also include maladaptive behaviours such as aggressive impulsiveness. The
potential for a disaster in aviation emanating from inadequate responses and decision making,
due to poor cognitive recovery, is significant, to the extent that airlines now address the issue
through TEM training (Thomas, 2004) (ICAO, 2005). TEM training is designed to sharpen
anticipation and an implicit recognition that the last line of defence in the airborne socio-
technical system is the crew. TEM training fits with and expands the crew’s existing CRM
interaction skills, with projective exercises, in both the simulator and more conventional
checklist and advisory form. However, TEM and CRM may raise the individual threshold of
susceptibility through being forewarned but neither provides the crew with a self-initiated
activating skill to recover their attention when overwhelmed and under duress. Pilot attributes
such as situation awareness and cognitive resilience have been well researched in functional
and neuropsychological terms attesting to their ability to predict success in pilot training
(Carretta, 2011; King et al., 2013; Sulistyawati, Wickens, & Chui, 2011). However, classroom
and simulated TEM while designed to enhance the anticipatory action and prime readiness for
action, execution relies on the individual and their personal state (Fornette et al., 2012). Pilot
error as at the origin of 70% or more of flying related incidents (ATSB, 2007, p38; ATSB,
2014, p39) continues to be at the source of most fatal incidents. Since few incidents have no
46
contribution from error made by pilots, it is necessary to address self-regulating mechanisms
to recover attention or ‘presence of mind’, to operate resiliently unaffected by preoccupations
or loss of mental energy due to accumulated fatigue (Vine et al., 2015) and the effect of anxiety
or depression, as described from a trait-based perspective in the ‘Attentional Control Theory’
(M. W. Eysenck et al., 2007).
2.25 Summary of Need for self-regulation training
Improved training to cope with the growing demands of safety-critical roles is imperative. In
this chapter, behavioural themes, ‘performance shaping factors’ and cognitive task analysis
have emphasised the need for effective SR skills in one such safety critical occupation, the pilot
domain. Reinforcing SR as the means for goal directed behaviour and achievement is shown
in Table 2.2. Hofmann et al., (2012) detailing core behaviours and functional abilities that
contribute to competent task execution. The list showing attributes that converge on attention
for executive functioning, working memory, inhibition and task switching (W. Hofmann,
Schmeichel, & Baddeley, 2012), together with eight behavioural markers as performance
shaping factors. The development of SR in behaviour commencing in early childhood through
to adulthood has been identified as a trainable attribute for the development of attention (Posner
et al., 2014). The distinction between control and regulation, however, does not have a clear
boundary or suggest whether the two can or need to act in tandem. Control seems to pivot on
inhibiting impulses to reduce ego-depletion and mental effort (Baumeister, Gailliot, DeWall,
& Oaten, 2006). Self-regulating behaviours are more plan-full for the management and
achievement of objectives. SR training can reduce responses to social threat by modifying
attention and subsequent stress reactions (Baert, Casier, & De Raedt, 2012), and recovery in
sports (Behncke, 2004).
47
2.26 Aim of the Study SR acts to control the achievement of objectives under cognitively demanding conditions by
actively monitoring and managing mental state to decrease cognitive overload, effect of fatigue
and negatively charged preoccupation.
1. The aim of the study is to evaluate the take-up of a SR technique as an instantaneous
recovery of attention and mental effort.
2. To test the proposed method as an unsupervised online delivery in a naturalistic
context embodying overload resistance due to cumulative diurnal fatigue.
3. User acceptance of the method will include self-reports of ease of acquisition and
utilisation of the technique outside of the study.
4. Baseline test scales used as performance shaping factors will be assessed to predict
the cognitive-behavioural connection of self-regulation by study completion.
48
3. SELF-REGULATION TRAINING
Self-regulation (SR) is a ubiquitous phrase in psychology, the key to performance and pivoting
here on the maintenance of attention in the pursuit of goals and objectives. The development of
SR is central to self-management and success in a variety of occupations, in sporting skills and
relationships. Several forms of SR training are explored and compared with conventional, virtual
and meditative perspectives.
Del Giudice (2015) described SR as the exertion of ‘effortful control,’ an executive function
underlying cognitive resilience (CR) with the purposeful ability to recover from adversity or
overload and to continue to function as required. Theories of SR and self-control (SC) linked to
attention tend to be interpreted as belonging to either resource, capacity or network models.
Because of the similarity of SC and SR, a clearer distinction was required between the two.
3.1 Self-Regulation and Self Control Kopp (1982) in reviewing the antecedents and development of SR, concluded that self-control
was less flexible and adaptive than SR. Kopp using the Oxford dictionary (1964) definition of
control meaning “hold in check”, with ‘regulate’ meaning “subject to restriction, rules and
adaptation” (Kopp, 1982). By contrast, Posner’s network attention theory (ANT) suggests the
difference evolves as a stage in the development of the attentional networks; self-control maturing
in the child to self-regulation in the adult, working in parallel with concurrent socialisation and
nurturing influences (Posner & Rothbart, 2009).
Traditional training approaches to improve SR and SC have tended to be based on the individual’s
emotional regulatory process or their cognitive resources. Staal (2004) suggested a transactional
model where an individual’s tendency to negative appraisal of threatening events, would
determine their mental state and subsequent performance. Here the transactional model involving
a motivational dimension, explains the ability to modify or improve SR with training. A view that
contrasts with the original apparently fixed resource or capacity models of Kahneman (1973) and
Wickens (1992). Posner & Rothbart (2009) however, see the development of SR based on the
49
ANT theory, as developmental occurring with growth in connectivity of the brain attentional
networks that relate to SR, further development of ability in the network model being possible
with specific training exercises.
Self-regulation is a construct that involves various self-management activities, mental states and
associated behaviours (Table 2.2) (Hofmann et al, 2012). Del Giudice (2015) suggested that a
self-regulating act can be proactive, either explicit, overtly deliberate or evolve from unconscious
decisions and valent impulses. Berger et al (2007) saw SR as more to do with monitoring and
self-control, as a reflex, adaptive or defensive behaviours, mediated in turn by the intensity and
temporal needs of the moment (Berger, Kofman, Livneh, & Henik, 2007). Hofmann et al (2012)
draws a distinction between SR and SC, while elsewhere they appear to be used interchangeably.
Hofmann et al saw SR as similar but different to SC which is deemed to be a narrower set of
behaviours, potentially a subset of the broader SR, which were more directly involved with
inhibiting and overriding unwanted impulses and reactions. In the Posner & Rothbart
developmental model, the ability to self–regulate and develop a competent ability to manage the
self, is crucial for social, academic and occupational achievement. SR allows the individual to
adapt to fulfil their intent through their executive faculties and cognitive control of attention and
management of affective states. SR as the executive provides the means by the individual to
withstand difficulties, distractions and overload firstly through planned strategies then through
the timely actions of SC. Suggesting that self-control is a discretionary instrument and surface
manifestation, a momentary expression of a psychologically deeper SR.
Limitations of SR as a limited ego resource was discussed by Baumeister et al., (2006) who saw
depleted ego resources as also diminishing SR (Baumeister, Gailliot, DeWall, & Oaten, 2006; Li,
Nie, Zeng, Huntoon, & Smith, 2013; Vohs, 2005). The question of the source of mental energy
and how it is recovered when depleted, had been investigated by the manipulation of motivation
with added incentives by Muraven & Slessareva (2003), the results of which had shown a direct
effect on ego depletion and subsequent effort. Inzlicht and Schmeichel proposed a mechanistic
50
resource model in which they sought to explain the Baumeister et al., ego depletion model of SR
as due to process rather than capacity. Such that mental effort in SC consumed in a preceding
activity was not immediately recoverable for a later one, referring to ego depletion as depletion
of strength of motivation and attentional focus (Inzlicht & Schmeichel 2012). Baumeister et al.,
had suggested that recovery of depleted ego resources could occur by strengthening SR through
practice, somewhat like muscle building Baumeister et al., (2006). While others such as Capa et
al., (2008) and Staal (2004), had previously concluded that the sustainability of effort had a
motivational dimension preceded by the individual’s expectation of success. The process-based
view appears to tap the omnibus construct of motivation as the available resource suggested by
Hofmann et al., (2012). Baumeister’s reference to ego strengthening with practice however,
provides a possible path for motivation to translate into mental effort through habit formation.
The chunking or assembly of an action sequence into a performance unit or habit, reduces the
level of mental effort required for repetition (Dezfouli & Balleine, 2012; Schmid, Wilson, &
Rankin, 2014; Smith & Graybiel, 2014; Yin & Knowlton, 2006). Comparing process and capacity
perspectives suggests that the ‘capacity’ in the resource model could be more than just a
metaphor. As demonstrated in a practical test by Gailliot, Baumeister et al., (2007) in which blood
glucose was manipulated to mediate self-control, finding that increasing glucose counteracted
ego-depletion; in parallel with the finding that glucose improved cognitive ability and helped to
counteract fatigue (Kennedy & Scholey, 2000; Owen, Scholey, Finnegan, & Sunram-Lea, 2013);
(Fairclough & Houston, 2004).
The view that SR is a self-monitoring mechanism not confined to a single process explains how
it acts differentially in separate functional domains as cognitive SR and emotion SR (Berger et
al. (2007). A position building on the view that SR is a global underlying executive directing
effortful control (Fonagy & Target, 2002; Kopp, 1982). Viewing SR as both a single underlying
process and one that can be selectively directed may seem to be a more logical, simpler and a
familiar explanation where emotion and reason vie for priority in decision and action. In this way,
51
the individual who has little need for cognitive control but more for emotional regulation at a
time, may choose to focus their energy and efforts accordingly. Both cognitive and emotional
perspectives suggest the possibility of a remedy consistent with the Baumeister et al., (2007)
emphasis of SR as being trainable so that mental effort can be improved or recovered.
3.2 Behavioural markers of Self-Regulation Self-regulation as an executive process is also visible in the behaviours of the two broad mental
states of coping posited by Monet & Lazarus (1977). They noted that preoccupation that comes
from concern, worry and fear, was a performance inhibiting characteristic related to an internally
focused mental state and that it reduced external awareness and responsiveness (Monat, 1977).
The internalised form (preoccupied or possibly beset by erroneous or incoherent thinking), tended
to seek avoidance and escape of the discomfort from perceived threat, rather than confronting the
problem. Direct action coping behaviours by contrast, were those they characterised with
immediate action to address a problem or to remove a threat. While the externally oriented mode
(represented by direct action coping) tends to be favoured as having greater potential for success,
it must also be accepted that on occasions avoidance behaviour can also be a more rational or
economic alternative to confrontation.
3.3 Methodological Issues in Evaluating Self-Regulation The object of SR is some performance and the achievement of a goal. However, SR is also present
in the various behaviours that sum to that achievement. Measuring and evaluating SR
operationally is facilitated by standardised behavioural markers that help to bring the various
neural and motivational perspectives used in describing SR towards a uniform taxonomy.
Attributes of operational performance are listed here in a proposed model of interdependent
competencies (Fig 3.1), in which each level provides the foundation and strength for the one
above, such that an increased capability of one will enhance or increase the capability of the next;
similarly, a weakening of one will reduce the capability of the next. The model (Fig 3.1) is
described here in behavioural rather than in a neurological form but consistent with attention
52
network theory involvement of the thalamus, cingulate gyrus and prefrontal cortex in enabling
behaviour, adaptation and subsequent learning in the brain system. The behavioural model is thus
convergent with the cross modal attention network, relating to the alerting, orienting and
executive functions in the developmental and occupational context (Posner & Rothbart,
2007)(Posner, 2012). Additional behavioural level contributions from the Monet et al., (1997)
theory of internal and external coping styles and Endsley’s (1995) performance-oriented construct
of situation awareness that underlie the key behaviours for performance under stress augment the
model. As a reference, at the operational level, the awareness, perception and anticipatory skills
involved in expert decision making by pilots, requires various forms of SR with effortful control,
at each stage or level of dependency, consistent with the demand made on the individuals personal
agenda, stress tolerance and the urgency of need. (Adams, 1993)(O'Hare, 2006).
Performance dependencies Behavioural Markers
Can see things others may miss
Ability to avoid becoming fixated
Can switch rapidly between demands
Remembers procedures and exceptions
Remembers despite interruption
Can anticipate sudden changes
Can deliver the necessary mental effort
Less vulnerable to emotional preoccupation
Figure 3.1 Proposed Hierarchy of Performance dependencies and behaviours
53
3.4 Comparison of Effect Size by Training Methods A common measure such as those established as ‘behavioural markers’ (Klampfer et al., 2001)
could provide a more uniform standard for evaluation and meaning for effect size differences.
The essential difference being the focus on specific observable and measurable acts rather than
inferred personality traits or attitudes, to establish potentially causal relationships and a
common language for utility in application. However, assembling meta-analytic studies of the
efficacy of different training strategies for the self-regulating competencies (fig.3.1), including
the underlying attributes and cognitive resilience overall, revealed few in which the
development group reported pre-post effect sizes for comparison, as defined by Rosnow
(Rosnow, Rosenthal, & Rubin, 2000). Similarly, a lack of consistency in specifying and
identifying behaviours and other attributes introduced ambiguities in their evaluation.
Harmonised occupational markers with a consistent behavioural theme would help to clarify
and standardise the nomenclature allowing for specific performance criteria to be established to
gauge the efficacy of any training.
3.5 Conventional Training Approaches Studies concerned with meditation, mindfulness, zone training and yoga, have until recently
tended to the anecdotal rather than experimental and have rarely listed any metrics or comparative
methodology. Therefore, the selection of studies was limited by categorisation of those from one
or other of the five methods of training as grouped in (Table.3.1) as being either practical
(categories 1,2) or metacognitive methods (categories 3,4). All studies were obtained online via
peer-reviewed journals, from the year 1995 to the present. Conventional training (Table 3.1) has
been well demonstrated to be a beneficial and effective means of transferring skills. Wickens et
al. (2013, p369) commented that when the training was about invariant emergency procedures
that needed to be retrieved rapidly, performance was best for well-formed habits retrieved from
long term memory when under stress. The studies included in the conventional training category
indicated a moderate effect size for task performance outcomes (Table 3.1).
54
However, the specificity of such skill meant that it tended to be vulnerable over the longer term
to a variety of issues. Skill erosion through a lack of currency and changes in the context or
operational, technical and instrumentation differences require constant updating Recent types of
SR training to ensure task compliance have tended to be of a practical form such as threat and
error management for aircrews and executives. The training is focused on preparation,
anticipation of threat and the development of an expectation of the inevitability of error. It is
primarily about crew resource management in the context of the flight deck but delivered in a
traditional classroom. The benefits of well-tried conventional forms of pedagogy are numerous
and include the immediacy and direct reinforcement by expert tutors, group interaction with
participants, responsiveness to student apprehension or befuddlement and the logistic benefits of
having all persons in the same place.
Simulators familiarise, diminish apprehension due to uncertainty and help to lay down action
sequences, simply gaining familiarity with a procedure can serve to raise the stress threshold for
that activity, potentially decreasing the demand made on attention resources and resilience (Keith
& Frese, 2008). Extensions of simulators to ‘Virtual Reality’ (VR) have found application in the
military, aviation, medicine and industry as another form of immersive training. These provide
benefits on the immediacy of access via computerised applications and the ability to set standards
of delivery. Additionally, meta-analytic studies to date have shown VR simulators for training in
Methods of Training Studies
N Sample
N
Effect size Cohens d, Hedges g
Effect Size Sources
1a. Conventional
1b. Simulation
2. Operant learning
397
24
19
15627
2183
2818
d 0.62
d 0.44
d 0.51
(Arthur, Bennett, Edens, & Bell, 2003)
(Keith & Frese, 2008)
(Stajkovic & Luthans, 1997)
3. Mindfulness 1
1
48
174
d 1.44
d 0.58
(Jensen, Vangkilde, Frokjaer, & Hasselbalch, 2012; Lebuda, Zabelina, & Karwowski, 2016) (Carmody & Baer, 2008)
4. CB Counselling 13
27
2334
1496
d 0.96
g 0.73
(Aldao, Nolen-Hoeksema, & Schweizer, 2010; S. G. Hofmann & Smits, 2008; Spek et al., 2007)(Spijkerman, Pots, & Bohlmeijer, 2016)
Table 3.1 Comparison of mean effect size by training methods
55
complete and complex surgical procedures were more efficient than basic simulators (Larsen,
Oestergaard, Ottesen & Soerensen, 2012). A meta-analysis of 14 studies of resilience training in
the military provided further support for efficacy of the method (Pallavicini, Toniazzi, Aceti, &
Mantovani, 2016). Behavioural and cued techniques are essentially reactive, reliable in response
to some prompted need, but not necessarily adaptive, and tend to be vulnerable to habituation. A
self-initiated operant strategy by contrast allows for discretionary responding when cued by
intuitive summations of observations or situational patterns.
3.6 Behavioural Operant and Cued Techniques The context here becomes incidental as the reward for exercising the self-initiated operant is
intrinsic and independent of time and place.
The self-initiated operant can itself withstand disruption or interference, and even increase if
greater effort or tempo of application is needed. The technique is consistent with Thorndike’s law
of effect which states that “Responses that produce a reward will occur again in that context”
(Gendolla et al., 2015, p158). In behaviourist terms, the reward complies with the notion of
contiguity, as when the reward availability is ‘soon, certain and positive,’ it is effective as
reinforcement and perpetuation. Operant conditioning involves a stimulus and reward, the
mechanism could be utilised to deal with preoccupation and deliver relief from anxiety and other
uncomfortable affective states (Skinner, 1953).
Activation of the self-initiated operant can be imperceptible or covert, have immediate effect and
occur without confounding any other task, meaning that uniformity in training is possible due to
independence of context or events. Both similar and general uses of operant techniques have
been reported in the clinical and educational literature to manage adverse mental states.
Cues are generally of two forms, specialised or common. Specialised cues form part of the pattern
matching that informs the expert for better decision making (G. A. Klein, 1997; M. W. Wiggins,
Azar, Hawken, Loveday, & Newman, 2014). They are sought to augment their understanding of
ambiguity, to reveal the truths behind concealed actions and to inspire the next move in dynamic
56
situations. Common cues exist to regulate, safeguard and reliably direct individuals to their
destinations. For example, everything from signs to siren alerts will bring a person to an attentive
state. However, a negative aspect of ‘common’ cues and signals is the tendency for repetition to
diminish their potency, such that habituation decreases their effect over time and distance (Cevik,
2014). Humans have a relatively meagre memory for odours when compared to animals however,
the directness of the neuroanatomical link between the olfactory bulb, the amygdala and
hippocampus, as the neural substrate of memory, provides a rapid direct path to emotional
memory.
Herz and Schooler (2000) presented the evidence that memories evoked by olfactory means
(odours in this reference), “were able to be distinguished by their emotional potency”. They found
that olfactory cues were reported as having a greater ability to tap emotional memory than other
stimuli, such that odours represented a special class of psychophysiological cues. The capacity
for odours to recall emotional memories was further demonstrated by Herz et al where the recall
of emotional autobiographical memory was significantly greater with an olfactory cue than by
any other sensory modality (Herz & Schooler, 2000). Herz et al drew the further distinction
between memory selection and recollection, stating that “it was during recall that the odours
exerted emotion” (p21). They concluded that the emotion brought forward did not retrieve the
specific details of the memory. Apart from the ability of the olfactory cue to access emotional
memory, the Herz et al., observation was that an olfactory cue, could retrieve an emotional
memory more effectively and possibly more rapidly than any other sensory mode, consistent with
separation of the olfactory pathways. The olfactory system may also be able to potentially provide
a rapid path to a select memory if paired at the time of creation, by an operant.
3.7 Metacognitive Self-Regulation Techniques Metacognitive SR techniques monitor and control thinking by maintaining emotional equilibrium
disengaging fear, anger and anxiety to provide a state that is neither aroused nor at rest but open
receptive and responsive. Meditation is a somatic technique that typically involves reflection and
57
exploration of personal thinking processes on the path to emotional equilibrium. Other
metacognitive techniques seek to achieve specific performances, with methods such as
visualisation and affirmation to clarify and focus the achievement of an objective. Cognitive-
behavioural methods (CB) used in therapy represents another form with the added intent of
challenging erroneous thinking and marrying ‘new’ thinking with successful personal action.
Several metacognitive techniques have been developed to enhance specific deficits in memory
recovery and social skills. Techniques vary from those that focus on body states to those that
liberate from self-preoccupation. As an operational method that readies the person for action,
meditation produces behaviour and thinking that is inherently vulnerable and uncertain in crisis.
Cognitive reflection is an inwardly focused state (Monat and Lazarus, 1977. p150) that is not
engaged with external reality and hence unsuitable for operational requirements that demand an
instant remedy. As an example, Keith and Friese (2005) investigated error management training
involving both simulators and metacognitive techniques, reporting that combined SR or
stabilisation of emotion and metacognitive activity successfully mediated performance
differences involving error induced events that required responses to unique situations. Keith et
al had also determined that the approach was better than avoidant and analogous transfer
techniques (Keith & Frese, 2005), lending further support to cognitive recovery and resilience as
an important performance enhancing factor. Trial and error practice has a degree of certainty as
a skills training method, but is reliant on habit formed responses generally not adaptable due to
the invariance of habit, for rapid recovery of attention and to free up cognitive resources when
needed in a variable and dynamic situation.
