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A Survey Study of Mental Health Professionals’ concept of mental illnesses. What are the main dimensions underlying

our understanding of Mental illnesses?

PSYCG096: Final Project (Research Project)- Individual Clinical Dissertation Candidate number: FMYS0 Student Number: 110013301 Word Count: 7, 626. Journal: This research is intended for the BioMed Central Journal (BMC). Contribution: The author was jointly responsible for data collection alongside another MSc student, and was solely responsible for data analysis, interpretation, and write-up of this research paper.

             

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Abstract  

Background. The history of psychiatry reveals many competing models of mental health. For this reason many have called for mental health professionals to move towards a more unified philosophy to refine the efficiency of mental health care, by improving professionals ability to work together. The current study intends to determine what present day mental health professionals view as the underlying models of mental illness. Methods. This research employed a questionnaire design administering the Maudsley Attitude Questionnaire, using an online survey system, sampling a wide spread of mental health professionals (N=837). The questionnaire assessed professionals’ attitudes towards three mental health illnesses; Major Depressive Disorder, Schizophrenia, and Antisocial Personality Disorder, across eight of the most prominent models of mental illness. Data was analysed by employing a two-way ANOVA and a Principal Component Analysis.

Results. A significant difference in professional endorsement of mental health models was found, and this was established for model endorsement for each mental illness. For schizophrenia it was found that professionals mostly endorse a biological versus social realist model, followed by a joint cognitive and behavioural component. For Major Depressive Disorder (MDD), professionals most significantly endorsed a social realist model, followed by a cognitive and behavioural component and least endorsed the biological model. Professionals most significantly endorsed a joint social constructionist and nihilist component for Antisocial Personality Disorder (APD), illustrating a potential lack of interest in claiming APD to be a mental illness. Conclusions. Mental health professionals are most committed to combination models of mental illnesses, coinciding with the movement of the biopsychosocial model. However some of the endorsed models do not correspond with clinical practice, for instance the biological model of MDD was the least significantly endorsed model. The research findings have several implications; on professional attitudes towards disorder responsibility, stigmatization, and potential changes to treatment regimes. For example; the importance professionals place on social elements could be further researched to clarify if they are indeed as important as professionals believe. Keywords: Survey, Mental illness, professional, training, attitudes, models.

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Introduction  Models of mental Illness

Throughout the history of mental health disorders, individuals have attempted

to understand mental illness in a diverse range of ways (Bertolote, 2008). These

approaches to explaining human behaviour hold certain perspectives, which contain a

set of assumptions about the human mind (McLeod, 2007). They hold important ideas

about the way we function, what parts of our behaviour are important to research and

using what methods. These perspectives have existed and evolved over the years to

produce a plethora of mental health models. Foerschner (2010) researched the origins

and timeline of mental illness throughout history, revealing dramatic chances in the

zeitgeist. These changes are important in understanding our interpretation of mental

illness in today’s modern era. Due to the large amount of previously reported

interpretations (Clare, 1976, Engel, 1977), there are currently a variety of ways to

understand mental illness from both mental health professionals (Deeley, 2006,

Broome, 2007), and from lay people (Tyrer & Steinberg, 2005). Therefore with so

many different mental health movements, teachings and research, these approaches

have developed into distinct models of mental illness, which form the science of

mental health.

It is important to understand what professionals working in mental health

perceive as the most influential models of mental illness. Ghaemi (2007) researched

the spread of mental illness models across professionals, and concluded that, although

psychiatric illnesses are complex phenomena that are best understood through a

pluralistic model, the most popular models at the time included biomedical, cognitive,

behavioural, psychodynamic and social perspectives. It is widely agreed that each

model has its own unique set of mechanisms that inform the way an individual would

classify, explain, and treat the mental illness (Ghaemi, 2007). Not only does this

affect the service user, but also influences the target and approach to research, for

example, either via laboratory experiments on genetic causes, or family therapy on

dysfunctional relationships. The way mental illnesses are interpreted at root level (i.e.

what symptoms are attributed to) has an immense impact on the empirical study of

mental health as a science (Good, 1995; Kleinman, 1998).

             

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Implications of Mental Illness Models

Research indicates that mental health professionals hold strong opinions

regarding models of mental illness, and these affect their willingness to provide

treatment in line with these models, such as medication versus psychological therapy

(Ahna, Proctora & Flanaganb, 2009). These opinions may however not be evidence-

based or follow protocol of current treatment guidelines, and for this reason

professionals’ attitudes may be negatively affecting the quality of treatment. Secker et

al (2010) followed this up using semi-structured interviews, with mental health

professionals on five different projects. They found that 2 radically different

approaches were mostly endorsed; clinical versus the social model of recovery. This

reflects a wide divide in professional attitude towards mental illness with regards to

treatment. Where these attitudes diverge from clinical guidelines, professionals may

be providing treatment based on their own clinical judgements rather than evidence-

based practice.