3.8 Cognitive Behavioural methods Amongst the cognitive-behavioural approaches, a widely-used method of self-management for
performance has involved a self-initiated process involving imagining the faultless achievement
of some needed action and objective, the channelling of thoughts and action. The simplicity of
the process involves an imaginary rehearsal with a successful outcome of the procedure.
58
The method serves to displace anxious preoccupation with success rather than anticipatory failure
in a mental sequence. By recalling a successful flow of the rehearsed process, the method
subsequently helps to prompt and cue-specific actions, such as a cockpit checklist, a tennis
strategy, perfect delivery of a speech or consistent application of a hospital protocol. The benefit
of the method is in the simplicity and utility of the approach and the ability to be invoked when
needed. However, its limitation is specificity of action. It is unlikely that the imagined flow in
playing the piano faultlessly will translate easily to jumping hurdles, conducting an engine failure
procedure in the air or some other unrelated performance-based activity. Nevertheless, the
essential mechanism, the replacement of worry and concern with emotional equilibrium, allows
for purposeful task-relevant behaviour to occur with less cognitive hindrance. The effects of
displacement of self-consciousness, emotional preoccupation and fragmented attention in
performance is a change in mental state, the effect described by Csikszentmihalyi (1990) as the
“Peak Experience” a positive and highly desired outcome of the ‘Flow’, or being in the ‘Zone’.
He described the ‘Flow’ as a mental state where no preoccupation, self-awareness or concern
existed, where all actions and cognitions were natural, effortless and made without error. Being
in the ‘Flow’ was associated with unconscious excellence and performance across all types of
sports (J. A. Young & Pain, 1999). The development by Nideffer (1976) of the attentional and
interpersonal styles theory similarly connected cognitive processes and emotional arousal, which
were specifically correlated with improved performance in sports.
Behncke (2004) summarised other cognitive-somatic methods which were relatively
straightforward and prevalent in sports, such as Schemas or patterned action, to produce a
deliberate reaction and response (Behncke, 2004), somewhat like the boxers automatic ‘jab and
parry’ ritualistic training exercise, that trains to avoid the slow evaluative pause in thought. Other
similar methods include Visuo-Motor behaviour rehearsal, Set theory, CB methods and variations
or combinations of those, all serving to deliver unencumbered action and dispel affective mental
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constraints through positive ‘Self-Talk’ in achieving performance (Hatzigeorgiadis, Zourbanos,
Galanis, & Theodorakis, 2011).
3.9 Self-regulation through Mindfulness A key outcome of SR is the management of affect. Mindfulness based stress reduction
mechanisms assisted by ‘Diaphragm Breathing’ behaviour (Ley, 1999) significantly reduce
negative emotion, reactivity (Brown, Goodman, & Inzlicht, 2013) and improve deployment of
attention (Goldin & Gross, 2010). In the version of mindfulness based on the Attention
Restoration Theory (ART), Kaplan focuses on attention and emotion regulation to manage
depletion of the executive function by engaging with the environment (Berman, Jonides, &
Kaplan, 2008; J. Kaplan, 2001; Kaplan & Berman, 2010; Friese, Messner, & Schaffner, 2012).
The Kaplan theory of ecological mindfulness training is a means for release from preoccupation
or stress achieved by the calming effects of immersion in nature. The method has found support
with evidence of the release in tension produced by more stressful closely built environments
(Berman et al, 2008). Mindfulness in its more usual form has been applied to a variety of clinical
and non-clinical experiments related to social anxiety disorder, generalised anxiety disorder and
error potentiated self-deprecation (Ley, 2003; Delgado et al., 2010; Teper & Inzlicht, 2013).
Underlying the subjective experience, the neurobiological effects of meditation and mindfulness
have indicated alterations of gray and white cranial matter providing evidence that the
mindfulness technique was something more than a mere temporary reduction of tension (Esch,
2014; Esch, Fricchione, & Stefano, 2003).
The Mindfulness method involves de-centering, development of self-compassion, and
progressively the reduction of self-preoccupation, to mediate beneficial change (Holas &
Jankowski, 2013). The general effect of Mindfulness as a psychophysiological method have
found gradual acceptance in organisational training in hospitals and aviation, with further
application in the improvement of student cognitive ability (Chiesa, Calati, & Serretti, 2011) by
mediating academic self-efficacy (Keye & Pidgeon, 2013). The somatic methods include
60
relaxation, self-contemplation, abreaction, meditation and the now popular Mindfulness training.
The methods, firstly involve focusing on the self then altering perception and meaning to then
refocus attention - away from the self (Dane, 2010; S. Kaplan, 2001; Prakash, Hussain, & Schirda,
2015). To achieve the desired state, they all share the same mechanism used to stabilise affect.
The achievement of equanimity thus results in more available energy and less inhibition of
personal performance. The method remains popular notwithstanding that they may trigger
cathartic outcomes from the release and surfacing of intense past trauma. The need to escape the
memory of trauma can have the reverse effect in producing increased inhibition and withdrawal
(Finkelstein, Wenegrat, & Yalom, 1982b; Sinhger & Ofshe, 1990) (Gilbert, 1999; Paul, Elam, &
Verhulst, 2007). The possibility of uncontained abreaction in mindfulness training is an issue as
the technique has no established method of dealing with those, unlike CB methods or
psychoanalysis. Despite the absence of tactical management procedures, introspective
Mindfulness involves voluntary self-exploration and is less likely to introduce the same level of
risk when delivered in organisational settings; unlike that experienced in the personal growth
movement seminars of the 1970’s and 80’s in which cathartic re-growth in the absence of close
management of negative effect was seen to have had unpredictable outcomes (Finkelstein,
Wenegrat, & Yalom, 1982a; Glass, Kirsch, & Parris, 1977).
Overall, Mindfulness has been demonstrated as a positive means of clearing the mind, although
it takes some time to reach ‘satori’ or perfect equanimity as the Zen would say (Odajnyk, 1998).
Vulnerability to disruption by crisis is addressed in the Zen by the training to ‘quiet the mind’
and ‘knock the monkey off the shoulder’ (often by the deliberation of Koans, a series of
impossible propositions given to engage the mind), to achieve recovery.
3.10 CB Methods and Counselling Cognitive behavioural methods (CB) are a set of mainstream techniques and procedures now
operating in most therapeutic interactions, variously as cognitive behavioural therapy or cognitive
behavioural training. Hanrahan et al. (2013) conducted a meta and primary data analysis of the
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efficacy of CB on pathological worry with adults, with results showing a high effect size (Cohens
d 1.81) in effectiveness when compared with non-therapy controls (Hanrahan, Field, Jones, &
Davey, 2013). The relevance of CB in SR and attention control was demonstrated in a recent
meta-analysis of 114 studies examining emotion regulation strategies across a mostly normative
population by Aldao et al. (2010). A high main effect was detected in the prevalence of
maladaptive or internalising strategies involving rumination, avoidance, and suppression as SR,
in some conditions (Aldao et al., 2010). The prevalence of self-preoccupying behaviour such as
rumination or ‘worry thinking’ illustrated the characteristic impact that worry has on external
awareness and attention, as detailed in Monat’s intrapsychic coping methods (Monat et al. 1977).
The CB method varies in duration, content and focus between practitioners but typically involves
a reduction and examination of thinking, feeling and clarification of misaligned assumptions,
biases and experience. The objective being to clarify thinking and behaviour. The directness of
the method and verifiability of progress or change in actual behaviour makes it a significant
contributor as an evidence-based method. A key factor of the CB method is the effect on attention
control and SR, related to the refocus of introspection to external awareness and attention. Diehl
et al., in two studies related to goal pursuit used the self- regulation scale (SRS) to show attention
control as the main effect in the outcomes (Diehl, Semegon, & Schwarzer, 2006). While the CB
method validates the need to resolve preoccupying mental issues in delivering the needed
cognitive performance, it remains as a time consuming. ‘hunt and peck’ method to regain mental
performance, unsuitable for the instantaneous recovery of attention when quickly needed.
3.11 Self-Regulation Techniques The four basic methods of SR training as indicated in Table 3.2 show the operant technique as
having the most utility and immediacy of effect (ie, 10 x 10 minute sessions) regarding SR,
including attention, cognitive recovery and generalisability. It is the simplest process requiring
the least expertise to teach and is generalizable, being both independent of context and any other
skills in application. Despite having a self-regulating effect, the method is not introspective and
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invites no need for rationalisation of past events or exploration of personal history. Due to its
operant mechanism, each success in application delivers further positive reinforcement. When a
specific behaviour has an immediate effect, and it is continually rewarded, it is highly resistant to
extinction. Associating an operant technique with an intrinsic reward, such as feeling good or
peaceful, being able to concentrate, manage a task and so on, delivers the necessary behavioural
dictum of ‘soon, certain and positive’ for sustained behaviour.
Table 3.2 Utility of four
self-regulation training
methods Methods of Training
Effect size 95% CI
Cohens d, from
(Table 3.1)
Time to acquire
Sessions
Embodies
recovery
method
Applies
to
context
Requires
expert
tuition
1.Conventional & Simulations Moderate to high Task-practice N/A Specific Yes
2 Behavioural-Operant Moderate to high 10 x 10 min Yes All No
3. Mindfulness Moderate to high 10–20 x 1 hour No All No
4. CB methods & Counselling Moderate to high 8-10 x 1 hour No Specific Yes
The utility of the four methods are compared and summarised in Table 3.2. The
psychophysiological mechanism of attention is explored in chapter four and compared with
alternative and similar mechanisms or procedures that have evolved over time.
Table 3.2 Utility of four self-regulation training methods
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4. PSYCHOPHYSIOLOGY of ATTENTION
4.1 Introduction Achieving objectives, responding to exceptions and recovering capacity, energy and motivation
undeniably result from adequate SR of a person’s psychophysiological state. The previous chapter
advanced the view that triggering mechanisms such as operant techniques were a more rapid
means of achieving attention recovery, than other methods such as Mindfulness training, which
require longer practice in achieving mastery. Operant techniques, by contrast, are instrumental,
based on the stimulus-response model of behaviour and operate at the neural level, are reinforcing
rather than habituation prone and able to be self-initiated rather than reflexive as in classical
conditioning. Operant training has the potential to raise the key performance behaviours (repeated
in Fig 4.1) of personnel in safety critical industries such as aviation, transport and nursing because
of the reduced time to acquire the skill and the immediacy of response when invoked.
Two factors that represent differences between instrumental or operant and classical techniques
of learning are: context independence and sustainability. Continual exposure to a fixed process
Proposed dependencies Related performance behaviours
Can see things others may miss
Ability to avoid becoming fixated
Can switch rapidly between demands
Remembers procedures, rules & exceptions
Remembers despite interruption
Can anticipate sudden changes
Can deliver the necessary mental effort
Less vulnerable to emotional preoccupation
Figure 4.1 Model of Behavioural dependencies and identified attributes
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in the classical conditioning model risks habituation and extinction of the response with time and
distance (Cevik, 2014) and desensitisation (Schmid, Wilson, & Rankin, 2014). The operant
method as a proactive reward seeking mechanism is less vulnerable to such decay or loss of
potency, provided the consequences or reward of such prompted behaviour continue. As an
adjunct to other self-regulating methods for goal achievement, operant techniques are quick to
learn, can be invoked covertly, self-initiated and universal or context-free in application. SR to
overcome hurdles to achievement has been extensively discussed in the literature from several
perspectives. Knoch and Nash (2010) considered the neurophysiological perspective by exploring
differences in SR, proposing a ‘neural-trait’ basis for self-control while implicating the lateral
prefrontal cortex (LPFC) in social decision-making aspects. The phrase ‘self-regulation’ (SR),
when used in reference to social-norms of behaviour is a reminder that the control of a
maladaptive hedonic impulse or its suppression, occurs through the executive functioning
processes of goal-directed and adaptive achievement-oriented behaviour (Hofmann et al., 2012).
SR has been explored with neuroimaging techniques and brain processes involved in mental
effort, finding that it is not just about self-control, that the strength of the intent in delivering the
effort required was important and emphasised SR as a choice (Radulescu, Nagai & Critchley,
2010).
4.2 Energy and Mental Effort Earlier work by (Kahneman, 1973) had proposed a finite optimally managed capacity for mental
effort. Kahneman had observed changes in ocular, auditory and perceptual performance as
demand shifted from one sense to another, concluding that the energy supplying effort was limited
and distributed or reapportioned from one physiological need to meet the demands of another,
demonstrating an automatic displacement or re-allocation of resources. Radulescu et al., (2010)
using functional neuroimaging techniques similarly observed the ability of the brain to marshal
further cognitive support when required from other regions when under load, to increase the
capacity for achievement of problem-solving and behavioural goals. The evidence of the
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reallocation of cognitive resources when needed provides support for SR as the director in a
volitional and interdependent network model (Fig 4.1). Radulescu’s distinction of mental effort
as being either passive (and reactive) or active (and discretionary) helped to separate ‘task driven’
reactive engagement from the active mobilisation of brain resources, further emphasising the
executive in the process. Mental effort was putatively considered by Radelescu et al., (2015), as
pivotal in achieving goal directed behaviour. Intention and realisation demand cognitive effort,
which is dependent on the availability of mental energy; particularly in overcoming mental
fatigue (Cockshell & Mathias, 2012; Engle-Friedman, 2014). Mental effort is logically dependent
on available mental energy and has been graphically observed by manipulating glucose
concentration in the brain (Lindseth et al., 2011; Sourkes, 2006). The process of glucose
degradation being totally dependent on the oxygen being conveyed in the bloodstream
(Fairclough, 2004). Mental effort however also improves with a reduction of stress (Sandi, 2013),
suggesting that mental energy becomes available for attention when released or reallocated from
the wasteful effort of resisting the intrusion of other distractions. Kaplan (1995) proposed an
ecological basis for the restoration of attention, called the Attention Restorative Technique (ART)
which diverted or released captured mental energy and effort. The ART operates by managing
attention through a ‘Mindfulness’ technique, in concert with the calming or tension releasing
influence of rural vistas and gardens. In a study of the ecological technique, improvements were
found in executive attention, that part of the attention network that manages conflict and controls
other networks (Posner, 2012). Cognitive performance had improved when other demands were
decreased, the executive benefiting from re-direction of shared mental resources (Berman,
Jonides & Kaplan, 2008; Kaplan, 2010). In a meta-analysis of 163 studies of the effects of
meditation similar improvements were found with respect to emotional and relationship issues
but only weak effect sizes on attention and cognitive measures with the lesser result ascribed to
various methodological and theoretical issues in the studies (Sedlmeier et al., 2012).
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Overall, SR is concerned with the management of disruptions to attention due to affective or
reflexive reaction, lingering pathologies or dysfunctional behaviours or no longer useful
defensive measures that need to be extinguished operating in a cognitive-affective feedback loop
(Carver, 2011). In a normally functioning brain the apparent availability of mental effort comes
from adaptation of resources through re-allocation (Kahneman, 1973), displacement or release
(Kaplan & Berman, 2010), with ultimate recovery achieved during sleep (R. E. Brown, Basheer,
McKenna, Strecker, & McCarley, 2012). Perceived capacity and effort may also be increased by
removing the cognitive load to improve attention span, arousal and vigilance by increased
cerebral glucose concentration or ingested agents such as the affective drugs amphetamine and
modafinil (Gore , Webb , & Hermes, 2010).
4.3 Mental Energy & Fatigue Mental fatigue is a psychoneurological state of depletion of energy occurring after prolonged
activity. Brain function is dependent on a number of systems and it appears unlikely that central
fatigue is due to just one of those, as a common symptom associated with many subjective
conditions (Hegerl, 2013). Although there are known brain networks that mediate mental fatigue
the exact mechanism of the fatigue symptom is still unclear although it presents as a loss of mental
energy. Neurotransmitters associated with enhanced cortical activation and wakefulness and
those that are present during exercise, are not conclusive in the management of fatigue (Meeusen,
Watson, Hasegawa, Roelands, & Piacentini, 2007). Harrington described the nature of fatigue
according to its source, that is whether it was central or peripheral. For example, peripheral fatigue
results from muscle fatigue and central fatigue refers to central nervous system processes.
Episodic fatigue can be specific and articulated in as many forms as there are human activities,
including the fatigue of stress, a parallel but different affective state. Fatigue most closely
resembles a state of exhaustion commonly identified by how it disrupts or interferes with full
functioning rather than what the cause is.
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Nevertheless, fatigue has many endogenous and exogenous contributors. Symptoms are present
in sleep deprivation, task overload, cognitive overload, circadian troughs (Kyriacou & Hastings,
2010), prolonged inactivity (Roach, Petrilli, Dawson, & Lamond, 2012), excessive food
consumption, exposure to heat (Qian et al., 2015), vibration, noise, oscillatory motion, alcohol,
drugs, dietary imbalances, strobe effect, emotional states - and it exists in most
psychopathologies. It is characteristic in older men and women. It seems that fatigue is a uniform
psychophysiological response by the brain in overload, when it lacks some essential nutrient or
when injured. Fatigued mental states often produce subjective expressions of helplessness,
vulnerability, impatience anxiety, disinclination to continue a thing and emotional numbness
(Harrington, 2012).
Fatigue in aircrew is a significant hazard with regulations and service times designed to avoid
accumulation and development of a chronic state. Cockshell and Mathias (2012) in a study
examining cognitive test performance with chronic fatigue patients found that even when effort
was high, performance was low (Cockshell & Mathias, 2012). The results demonstrated the
intractability of the condition at the extreme state. A low mental energy state occurs within the
daily circadian cycle, irrespective of any prior fatigue-inducing activity. The circadian dip
determines alertness at the characteristic mid-afternoon, early evening and pre-dawn dip, when
cognitive task performance and responsiveness are low (Dongen & Dinges, 2000). Fatigue is
cumulative and sleep is the only known means to recuperate from it.
4.4 Methods of Arousal While attention studies have tended to focus on arousal and sustaining attention, fewer of those
have focused on endogenous means of recovery from fatigue lapsed states, as in initiating a return
to alertness in other ways than sleep. Fatigue features in most operational contexts such as driving
too far, sitting too long in the one position and high cognitive demands from task overload,
inevitably resulting in diminished cognitive performance. That different stimuli can trigger the
physiological effects of arousal suggests that arousal is multidimensional having both specialised
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and generalised components (Langner & Eickhoff, 2013). The pervasiveness of the problem
prompted the search for countermeasures and strategies to initiate revival and recoup mental
energy. These have involved exogenous means such as chemical stimulants, a change in posture
or body movement, vocalising, caffeine drinks and exposing the face to chilly air to break the
descent into sleep. For example, chilly air has been reported to temporarily stimulate an increase
in respiration and arousal, to increase cardiac output, cerebral blood flow, oxygenation and
glucose usage (Reyner & Horne, 1997).
Chemical stimulants afford a rapid and certain effect associated with ease of administration. For
example, Dextro-amphetamine had been widely used as a fatigue countermeasure to sustain
attention by military pilots on combat sorties dating from World War Two and used in almost all
subsequent conflicts despite the potentially serious side effects of long term use. Common side
effects included dizziness and blurred vision, psychosis and hallucinations (Estrada et al., 2012).
Even the seemingly innocuous Ginko has been reported to risk subdural hemorrhages with
prolonged use (Rowin, 1996) failing to fit the criteria for a safe attention recovery pill. The wide
search for wakefulness extenders also included chewing Caffeine impregnated gum. However,
Modafinil to replace Dextroamphetamine has become widely used in the military aviation sector
(Sheng et al., 2013; Turkington, Hedwat, Rider, & Young, 2004; Wesensten et al., 2002) showing
fewer side effects than Dextroamphetamine. Existing pharmacological interventions to improve
cognitive performance either enhance the activity of wakefulness-promoting neurotransmitters
(ie, amphetamines) or inhibit the activity of sleep-promoting neuromodulatory systems such as
Caffeine (Wesensten, 2012, pp37).
Smelling Salts: Smelling salts have also offered an apparent means for instantaneous cognitive
revival. Sensory inputs together with their detection, transmission, cognition and motor effect can
result in automatic as well as discretionary actions.
Keller draws the relationship between attention and consciousness as mediated by the olfactory
system (Keller, 2011). Brain injury patients in a prolonged coma may have a variety of stimulants
69
applied to them in the process of recovery, including olfactory stimulants. In the 19th century,
smelling salts were often used to assess if the patient was brain dead based on the speed and
certainty of response via the trigeminal path. McCrory (2006) described the use of Ammonium
Carbonate the most popular of those as a restorative, also called smelling salts (chemical
(NH4)2CO3H20)) with subsequent variations including those of ‘Sal Ammoniac’. Solutions of
mixtures of dilute ammonia, water and ethanol are commonly available as aromatic spirits of
ammonia easily obtained via the internet (Amazon, 2016).
Despite the connection between attention and arousal, there is a difference between chemical
brain-state arousers and the mechanisms that invoke a change in mental-state. The release of NH3
in the nose, of the ‘smelling salt’, triggers the inspiration reflex and a change in breathing results
in an apparent increase in alertness (McCrory, 2006). The reflex triggered by the ‘salts’ has been
used as an on-the-spot diagnostic often rendered to competitors suspected of concussion in
various contact sports, albeit with unconfirmed validity of its efficacy for actual cognitive
revival. Arzi et al., (2010) investigating respiratory patterns due to odours in sleep, found that
while strong odours that activate both olfactory and trigeminal neural receptors can induce
arousal, mild olfactory odours alone appear to not do so (Arzi, Sela, Green, Givaty, Dagan, &
Sobel, 2010). An explanation being that the arousal effect of the smelling salts acts on the
nociceptors to alert the organism by activating the trigeminal pain system, but diverges in their
action from the attention recovery mechanism proposed in this study; where the ‘sniff’ draws a
sudden volume or air at a greater pressure to stimulate the olfactory nerve as an operant to change
mental state. Chemical stimulants by contrast such as ‘smelling salts’ can be experienced without
a link to any specific odour. The action being a neurochemical effect of the NH3 without any
specific action on mental state. Of interest in this study is arousal to effect a change in the level
of attention through the activation of the aspiration reflex and a secondary action involving
retrieval of an associated mental-state. Masaoka et al., (2011) had demonstrated the link and
immediacy of activation and retrieval of autobiographical memories with an associated odour. In
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their study, subjective arousal and consequent association of pleasant memories resulted in deep
slow breathing rates. Masaoka et al., had concluded that since odours are intangible, their
association was one of memory and emotion indicative of higher cognitive functions (Masaoka,
Sugiyama, Katayama, Kashiwagi, & Homma, 2012). In a further confirmation of the association
of the link between an olfactory stimulus and memory, Cortese et al (2015) had tested the
responsiveness of veterans with PTSD. The study finding an attentional bias to specific threat
odours, including fuel, gunpowder, blood and burning hair, resulting in elevated emotional
responses and changes in heart rate; further demonstrating the capacity for direct activation of
specific episodic memories through the olfactory path and the limbic system (Cortese, Leslie, &
Uhde, 2015).
4.5 Nasal olfactory action and the sniff Olfactory action occurs with nasal inspiration or a sniff involving a change in the rate and volume
of air passing through the nose. Normal nasal inspiration has the function of filtering clean moist
air to the lungs. The nasal ‘sniff’, a short sharp inspiration accompanied by only a minor
associated exhalation also has another function, that of passing air over the olfactory neurones in
the dorsal posterior recess of the nasal cavity, which connect with the olfactory bulb in the brain.
Normal sniffing is a semi reflex response that occurs with the detection of new odours by the
receptor neurons in the olfactory mucous (Fig 4.2).
Physically, the receptive area of the nerves in the olfactory epithelium cover some 5 cm2 of the
nasal cavity with 10-20 million bipolar sensing neurons each acting through 10-20 cilia sensitive
to specific odorants (Fig 4.2). The axons of the olfactory sensing neurons pass through the
cribriform plate of the ethmoid bone above the roof of the nose. They then enter the olfactory
bulbs which have a neural path into the limbic system and the five regions of the olfactory cortex,
the anterior olfactory nucleus, olfactory tubercle, piriform cortex, and parts of the amygdala and
entorhinal cortex resulting in rapid access to long-term memory
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Figure 4.2: The Olfactory Pathway Barrett, K., Brooks, H., Boitano, S., Barman, S. (2010). Ganong's Review of Medical Physiology (23 ed). McGraw Hill Medical, p593.
4.6 The Sniff as an Analogy of the Startle The startle resembles the sniff, with a more sudden activated nasal inspiration, after that sharing
the same neural path through the limbic system as the sniff to swiftly stimulate and retrieve
memory.
However, unlike the sniff, the startle involves a sequence of involuntary actions related to fear
conditioning through the two key structures of the amygdala and the hippocampus (Jacobs,
Renken, Aleman, & Cornelissen, 2012). Koch (1999) refers to the startle as a fast twitch of facial
and body muscles evoked by a sudden unanticipated and intense olfactory, tactile, visual or
acoustic stimulus. The physiological responses involve eye-lid-closure, contraction of facial,
neck and overall skeletal muscles, an acceleration of the heart rate, with arrest or pause of ongoing
behaviours. Additionally, reflexive sniffing (Tomori et al, 1998) also occurs in response to sudden
stimuli such as an unanticipated noise modulating the breathing pattern in the preBötzinger
Complex rhythm generator (Feldman, Del Negro, & Gray, 2013).
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4.7 The Role of the Amygdala in Rapidly Cued Attention A sharp short inspiratory sniff can stimulate the epithelium and activate the olfactory bulb
(despite the absence of any odour) to transmit a stimulus via the limbic system and frontal
memory centres of the brain to evoke the associated memory or calm mental-state. An essential
difference between this method and the startle response is the avoidance of the ‘fear’ component
in the startle, presumably because the path bypasses the brainstem startle reflex circuit and the
direct connection with the amygdala (Hitchcock & Davis, 1991). Consistent with the earlier
finding by Lang et al (1990) that the startle response as an aversive reflex, was enhanced under
conditions of fear but was able to be diminished or overridden with a pleasant emotional context.
This variability based on aversive or appetitive inputs separates the startle response from general
arousal conditions (Lang, 1990) and allows for the parallel of the sniff and startle in establishing
arousal, orientation and an attentive mental-state. While much of same neural network is used for
both sniff and startle, involvement of the amygdala in the startle condition suggested that the
amygdala has a central role in modulating stimulus-response associations at the core of Pavlovian
learning (Mirolli, Mannella, & Baldassarre, 2010). Further suggesting that the influence of the
amygdala extends to most affective responses and basic behaviours such as regulating body and
brain states, planning and decision making. Other sensory stimuli such as the acoustic startle
response were tentatively suggested by Koch (1999) as a typical protective reaction, the process
mediated via the circuit path located in the lower brainstem involving the caudal pontine reticular
nucleus which also modulates the acoustic startle response. Additionally, the aspiration reflex,
also known as the ‘gasp’ is commonly associated with other physiological reactions and is also
observed with the acoustic startle response in humans (Yeomans & Frankland, 1996). The
aspiration reflex was suggested by Tomori et al., as occurring with arousal (Tomori, Benacka, &
Donic, 1998) and as a strong inspiratory effort but not one that was necessarily followed by a
corresponding full expiration. It was compared with the sniff and the sigh as being triggered from
the upper nasal airway (fig 4.3) with a short latency, sudden onset and having an equally sudden
termination. However, Tomori et al., draw the distinction that the gasp and the aspiration reflex
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are different in several ways, pointing out that the gasp occurs mainly with severe hypoxia and
asphyxia when ‘eupnoic’ respiration falls and evident as a cyclic repetition of longer-lasting
spasmodic inspirations.
Of specific interest is the speed of activation of the startle response which is near instantaneous
due to the utilisation of multimodal sensors, including the epithelial receptors of the olfactory
bulb with their receptors transmitting directly into the limbic system of the brain (fig 4.2).
Olfactory stimuli are more rapidly activated than visual stimuli (Keller, 2011) because of their
direct relay to the limbic system and areas which are associated with memory and emotion rather
than first going via the Thalamus (Sullivan, Wilson, Ravel, & Mouly, 2015). The overall path
subsequently linking the aspiration (sniff) with emotion and motivation (amygdala), learning and
memory (hippocampal formation), and sexual behaviour (hypothalamus) (Blumenthal, 2015).
Mainland et al., had proposed that the sniff and the gasp are an integral part of the olfactory
system. Their review suggested that the ‘sniff’ was an essential part of the ‘Olfactory Percept’ ,
featuring in odorant detection and sampling, that it drives activity in the olfactory cortex and is
modulated by the olfactomotor system (Mainland & Sobel, 2006). The difference between the
nasal sniff and normal breathing is a physiological one, so that nasal ingestion of air carries both
air and any potential airborne contaminants to the olfactory receptors, without also transporting
particles to the lungs.
Laing (1983) described the rate and volume of air in the sniff as averaging an intake velocity of
27 L/min with a volume of 500 cm3. During the sniff, air enters through the anterior nares (nasal
opening) passing through to the upper airway and to the pharynx at the top of the throat at which
time any particulates can be coughed out or swallowed. Mainland cited Zhao (2005) as suggesting
that the internal structure of the nose channelled a lesser amount of air, between 5-10% that passed
into the nose, to reach the olfactory epithelium (fig 4.3).
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The change in the rate and volume of air inspired increases with exertion and logically decreases
in both REM and NREM sleep (Scott, 2006) at a low arousal state, and shows a modulating
olfactory bulb response during normal sniffing. Supporting the relation between sniffing and the
hippocampal theta rhythm (Balu, 2004), that during concentrated attention of mental tasks the
theta rhythm is generated elsewhere in the frontal midline cortex.
4.8 The Breathing mechanism In normal breathing, the lungs are the interface between body and environment and operate as
both voluntarily and autonomic transfer air into and out of the body. Despite variations in oxygen
(O2) and carbon dioxide (CO2), metabolic control of breathing maintains the arterial pressures
(PaCO2 and PaO2) and acid-base (pH) levels of the blood at constant levels. A neurochemical
process originating in the respiratory foci in the brain-stem activate a rhythmic action by the lungs
to draw in air. Action by the lungs subsequently increases O2 in the blood and triggers the lungs
to release excessive CO2 from blood into the atmosphere. Peripheral chemoreceptors in the aorta
and carotid artery help regulate this CO2 / O2 / pH balance in the blood and brain. The breathing
process can automatically respond to changes in psychophysiological demands such as additional
exertion as well as emotional demands like anxiety (Ley, 1999).
Figure 3 Path of Nasal Air (From Kandel ER, Schwartz JH, Jessell TM [editors]: Principles of Neural Science, 4th ed. McGraw-Hill, 2000.)
75
Dual control of breathing is physically possible via the volitional expansion of the chest cavity
and the downward and upward movement of the diaphragm situated below the rib cage. By
thrusting the stomach muscles in and out to manipulate the movement of the diaphragm the lung
space is expanded or compressed. Using the assisted abdominal action on the diaphragm enables
a fuller aeration of the lung space, which does not occur in normal breathing. Lung volume
changes also occur with both voluntary and reactive changes in the rate of breathing to meet
bodily demands and activities. The CO2 / O2 balance in the body is critical to functioning as
variations in saturation, blood acid-base level (pH), rate of inspiration (over-breathing and under-
breathing) and cellular metabolic requirements determine the dilation or constriction of blood
vessels, delivery of glucose to brain cells and modulation of heart rhythms. Additionally,
hypocapnia or reduced CO2 levels (from over-breathing), may change blood pH levels,
particularly at times of stress. If these conditions are persistent and not normalised in renal
buffering of pH by excreting the fixed acids and recycling the bicarbonate, reduced physical
endurance and fatigue may occur, with extended alkalosis risking platelet aggregation and life
threatening blood clotting. As a near automatic and unconscious process, breathing is regulated
for metabolic and homeostatic purposes in the brainstem having a singularly important role in
regulating the health of both body and mind (Homma & Masaoka, 2008; R. Ley, 1999).
4.9 Measured Breathing and Mental State The oldest known reports of systematic manipulation of breathing appear to have evolved from
the yoga tradition with the intention of heightening perception and philosophical enlightenment,
with other practical benefits observed for stress management (Riley & Park, 2015). Prana is the
Sanskrit word for "life force" or vital principle, a central concept in Yoga. In Yoga breathing is
focused on the maximum absorption of ‘prana’ through the nose with channels (analogous to the
epithelial-olfactory system) situated in the upper part of the nostrils for circulation to the brain
(Gilbert, 1999). Beyond that, Yoga and similar philosophical approaches to obtaining
enlightenment and self-regulation have few references identifiable in modern biology, usually
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favouring metaphysical discourse rather than experimentation, although some superficial
similarities are evident (Barrett, 2010).
A measured and self-inspired repetition or cadence in breathing, to control mood and cognition
has long held a central role in SR, forming the basis of present and traditional self-management
training techniques in Christian ritual, Mindfulness, Yoga (Gilbert, 1999) and deeply embedded
in Buddhist rituals. Mental changes in perception and mood were attributed as a positive
achievement and a reflection of a higher consciousness. More practically, breathing techniques
were used as preparatory training in enhancing speed, attention and response for various eastern
martial arts training systems. Bernardi et al., (2001) had suggested that the introduction into
western cultures of formal rhythmic breathing techniques, as a self-regulating mechanism,
originated with Knights returning from 11th-12th century Crusades. The Knights had probably
been exposed to monks and devotees, in Arabia, India and Tibet, for whom measured breathing
techniques generated the mental states representative of an enlightened awareness. The Rosary,
a ritual associated with a rhythmic verbal cadence, had also been coincidentally traced back to
the 12th Century by Thurston (1856-1939) an English priest and scholar. The ‘Rosary’, was aided
by rhythmic recitation using a string of beads, with each bead fingered for the verses of the ‘Ave
Maria’, while responding to a rhythmic counterpoint by a priest. The assisted recitation technique
had become a common religious ritual in western Christianity, Buddhist rituals, the Hindu ‘Japa
mala’, Asian ‘Juzu’, and the Islamic ‘Tasbeeh’ rituals. Bernardi et al. had investigated the effect
of rhythmic breathing on cardiovascular rhythms and baroreflex sensitivity. By comparing the
vocal effects of the Ave Maria with the classic Hindu Mantra, finding that both had a measure
that regulated breathing with an approximate 10 second, six breath/min cycle of respiration,
compared with that of the normal adult of about 12 breaths/min). The respiratory range for the
average adult being 12-20 breaths/min (Barrett et al. 2010, p593). Bernardi had reported that the
rhythmicity of the slowed breathing study to have significantly positive effects on regulating the
cardiovascular system to enhance heart rate variability and baroreflex sensitivity in their study.
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Measured breathing with repetitive verbalisations, has the effect of altering perception, reducing
negative emotion and fear. Efficacy of the psychophysiological process, used for relaxation had
also been employed to extend physical endurance in sports (Litchfield, 2003). The model
supported Ley’s (2003) dual view that changes in breathing follow changes in emotion and
cognition and conversely that breathing can lead to changes in emotion and cognition (Ley, 2003).
4.10 Operant Learning It is suggested that a possibility exists in utilising the olfactory sniff as a cue for the rapid retrieval
of memory, to generate a practical self-regulating technique assisting the recovery of attention.
The established mechanism of pairing a stimulus with a response is known as ‘Operant or
instrumental learning’ (Blaisdell, 2008; Fantino & Stolarz-Fantino, 2012). The behaviours are
enabled or strengthened consequent to a reward or weakened if the consequence is aversive,
corresponding with the first theory of instrumental learning – termed Thorndike’s ‘The law of
effect’ and the subsequent work of Skinner (1953) and Watson (1924). Operant procedures are
deemed to be superior to classical conditioning as a means of learning to engage in a preferred
behaviour limited to a simple reaction. In operant learning, a specific behaviour is reinforced in
a schedule associated with a specific (conditioned) stimulus. As the training progresses the
behaviour becomes part of a feedback loop. The effect depends on the strength of the consequence
(Jozefowiez & Staddon, 2008) and the natural relatedness of the reinforcer, such that the
contiguity and outcome are closely linked (Gendolla, Tops, Koole, 2015). The ‘Skinner-Watson’
behavioural dictum of reinforcement to obtain repetition, ‘soon certain and positive’ describes
the reliability of the outcome and the parameters for sustainable performance.
The stimulus, response and outcome model (s-r-o) where the response is motivated by the
outcome (Blaisdell, 2008) assists in the achievement of goals through self-directed and self-
regulated behaviour. The way associative learning occurs beyond the normal acquisition,
formation, consolidation, reinforcement and extinction of learning stages is not clear yet, or how
a behaviour can change mental-state. The Hebbian view that associated learning arising from
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experience modified the synaptic transmission and behaviour of other neurons, when consistently
fired the presynaptic neuron would likely excite or attenuate the postsynaptic neuron (Hebb,
1949).
In summary, in the rART model a calm and clear mental state is achieved by the initial diaphragm
breathing practice at (A) (fig 4.4) (Arch & Craske, 2006) to establish the operant or link with the
cue (the sniff). The sniff (B) acts as the cue that transmits the stimulus or signal for recall of the
associated positive or pleasant mental state, previously established with diaphragm breathing.
The rART procedure as a self-regulating skill links several psychophysiological events to recover
attention when needed. The means to impart the skill and establish a measure of mental state to
gauge status and change is detailed in the next chapter.
The rART exercise was unlikely to meet the logistics and quality control criteria for large scale
training while using the traditional classroom format, with minimally trained instructors. The
rART exercise was thus designed to be delivered over the internet in video form with a specific
computer-controlled delivery sequence to participants amid everyday distractions and cumulative
fatigue, as detailed in chapter 5.
(A) Association In Preparation (B) In Execution
Figure 4.4 Proposed operant recall of mental state to improve attention
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5.0 METHODOLOGY
5.1 Introduction The preceding research had identified the criteria and outcomes for a rapid psychophysiological
SR control mechanism to recover attention and improve mental effort. A testable countermeasure
to address diminished cognitive performance due to stress and fatigue was hypothesised, for the
recovery of waned attention and mental effort. The proposed mechanism would allow the
individual to self-regulate their mental state to escape the disruption and discomfort of anxiety,
preoccupation or overload - to regain the mental clarity achieved and previously memorised, by
a short series of repetitive diaphragm breathing and cueing exercises.
5.2 Research Design An empirical study was formulated that could explore a self-regulating countermeasure as a
recovery skill, also that it could be conducted in-vivo to take advantage of naturally occurring
‘noise’ in daily life. The natural development of fatigue and inevitable distractions adds to the
external validity of the process and avoids laboratory bias (Levitt & List, 2007) through the
‘Hawthorne effect’ (Adair, 1984). The research design would thus involve a sequence of daily
unsupervised online exercises to be completed at night just prior to sleep, with each second
session loaded with two extra, mildly taxing, questions typical of standardized IQ tests and
characteristic short term memory question forms that had been assessed as sensitive to fatigue
(Ackerman & Kanfer, 2009).
By taking advantage of the natural level of fatigue and decrease in alertness due to the late night
circadian trough (Kyriacou & Hastings, 2010), recovery of mental effort and task focus could be
tested with the proposed rapid attention recovery technique. The object of recalling a calm mental
state is to reduce preoccupation and reluctance to engage in arduous mental activity when tired.
The study would utilise the challenge questions as the last items in sequence delivered in the daily
sessions and as a means of confirming completion of the session, further verify compliance with
the unsupervised training. The study incorporates both qualitative and quantitative components
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consistent with a mixed methods approach (Johnson & Onwuegbuzie, 2004). A baseline of mental
alertness and fatigue management constructed and tested with a similar and independent group
of participants would provide comparative measures to classify pre-training SR status. Questions
requesting information about actual self-management of behaviours preceding the study would
provide comparatively greater predictive validity than attitudinally oriented questions.
5.3 A Technique to Achieve Attention Recovery A method for recovery of attention is proposed based on Thorndike’s 1898 instrumental learning
theory and the law of effect involving an operant control (Jozefowiez & Staddon,
2008)(Blaisdell, 2008). The direct psychophysiological nature of the operant mechanism could
deliver a more efficient and easily repeatable procedure than other meta-cognitive methods;
independent of time, location and context. The proposed application of the SR technique for
hazardous occupations may have greater utility than mindfulness training and yoga. The
procedure involves a sequence of natural psychophysiological behaviours that activate specific
brain mechanisms to disencumber mental state and regain mental alertness when fatigued.
Comparatively productive outcomes could be achieved devoid of the complexity found in
classical cognitive-behavioural methods (CB), by circumventing the need for introspection and
the typically longer training period of meditatively oriented procedures needed to achieve
mastery.
A sequence of short exercises was designed in which the nasal ‘sniff’ was established as the
activating stimulus or operant (Fantino & Stolarz-Fantino, 2012), and paired in sequence at the
end of the expiration phase of the diaphragm breath (fig.5.1) to achieve the switch in mental
state; a procedure that in part mimic’s the common and natural means of reducing affective
discomfort when stressed by taking a deep breath or making a sigh. In the procedure, the
initiating nasal ‘sniff’ acts as a stimulus to instantly retrieve the associated memory from the
frontal cortex via the olfactory path and the limbic system to invoke the mental state that had
been previously practiced and located in memory during the training exercise. Once firmly
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established in memory the use of the recovery technique or mechanism would thus be available
‘on-demand’ to clear the mind through the activating sniff alone, without requiring concurrent
diaphragm breathing or intense focus on the self, as in mindfulness preparation. The rapid action
of a covert self-regulating device, independent of context, would make the technique usable in
any context.
5.4 Issues in Delivering Online Training Online delivery of testing and training has become popular as ‘distance education’, offering
logistic advantages over classroom attendance and traditional paper and pencil forms. Once
unique, online courses now emanate from most universities and number millions of students per
annum who appear to be very comfortable with the technology (Means, Toyama, Murphy, Bakia,
& Jones, 2009). The teaching presence and community offered by the classroom may be in
distinct contrast to that of online learning, but does not appear to have been discouraging. Specific
effectiveness of online or screen-based learning offers in terms of the rate of skill, satisfaction
and knowledge acquisition was assessed in a three-year longitudinal assessment of medical
students at an American university (Schimming, 2008). Results indicated increased satisfaction
due to increased control via self-paced units which also resulted in greater engagement. Questions
of engagement, certainty of achievement and the efficacy of online delivery have received
positive support. However, it is not yet known if engagement with a computerised course
specifically equates to the assistance that social engagement offers by group-classroom training.