Explanatory models of mental illness can also have significant implications

for personal responsibility, and has potential implications in the criminal justice

system. Where behaviour is construed as a symptom of biochemical factors, the

individual is considered to not be in control, or hold responsibility, for their behaviour

(Williams, 2003). This model may justify a ‘not guilty by reason of insanity’ (NGRI)

defence, removing the individual’s responsibility for their crime (Robinson, 1998).

Slovenko (1995) highlights that almost all cases proposing this defence end with the

defendant being indefinitely committed to a psychiatric hospital, rather than a prison,

showing model interpretation holds a large bearing on an individual’s life outcome.

Explanations of a mental disorder may also impact on stigmatization. Jorm &

Griffiths (2008) believed that stigmatizing attitudes are elevated by psychiatric

labelling as well as by conceptualization of symptoms as a medical illness. The

research surveyed 3998 Australian Adults using four vignettes and measured attitudes

using a social distance and dangerousness scale. It was found that belief in

dangerousness for schizophrenia was predicted by medical illness conceptualization

and genetic causal factors. Therefore the biomedical models for mental disorders such

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as schizophrenia, may contribute to stigma. So discovering the general attitude with

which professionals view disorders could help in implementing systems to reduce

stigma accompanied by these attitudes. In support of this, research indicates that

biological explanations reduce the amount of empathy professionals provide for their

patients (Gibson, 2015; Lebowitzl & Ahn, 2014), a slightly alarming concept

considering the critical nature empathy plays in mental health care.

Finally, the models professionals choose to endorse have implications for

housing and social benefits. Burgoyne (2014) conducted a qualitative systematic

review of mental health and the setting of UK housing support, focusing on the

structural aspects of housing. Thematic analysis developed a conceptual model

containing three main determinants that enabled users to benefit from support. These

three factors were autonomy, domain and facilitation; the researchers concluded that

the “Tripod Model” illustrates the relationships between these themes. Burgoyne

(2014) suggested mental health diagnosis, treatment and support is required in an

acceptable balance to increase the chances of fruitful and continuous housing

outcomes for service-users. However, if a mental health professional chooses to

support a biological model of a mental health illness, they may focus on researching

particular aetiological models and certain treatments based on these models, therefore

potentially paying less attention to housing and social benefits issues, which appear to

play a large part in recovery.

Psychiatrist’s Perspectives

Previous investigations into this field of mental health, although somewhat

limited, have established some informative findings. Harland et al (2009) used an

online version of the Maudsley Attitude Questionnaire (2004) on trainee psychiatrists

from South London and Maudsley National Health Service (NHS), to measure how

respondents understood familiar mental illnesses in terms of propositions taken from

different models. Harland and colleagues (2009) established that within this niche

group of trainee professionals no single model was solely endorsed, and model

endorsement varied for each of the four chosen disorders i.e. Antisocial Personality

Disorder (APD), Major Depressive Disorder (MDD), Generalised Anxiety Disorder

             

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(GAD), and Schizophrenia. The most prominent mental illness interpretation, found

using a rigorous principal component analysis, was the attitude that schizophrenia was

explained and to be treated by the ‘biological’ model, but APD was the least endorsed

by this model. The investigative team concluded that trainee psychiatrists prefer

biological explanations for schizophrenia, but this exclusive attachment is not carried

over onto other mental disorders. Moreover, the researchers established that trainee

psychiatrists, as a profession, organise their perspective of mental disorders in a

biological versus non-biological dynamic (Harland et al, 2009). Such a simplistic

outlook on mental illness could be argued to be reductionist and may limit the

provision of quality standard care for all mental illnesses. However, McCabe and

colleagues (2006) argue that the modest convenience sample in this research limits

the generalizability of findings.

For this reason, the current research aims to establish whether this is the case

across all mental health professionals, as an overall group bias could have significant

effects for patients suffering from mental illnesses. Neglect of evidence-based

practice or national practice guidelines in favour of preferred models could negatively

impact on patient care.

Psychologist’s Perspectives

Research by Read, Moberly, Salter and Broome (In Press), similarly

conducted a study using an identical methodology with trainee clinical psychologists.