In the report of a study of a web-based college course focused on teacher presence and sense of
community (Shea, 2006), ‘directed facilitation’ contributed more to the factors of engagement
and sense of ‘connectedness and learning’, with instructional design and organisation running
second. At the structural level, Means et al. (2009) concluded from their meta-analysis of
evidence-based practices in online learning, that significant differences were found when the level
of interaction in the delivery format was considered, further moderated (in some cases) by the
perceived attractiveness of the on-screen presentation. The finding is important for the online
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delivery of the short course in the proposed rapid attention recovery technique which had evolved
out of typical practical face to face interaction and where instruction had required scrutiny of
participant behaviour and practice. The need for remedial tuition for participants’ who were
learning an unfamiliar behaviour was inevitable. The active and supportive presence of the
facilitator thus seen as necessary to ensure that practise occurred in the development of the skill.
Student engagement and subjective perceptions had been raised as an issue following completion
in an online course on aviation physiology by aviation students’ (Artino, 2009). Artino had found
that students’ intent on becoming aviators employed greater SR strategies, pointing to the
perceived regard they held for their career choice. Despite the greater self-regulating capacity of
the aviation cohort, Artino found an unexpected dissatisfaction evident in their reports that were
related to the design of the online presentation, which may have simply emphasised the need for
some novelty in presentation of the subject-matter, greater context or a smoother sequence of
learning points. It has long been known that practical demonstrations and learning to ‘do’ a thing
offer greater opportunity for relatedness and engagement than simply learning ‘about’ a thing.
For example, a course in physiology, short of participating in a dissection, must essentially be an
abstract ‘look and remember’ exercise. When there is no opportunity to participate and become
immersed, by manipulating or experimenting the subject the content must rely on interest and
novelty to ensure continued attention and engagement.
The efficacy of an online delivery of a course in Mindfulness-based intervention, generally
defined as an awareness of body sensations and mental state focused on the moment, was
explored in a meta-analysis by Spijkerman et al., finding that stress was well mediated by the
interactive or guided method of Mindfulness-based intervention in contrast to the unguided
method, as demonstrated by a slightly larger effect size (g = 0.51) in the study (Spijkerman et al.,
2016). While support for the social context in guided interventions was provided in the Artino
and Spijkerman studies, Kearns (2011) in a simulator study evaluating a computerised ‘single-
pilot’ resource management course adapted from crew resource management principles (Salas,
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Wilson, Burke, & Wightman, 2006; Seamster, Boehm-Davis, Holt, & Schultz, 1998), found that
online training as an instructional delivery technique had proved effective in improving
situational awareness, even though the crew context was absent, as it would normally be in single-
pilot general aviation general aviation operations (Kearns, 2011). The finding supported the view
that the key difference in online training related to the perceived quality of the content and the
degree of interaction available in a course. Kearns study would suggest that the interaction in the
single pilot resource management course was one of involvement with the screen material and
active manipulation of the simulator rather than the social interaction with others, had they been
available, for example, by interaction with air traffic control personnel. With the perspective of
involvement and engagement in mind for the rART study, the proposed attention recovery
technique instruction to be conducted unsupervised and administered remotely was designed with
video and text, and some voice-over on images, the main component being the demonstration and
guided exercise in practicing the technique.
5.5 Unsupervised Baseline Testing The attention recovery study was constructed to be delivered online and unsupervised. The
preliminary baseline testing involved anonymous self-reports of how well participants managed
their sleep and recovered from fatigue, further evidenced by the extent they were experiencing
cognitive failures and level of workload strain. Additional tasks related to on-screen problem
solving with items that delivered additional mental load exercising executive functioning, short-
term memory and choice reaction speed in processing. It was presumed that the ‘cloak of
anonymity’ would encourage authentic responding on the self-report scales.
Unsupervised online testing can be problematical with respect to the authenticity of responses
where personal gain is dependent on performance. Cheating, in contrast to response inflation in
this study, was not seen as relevant as response distortion or inflation may be. Distortion and
inflation tending to occur where items are perceived as likely to violate social norms, risk a stigma
(Trappmann, Krumpal, Kirchner, & Jann, 2013), or are perceived to diminish positive regard for
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the self. However, some inaccurate responding can also be authentic. Respondents may simply
not know what they think or feel about a thing or indeed how much so - and thus default to the
most socially desirable response. Hence accuracy and authenticity of responses are potentially
significant confounding issues in unsupervised self-report based testing that does not specify clear
and observable behaviours and response sets.
Approaches used to check for authenticity, have included statistical response probability
procedures, repeat with mirror forms of tests and objective post-test verification. Another method
for questionnaires has involved writing questions that are concrete and objective with greater face
validity. The Item Sum Total method (IST) for sensitive questions introduced by Trappmann
(2013), diverts perceived threat to the respondent by switching the object of the question to focus
on something external to the respondent and less likely to evoke defensive responding. Early
experience with computerised testing (Richman, 1999) had also shown that controls such as
preventing backtracking and skipping on questionnaires resulted in less distortion than on the
alternative modes of pencil tests and face to face interviews. Richman et al. (1999) in a meta-
analysis comparing pencil, computer and interviews on social desirability responding, reported
finding a near zero effect size across 61 studies showing a lesser distortion on the computerised
delivery than in interviews and pencil forms.
A Baseline test was constructed to be delivered for anonymous execution, preparatory to the
attention recovery exercises. The delivery system was programmed to control entry and departure
at each stage of the course. Participants would complete a question set and be politely ejected
with a popup note to return the same time the next day. The mental alertness and fatigue scales
were delivered as a single screen-full of 20 Likert-scaled questions (Appendix B), while the
performance items were delivered as single question screens. Participants could not go back once
the submit button had been pressed, nor could they skip a question, some performance questions
allowed for repeated attempts with the average score taken as the final item score. The challenge
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questions delivered daily after each training session were single screen displays that only allowed
forward movement.
5.6 The Research Hypothesis The study investigated whether the proposed rapid attention recovery technique, as a means of
self-regulation added or improved the ability to maintain performance on unwelcome cognitive
tasks at the end of the day when fatigued. The challenge for participants was to complete the
training sequence just prior to sleep over the ten days of the course.
Hypothesis 1. Self-regulation scores on the independent perception variables of mental
alertness and workload strain would predict the dependent variable of fatigue
management scores.
Hypothesis 2. Participants reporting higher scores on the independent variables of mental
alertness and fatigue management would report transfer and utilisation of the attention
recovery technique to their daily activities.
Hypothesis 3. Participants, who reported higher scores on mental alertness and fatigue
management, were more likely to adhere to instructed session times and complete the
course within the allocated time.
Hypothesis 4. Participants who had identified themselves as pilot candidates would be more
likely to complete the attention recovery training and score higher as predicted on the
baseline measures denoting positive self-regulating than others.
5.7 Overall Structure of the Study A short online course including a baseline test and video demonstration was constructed to
administer the attention recovery training with the objective of establishing the viability and
efficacy of the technique as an addition to a person’s self-regulating repertoire of skills, when
delivered unsupervised to anonymous participants.
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The study design specified late night activity before sleep to practice the method and to take
advantage of any natural reluctance to engage in an arduous mental activity, due to end-of-day
fatigue and the characteristic post-dinner circadian trough (Kyriacou & Hastings, 2010) that
signals a decline in alertness and impending sleep at that time. The process was also expected to
encounter levels of emotional resistance where the ‘imposed study activity’ competed with the
distracting influence of a more attractive or novel experience, such as watching the ball game in
progress on TV or conversations with a friend. The need to introduce complicated or artificial
laboratory stressors to replicate those stressors was removed by positioning the attention recovery
training exercise to take advantage of the inevitable accumulated stressors participants experience
each day. Participants had the opportunity to exercise the self-regulating attention recovery
technique as they developed the skill. By utilising the technique, reluctance, and emotional
tension would be released. The effect of the technique would be reinforced by the established
‘behavioural’ technique that delivered a positive perception and an immediate outcome in the
context of the behaviourist dictum to ensure reinforcement of a procedure, as depending on the
exercise or consequence being ‘soon-certain-and positive’.
5.8 The Study Development Group The baseline development group comprising students in an aviation course from a different
university were requested by their instructor to complete the development survey (Appendix A)
to provide a specific benchmark sample for the development of test items to be subsequently
delivered to the experimental group in the study. The development group were asked to complete
the baseline test in the one sitting and at night after day classes, to approximate the conditions the
volunteer experimental group would experience at a later stage. The context of the development
group was as a semi-supervised group insofar as the request to do the test was formal and results
were reviewed by the course lecturer in feedback sessions with participants. A feature that was
examined in the retest of the baseline measures at an average of 30-40 days later.
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5.9 Criteria and Development of the Test Instruments Participants achieving the goals of the study, as evidenced by the baseline test and sequence of
challenge items, over the programmed ten days of the training, would provide data supporting
improvements in self-regulation. The baseline test was developed as a measure of pre-existing
ability to self-regulate and potentially to predict completion of the 10 session course.
The baseline test was used to detect any subsequent change in cognitive performance by
participants over the sequence of the five sets of challenge test items, that were delivered
concurrently with the training sessions. The baseline test included behavioural self-report and
cognitive test items constructed for online delivery to participants. Test items were derived from
established commercially available instruments displaying performance figures and
demographics further modified with a development group of like students from the aviation
school of another university, who had not been informed of the purpose and were not part of the
rART attention recovery training exercises.
5.10 Baseline test development Construction of the baseline test for the experimental group involved delivery of the test items
online to an independent development group (n=61) of aviation students (Appendix A, table A1).
The test items were assembled to correspond as much as possible with the behavioural markers
established in chapter 2, subsequently analysed for their utility and reliability based on student
performance and modified for subsequent inclusion into the study baseline test together with the
diurnal challenge questions accompanying the 10-minute training video. Self-report test items
below a reliability of r = 0.8 were discarded.
Functional test items incorporating the dimensions of executive functioning, short-term memory
and choice reaction speed, demonstrating a mean item difficulty in the average range (50-75)
(Table 5.2), were retained to contribute to mental load in the process, rather than as a specific test
of proficiency or intelligence.
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Confirmation of the usability of the items was achieved with retesting over a period of 30-40
days. Items deemed to be too specific to aviation and unsuitable for the general population of
students were discarded. Construction of the questionnaire items was confined to items that were
clearly behaviourally based. More traditional questionnaire measures of values, attitudes and
beliefs were rejected as potentially unverifiable in this study. Test items were sourced from
Goldberg’s, (2006) international personality item pool (IPIP), utilising a reduced version of
Broadbent’s (1982) cognitive failure scale, as modified and reduced by (Wallace & Chen, 2005).
The fatigue management scale (Appendix B), a behavioural scale previously developed for an
evaluation of mobile equipment operators had shown the required accuracy and reliability (10
items; α = .85) was utilised for the benchmark test. Results from the initial development group
sample of student pilots (n = 64) (M = 76.23, SD = 11.7) were compared with those from an
industrial sample (n = 1129) of rail, road and public transport drivers (M = 76, SD = 14.18). A
feature of the scale was the similarity of style with the mental alertness scale, a modified cognitive
failure scale (Broadbent et al, 1982), involving behaviourally phrased questions indicating
increased fatigue and potentially poorer self-regulation (SR).
The eight behavioural markers previously associated with the SR model (fig 4.1) and the
Hofmann et al., (2012) SR mechanisms dependent on executive functions (Table 2.1) were
matched with the baseline test items as measures of SR (Table 5.1).
The cognitive performance items delivered every second day as challenge questions to the
experimental group were constructed to provide added cognitive load, to the naturally fatigued
late night mental state of the participant, potentially evoking emotional resistance and cognitive
reluctance as commonly experienced under stress. Overcoming affective resistance was thus
posited to be a measure of SR and recovery of attention, attributes designed to be enhanced by
the rART training. Similarly, the array of questions comprised of verbal reasoning and spatial
memory items that were gauged as in the moderate to easy level of difficulty (Table 5.2), required
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no particular knowledge or learned ability, but needed to be read carefully, requiring attention
and mental effort to solve, drawing on behaviours as attributes defined in Table 5.1.
The items had the singular purpose of adding cognitive load as affective interference and were
not delivered to gauge intelligence. The established taxonomy of the three SA levels (Endsley,
1995) provided relevant behavioural criteria and categories to frame the study objectives. The
subsequent baseline test instrument items (Table 5.1) were those that had also been supported by
prior research before use and had documented evidence for their construct validity, reliability and
sensitivity. The original coping and resilience scale obtained from the IPIP library (Goldberg,
2006) used in the development group trial, was replaced for the study group by the modified
NASA Task Load Index (TLX) (Binder & Desai, 2011; Hart & Staveland, 1988) as an alternative
measure able to combine both affect and perceived load. The TLX parallels the Trappmann
(2013) ‘Item Sum Total’ (IST) approach in eliciting greater authenticity and accuracy of
responses by way of externalising the apparent target of the self-report questionnaire away from
the self to the role. For example, “How difficult is this role to do” versus “I find this role difficult
to do”. The use of the NASA TLX instrument also provided context to the strain felt by
participants that was absent in the more traditional coping scale (i.e., time pressure frustration
Table 5.1 Eight Behavioural markers associated with baseline test measures
Can deliver the
necessary mental
Find it easy to
remem
ber despite
Rem
embers
procedures, rules
Can sw
itch
attention rapidly
Can see things
others may m
iss
Ability to avoid
becoming fixated
Can anticipate
sudden changes
Less vulnerable to
emotional
Memory √ √ √ √ √
Choice Reaction Speed √ √ √ √ √ √ √
Executive Functioning √ √ √ √ √ √ √
Mental alertness √ √ √ √ √ √ √ √
Manages Fatigue √ √ √ √ √ √ √
Work Strain/Coping √ √ √ √ √ √
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and difficulty). Items in the development survey that were not directly comparable with the
primary study outcomes to be measured were also dropped to achieve a more parsimonious test.
The final form of the baseline test was reassessed according to the performance shaping factors
identified as behavioural markers in chapter two and the investigation of behaviours by
experienced aviators (Adams, 1993; O'Brien & O'Hare, 2007). The final delivery version was
modified with a reduced number of items and scales (Table 5.1). The baseline test emphasises
the cycle of perception, cognition and behaviour in the self-regulation of stress, such that the
better behavioural management of fatigue would results from perception of the stress of the
increased mental effort required for the cognitive tasks.
5.11 Development of the baseline test The six scales in the baseline test previously suggested as measures of the behavioural markers
(Table 5.1) and as a set of competencies (Hofmann et al, 2012), were proposed as self-regulation
(SR) skills by matching with defined supportive behaviours in the baseline test (table 5.2).
Consequently, the eight behavioural markers were linked to short term memory, choice reaction
speed and executive functioning (table 5.1). The final 30 items in the survey delivered to the
experimental group were designed as a baseline assessment of individual SR skills using self-
reports of functioning and fatigue management, rather than any expression of values or precedent
knowledge. The benchmark test was subjected to trials by the aviation students at another
university (Table 5.3) demonstrating acceptable reliabilities, inter-item correlation, and
functional-item discrimination.
A web-based test delivery system was coded and a website constructed with the URL
‘satraining.com.au’ established for the study. The system delivered both the testing and the staged
daily training components in the one instrument to provide a seamless experience for participants,
track progress in real time and accommodate a daily SMS reminder system to alert participants
to continue to complete the training. Participants were controlled in both the sequence and in how
much they could specifically do in each daily session. Instructions were reiterated at each entry
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or login and questions regarding understanding and ease of execution were also provided. As
most participants were anticipated to come from the study university, anonymity was a
prerequisite to prevent leakage of performance results from the tests that could result in
inadvertent influence on student reputation. The study was designed with mechanisms to ensure
delivery of the content according to a structure that afforded anonymity and provided more
experimenter control in the execution of the sequence of exercises in the delivery of the content
5.12 The Attention Recovery Demonstration Video A five-minute demonstration video was scripted and filmed. A young female actor was hired to
demonstrate the diaphragm breathing technique and cued sequence, accompanied with voice-over
instructions and a static image (Appendix C). Actors were already familiar with the diaphragm
breathing technique as a method for improving voice production in singing and acting.
Instructions were provided and displayed to participants prior to each video session
demonstrating the sequence (fig 5.1). The video was designed to be controlled by the participant
and able to be played as often as required in each session. Each step of the process was timed and
audibly counted down to provide a timing reference for later practice.
Participants were recruited using a passive broadcast method, posters (Appendix E), endorsing
the required skills for aviators and were attached to faculty and library notice boards inviting
aviation and all other students to access the website to participate in the baseline test and the
attention recovery training.
5.13 The Aviation Student Groups Students from the aviation school represented the initial source for the experimental group.
Demographics of the development group included academic years, age and flying credentials
listed in the results section (Table 6 .1).
Experimental sample demographics together with completion rates are shown in the results
section (Table 6.4).
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To continue required participants to acknowledge and download the ethics page on the website if
required. Participants for the attention recovery training were enrolled as volunteers from all
levels of the aviation school and from other faculties of the university. Notices and flyers
informed the website URL (http://satraining.com.au) to access the study webpage (Appendix E).
The required description of the study was displayed as was the procedure in point form.
Enrolment in the study was dependent on progressive acknowledgement of the ethics criteria and
indicated procedures. The required participation information form and privacy assurance
document were also linked as PDF files for inspection and download on the first webpage.
Participants accessed the setup page nominating their location as the study university or some
another location. Confirmation enabled access to the next page displaying a cryptic login ID.
On conclusion of the baseline questionnaire, participants were instructed that they would be
reminded by SMS to return the next day/night to begin the first session of the attention recovery
Table 5.2 Baseline test scale definitions
Manages Fatigue3 Self-management of sleep requirements to ensure adequate cognitive resources
Mental Alertness1 Measures the extent of every day slips in perception, memory and coordination
Choice Reaction speed 4 Ability to make rapid and effective decisions to changing circumstances
Executive Functioning4 Use of logic and deductive thinking to manage developing issues.
Working Memory4 Ability to retain and recall information in the short term
Subjective (strain)2 Identifies perception of stress on six potential influencers described in the TLX
1Mental alertness derived from the Broadbent et al (1982) Cognitive Failures scale.
2TLX (NASA Task Load Index) (Hart & Staveland, 1988) 3, 4 Derived from the SSA Mobile Equipment Operator test V2.1a (Rosenweg, 2015)
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training (fig 5.1) requiring a 10-minute application each day and the completion of two further
challenge questions every second session. A confirmation SMS was sent to participants with the
login ID as the message.On login to the baseline test participants were advised to record their
respondent ID and that no retrieval of the login code was possible if lost. Instruction in the rapid
attention recovery technique proceeded with a slow and rhythmic display of the diaphragm
breathing method by the model. At each exhalation of breath, participants were instructed to do
an exaggerated nasal sniff (fig 5.1), pause for a few seconds then begin again.
5.14 The Rapid Attention Recovery Instruction Set
Progressing automatically to the next page, participants provided their mobile phone numbers
and the time for their preferred late-night SMS reminder. The exercise could be done as often as
needed, with a minimum of five expirations and sniffs advised and modelled in the video
demonstration and as depicted in the static image, to allow for the association of the ensuing
calmed mental state to form an association with the nasal sniff for later retrieval. No other
instruction was given except that the procedure did not need to be repeated in full once the whole
94
training sequence had been completed, with the advice that that the ‘sniff’ would retrieve the
calmed mental state automatically.
5.15 Data Collection Participant responses were collected via the online system and retained in the system database for
analysis. The question / item number was recorded for each time of entry and exit and exported
to MS Excel files and input to SPSS V23 for analysis. In this study both full and partial
completion records were sought to identify the point at which participants departed from the
study.
Hypothesis One was examined using a multiple linear regression with the self-regulation
subscales of mental alertness and fatigue management as the predictor variables and
perception of workload strain as the criterion variable.
Hypothesis Two was assessed using multiple linear regressions, with mental alertness and
fatigue management as the predictor variables. For the first regression, perceived rART
efficacy was the criterion variable, and was intended to represent the likelihood that
participants would transfer the attention recovery technique to other daily activities. For
the second regression, participant perception of the exercise was the criterion variable
and was intended to represent how participants felt about the exercise, which would also
imply carry-over to other daily activities.
Hypothesis Three. Participants, who reported higher self-regulation scores on mental alertness
and fatigue management, were more likely to complete the course as instructed and
within the specified time allocated. Non-compliant progress through the training
sequence by participants would predict lower retention rates and early termination
before completion of the training sessions.
Hypothesis Four. Student pilots would be more likely to complete the attention recovery
training and score higher on the self-regulating scales than general non-aviation
students.
95
5.16 Statistical procedures. To examine Hypotheses 1, 2, 3 and 4, a series of multiple linear regressions were performed to
ascertain if the independent (predictor) variables significantly predict each dependent (criterion)
variable. Multiple linear regressions were used to determine a predictive relationship amongst a
set of dichotomous or interval predictor variables and an interval level criterion variable.
The standard “enter” method of multiple regressions was used, in which predictor variables are
entered simultaneously into the model. To determine whether the predictor variables collectively
predicted the criterion variable, the F test was used. The R2, the coefficient of determination, was
the statistical output used to ascertain how much variance in each criterion variable was accounted
for by the total collection of predictor variables. Where any overall regression model was
significant, the individual predictors were examined using t tests. For significant predictors, every
one unit increase in the predictor would correspond to an increase or decrease of the criterion
variable relative to the unstandardized beta coefficient.
Prior to each analysis, the assumptions of the multiple linear regression were assessed. These
assumptions included linearity, homoscedasticity, and absence of multicollinearity. Linearity is
the assumption that there is a straight-line relationship between the predictor variables and the
criterion variable and assessed through the examination of scatterplots. Homoscedasticity is the
assumption that the distances between observed and predicted values are normally distributed
and examined through scatterplots. The absence of multicollinearity as a check for the assumption
that the predictor variables were not too highly correlated, was assessed using Variance Inflation
Factors (VIF). Any VIF scores higher than 10 were deemed to be are indicative of the presence
of multicollinearity (Stevens, 2009). Comparative Analyses were assessed using one independent
sample t test and one multivariate analysis of variance (MANOVA).
The independent sample t test is appropriate for use in determining if any statistically significant
differences between two independent groups exist on a single continuous dependent variable
(Field, 2009). MANOVAs are the appropriate analysis to use when the effect of one categorical
96
independent variable is assessed on more than one dependent variable but is only applicable when
the dependent variables are related in some way (Field, 2009).
Based on this rationale, the study completion rate is a single score that should not be correlated
with either of the subscales of SR, meaning that it is appropriate for use in the t- test. Similarly,
because the scales of mental alertness and fatigue management are both subscales of SR, they can
be used together as a series of dependent variables in a MANOVA. The independent variable for
both analyses was the type of participant (i.e., pilot candidate vs. non-pilot candidate).
Prior to analysis, the assumptions of these comparative analyses were assessed. Both analyses
were conducted based on the assumption that data followed normality and homogeneity of
variance; however, the MANOVA also assumes that homogeneity of covariance has been met,
as the multivariate equivalent of homogeneity of variance. Normality in terms of these
comparative analyses is the assumption that the data are normally distributed was examined using
a Shapiro-Wilk test for each dependent variable. Homogeneity of variance and its multivariate
equivalent, homogeneity of covariance, are the assumptions that the groups under examination
have equal error variances. Homogeneity of variance was assessed using Levene’s test, while
homogeneity of covariance was assessed using Box’s M test.
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6. RESULTS
6.1 Introduction
The following chapter details
The present study investigated a technique of Self-Regulation (SR) that resulted in a rapid
recovery of attention (rART). Based on a self-initiated, context-free cued-recall or operant for
retrieval. The study was designed to occur in a naturalistic context within the range of normal
distractions and interruptions experienced by participants at the end of the day, when the effects
of fatigue and temptation were likely. The online and unsupervised delivery of the testing and
training requires SR for continued achievement in the face of competing demands, distractions
and the inevitable end-of-day fatigue. Cognitive processing and performance varies
systematically across circadian time, tasks tend to become more arduous around 7 pm in the
evening and very early in the morning around 4-4:30 am than they are at 9 am in the morning
(Dongen & Dinges, 2000; Kyriacou & Hastings, 2010). Progress and achievement with the rapid
attention recovery training task and the challenge questions were reviewed at each session to
identify the success by way of reports of the extending their use of the rapid ART technique to
other activities outside of the study. Overall, perceived efficacy of the technique was determined
by the extent of participant self-reports of utilisation outside the study.
The development group demographics The baseline test development and retest results The demographics of the experimental group Administration of the online study Issues in the attraction, retention and performance by participants Time and duration in the study by group, age and gender Study completion rates by session, group, age and gender Experimental group performance on the study Results of the four hypotheses Efficacy of the attention recovery technique Gender differences in the study
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6.2 Hypothesis
Hypothesis 1. Self-regulation scores on the independent baseline self-perception
variables of mental alertness and workload strain predict fatigue management.
Hypothesis 2. Participants reporting higher scores on the independent variables of
mental alertness and fatigue management would report transfer and utilisation of the
attention recovery technique to their daily activities.
Hypothesis 3. Participants, who reported higher scores on mental alertness and
fatigue management, were more likely to adhere to instructed session times and
complete the course within the allocated time.
Hypothesis 4. Participants who had identified themselves as pilot candidates would
be more likely to complete the attention recovery training and score higher as
predicted by the baseline measures denoting positive self-regulation, than others.
6.3 Demographics of the baseline test development group The baseline test development sample (n = 61) results provided comparative evidence for the
group of scales indicative of positive self-regulation with that of a subsequent similar group in
the study experimental sample. The baseline test development sample of 61 students from the
aviation faculty of another university were in one of the three years of their course or in a post-
graduate aviation program (Table 6.1), predominantly male (69%), with a modal age of 22 years
with most in the second year of their course - with an overall 18% complement of female trainees.
Five trainees of the 61 representing 8.2% of the sample had a first language other than English.
The test of comprehension as gauged by the Kincaid model (Appendix B, table B2) preceded the
delivery of the baseline test. Respondents who failed to achieve the required 100%
comprehension rate were excluded from the study.
99
Flying Credentials
1st Year 2nd Year 3rd Year Post Graduate Totals
M F Mn
(Age) M F
Mn (Age)
M F Mn
(Age) M F
Mn (Age)
N
Nil 32 8 22 1 22 1 1 36 43
Ab initio 6 1 21 1 33 8
GFPT 2 22 2
PPL 1 22 1
CPL 1 (37) 1 (21) 4 (29) 6
ATPL 1 27 1
Totals 2 51 2 6 61
1See footnote for credentials
Pilot credentials of most respondents in the development sample reflected their early stage of
flying training, leading to the initial general flying progress test status (GFPT). The majority of
the sample (71%, n=43) in the second year of their course had not commenced flying training at
the time of testing. Ten (16.4%) participants had either basic or professional pilot qualifications
with the required medical clearance denoting a standard of physical fitness (CASA_Medical,
2016). The study baseline test development group of 61 student pilots completed the first test and
a second test after a period of 21 – 30 days. The development sample showed an overall
improvement of scores on second administration due to familiarity with the test. The scale means
In summary, the effect size of the difference between the two test administrations, utilising
Cohen’s d, showed a moderately high difference between first and second administration on two
of the five scales related to mental alertness (d = .70) and self- management of fatigue (d = .85),
1 1 License / minimum experience categories Ab-initio (Commenced flying training – instructor supervised) GFPT (General flying progress test – Solo + 30 hours experience – flight in training area) - Class 2 medical clearance PPL (Private Pilot License – Graduated 50+ hours experience – non-paying passenger carrying) - Class 2 medical clearance. CPL (Commercial Pilots License – 150+ hours experience – paying passenger carrying) - Class 1 medical clearance ATPL (Airline Transport Pilots Licence – 1500+ hours experience) - Class 1 medical clearance11
Table 6.1 Aviation Experience Development Group Benchmark Test
100
of the initial development group test (Table 6.2) were subsequently used for comparison with the
experimental group baseline test results (table 6.3). but a lower mean effect size of (d = .31) on
the cognitive abilities scales of executive functioning, choice reaction speed and short term
memory. Improved scores were expected on retesting suggesting greater familiarity with test
items (table 6.3); a marginal retest effect was also evident in the difference in standard deviations
between the two results.
Development Group Baseline Scales
n of
Dev’t test items
Group
Mean n= 61
SD Alpha Stand’
Intra class Corr’n
Mental Alertness 14 80.95 10.97 0.873 .870
Manages Fatigue 10 75.25 11.62 0.808 .797
Functional Performance Items Mean Item Diff’y
Executive Functioning element 6 61.56 18.21 .74
Choice Reaction Time element 5 69.83 18.61 .76
Working Memory element 5 61.370 12.81 .77
The functional or performance items, were introduced to marginally increase the arduousness of
the test rather than their difficulty. These involved elements of executive functioning, choice
reaction time and working memory. A high degree of stability was observed with no practical or
significant differences and low effect sizes (Cohens d) in test-retest results.
6.4 Overview of Experimental Group Study Participation The study was delivered online and unsupervised to volunteers attracted by the flyer detailing a
study of a means of possible improvement in Self-Regulation comparative to those of an Air
Force pilot (Appendix E). The study proceeded with the online system executing the
questionnaire and display of the videos in a programmed sequence.
Table 6.2 Initial development group baseline statistics
101
Completion of the training sequence in the specified time was variable (Table 6.4) with sustained
application achieved by fewer than 21% of the original participants who had commenced the
training. Consistent with the requirements for anonymity in the study, no reasons were sought or
provided for early departures.
Scale Title Effect size
d
Retest
Mean n=61
Std Error
Retest Mean
St Dev Retest
Initial Test
Mean
N=61
Std Error
Initial Mean
St Dev Initial
Sig Diff
Means
Table 6.3 Re-test development group baseline test results
Mental Alertness 0.70 87.95 1.22 9.52 80.95 1.35 10.57 .000
Manages Fatigue 0.85 84.48 1.37 10.67 75.25 1.43 11.2 .000
Perception of workload n/a n/a n/a n/a n/a n/a n/a n/a
Executive Functioning 0.35 64.23 2.3 17.96 58.02 2.33 18.21 .060
Choice Reaction Time 0.43 72.87 1.95 15.21 65.67 2.35 18.33 .020
Working Memory 0.30 63.02 1.21 9.48 59.67 1.65 12.85 .104
102
Table. 6.4. Demographics by study completion and departure rates
Session Study
Item No Completed
Number of respondents
leaving study
% Male Mean Age Male
Female Mean Age
Female
Baseline Test
1 27 12.22% 27 29.78 0 - 11 3 1.36% 3 22.0 0 - 14 1 0.45% 1 33.0 0 - 21 1 0.45% 1 22.0 0 - 23 4 1.81% 4 26.25 0 - 24 13 5.88% 13 28.62 0 - 25 1 0.45% 1 38.0 0 - 26 3 1.36% 3 35.33 0 - 27 3 1.36% 3 28.67 0 - 28 2 0.90% 2 35.0 0 - 29 1 0.45% 1 22.0 0 - 30 43 19.46% 18 24.11 25 29.431 3 1.36% 1 22.0 2 25.0
Baseline test completed – Training commenced
32 3 1.36% 2 21.0 1 42.0 Session 1 33 18 8.14% 7 25.0 11 26.8
35 2 0.90% 0 0.0 2 32.0 Session 2 36 11 4.98% 6 31.5 5 23.6
38 1 0.45% 0 0.0 1 33.0 Session 3 39 9 4.07% 5 33.8 4 26.3
40 1 0.45% 1 42.0 0 0 Session 4 42 4 1.81% 3 39.0 1 22.0
43 1 0.45% 0 0.0 1 28.0 44 2 0.90% 1 33.0 1 28.0
Session 5 45 5 2.26% 1 33.0 4 28.8 46 1 0.45% 0 0.0 1 20.0
Session 6 48 3 1.36% 2 25.0 1 28.0 Session 7 51 5 2.26% 1 33.0 4 28.5 Session 8 54 2 0.90% 1 42.0 1 38.0 Session 9 57 2 0.90% 0 0.0 2 31.0
Session 10 63 46 25 21
Incomplete 175 108 67
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6.5 Experimental Group - Enrolment, Retention & Performance A total number of 385 participants comprising student volunteers from a university aviation
training school and general non-aviation students accessed the study website and established an
anonymous login. Of the 221 entries that had commenced the baseline test, 175 (79.3%)
proceeded to completion of the baseline test and some portion of the training sequence, with
46 participants completing the full study test and training sequence, representing a completion
rate of (20.72%) (table 6.4).
Participants terminating their participation before completion (n=175) included n=131 students
with no flying experience and n=44 with some aviation experience (table 6.6). Individuals who
had commenced and terminated their participation prior to completion (n=121), represented 69%
of total terminations, indicating a ratio of 3:1 of ab-initio and general students to experienced
pilots departing the study. The number of young and mature age participants terminating early
were near equal at 92 and 93 persons respectively. The rate of departure was assessed and
compared with results on the mental alertness and fatigue management scales of positive self-
Table 6.5 Aviation experience by age and gender completing the study
Years Aviation
Experience
Age Range 18-25
Age Range 26-30
Age Range 31-35
Age Range 36-40
Age Range 40-45
Age Range 46+
Totals
M F n M F n M F n M F n M F n M F n N
None 4 4 8 2 2 4 2 1 3 4 3 7 1 3 4 3 2 5 31
1-2 1 1 2 1 1 1 1 1 1 5
3-10 1 1 1
11-15 1 1 3 1 4 5
16+ 1 1 3 - 3 4
Totals 5 5 10 2 2 4 2 2 4 5 4 9 2 4 6 9 4 13 46
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regulation. Pilots scored significantly higher than non-pilots on mental alertness t (219) = 2.617,
p< .009 and management of fatigue t (219) = 2.810, p<.005.
6.6 Experimental Group Compliance with Instructions Compliance behaviour and a capacity to remember and adhere to instructions is deemed to be a
facet of the conscientiousness dimension and of positive SR. Instructions provided to participants
in this study included the request to login nightly and attend to the training just before sleep at
night. Fig 6.1 shows slight variation to instructions on entry time with a non-significant difference
between participants who completed the training to those who did not. Partial completers tended
to engage in the study earlier in the evening, prior to 2000hrs, compared with the completion
group who tended to engage late evening, between 21:00 and 24:00 hrs (Table 6.7). Data related
to compliance with instructions to access the study just before sleep is indicated in the time of
entry and compared with their membership of the complete or incomplete group (fig 6.2) and
table 6.8. The greatest number of early terminations occurred during the baseline testing stage
with 105 (47.5%) individuals departing the study prior to commencement of the rapid attention
recovery sequence of training. Represented by 27 (51%) females with a mean age of 27.25 years
and 78 males with a mean age of 28.2 years. Another 70 male and female participants (32%)
progressively departed during the training before completion. The remainder of the 46
Table 6.6 Demographics of early terminations experimental group
Years Aviation
Experience
Age Range 18-25
Age Range 26-30
Age Range 31-35
Age Range 36-40
Age Range 40-45
Age Range 46+
Totals
M F n M F n M F n M F n M F n M F n N
None 26 15 41 14 13 27 15 10 25 5 - 5 11 6 17 10 6 16 131
1-2 6 6 3 3 1 1 2 2 2 13
3-10 5 5 5 2 7 1 1 1 1 14
11-15 1 1 1 1 1 1 1 1 1 1 5
16+ 1 1 1 1 1 2 3 1 1 5 1 6 12
Totals 38 16 54 23 15 38 18 11 29 7 2 9 13 7 20 18 7 25 175
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participants 25 males and 21 females completed the training. Expected days to complete the
course was 13 days or 312 hours’ total including weekends. Table 6.7 shows the mean days to
complete the course by the Days-Full (completion) group and the Days-Partial (non-completion)
group.
Compliance with the study instructions for entry to the training on successive days-nights were
not adhered to by either course completers (Days-Full) or non-completers (Days-Partial) (Table
6.7). Participants had been sent an SMS daily reminding them to enter the course at a time they
had specified during their setup in the study. That this was not adhered to suggesting the free
times nominated, were in conflict with other personal demands, the SMS being ignored.
Table 6.8 shows the mean hours between entry at each question number (stage). The actual
duration of 240 hours was extended with additional hours due to the non-entry on the three
weekend nights (Friday – Sunday) when participants would likely be otherwise engaged. By
contrast, both groups complied with the preferred late evening entry time except for females in
Table 6.7 Time and days on course by age and completion status
Age Range 18-35 26-30 31-35 36-40 40-45 46+
Gender M F M F M F M F M F M F
Days - Full 31.5 23.8 83.1 87.3 19 27.8 49.1 15.8 44.8 18.9 24.3 42.7
Days - Partial 27.3 31.8 34.3 45 33.3 27.1 - 58.7 25.9 42.1 68.3 54.3
Accessed Time of day/night 00:00 - 24:00hrs
Time Full 23:00 22:30 21:00 22:00 10:30 18:00 21:30 22:00 20:30 21:30 18:30 20:30
Time Partial 00:00 23:30 21:00 20:30 22:00 13:30 - 18:30 00:00 21:00 18:00 22:00
106
the 31-35 age group and males in the 46+ age group. Entry times for both groups are shown
graphically in fig 6.1.
(showing percent of the total sample accessing the online system by time of day)
Figure 6.1 Study login times by course completion status
Table 6.8 Hours elapsed between log-ins and training sessions - all participants
Q'n No
Completed Group Mean time (hours) between sessions (ideal = 24 hrs)
n completed all sessions
Incomplete Group mean time (hours) between sessions
n not completed all sessions
30 59 46 242 73
31 12 46 35 70
33 104 46 281 49
36 59 46 214 36
39 55 46 361 26
42 102 46 145 21
45 55 46 151 13
48 58 46 160 9
51 87 46 274 4
54 89 46 445 2
57 76 46 62 45 46
107
Figure 6.2 Comparison of elapsed log-in times between sessions.
weekday. Study sessions (table 6.8, fig 6.2) concluded with the question at end of each session
regarding ease of use of the technique. A notable difference was found between completers and
non-completers on their compliance in sequentially executing each session at 24 hour intervals
as requested. While neither group were precisely compliant with the 24-hour sequence between
sessions, fig 6.2 illustrates the completion group as significantly more compliant than the non-
completion group, with a lesser variation in elapsed time between sessions. Non-completers with
inconsistent and highly variable attendances or log-ins had all left the study by the third last
session (question 54) (Table 6.8, fig 6.2).
0
50
100
150
200
250
300
350
400
450
500
30 31 33 36 39 42 45 48 51 54 57 62
Completed Group (hours) Incomplete Group (hours)
108
6.7 Perception of Workload Strain Stressful influences related to workload that were not directly generated by the study were
identified by participants with the modified Task Load Index (TLX) instrument. The modified
TLX was delivered online as a component of the baseline test and completed before
commencement of the rART training exercises. Perceived strain, denoting greater demand on
coping resources were expected to be inversely related to mental alertness and fatigue
management, were not evident in the data. However, a significant difference was seen on
perceived strain by gender (fig 6.5).
Frequencies and percentages were calculated for each of the strain sources that participants
indicated as present in their student role (Table 6.9).
The largest overall source of strain reported was mental demand, with more than twice the number
of participant’s n = 72 (31%) identifying this source of strain in the total sample. The least strain
type reported by participants was physical demand n = 7 (3%). The ‘Effort’ facet was the second
least reported source of perceived workload strain (PWS), with n = 11 participants (5%). While
frustration, n = 30 (13%), pace of work n = 33 (14%), and performance n = 25 (15%) had similar
frequencies. A total of n = 41 (18%) participants did not provide a response to the TLX question.
A moderate level (M=57.5, SD=18.79) of PWS was reported by 72% of the final sample (n=46)
(Table 6.10) who had completed the full sequence of study tests and training. Participants
(n=144). terminating the study at various stages (Table 6.8), prior to full completion of the 63
items in the study exercises, indicated no significant difference in their level of PWS (M= 38.3,
SD=17.72) compared to those who had completed the study sequence t (186) = 1.26, p<.05.
To further distinguish participants not completing the study from those who had completed, the
two groups were compared as a ratio of completed to total group (Table 6.10).
The ratio of those completing to those not completing was 1:5.2, representing approximately 20%
of the total sample as depicted in the coping with perceived workload (PWS) (Table 6.8)
109
and (Fig 6.3). Mental demand was reported as the strain facet making the highest demand on
coping skills, as represented by 41% of the sample who had completed the course.
Analysis of the means for perceived workload strain (PWS) (Table 6.11) with a test value = 50,
showed results significantly lower by 7.8 (95% CI, -13.7 to -2.0) than a hypothesised normal
population score of 50 (43) = -2.692, p = .01. A comparison by Gender between high and low
coping scores on PWS revealed two distinct distributions in the six facets of the scale with the
Table 6.10 Ratio of Perceived workload strain by completions group
Workload Strain n = 44 Frequency Percent Cumulative
Percent
Ratio of completed
to not completed
Frustration 6 13.6 13.6 1:5
Mental Demand 18 40.9 54.5 1:4
Pace of Work 10 22.7 77.3 1:3.3
Performance 9 20.5 97.7 1:3.9
Physical Demand 1 2.3 100 1:7
Effort 0 0 0 -
Total 44 100
Figure 6.3 Perceived source of workload strain – completion group
110
theme of how hard it is to achieve and cope with the workload. Males reported higher coping
(n = 25, M = 50.24, SD = 18.06) than Females. Levene’s test for homogeneity showed the
assumption for homogeneity was met with the equality of variances for Mental Alertness (p=.22),
Manages Fatigue (p=.14), reported Efficacy of the rART, Perception of workload strain (p=.11).
No difference was found in the equality of means by Gender on the Manages Fatigue scale t (42)
=.96, p = n.s. There was a statistically significant difference in PWS scores between males and
females t (42) = 3.23, p < .002. The mean difference for Males was 16.97 (CI95%, 6.4 to 27.6)
higher than female PWS scores with a higher effect size for Cohens d = 0.97. Results for the
cognitive performance items of working memory, choice reaction speed, executive functioning
and the daily challenge test items 1- 5, showed considerable variability between genders and
successive executions, while there was no significant difference between the genders in reports
of the efficacy of the rapid attention recovery technique
t (42) = .636, p > .528, and corresponding ease of use of the technique (fig 6.5).
Table 6.11 Perceived Workload Strain one-sample test
test value = 50 t df Sig.