In line with Harland and Colleagues (2009), they found no single model was solely

endorsed. Rather, trainee clinical psychologists gave equal value to cognitive,

behavioural and psychodynamic interpretations over biological models of mental

disorders, across diagnoses. Moreover, much like Harland and colleagues (2009)

biological vs. non-biological dynamic, a similar contrasting belief system was found

with trainee clinical psychologists. They organised their attitudes on a biological-

psychosocial scale, a cognitive-behavioural continuum, and a psychodynamic-

spiritual dimension. It would be informative to see if these dynamics are a

phenomenon that occurs across all mental health professionals, or simply a product of

psychiatric or clinical psychology professional training.

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Both Read, et al (In Press) and Harland and colleagues (2009) research,

provides an emerging understanding of the attitudes of two prominent mental health

professions. However, psychiatry and psychology are only two of many mental health

professions that comprise psychiatry’s multi-disciplinary team (Jefferies & Chan,

2004, Craddock et al, 2008). It is therefore of interest to establish whether the same

underlying attitudes and biases are prominent within the broader spectrum of mental

health professions, which would be adversely affecting the multi-disciplinary format

used in UK mental health care.

Furthermore, the highest form of treatment and teaching quality can be seen to

potentially be lacking in the academic department of psychiatry. Miresco and

Kirmayer (2006) used a vignette method to explore whether an implicit mind-body

dichotomy existed amongst the department staff, since many have argued this issue no

longer exists. They established that when staff discussed a behavioural symptom it

was deemed due to psychological, not neurobiological causes, and with this view

service users were mostly considered to be somewhat responsible for their own

disorders. Although the outcome of this study informs of some potentially prejudicial

beliefs and practices, other research has found no such issue. For example, Brog and

Guskin (1998) used a questionnaire methodology to find students undergoing a

medical degree placed equal importance on biological and psychological elements

when contemplating treatment of mental illnesses as a whole. Some of the early

research in this field acknowledged the same mixed results issue, for example Rabkin,

(1972) deemed the available research on mental health professionals attitudes to be

mixed and lacking in theoretical basis.  

Overall, research in this field is limited and findings are mixed. The current

study aimed to use an exploratory analysis to examine the significant structures of

professional attitudes towards models of mental illness. It was hypothesised that each

mental illness would be rated differently in terms of the explanatory models.

Previous research suggests that psychiatrists most strongly endorse a biological model

of schizophrenia (Harland et al, 2009), in line with NICE guidelines (NICE, 2014).

Therefore, it was hypothesised that a biological model of schizophrenia would be

most strongly endorsed by all professionals. Similarly the study aimed to explore

             

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which models professionals significantly endorse per mental illness and whether they

are in line with recent research evidence in the same area.

Methods

Study Design Study Aims

This research aims to understand whether mental health professionals, as a

unit, place significantly different amounts of importance on different models of

mental illness, and whether this difference can be found for three specific mental

illnesses i.e. Schizophrenia, Major Depressive Disorder (MDD), and Antisocial

Personality Disorder (APD).

Ethical Approval

The Ethical Committee of University College London approved this study.

The link and research information was emailed to over 375 university administrators

and secretaries. An unknown amount of participants responded from the twitter and

online lancet advertisements. In total 829 professionals responded and 344 were

completed in its entirety.

Setting

This research utilised an online questionnaire survey system whereby a link to

the questionnaire could be sent over the Internet and accessed in various locations

across the UK. For this reason, the setting of the research covers several intended

locations and many more, which the researchers may be unaware of. The

questionnaire link was sent to; the top (up to) 100 University courses for nursing,

social work, occupational therapy, clinical psychology doctorate, and psychology and

psychiatry. (See Appendix 1 for a comprehensive list). Additionally, several social

media networks such as twitter accounts were used by the investigative team to

circulate the questionnaire link further, and the Lancet Online Journal also advertised

the link to the questionnaire on their website for eligible readers to complete.

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Sample

As this research aims to determine what underlying models all mental health

professionals utilize for certain mental illnesses, the research intended to draw upon a

wide variety of mental health professions. With regards to professional disciplines in

mental health, this included; psychiatry, clinical or counselling psychology, mental

health nursing, occupational therapy, social work, and arts therapy. Write-in options

were available for those who felt the available options did not match their

professional status (see Appendix 2). This sample group was intended to encompass

all professionals who may work in direct contact with patients of mental health

illness.