(2-tailed) Mean
Difference
95% Confidence Interval of the DifferenceLower Upper
Coping with PWS -2.692 43 .010 -7.7955 -13.635 -1.956
111
6.8 Experimental group baseline test performance by Gender Comparison of gender differences on all results for both males and females are shown in table
6.12 and fig 6.6. PWS is indicated as the measure having the largest effect size (d = .97) amongst
the non-functional abilities test items. The data in table 6.12 shows the relative performance on
the TLX PWS scale as 44% of males having reached baseline compared with 9.52% of females.
Results for the cognitive performance items of working memory, choice reaction speed, executive
functioning and the daily challenge test items 1- 5, showed the most variability.
Figure 6.4 Gender by coping with perceived workload strain
112
Note: Fourth Challenge group items deleted due to outliers.
Scale Title Effect Size d A‐B
%=> criterion A Male
%=> criterion B Female
Mean A
n=25 Male
St Dev A
Male
Mean B
n=21 Female
St Dev B
Female
Mental Alertness 0.15 84.00% 71.43% 60.72 12.00 58.52 17.36
Manages Fatigue 0.34 60.00% 47.62% 52.16 14.39 46.29 21.39
Coping Work Load Strain 0.97 44.00% 9.52% 49.76 18.06 33.81 15.17
Choice Reaction Speed ‐0.64 48.00% 80.95% 49.72 25.78 63.62 16.81
Executive Functioning 0.02 76.00% 66.67% 68.64 27.23 68.00 29.08
Working Memory ‐0.51 64.00% 80.95% 59.24 17.68 68.10 18.07
Reported rART Efficacy 0.08 80.00% 76.19% 60.24 24.58 58.52 20.12
First Challenge Question 0.05 76.00% 76.19% 77.88 23.10 76.90 20.24
Second Challenge uestion ‐0.02 96.00% 80.95% 83.72 22.64 84.10 23.34
Third Challenge Question 0.89 84.00% 47.62% 82.52 20.58 61.62 27.49
Fifth Challenge Question 0.32 96.00% 85.71% 77.56 15.86 72.14 19.45
Table 6.12 Experimental group baseline test means by Gender
Figure 6.5 Experimental Group total test results by gender
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6.9 Sample Bias and Generalisability of results To achieve generalisation of the results, the recruiting advertising attracted students with a desire
to perform better academically or seek to experience a novel self-improvement process. As such
the total sample could be deemed to be a biased sample. The ‘Hawthorne effect’ was not deemed
to be present in the study. Participation was anonymous and not about any particular or special
attention or even about an awareness of their individual part in the study or relevant to the
presence of any experimenter. Nevertheless, it would be true to say the sample of students (both
aviation and other faculty) were self-selected by the invitation to learn a technique to improve,
thus representing other than a disinterested random group. In that invitation, they are viewing the
experiment in terms of their personal needs, rather than the experimenters, in which case the
resultant bias is difficult to identify; but one likely to be replaced by their sense of self-efficacy.
6.10 Results for Hypothesis 1. Fatigue affects Behaviour
The independent variables of mental alertness and workload strain would predict the dependent
self-regulation variable scores for fatigue management.
A multiple linear regression analysis was conducted for hypothesis one to assess whether a
relationship existed between Mental Alertness (behaviours denoting prevalence of cognitive
failure or alertness) and Perceived Workload Strain (PWS) (extent and type of strain experienced)
with Fatigue Management (how well fatigue was being managed). The 'Enter' variable selection
method was chosen to include all selected variables into the model. The assumption of normality
was assessed by plotting the quantiles of the model residuals against the quantiles of a Chi-square
distribution, shown as a Q-Q scatterplot (DeCarlo, 1997).
The data was inspected for the assumption of normality and whether the quantiles of the residuals
deviated from the theoretical quantiles, such that strong deviations from the theoretical quantiles
would have indicated that the parameter estimates were unreliable. Assumption of
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homoscedasticity was also assessed by plotting the model residuals against the predicted model
values (Osborne & Waters, 2002) and inspected to confirm that the points appeared as randomly
distributed with a mean of zero and no apparent curvature.
A Q-Q scatterplot of the model residuals is shown in Fig 6.6 and a scatterplot of predicted values
and model residuals is depicted in Fig 6.7. Because both plots followed the parameters necessary
to assume normality and homoscedasticity, both assumptions were met. Variance Inflation
Factors (VIFs) were calculated to detect multicollinearity between predictors where the VIFs
were in the unacceptable range of five to ten (Menard, 2010). VIFs for this model were both
shown to be 1.12, such that multicollinearity was not a concern. Table 6.13 presents the Variance
inflation factor for each predictor in the model.
Table 6.13 VIF for Mental Alertness and Fatigue Management
Variable VIF
Workload strain 1.12
Fatigue Management 1.12
Table 6.14 Regression predicting Fatigue Management on Mental Alertness and Perceived Workload Strain
Variable B SE β t p
(Intercept) 3.23 3.41 .00 -0.95 .344
Mental Alertness 0.73 0.06 .67 13.07 < .001
Perceived workload strain 0.21 0.05 .20 3.84 < .001
Note: F (2,185) = 122.16, p<.001, R2 = .57
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The results of the linear regression model, F (2,185) = 122.16, p < .001, R2 = .57, were significant
indicating that Mental Alertness and Perceived Workload Strain explained approximately 57%
of the variation in Management of Fatigue. Since the overall model was significant, the individual
predictors were examined further. Both mental alertness and coping with perceived workload
strain were found to be significant predictors of fatigue management at the p < .001 level. Results
indicated that a single unit increase in mental alertness corresponded with a 0.73-unit increase in
management-of-fatigue scores, while a single unit increase in perceived workload strain
corresponded with a 0.21unit increase in Management of Fatigue. Table 6.14 summarizes the
results of the regression model.
Figure 6.6 Q-Q scatterplot for normality for Mental Alertness and Perceived Workload Strain predicting Fatigue Management.
Figure 6.7 Residuals scatterplot for homoscedasticity of Mental Alertness and Perceived Workload Strain predicting Fatigue Management.
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6.11 Results for Hypothesis 2 - Self-regulation predicts rART usage
Participants reporting higher scores on the independent variables of self-regulation, mental
alertness and fatigue management, would report transfer and utilisation of the attention recovery
technique to their daily activities. To inform hypothesis two, a series of two multiple linear
regressions were conducted. The first multiple linear regression analysis was conducted to assess
whether a relationship existed between Mental Alertness and Management of Fatigue and
perceived efficacy of the rART. The variable of Perceived rART Efficacy was intended to
represent the extent to which participants had gained some competence due to the training and
had transferred the attention recovery technique to assist with other daily activities.
Hypothesis two – regression one.
To inform hypothesis two, a series of two multiple linear regressions were conducted. The first
multiple linear regression analysis was conducted to assess whether a relationship existed
between Mental Alertness and Management of Fatigue and perceived efficacy of the rART. The
variable of Perceived rART Efficacy was intended to represent the extent to which participants
had gained some competence due to the training and had transferred the attention recovery
technique to assist with other daily activities. The 'Enter' variable selection method was chosen
for the model, forcing all selected variables into the analysis simultaneously. The assumption of
normality was assessed by plotting the quantiles of the model residuals using a Q-Q scatterplot
(DeCarlo, 1997). The assumption of homoscedasticity was assessed by plotting the model
residuals against the predicted model values (Osborne & Waters, 2002).
Fig 6.8 presents a Q-Q scatterplot of the model residuals. Fig 6.9 presents a scatterplot of
predicted values and model residuals. Visual examination of these plots indicated that the
assumptions of normality and homoscedasticity were met. Variance Inflation Factors (VIFs) were
calculated to detect the presence of multicollinearity between predictors. Because neither VIF
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exceeded 5, there was no cause for concern of multicollinearity. Table 6.15 presents the Variance
Inflation Factor for each predictor in the model.
The results of the linear regression model were not significant, F (2,41) = 0.83, p = .445, R2 =.04,
indicating Mental Alertness and Fatigue Management did not explain a significant proportion of
variation in Perceived rART Efficacy. Since the overall model was not significant, there was no
evidence of the individual predictors of the technique showing any effect over the study training
development time and were not examined further.
Table 6.16 summarizes the results of the regression model for hypothesis two and regression one.
Table 6.15 VIF for Mental Alertness and Management of Fatigue
Variable VIF
Mental Alertness 2.85
Management of fatigue 2.85
Figure 6.8 Q-Q scatterplot for normality for Mental Alertness and Fatigue Management predicting Perceived rART Efficacy
Figure 6.9. Residuals scatterplot for homoscedasticity for Mental Alertness and Management of Fatigue predicting Perceived rART Efficacy
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Table 6.16 Regression predicts rART Efficacy on Mental Alertness and Fatigue
F (2,41) = 0.83, p = .445, R2 =.04
Hypothesis two – regression two.
The second multiple linear regression analysis for hypothesis two was conducted to assess
whether a relationship existed between Mental Alertness and Fatigue Management and Perceived
Ease of rART Method. The use of Perceived Ease of rART Method as the criterion variable was
intended to represent how participants felt about the exercise, which may also imply a carry-over
to other daily activities. The 'Enter' variable selection method was chosen for the linear regression
model. The assumption of normality was assessed by visual examination of a Q-Q scatterplot
(DeCarlo, 1997). The assumption of homoscedasticity was assessed by plotting the model
residuals against the predicted model values (Osborne & Walters, 2002). Variance Inflation
Factors (VIFs) were calculated to detect the presence of multicollinearity between predictors. All
predictors in the regression model have variance inflation factors (VIF) less than 10, indicating
an absence of multicollinearity.
Variable B SE β t p
(Intercept) 44.84 13.81 0.00 3.25 .002
Mental Alertness 0.46 0.37 0.32 1.24 .222
Fatigue Management -0.24 0.30 -0.21 -0.80 .430
Table 6.17 VIF for Mental Alertness and Fatigue
Variable VIF
Mental Alertness 2.85
Fatigue Management 2.85
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Table 6.17 presents the Variance Inflation Factor for each predictor in the model. Fig 6.10
presents a Q-Q scatterplot of the model residuals. Fig 6.11 presents a scatterplot of predicted
values and model residuals. Visual examination of both plots indicated that normality and
homoscedasticity could be assumed. The results of the linear regression model were not
significant, F (2,41) = 0.89, p = .416, R2 = 0.04, indicating Mental Alertness and Fatigue
Management did not explain a significant proportion of variation in Perceived Ease of rART
Method. Since the overall model was not significant, the individual predictors were not examined
further. Table 6.18 summarizes the results of the regression model.
Note. F (2,41) = 0.89, p = .416, R2 = 0.04
Variable B SE β t p
(Intercept) 30.70 5.38 0.00 5.70 < .001
Mental Alertness 0.16 0.15 0.28 1.09 .281
Fatigue Management -0.05 0.12 -0.11 -0.42 .674
Table 6.18 Regression predicting Perceived rART Efficacy on Mental Alertness and Fatigue Management
Figure 6.10 Q-Q scatterplot for normality for Mental Alertness and Fatigue Management predicting Perceived Ease of rART Method
Figure 6.11 Residuals scatterplot for homoscedasticity for Mental Alertness and Fatigue Management predicting Perceived Ease of rART Method
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6.12 Results for Hypothesis 3. Self-regulation predicts course completion
Participants, who reported higher scores on mental alertness and fatigue management, were more
likely to adhere to instructed session times and complete the course within the allocated time.
To examine hypothesis three, a multiple linear regression analysis was conducted.
This analysis was designed to assess whether a relationship existed between Mental Alertness
and Fatigue Management and Course completion. The 'Enter' variable selection method was
chosen for the linear regression model. The standard test for normality was assessed using a
Q-Q scatterplot (DeCarlo, 1997). Homoscedasticity was assessed by plotting the model residuals
against the predicted model values (Osborne & Walters, 2002). Fig 6.12 presents a Q-Q
scatterplot of the model residuals. Fig 6.13 presents a scatterplot of predicted values and model
residuals. Visual examination of this plot indicated that there may be a deviation from normality
based on the combination of the variables Mental Alertness, Fatigue Management and Course
completion. However, homoscedasticity could be assumed, based on the visual examination of
fig 6.12. Variance Inflation Factors (VIFs) were calculated to detect the presence of
multicollinearity between predictors. Again, the use of these two predictors did not result in VIFs
that exceeded 5, and multicollinearity was not established in this analysis. Table 6.19 presents
the VIF for each predictor in the model.
While late evening login time for task execution showed a slight non-significant difference in
time of entry by the two groups of completers and non-completers as depicted in (Ch 5, fig 6.2),
the time between sessions varied considerably with no respondents successfully completing
Table 6.19 VIF for Mental Alertness and Fatigue Management
Variable VIF
Mental Alertness 2.31
Fatigue Management 2.31
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within 12 days of start despite the SMS reminders. However, the variance between completers
and non- completers was significant.
Figure 6.12 Q-Q scatterplot for normality for Mental Alertness and Fatigue Management predicting Rate of Completion
Figure 6.13 Residuals scatterplot for homoscedasticity for Mental Alertness and Fatigue Management predicting Rate of Completion
Consequently, the time between sessions variable could not be used in the analysis, as it did not
vary either side of the required time. It is worth noting that the entire sample followed this trend.
The results of the linear regression model were not significant, F (2,217) = 2.70, p = .070, R2 =
0.02, indicating Mental Alertness and Fatigue Management did not explain a significant
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Table 6.20 Regression predicting Completion by Mental Alertness and Fatigue Mgmt
Variable B SE β t p
(Intercept) 53.90 5.51 0.00 9.79 < .001
Mental Alertness -0.11 0.14 -.08 -0.79 .433
Fatigue Management 0.26 0.13 0.21 2.03 .043
Note. F (2,217) = 2.70, p = .070, R2 = 0.02
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proportion of variation in Rate of Completion. Since the overall model was not significant, the
individual predictors were not examined further.
6.13 Results for Hypothesis 4 - More aviation students complete the course
Participants who were identified as aviation students would be more likely to complete the
attention recovery training and score higher on the self-regulating scales than others.
Hypothesis four was assessed using one independent sample t- test and one multivariate analysis
of variance (MANOVA). The independent sample t-test (table 21) was conducted first and was
designed to examine whether the mean of Rate of Completion was significantly different between
the aviation candidates and non-aviation candidates, as grouped and based on their flying
experience. One group consisted of participants with zero years of flying experience, and one
group consisted of participants with one or more years of flying experience. Prior to the analysis,
the assumptions of normality and homogeneity of variance were assessed.
A Shapiro-Wilk test was conducted to determine whether Rate of Completion could have been
produced by a normal distribution. The results of the test were significant, W = 0.90, p < .001,
suggesting that Rate of Completion was unlikely to have been produced by a normal distribution,
thus normality cannot be assumed. However, consistent with the Central Limit Theorem the
mean of any random variable will be approximately normally distributed as the sample size
increases, therefore, with a sufficiently large sample size (n > 30), deviations from normality
would have negligible effect on the results. Levine's test was used to assess whether the
homogeneity of variance assumption was met, such that the variance of the dependent variable
was approximately equal in each group, represented by each combination of factor levels in the
independent variables. Levine's test F (1, 227) = 1.34, p = .248, indicated that the assumption of
homogeneity of variance was met.
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The result of the independent samples t-test (table 6.21) was not significant, t (227) = -0.76, p =
.447, suggesting that the mean of Rate of Completion was not significantly different between the
pilot and non-pilot groups.
A MANOVA was conducted to determine differences in Mental Alertness and Fatigue
Management. Because the scales of mental alertness and fatigue management are both subscales
of the self-regulation construct, they could be used together as the correlated series of dependent
variables in this MANOVA. In the analysis, the assumptions of the MANOVA were assessed and
normality was assessed using a Shapiro-Wilk test for each of the two dependent variables, while
homogeneity of variance and covariance matrices were assessed with Levine’s test and Box’s M
test, respectively.
The results of the Shapiro-Wilk test for Mental Alertness were not significant (W = 0.99, p =
.101), but were significant for Fatigue Management (W = 0.99, p = .022), given that the sample
size was large enough to reduce some of the effects of non-normality on the results.
Results of Levine’s test indicated that neither the Mental Alertness (p = .869) nor the Fatigue
Management variable (p = .091) had any significant violation of homogeneity of variance.
Similarly, Box’s M test did not indicate any significant degree of violation to the assumption of
homogeneity of covariance matrices (p = .370).
Table 6.21 Independent Samples t-Test for pilot experience by completion
Variable
Nil years pilot experience
Some year’s pilot experience
M SD M SD t p d
Rate of Completion 56.36 25.56 59.36 28.20 -0.76 .447 0.11
Note. Degrees of Freedom for the t-statistic = 227. d represents Cohen's d.
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Results of the MANOVA showed a significant difference between student pilots and non-pilot
students in terms of the two dependent variables (i.e., Mental Alertness and Fatigue Management)
at the p < .05 level F (2, 217) = 3.20, p = .043.
This finding
indicated that the difference could exist on one or both subscales. Additional testing was
conducted to identify where the pilot versus non- pilot differences lay. To accomplish this, two
ANOVAs were conducted, one for each dependent variable. (Mental Alertness and Fatigue
Management)
Analysis of variance for mental alertness. The first analysis of variance (ANOVA) was conducted to determine whether there were
significant differences in Mental Alertness based on placement in a pilot versus non-pilot group.
Prior to the analysis, the ANOVA assumptions were examined.
The Shapiro-Wilk test conducted for the MANOVA had previously indicated that any deviation
from normality in this variable was explainable by random chance, thus normality can be
assumed. Levine's test for equality of variance was used to assess whether the homogeneity of
Table 6.22 Analysis of Variance for Fatigue Management by Pilot Experience
Variable df SS MS F p η2
Pilot Experience 1 1722.03 1722.03 5.35 .022 0.02
Residuals 219 70548.89 322.14
Table: 6.22b Descriptive statistics for Mental Alertness by Pilot Experience
Pilot Experience M SD n
Nil years pilot experience 55.93 17.79 161
One or more years’ pilot experience 62.21 18.38 60
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variance
assumption was met. The result of Levine’s test was not significant when examining this variable
alone, F (1, 219) = 0.09, p = .761, indicating that the assumption of homogeneity of variance was
met for the first Anova. The second ANOVA was conducted to determine whether
there were significant differences in Fatigue Management based on placement in pilot versus non-
pilot group. Prior to the analysis, the ANOVA assumptions were examined. The overall model
was significant at the 95% confidence level, F (1, 219) = 5.35, p = .022 (Table 6.22b), indicating
that there were significant differences in Mental Alertness based on group placement in either the
pilot or non-pilot group. Examination of group means showed that participants in the group with
one or more years of flying experience had on average significantly higher levels of Mental
Alertness. The means and standard deviations are presented in Table 6.24. Although the overall
model was significant, post-hoc testing was not conducted. Since all independent variables in the
model had only two factor levels, pairwise testing would not contribute to the analysis.
Analysis of variance for fatigue management.
The Shapiro-Wilk test conducted for the MANOVA previously indicated that the distribution for
this variable was unlikely to have been explainable by random chance (W = 0.99, p = .022).
Figure 6.14 Means of Rate of Completion by Pilot Experience.
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However, as per the CLT the sample size was large enough to reduce some of the effects of non-
normality on the results. The result of Levine's test was therefore not significant when examining
this variable alone, F (1, 218) = 2.13, p = .146, indicating that the assumption of homogeneity of
variance was met for the ANOVA.
The overall model was significant at the 95% confidence level, F (1, 218) = 6.08, p = .014 (Table
6.23), indicating that there were significant differences in Fatigue Management by student pilots.
Examination of the group means indicated that, on average, participants in the group with one or
more years of pilot experience had significantly higher levels of Fatigue Management skills than
those in the group with no aviation experience.
Means and standard deviations are presented in Table 6.24. Although the overall model was
significant, posthoc testing was not conducted. Since all independent variables in the model had
only two factor levels, pairwise testing would not contribute additional information to the
analysis.
Table 6.23 Analysis of variance for Fatigue Management by Pilot Experience
Variable df SS MS F p η2
Pilot Experience 1 2260.80 2260.80 6.08 .014 0.03
Residuals 218 81012.24 371.62
Table 6.24 Descriptive statistics Fatigue Management by Pilot Experience
Pilot experience M SD n
Zero years Pilot experience 44.59 18.23 160
Some years Pilot experience 51.79 21.84 60
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6.14 Contribution of Gender to the study.
Gender differences were not specifically hypothesised and included in the study. However, the
data suggests a significant contribution by that variable and are worth noting. Self-Regulation
differences as measured by the independent variables of mental alertness, fatigue management
and perceived workload gender differences were evident in the data, which was assessed using a
multiple linear regression with the three predictor variables, but also included the control variable
of gender. By controlling for gender, gender-based differences were parsed out, and all
participants could be treated as equal in terms of gender. This allowed the analysis to identify
whether gender-based differences explained more of the variance in study completion rates than
the independent variables of mental alertness, fatigue management, and perceived workload
strain. The 'Enter' variable selection method was chosen for the linear regression model.