Materials Measures

The questionnaire begins with a demographic section comprising items

relating to professional background, work setting, country of birth and residence (see

Appendix 3). The main section of the questionnaire used an adapted version of the

Maudsley Attitude Questionnaire (MAQ) developed in 2004; this can be found in

Harland et al (2009). The MAQ was used removing all questions related to

Generalised Anxiety Disorder (GAD) and several questions from section 1 (Questions

3,4,5,6,8,9,10,11, and 12), as they were no longer relevant to the research question.

This helped boost response rates by shortening the length of the questionnaire.

Additionally, the questionnaire was moved on to the online UCL questionnaire

website “Opinio” changing small layout elements of the original.

The order of the sections were also altered so that further demographic and

professional questions could be added to the end of the questionnaire, reducing

attrition caused by initial mundane questioning. The adapted and used version of the

MAQ can be found in Appendix 4. The main section consists of questions created to

explore mental health professionals’ attitudes towards mental illness by seeing how

respondents interpreted models of mental illness. The researchers utilized the models

initially proposed by Harland et al (2009). These models include; biological,

cognitive, behavioural, psychodynamic, social realist, social constructionist, nihilist,

             

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and spiritual frameworks. For each model the research followed Harland et al’s

(2009) formulation of 4 questions per mental illness to understand the entirety of the

models with regards to their aetiology, classification, research and treatment. Each of

the questions were then asked with reference to the three disorders using DSM-V

criteria, these were; Schizophrenia, Major Depressive Disorder (MDD), and

Antisocial Personality Disorder (APD). A breakdown of the questions asked per

model can be found in Table 1. The compiled questions were randomised

accordingly. Responses were laid out utilizing a five-point Likert Scale (Likert,

1932), allowing for a neutral response option, with significantly strongly agree

receiving a 5, and significantly strongly disagree receiving a 1. Table 1. Questionnaire items arranged by model (number of the item corresponds to the order of the item’s appearance in the questionnaire) ___________________________________________________________________________ Biological 1. The disorder results from brain dysfunction 6. The ideal classification of the disorder would be a pathophysiological one 9. The appropriate study of the disorder involves discovery of biological markers and the effects of biological interventions 17. Treatment of the disorder should be directed at underlying biological abnormalities Cognitive 15. Maladaptive thoughts and beliefs are normally distributed in the population and it is the extreme ends of this distribution that account for the disorder 24. The disorder is nothing other than the sum of maladaptive thoughts, beliefs and behaviours 20. The study of the disorder should concentrate on understanding cognitive distortions and reasoning errors 7. The disorder should be treated by challenging and restructuring maladaptive thoughts and beliefs Behavioural 31. The disorder results from maladapted associative learning 3. The disorder is best approached through the study of abnormal behaviour 11. Studying the associations between antecedents and consequents in patients’ behaviour is the best basis for modification of the disorder 19. The Behavioural problems in the disorder are best modified by associating new responses to a given stimulus. Psychodynamic 26. The disorder results from the failure to successfully complete developmental psychic stages 18. The disorder is due to unconscious factors (as defined psychodynamically) 22. The structure of the disordered psyche and its unconscious mechanisms is best understood by a study of individual cases 28. Treatment of the disorder requires resolution of disturbed early object relationships Social realist 14. Social factors such as prejudice, poor housing and unemployment are the main causes of the disorder 2. The disorder arises as a consequence of social circumstances or conditions 5. The research into the disorder should focus on the identification of causative social factors 29. Government policies to reduce prejudice, poor housing and unemployment are the way to eradicate the disorder Social constructionist 16. There is no universal classification of disorder, only culturally relative classifications 32. The disorder is a culturally determined construction that reflects the interests and ideology of

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socially dominant groups 13. The disorder can only be understood in the context of local meanings and these meanings cannot be extrapolated to universal classifications 10. Treatment of the disorder should be based on whatever folk treatments and models are accepted as appropriate by the patient and their local community Nihilist 23. Attempts to scientifically explain the disorder have resulted in no significant knowledge 27. All classifications and ‘ treatments ’ of the disorder are myths 12. Mental health professionals have no ‘ expertise ’ of the disorder over and above anyone else 4. The management of the disorder is best left to the resources of the individual Spiritual 8. Neglecting the spiritual or moral dimension of life leads to the disorder 30. The disorder is better understood through religious or spiritual insights 25. Consulting a spiritual authority can give a better understanding of the disorder than psychiatry 21. Adherence to religious or spiritual practice is the most effective way of treating the disorder Study Procedures

The study design used an exploratory study. As previously mentioned, the

survey was compiled in an online document on the UCL Questionnaire website

‘Opinio’. The link to this questionnaire was then circulated via email to the University

department/administrators, via the researchers twitter account, and the online lancet

journal. The Opinio survey systems collated results online and compiled them into an

SPSS Data file, PDF report, Html Report, and Raw data report, removing any issues

over anonymity when moving data for statistical analysis.