Normality was assessed through visual examination of a Q-Q scatterplot. Homoscedasticity was
similarly assessed by plotting the model residuals against the predicted model values. Fig 6.16
presents the Q-Q scatterplot of the model residuals. Fig 6.17 presents the scatterplot of predicted
values and model residuals. A slight deviation from the hypothetical quantiles in the Q-Q plot,
indicated that the assumption of normality may not have been met for this analysis and the results
should be interpreted cautiously. Variance Inflation Factors (VIFs) to detect the presence of
multicollinearity between predictors were calculated. All predictors in the regression model had
variance inflation factors (VIF) less than 5, indicating no cause for concern (Table 6.26). The
results of the linear regression model were not significant, F (4,171) = 2.26, p = .064, R2 = 0.05
(table 6.27), indicating the variables of Gender, Mental Alertness, Perceived Workload Strain,
and Fatigue Management did not explain a proportion of the Rate of Completion. Because the
model was not significant, individual predictors were not assessed.
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Note. F (4,171) = 2.26, p = .064, R2 = 0.05
6.15 Gender bias in task completion
Table 6.26 VIF for Gender, Mental Alertness, Workload Strain and Fatigue Management
Variable VIF
Gender 1.02
Mental Alertness 2.25
Fatigue Management 2.27
Perceived Workload Strain 1.18
Table 6.27 Analysis of variance for Gender, Mental Alertness, Fatigue & workload strain
Variable B SE β t p
(Intercept) 55.30 6.39 0.00 8.65 < .001
Gender 3.73 3.48 0.08 1.07 .286
Mental Alertness -0.12 0.14 -0.09 -0.85 .397
Fatigue Management 0.16 0.14 0.13 1.20 .231
Perceived Workload Strain 0.20 0.11 0.15 1.85 .066
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Extending the exploration of the Gender variable with the same statistical treatments as for the
hypothesis, a multiple linear regression analysis was conducted to assess whether a relationship
existed between Gender, Mental Alertness, Fatigue Management, and Perceived Workload Strain
and Overall Cognitive Abilities as measured by short term memory, choice reaction speed and
executive functioning. By controlling for gender, gender-based differences were parsed out, and
all participants could be treated as equal in terms of gender. This allowed the analysis to identify
whether gender-based differences explained more of the variance in completion rates than the
independent variables of mental alertness, fatigue management, and perceived workload strain.
The 'Enter' variable selection method was chosen for the linear regression model.
The assumption of normality was assessed by visual examination of a Q-Q scatterplot. The
assumption of homoscedasticity was assessed by plotting the model residuals against the
predicted model values. Fig 6.18 presents a Q-Q scatterplot of the model residuals. Fig 6.19
presents a scatter plot of predicted values and model residuals. Based on examination of the two
plots, the assumptions of normality and homoscedasticity were met. Variance Inflation Factors
(VIFs) were calculated to detect the presence of multicollinearity between predictors. All
Figure 6.16 Q-Q scatterplot for normality for Gender, Mental Alertness, Perceived Workload Strain, and Fatigue Management predicting Rate of Completion
Figure 6.17 Residuals scatterplot for homoscedasticity for Gender, Mental Alertness, Perceived Workload Strain, and Fatigue Management predicting Rate of Completion
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predictors in the regression model have satisfactory variance inflation factors (VIF) less than 5.
Table 6.28 presents the VIF for each predictor in the model.
Table 6.28 VIF for Gender, Mental Alertness, Fatigue Management, and Perceived Workload Strain
Variable VIF
Gender 1.03
Mental Alertness 2.07
Fatigue Management 2.21
Perceived Workload Strain 1.18
Figure 6.18. Q-Q scatterplot for normality for Gender, Mental Alertness, Fatigue Management, and Perceived Workload Strain predicting Overall Cognitive Performance
Figure 6.19. Residuals scatterplot for homoscedasticity for Gender, Mental Alertness, Fatigue Management, and Perceived Workload Strain predicting Overall Cognitive Performance
Variable B SE β t p
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Note. F (4,170) = 1.31, p = .269, R2 = 0.03
The results of the linear regression model were not significant, F (4,170) = 1.31, p = .269, R2 =
0.03, indicating Gender, Mental Alertness, Fatigue Management, and Perceived Workload Strain
did not explain a significant proportion of variation in Overall Cognitive Abilities scores. Since
the overall model was not significant, the individual predictors were not examined further. Table
6.29 summarizes the results of the regression model.
(Intercept) 62.16 5.56 0.00 11.18 < .001
Gender: Male 4.37 3.03 0.11 1.44 .152
Mental Alertness -0.19 0.12 -0.17 -1.59 .114
Fatigue Management 0.16 0.12 0.15 1.37 .174
Perceived Workload Strain -0.04 0.09 -0.04 -0.43 .669
Table 6.29 Regression predicting Cognitive Performance on Gender, Mental Alertness, Fatigue Management and Perceived Workload Strain.
Figure: 6.19 Total Group Report of RART Efficacy
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6.16 Efficacy of the rapid ART Technique by gender
While reports by participants of the efficacy of the rART training were independent of study
predictors, total group result showed an overall positive trend in utilisation with corresponding
reports of ease of use of the technique (Fig 6.20). Efficacy of the technique, reported as having
been extended into other aspects of participant daily activities was seen to be near equal in number
for females and males, with a total group mean of 59.4 and with females reporting a slightly
higher level of efficacy and utilisation than males.
Figure: 6.20 Efficacy of rART by Gender
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7. DISCUSSION
Introduction Study Objectives The study had two objectives and four testable hypotheses to explore the rapid attention recovery
technique as a Self-Regulation skill and as a means for recovery of attention. . The first objective
of the study involved the investigation of the efficacy of a rapid attention recovery technique as
a SR skill when subject to fatigue, preoccupation and distraction. The second, investigated the
efficacy of delivering that training technique unsupervised and online.
It was emphasised in this study that human error continues to be the major contributor to incidents
across all industries and the reason for the non-achievement of zero-harm in organisations. While
human error and fatigue specifically, have received considerable emphasis and are now well
accepted as a category of fault, little or none of the insights developed in the social and neural
sciences regarding self-regulation have emerged to influence the way organisations prepare
people for their employment. A growing trend has emerged in the education industry which has
recently seen the selective implementation of MT (mindfulness training) as preparatory training,
offered as an option in some secondary schools and to medical school graduates. SR (self-
regulation) also has a specific and crucial application in the healthcare industry due to the threat,
vulnerability and temporal constraints that exists in those environments. SR training to maintain
situational awareness, attention to the task and responsiveness to threat, requires understanding
of the mechanism involved in the training. Meditation for example, long identified as a
contemplative rather than as an ‘action-based’ solution has tended to be ignored in western
cultures. The rART (rapid attention recovery technique) study in utilising a different mechanism
works to achieve a similar and more rapid effect. A significant consideration in the study also
related to what it was that was to be improved, what universal markers could be advanced,
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measured and assessed as indicators for achievement, for example what behaviours do you see
that shows the rArt is working and effective? Since for many the training medium is important
for engagement and retention, this study evaluated the online medium as the vehicle for such
training.
In the preceding chapters the behavioural markers for performance were identified as a standard
for the achievement of action and a target for subsequent testing. A valid neurologically based
underlying mechanism for the expression of those was proposed in terms of an actionable process
of SR following the Hofmann, Endsley and elements of the three attention models discussed in
chapter two.
Training modalities and psychophysiological correlates were examined and compared for their
utility and efficacy resulting in one universal and rapid means to activate attention. Achieved
through a neurophysiological device acting to clear mental space to allow for a clearer focus and
increased responsivness. Comparison was made with MT (mindfulness training) and CB
(cognitive -behavioural) methods as having similar objectives through the process of meditation
and diaphragmatic breathing in one and improving coping through symantic clarification in the
other. Other more conventional training approaches by comparison had less certainty of effect
and a much slower rate of achievement. They were also subject to the same interruptions that they
were seeking to overcome, ie., forgetting to use a checklist, and could only be implemented after
the fact of cognitive failure, when there was evidence of failure, rather than as preventative action.
The Study Background
The second objective of this study was in delivering the training unsupervised and in a naturalistic
setting, competing with the distractions and fatigue that are an inevitable part of every students
life. The study was the second investigation of the rART mechanism (Rosenweg, 2006), the first
having been a small pilot-study with 32 police candidates and chemical plant operators, in the
disciplined peace of a classroom setting with face-to-face instruction and personal follow-up. The
difference in engagement between the two applications was subsequently evident in the high
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attrition rate and variable attendance in participation in the online study. The unsupervised online
context was expected to provide the means to test the the model with the least input by an
instructor.
Training that allows the individual to learn to recover their presence of mind under stress or to do
so without further reminders, has favoured action environments in which development was
assumed to go hand in hand with application and practice, rather than contemplation. How to
improve SR, has become more formal and scientific, through the exploration of brain-states and
the neural networks involved. As with the Tang, Rothbart & Posner, (2012) studies utilising
Posner’s attention network theory to better understand the Mindfulness technique in
development. While conventional SR training methods may be used to regulate behaviour and
help to ensure achievement for the individual, in the rART study the recovery technique is
proposed as an instantaneous method, triggered by an operant to unload the persons stressed or
distracted mental-state and direct their full attention to the problem. A mechanism suitable for
troubled times.
Comparison of the technique has been made with other methods and training modalities,
including Cognitive Behavioural methods and Mindfulness training with which it shares
diaphragmatic breathing in the establishment phase. The mechanism necessarily diverts from
meditation in using the attention network theory and instrumental conditioning. Other well
developed cognitive behavioural, meditative or ecologically oriented measures, as described in
Kaplan’s ART theory (Kaplan & Berman, 2010) have demonstrated the validity and viability of
adding the management of mental-state to more fully define self-management. Tang, Posner and
Rothbart have similarly applied Posner’s attention network theory to mental-state training and a
better understanding of the neurological or network basis contributing and enabling the
development of SR. Further identifying the action in the neural paths will help to sharpen and
guide future strategies and interventions.
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Controls and Structure in the Course
The proposed training exercise was anticipated to be offered to those who had an interest in
improving their self-regulation. That interest suggests an immediate bias in the sample. The
objective was to teach a SR skill to students attracted to the possibility of improving their attention
and resilience, but with no experience to understand the concept. Consequently, participants were
informed at start regarding the manner in which the study was to be conducted. Additionally the
course was structured to ensure that any variation due to the way it was done would not confound
the results. Systematic controls included a daily reminder via an SMS message to each participant,
access to the course was constrained to occur after a a certain time in the evening, just prior to
sleep and the computerised process ensured that the delivery was uniform and identical for all
participants. The one-way direction of the program prevented digression and distraction as all
participants could only go forward. The video instruction was timed to run for a certain time but
that could be replayed as often as required. A progressive question check inviting self-report of
engagement in the process ran after each session. Weekends were avoided as likely not available
due to social needs. While entry time of day to the sessions were very similar for most
participants, consistently late evening as suggested in the setup, the daily return to the study was
not as consistent with some participants doing a part then returning after a week or more to resume
the training. There was no exit interview for those terminating the course prior to completion,
hence it is not known why students departed. It could be surmised that some forgot to return,
captured by other tasks, or were faced with more seductive attractions at the late night time for
the exercise, such as sleep. Course experience of the design may not have been sufficiently
engaging, attractive or entertaining leaving the participant open to boredom and to downgrade
the study as a priority. Time between sessions were significantly greater than planned. A number
of students returned to the study after an absence of a week or two to resume the course before
eventually ceasing their participation altogether. It is not known if their return was based on a
waning sense of obligation to continue or whether they had experienced sufficiently positive
137
results after a few short sessions to encourage continuation, for a time. Benchmark test results
were obatained from 175 participants who terminated early and final full study results from an
additional 46 participants.
What difference was sought
A key difference sought in implementation, compared to mindfulness, CB, resilience training and
other metacognitive methods in general, was the rapidity of acquiring the self-regulating skill at
a basic level. The target condition being instant access to greater mental clarity and
responsiveness while in or together with, an energised mental state not crowded with unfinished
business. An ability that may be considered as more appropriate for ‘high personal demand’
scenarios and occupations and where sustained attention was required. Although an optimum
training schedule was not defined in this study and no measure or grade of achievement was
obtained, it appeared that the short 10 minutes per day for 10 days’ practice of the rART was
sufficient for some, with participants reporting a 65% degree of efficacy and presumably
satisfaction with the results based on report of use of the technique elsewhere.
At the theoretical level, SR helps to shape the individual’s choice of coping style, which in turn
influences the individual’s resilience or recovery and related capacity for mental effort. In this
respect, the development of SR in childhood has the potential capacity to inoculate the person in
later life to serious stressors that might otherwise result in problem behaviours. The pivotal issue
being the acquisition of mental control, rather than experience the trauma of the unprepared. SR
invoked by a simple operant, suggests the operation of an explicit choice. In this respect, SR
should be distinguished from self-control. While self-control has a similar and limited capacity
to reduce disruptive behaviours, its focus is significantly more directed to repression of impulse
rather than in freeing up cognitive capacity and may be counter-productive. SR is an executive
process directing behaviour into the direct-action form of coping and mental state as characterised
by Monet & Lazarus (1977). As an executive function, SR techniques with the ability to remove
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preoccupations and worry thinking will reinforce cognitive resilience, the ability to recover from
adversity or overload and to continue to function as required.
Study Outcomes The study attracted some 400 students in total, of whom 228 initiated a log on and progressed to
the baseline survey stage. Of those, 175 completed the baseline test and partially completed the
training, prior to relinquishing their involvement. This left 46 students in the 18-55 age range
with a gender and flying experience distribution of 9 pilots amongst 25 males and 6 pilots amongst
21 females, with n=31 (two thirds) of general non-pilot students in the sample, completing the
course. A nominal criterion was used in the study as the cutting score for the mental alertness and
fatigue management scales serving as the baseline criteria for comparative purposes. When the
experimental group were compared with the development group and a further industrial sample
of drivers (total n = 1129), the experimental group mean test performance was found to be
between 50-70% of other groups relative to the criterion previously established empirically for
safe behaviour in industrial settings. The significant difference between the samples confirming
less well developed self-regulation skills in the experimental group.
Control Group A control group (n=61) was established with a like group of trainee pilots, at another university.
Baseline tests were completed as required prior to their engaging in a traditional Resilience
training course conducted at the university. The resilience course involved emotion management
and development of self-awareness, coupled with semantic reframing of critical situations to build
a strategy against personal vulnerabilities. Management of the control group was subsequently
unsuccessful, their contribution to the study was negated as a comparison to the rART technique
due to lack of data with respect to the Resilience course outcomes.
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Outcomes with respect to the first hypothesis were partially met. It was expected that participant
mental alertness and their perception of workload strain would result in greater self-regulation of
their fatigue levels and sleep behaviour. That is, that all three measures would show a logical
correlation. If coping with personal strain was low then a corresponding lower fatigue
management score would be achieved and a lower alertness result. The implication suggesting
that poor self-regulation of fatigue resulted in functional decrements on alertness. This aspect was
evident in the female sample but only slightly mirrored in the male sample (fig 6.4). In both
groups scores on mental alertness and management of fatigue were well below normative
graduate and adult samples indicating less maturity in coping overall. In a future study of the
same dimensions an extended measure of coping styles would help to explain what kind of coping
the participants had used to manage their stress. For example, was it addressed directly or was it
escaped as in the Cosway, Endler, Sadler & Deary, (2000) model of coping in which the coping
options included task related, emotional, avoidance, distractive or social behaviours. Except for
the option of ‘task related’ the remainder of the options are clearly avoidance measures consistent
with Monat & Lazarus (1977) theory of direct action and intrapsychic coping. Pointing to the
tendency for those with intrapsychic tendencies to tolerate their condition and discomfort and
remain unresolved more than others, thereby accumulating stress.
The second hypothesis also counted on proactive behaviour amongst the students and was
partially supported. The hypothesis being that those reporting greater mental alertness and the
management of their fatigue would also tend to be alert to utilising the rART technique elsewhere
in their academic experience. They would report efficacy of the rART by transfer and utilisation
of the attention recovery technique to their daily activities. In the event a larger number (M =
65%) of those completing the training reported greater efficacy of the rART in doing so, however
that outcome measure was not associated as predicted by their mental alertness and fatigue
management scores.
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The third hypothesis was not supported. It detailed that participants, who reported higher mental
alertness and fatigue management, were less likely to be disrupted and hence more likely to
adhere to instructed session times and complete the course within the allocated time, was not
found. A significant difference existed between course completers and non-completers (fig 6.2),
on both study entry and completion. However, there were no significant score differences on the
self-regulating scale of mental alertness and fatigue management to predict that outcome.
Similarly, there were no specific attributes in the demographics of the two groups that would
differentiate them. The data showed just as many males and females completed the course,
removing a possible gender factor. The finding that females scored lower with respect to the
perceived strain of their academic workload, than males, had no significant effect on any of the
measures. The strain may have been a factor in participating in the study and account for the
slightly greater appreciation of the efficacy of the rART method reported by females.
The fourth hypothesis was not found, it was expected that those having started flying training,
would show greater interest in developing the rART SR skill and complete the course. That
difference was not seen in the data, as some pilots also terminated their participation early in the
study. The hypothesis was not found to be true and participants who were identified as aviation
students were no more likely complete the attention recovery training than others. While the pilots
did score significantly higher on the self-regulating scales than others, that was not translated to
completing the course.
Participants provided a near uniform agreement of the ease of the method. The baseline test was
administered as a means to assess current SR skills, before the training sessions. Participants were
instructed to practice the rapid ART (SR) technique for ten minutes just prior to sleep at night. It
was considered that the two major distractions of end-of-day-fatigue and possible reluctance due
to the temptation of alternative activities (ie, late night movie on TV) would provide sufficient
natural fatigue and hedonic resistance to tempt avoidance of what would seem an arduous activity,
testing the participants resolve to continue and complete the training sequence.
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Participant behaviour
The study design and delivery was an unsupervised and online course to augment self-regulation
skills with a technique to rapidly recover attention. While encouraging, results were obtained on
several aspects leading towards a take-up of the skill by participants, a number of other study
management issues and the research design prevented a fuller exploration of the technique. The
study attracted an initially large number of interested volunteers amongst the student population
at the start of the academic year. That most participants were in their second year of a course
suggested that their perception of strain and feelings of the need to improve their mental output
and effort was likely to have been driven by their academic experience to date. However, because
a large number also departed the study after the benchmark testing, suggested that the online
training while convenient, may not have been well enough explained. Alternatively, the brevity
of the process may have disguised the potential in the exercises. By attracting a large number to
the study revealed a desire by students for a means to cope and perform better in their courses or
in general. Student conduct within the study had shown that their SR skills in the achievement of
the study protocoles were quite marginal and evidence of a conscientious approach was lacking
given the generally spasmodic, intermittent participation and final termination before completion
by some 78% of the enrolled group. When these aspects were considered in comparison with the
observations of the Artino et al (2010) study and the early classroom based pilot study
(Rosenweg, 2006), the importance of a social context became apparent, it seemed likely that the
absence of a person (teacher) in the process contributed to the disengagement. Another aspect of
the study distancing rather than engaging participants concerned the ethics requirement
demanding anonymity for students, which also meant that there was no way to personalise any
one participants activity or progress with feedback or acknowledgment. A future study in this
direction could remedy that aspect by personalisng the relationship, for example, with a
welcoming letter and progressive acknowledgement of progress.
142
Analysis of the final retention rate indicated the largest number of early terminations or departures
occurring between the completion of the baseline test component and the first training session.
The retention and completion rate for pilots was 25.4% and 23.7% for non-pilots. Being a pilot
did not predict completion. No exit questions were provided to participants in the anonymous
study and no pattern was seen in the data. Relinquishing the training at that incomplete stage,
suggests that having been attracted to the study offering training in a SR technique, then having
inspected the first training session - the technique had no personal appeal to those seeking a
different method of SR. Later terminations may possibly have been due to boredom with an oft-
repeated procedure. A third possibility may have been the lack of positive results emanating from
a poorly executed attempt at the training procedure, as it had become known from the earlier
pilot-study with police academy candidates and chemplant operators that some people had
difficulty in achieving diaphragm breathing. Another possible reason for withdrawal is
discouragement when no immediate correction or feedback was available to help achieve a level
of mastery. Artino et al had found a further important aspect in a study with an aviation training
group, that involved their perception of the value of the training (Artino & Berman, 2010),
disengagement occurring where the training process did not seem to add any benefit to what
participants were doing. In conventional training devaluation of content can occur because of a
confused message, poor material and sometimes due to a defensive reaction to an inability to
acquire or understand the subject matter.
Perceived ‘mental demand’ of daily tasks (derived from the NASA TLX) was reported with
female students tending to report greater strain than males, however, this difference did not appear
to have had any impact on reports of the efficacy and transfer of the rART skill to activities
outside of the study with female and male participants reporting equal efficacy and utilisation.
The baseline measures of mental alertness and management of fatigue at commencement did not
predict subsequent retention rates for those departing the study before completion, even though
the SR relationship between the two behavioural measures in the baseline test at start were highly
143
correlated. Results for both genders showed a lesser ability to manage fatigue resulting in greater
perceived workload strain. Conversely, increased mental alertness and decreased perception of
workload strain together benefited from the better management of fatigue. The two SR scales of
mental alertness and management of fatigue did not however predict the perceived efficacy of the
rART technique by those completing the sequence of training, but by inference the completion
of the training could infer at the least a greater interest in acquiring additional SR skills.
Whilst efficacy of the rART technique was reported by the sample that had completed the
training, it was not predicted by the baseline measures of those who had left the study before
completion, or in the progressive study retention rates. A lack of confirmation of that data could
signify that SR has many masters, not just alertness and fatigue. If the individual feels immune
or has become numb with fatigue (as with prolonged high level exposure) then normal indicators
that signal a needed change may become unreliable or defensively suppressed until sleep was
available. A similar state to continuing to drive late night while experiencing short duration head-
snapping micro-sleeps. A significant difference was shown, in which pilots showed greater ability
than others, to maintain their mental alertness and manage fatigue.
Study methodology and issues The attractiveness of the study and the possibility of improving cognitive ability was attractive to
more than 400 students opening the possibility that a re-engineered approach to the study could
improve retention for the training. While not a universal finding, the research by others pointing
to the social benefits of a collaborative and an interactive format such as that is found in classroom
teaching, suggests a need for a closer and more intensive contact with participants to achieve the
needed engagement. This was not possible in this study as participants were anonymous and the
training remotely administered. In parallel, the study did not have a programmed feedback system
such that success or failure with the training sessions and activities could be assessed and
addressed with further inputs. Another aspect that relates to perceived ‘value’ involves the brevity
of the training sessions, with no intellectual content to support the cause and effect of the
144
technique as a self-regulating mechanism, the credibility of the process may not have been clear
to participants. The poor retention rate and disregard of the training schedule, except for the time
of day in which it needed to be done, for example, extending for some participants to two to four
weeks for the planned 12-day schedule. Structural aspects of the study involving the presentation
of the baseline tests at the commencement of training may have been better explained or displaced
to another stage, perhaps offered progressively with the training sessions. That would have
obviated the need for the challenge questions and promoted the training as something other than
a school exam. In this study, the quality of the presentation was mostly acceptable and there were
no faulty programming issues experienced to discourage participants.
At the research design level, the study achieved a partial support of several of the hypothesis. The
use of the established scales to measure the extent of SR with behavioural evidence of self-
maintenance could potentially have limited the range of the SR construct despite their statistical
accuracy and reliability. To assess actual change or efficacy of the technique two different forms
of validation could be used. The first a comparative study with a similar method to establish
superiority against other techniques and secondly an experimental before and after design to
deliver accurate metrics regarding acquisition and mastery.
The absence of a control group in the classical sense made generalisability impossible to
determine. Using mindfulness training as a control was not deemed to be viable as that technique has no
comparative recovery mechanism, other than the breathing, that can be used to change mental state in a
lengthy process over some time. Secondly, proving experimentally that the switch in mental state with a
nasal sniff produces a significant change in mental state was not able to be conducted by remote online
administration. A means of distinguishing the calmness of mental state in a before and after assessment of
cortisole as a stress indicator may have been reliable even though the main effect was deemed to be the
action of the Amygdala. Anecdotal evidence of extended use of the rART method was used to identify
successful acquisition of the rART technique.
145
Future Directions The study pointed to a more critical experimentally based investigation of the neurophysiology
of the rART technique. The action of taking a deep breath to feel better and the sniff to mentally
direct attention is a common experience amongst sports people and counsellors with their clients.
The difference between the olfactory path of the sniff and the multi-sensory activation of the
startle appears to be the threat context of the startle and the directing action of the amygdala.
Location of the calm mental state memory accessed by the operant sniff, in the brain and whether
that has a consistent hemispherical location could also have implications for mental health,
although this was not able to be explored within the constraints of the current study. A
confirmation that the threat is replaced by the calmness obtained by the initially established
diaphragmatic breathing could have implications for a simple means to stabilise mental-state
under stress. Of necessity a more conclusive outcome would need to be obtained such that testing
with objective tests of attention, reaction time and cortisol secretion could provide validation that the method
improves calmness, attention and self-regulation.
146
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APPENDICES
Appendix A: Test Development Statistics
Group Statistics TIME N Mean Std. Deviation Std. Error Mean
Mental Alertness 2 59 88.1963 9.5163 1.2389
1 65 81.6694 10.8942 1.3512
Manages Fatigue 2 59 84.6485 10.5655 1.3755
1 65 76.0755 11.4920 1.4254
Executive Functioning 2 59 64.2039 18.1069 2.3573
1 65 58.8305 17.8715 2.2166
Choice Reaction Time 2 59 72.9360 15.6396 2.0361
1 65 67.0000 18.7524 2.3259
Working Memory 2 59 62.9530 9.7160 1.2649
1 65 59.8370 12.8992 1.6000
Table A1: Statistics Baseline test-retest administration
Table A2. Comparison of development group baseline retest scores time 2 with time 1
t‐test for Equality of Means ‐ Equal Variances not assumed
t df Sig.
2-tailed Mean
Difference Std. Error Difference
95% Confidence Interval of the
Difference Effect size
Cohens d Lower Upper
Mental Alertness 3.560 121.829 .001 -6.52689 1.83326 -10.156 -2.89771 0.65
Manages Fatigue 4.328 121.978 .000 -8.57294 1.98088 -12.494 -4.65159 0.78
Executive Functioning 1.661 120.522 .099 -5.37344 3.23584 -11.779 1.03303 0.30
Choice Reaction Time 1.920 121.161 .057 -5.9356 3.0912 -12.055 .1842 0.35
Working Memory 1.528 118.098 .129 -3.1156 2.0396 -7.1545 .9233 0.28
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Development Group Baseline Scales
n of
Dev’t test items
Group
Mean n= 61
SD Alpha Stand’
Intra class Corr’n
Mental Alertness 14 80.95 10.97 0.873 .870
Manages Fatigue 10 75.25 11.62 0.808 .797
Functional Performance Items Mean Item Diff’y
Executive Functioning element 6 61.56 18.21 .74
Choice Reaction Time element 5 69.83 18.61 .76
Working Memory element 5 61.370 12.81 .77
Scale definitions:
Manages Fatigue: Self-management of sleep requirements ensure availability of cognitive resources
Mental Alertness: Measures the extent of every day slips in perception, memory and coordination
Choice Reaction Speed: Ability to make rapid and effective decisions to changing circumstances
Executive Functioning: Use of logic and deductive thinking to manage developing issues.
Working Memory: Ability to retain and recall information in the short term
Subjective (strain): Identifies perceived strain in coping with the task via six graded elements in the NASA TLX.
Table A4. rART Baseline Test Statistics Experimental Group n= 221
n/N of
items
Cases
Alpha
(Std)
Intra-class
Correl’n
Inter-item
Correlat’n
R2 F
(.001)
KMO
rART Baseline Survey Student Pilots1
33/632
221 .833 .807 .094(ns) .675 58.5 .823
1Dependent variable: Mental alertness. Predictors: Choice Reaction Speed, Executive Functioning, Manages Fatigue, Working Memory. 2 30 items in the rART exercise & procedure are not included in the baseline test statistics.
Table A3 Summary – Development Group Baseline test scale reliabilities and item statistics
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Table. A5. Study completion rates, age & gender by session for 221 enrolled participants
Session Study Item
No Completed
Number of respondents
leaving study % Male
Mean Age Male
Female Mean Age
Female
Baseline
1 27 12.22% 27 29.78 0 - 11 3 1.36% 3 22.0 0 - 14 1 0.45% 1 33.0 0 - 21 1 0.45% 1 22.0 0 - 23 4 1.81% 4 26.25 0 - 24 13 5.88% 13 28.62 0 - 25 1 0.45% 1 38.0 0 - 26 3 1.36% 3 35.33 0 - 27 3 1.36% 3 28.67 0 - 28 2 0.90% 2 35.0 0 - 29 1 0.45% 1 22.0 0 - 30 43 19.46% 18 24.11 25 29.431 3 1.36% 1 22.0 2 25.0
Baseline test completed – Training commenced 32 3 1.36% 2 21.0 1 42
Session 1 33 18 8.14% 7 25.0 11 26.8 35 2 0.90% 0 0.0 2 32.0
Session 2 36 11 4.98% 6 31.5 5 23.6 38 1 0.45% 0 0.0 1 33.0
Session 3 39 9 4.07% 5 33.8 4 26.3 40 1 0.45% 1 42.0 0 0
Session 4 42 4 1.81% 3 39.0 1 22.0 43 1 0.45% 0 0.0 1 28.0 44 2 0.90% 1 33.0 1 28.0
Session 5 45 5 2.26% 1 33.0 4 28.8 46 1 0.45% 0 0.0 1 20.0
Session 6 48 3 1.36% 2 25.0 1 28.0Session 7 51 5 2.26% 1 33.0 4 28.5Session 8 54 2 0.90% 1 42.0 1 38.0Session 9 57 2 0.90% 0 0.0 2 31.0
Session 10 63
Sample total 175 108 67
Completed Training 46 25 21
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Appendix B. Detail of the Online Questionnaire
Mental Alertness ‐ The Modified Cognitive Failures Scale Question Text
Please respond with 0 = never to 5 = Always
1 Forgetting where I have left something I use in my job, like keys, a file or equipment.
2 Becoming distracted by co‐workers into doing something else (unintentionally).
3 Not hear instructions or important sounds when doing something else.
4 Drifting off into a daydream when I ought to be listening.
5 Going back to check if I have turned off work equipment.
6 I need to check names of people at work over and over because I haven't remembered them.
7 I forget the procedures for some tasks.
8 Looking and not seeing the thing I want, even though it's there, like notices or equipment etc.
9 Unintentionally hitting the wrong switch on things.
10 Remembering what was needed to complete the job or a task.
Manages Fatigue Scale
11 I am falling asleep without meaning to do so.
12 My thoughts wander and become disconnected.
13 I wish I had more energy to do things.
14 It is hard to sleep when thoughts keep me awake.
15 I don't rest well and wake up still tired.
16 I need more sleep now than I did before.
17 I miss things that are normally obvious.
18 Lack of sleep affects my coordination and judgement.
19 I don't rest well enough to recover my energy for the next day.
20 I struggle to concentrate at night
21 * NASA TLX perceived workload strain
22 Can you make a story here? INSTRUCTIONS: Complete the exercise by dragging the pictures into the boxes below with using your mouse to make a logical story. (Exec Functioning)
23 You have a hat with 35 black tags and 35 red tags in it. Without looking into the hat, how many do you have to take out of the hat, one at a time, to be sure that you have two of the same colour? (Exec Functioning)
24 *Free text entry = Number Pyramid – Add the missing number. (Exec Functioning)
25 *Simple Maze – memory question (Short term Memory)
Table B1. Online questionnaire and presentation order
168
26 Can you remember the order these images were shown in? INSTRUCTIONS: Use your mouse to drag the images into the boxes IN THE ORDER they were shown here. (Short term Memory)
27 * Short Term Memory question find pairs of images in a grid hidden after viewing.
28 Can you tell how many small grey squares there are in each group of changing squares?
Type in the number into the text box. (Choice reaction speed)
29 * Count back with 5 sec time (Choice reaction speed)
30 *Target and shoot down aircraft symbol (Choice reaction speed)
31
INFORMATION for the rapid ART Exercise. Welcome to the training part of this project. You have now completed the benchmark portion of the project. This next part involves you in practicing the rapid attention recovery technique. You will be sent an SMS reminder message each day at your nominated time. Please login with your id to do this exercise for 5 minutes at the end of each day, directly before sleep. In addition to the exercise, every second day you will be asked to complete two challenge questions. The total time of your participation is 10 days. You should now answer the question below and proceed to view the 5 minute introductory video The rapid attention recovery technique instruction will follow. It is very important that the whole sequence of exercise is completed Thank you for your participation.
32 VIDEO intro by male presenter
33 Video Schematic and female presenter demonstrates technique.
34 Exercise 2:‐ Video Schematic and female presenter demonstrates technique. Then also please indicate how easy you are finding this technique to learn.
35 My house is east of my office and west of the station, If I want to catch a train straight from work, in which direction shall I travel?
36 *Simple Maze – short term memory
37
INFORMATION for the rapid ART Exercise. Welcome back to the training part of this project. This is the third of ten sessions of the project. This next part involves you in practicing the rapid attention recovery technique again. You should now answer the question below and proceed to view the 5 minute introductory video The rapid attention recovery technique instruction will follow. A reminder ‐ It is very important that the whole sequence of exercise is completed Thank you for your participation.
38 VIDEO intro by male presenter
39 Video Schematic and female presenter demonstrates technique. Then also please indicate how easy you are finding this technique to learn.
40 Exercise 4: ‐ Video Schematic and female presenter demonstrates technique. Then also please indicate how easy you are finding this technique to learn.
41 *Simple Maze – short term memory
169
42 The opposite of 'right' is the opposite of. . . .
43
INFORMATION for the rapid ART Exercise. Welcome back to the training part of this project. This is the fifth of 10 sessions of the project. This next part involves you in practicing the rapid attention recovery technique again. You should now answer the question below and proceed to view the 5 minute introductory video The rapid attention recovery technique instruction will follow. A reminder ‐ It is very important that the whole sequence of exercise is completed Thank you for your participation.
44 VIDEO intro by male presenter
45 Video Schematic and female presenter demonstrates technique. Then also please indicate how easy you are finding this technique to learn.
46 Exercise 6:‐ Video Schematic and female presenter demonstrates technique. Then also please indicate how easy you are finding this technique to learn. Then also please indicate how easy you find this technique to learn.
47 *Simple Maze – short term memory
48 Please read the text carefully and identify the correct answer
49
INFORMATION for the rapid ART Exercise. Welcome back to the training part of this project. This is the seventh of 10 sessions of the project. This next part involves you in practicing the rapid attention recovery technique again. You should now answer the question below and proceed to view the 5 minute introductory video The rapid attention recovery technique instruction will follow. A reminder ‐ It is very important that the whole sequence of exercise is completed Thank you for your participation.
50 VIDEO intro by male presenter
51 Video Schematic and female presenter demonstrates technique. Then also please indicate how easy you are finding this technique to learn.
52 Exercise 8:‐ Sound is required in this video. {#VIDEO=CATE_RARTn2.mp4#} Then also please indicate how easy you find this technique to learn.
53 *Simple Maze
54
After making a trip to the market and a trip back you are given another job. Your taxi can only take 5 passengers at a time. You need to transport 16 people from A to B How many trips or journeys do you have to make?
170
55
INFORMATION for the rapid ART Exercise. Welcome back to the training part of this project. This is the ninth of 10 sessions of the project. This next part involves you in practicing the rapid attention recovery technique again. You should now answer the question below and proceed to view the 5 minute introductory video The rapid attention recovery technique instruction will follow. A reminder ‐ It is very important that the whole sequence of exercise is completed Thank you for your participation.
56 VIDEO intro by male presenter
57 Video Schematic and female presenter demonstrates technique. Then also please indicate how easy you are finding this technique to learn.
58 Exercise 10:‐ Video Schematic and female presenter demonstrates technique. ‐ Then please indicate how easy you are finding this technique to learn.
59 PLUGIN = Short Term Memory
60 Aircraft manufacturers sold to 35 Airlines, 30 bought Boeings and 15 bought Airbuses, how many airlines bought both?
61 I now constantly use the rapid attention recovery technique in my work.
62 The rapid ART technique now helps me to recover attention when interrupted.
63 Ease of use of the rapid ART technique – using a modified TLX question format
171
Table B.2 Preliminary literacy Test (conducted at start of the baseline survey)
"When we were very young we lived on a farm and every year it sometimes rained non-stop for about a month. We had to put buckets in the rooms to cope with the leaks. At the time as kids we thought it was funny, particularly when we knocked the buckets over and spilled water everywhere. Our neighbour who had a parallel experience was not as amused as we were. These days, living in a high rise, we don't have that problem, although the basement sometimes floods in a heavy rain"
1. Spilling water was funny
Yes
No
2. I live on the farm
Yes
No
3. Basements always flood
Yes
No
4. It always rained on the farm
Yes
No
5. Our neighbour was also amused
Yes
No
Table B2. Study Survey Reading Grade
Readability Formula Study Test
Score 7th grade level Fairly easy to read.
Range 0 - 100 Flesch-Kincaid Reading Ease 74.1
Table B3. Flesch-Kincaid Formulae Grade Levels
A grade level (based on the USA education system) is equivalent to the number of years of education a person has had. A score of around 10-12 is roughly the reading level on completion of high school. Text to be read by the general public should aim for a grade level of around 8.An average grade six student's written assignment (age of 12) has a readability index of 60–70 (and a reading grade level of six to seven). - Accessed via (https://readability-score.com
Score School Level Notes
90.0–100.0 5th grade Very easy to read. Easily understood by an average 11-year-old student.
80.0–90.0 6th grade Easy to read. Conversational English for consumers.
70.0–80.0 7th grade Fairly easy to read.
60.0–70.0 8th & 9th grade Plain English. Easily understood by 13- to 15-year-old students.
50.0–60.0 10th to 12th grade Fairly difficult to read.
30.0–50.0 college Difficult to read.
0.0–30.0 college graduate Very difficult to read. Best understood by university graduates.
172
The modified form of the NASA Task Load Index utilised in the study.
Higher ratings denote greater strain placed on coping (self-regulation) skills.
How stressful do you find the mental effort required in what you do (e.g. thinking, deciding, calculating, remembering, looking, searching, etc)? Do you find the tasks easy or demanding, simple or complex, exacting or forgiving?
Mental Demand
Low High
How exhausting do you find the physical activities that are required in what you do (e.g. pushing, pulling, turning, controlling, activating, etc)? Are the tasks easy or demanding, slow or brisk, slack or strenuous, restful or laborious?
Physical Demand
Low High
ow much time pressure is there due to the rate or pace in what you do? Is the pace slow and leisurely or rapid and frantic?
Pace of Work
Low High
How successful can you be in what you do in achieving the goals in what you do? Consider if there are any inhibiting problems in the way the work is done or the way the organisation supports it?
Performance
High Low
How hard do you have to work in what you do (both mentally and physically) to accomplish the required level of performance for this role?
Effort
Low High
How insecure, discouraged, irritated, stressed and annoyed versus secure, gratified, content, relaxed or complacent do you feel and does the system of work and typical outcomes in what you do affect you?
Frustration
Low High
Table B3 Perception of stress and coping with the TLX
173
Table B.4 Fatigue Management & Alertness Baseline Questions
174
.
Left Column: Reaction speed & Accuracy.
1. Count grey squares constant changing position
2. Shoot (Green button trigger) when a/c targeted
3. Select number on Timed count down x 2
Middle column Short term memory.
1. Order the briefly displayed symbols.
2. Locate pairs of images after memorising
3. Trace button path in maze after memorising
Right column: Executive functioning
1. Drag into logical order of story
2. Identify and enter missing number.
3. Simple problem-solving question
Table B.5 Functional performance test questions
175
Appendix C: Rapid ART Instruction
Figure C1. Online demonstration of the rART procedure Figure C0.1. Video: Actor voice over demonstrating the rART technique
176
Appendix D. Ethics Clearance From: RES Ethics <[email protected]> Date: Tuesday, 22 September 2015 17:21
SHR Project 2015/164 – Evaluation of a self-regulating skill for rapid attention recovery (rART).
(Attention at the moment of demand: an operant technique for recovery of situation awareness).
I refer to the ethical review of the above project revised protocol by a Subcommittee (SHESC2) of Swinburne’s
Human Research Ethics Committee (SUHREC). The responses to the review, as emailed today with attachments
on behalf of the chief investigator/supervisor and student investigator, were put to the Subcommittee delegate
for consideration and feedback sent to you. Your response to the feedback also emailed today with attached
revised consent information, accords with the feedback.
I am pleased to advise that, as submitted to SHESC2 and today, the project may proceed in line with standard
on-going ethics clearance conditions here outlined.
All human research activity undertaken under Swinburne auspices must conform to Swinburne and external
regulatory standards, including the current National Statement on Ethical Conduct in Human Research and with
respect to secure data use, retention and disposal.
‐ The named Swinburne Chief Investigator/Supervisor remains responsible for any personnel appointed to or
associated with the project being made aware of ethics clearance conditions, including research and consent
procedures or instruments approved. Any change in chief investigator/supervisor requires timely
notification and SUHREC endorsement.
‐ The above project has been approved as submitted for ethical review by or on behalf of SUHREC.
Amendments to approved procedures or instruments ordinarily require prior ethical appraisal/clearance.
SUHREC must be notified immediately or as soon as possible thereafter of (a) any serious or unexpected
adverse effects on participants any redress measures; (b) proposed changes in protocols; and (c) unforeseen
events which might affect continued ethical acceptability of the project.
At a minimum, an annual report on the progress of the project is required as well as at the conclusion (or
abandonment) of the project. Information on project monitoring and variations/additions, self-audits and
progress reports can be found on the Research Intranet pages.
A duly authorised external or internal audit of the project may be undertaken at any time.
Please contact the Research Ethics Office if you have any queries about on-going ethics clearance. The SHR
project number should be quoted in communication. Researchers should retain a copy of this email as part of
project recordkeeping. Best wishes for the project, in particular to Mr Rosenweg.
Yours sincerely, Keith Wilkins for Astrid Nordmann Secretary, SHESC2
Keith Wilkins Secretary, SUHREC & Research Ethics Officer Swinburne Research (H68) Swinburne University
of Technology P O Box 218 HAWTHORN VIC 3122 Tel +61 3 9214 5218 9214 5267
177
Appendix E. Call for Volunteers