Pilot Phase

A preparatory trial phase was conducted to test whether the online survey

system worked and if the questionnaire contained any errors in clarity and formatting

that could be amended before conducting the data collection phase. The draft

questionnaire survey was sent out to the UCL Division of Psychiatry staff and the

students of the 2014-2015 MSc Clinical Mental Health Sciences course. The draft link

was circulated with an accompanying paragraph stating the main aims of the research

and the need for participants to complete the survey and provide feedback for the final

research phase. Feedback was used to remove Generalised Anxiety Disorder (GAD)

from the questionnaire, as respondents felt the questionnaire was too long and GAD

would provide little valuable findings. In total 104 participants began the pilot phase

survey, and 32 completed it.

             

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Validation Study

As the research used a previously validated questionnaire i.e. the MAQ by

Harland et al (2009), a repeated validation study was deemed unnecessary as

construct validity had already been accepted.

Type of analysis used

Methods used for analysis began using a within subjects two-way ANOVA to see

whether professional ratings significantly differed between categories i.e. between the

three mental illnesses, between the eight models of mental illnesses, and the

interaction between these two categories. Three principal component analyses (PCA),

one per mental illness, were then used to investigate which model factors grouped

together to produce specific professional attitudes.

Consent

Participant consent was received through their commencement of the survey.

If the participant was not willing to begin the survey they were not under any duress

to begin it, and were able to exit the online survey system whenever they felt they

wanted or needed to. The informed consent sheet can be found in Appendix 5.

Declaration of Interest None known.

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Results

Respondent’s demographic and professional background

The sample of mental health professionals is illustrated in Table 2. From the

608 respondents, the mean number of years working within the field of mental health

was 11.65, with a ranging from 0-45 years. The majority of participants retained a

recognized professional qualification, and were working in a health care setting in the

field of psychiatry or focused in clinical or counseling psychology, mostly in the field

of depression and anxiety. The average age of the respondent was calculated at 40.26,

ranging from 19-99, with almost 70% majority female respondents. The majority of

respondents identified their ethnicity as white British, with the least represented

ethnicity being Black/Black British African.

 Table  2.    Respondent’s  demographic  and  professional  background  summary    

Demographic/professional background variable No. Of

Respondents Mean Range -Years working in Mental Health -Recognised Qualification Qualified Professional Training for Professional Qualification Working in Mental Health research Working in Mental Health Care Postgraduate student in mental health Undergraduate student in mental health -Profession qualified/training in Psychiatry Clinical or counselling psychology Mental Health Nursing Occupational Therapy Social Work Art Therapies Not Applicable Other* -Age -Sex Female Male -Field of Work Healthcare Setting Research/Academia Other Not Answered -Engaged in Research

608 630 378 (60%) 87 (13.8%) 67 (10.6%) 45 (7%) 41 (6.5%) 12 (1.9%) 630 86 (13.6%) 159 (25%) 59 (9%) 15 (2.3%) 75 (11.9%) 25 (3.9%) 136 (21%) 73 426 427 297 (69.56) 130 (30.44%) 702 392 (55.8%) 206 (29.3%) 104 215 631

11.65 - - 40.26 - -

0-45 - - 19-99 - -

             

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Yes No -Mental Health Population Child and Adolescents Dementia Depression and Anxiety Eating Disorders Intellectual/Neurodevelopment Personality Disorders Psychosis Substance Misuse Not Applicable Other Not Answered -Ethnicity White British White Irish White other Asian/Asian British: Indian Asian/Asian British: Pakistani Asian/Asian British: Bangladeshi Asian/Asian British: Other Black/Black British: Caribbean Black/Black British: African Mixed: White and Black African Mixed: White and Asian Mixed: Other

296 (46.9%) 335 428 112 (26%) 87 (20%) 299 (70%) 98 (23%) 97 (22.6%) 230 (53.8%) 228 (53.7%) 160 (37%) 53 40 418 424 256 (60.37%) 31 (7.3%) 96 (22.6%) 10 (2.3%) 2 (0.5%) 1 (0.2%) 6 (1.4%) 2 (0.47%) 3 (0.7%) 1 (0.2%) 7 (1.6%) 5 (1.17%)

- -

- -

* Available in Appendix 2. Table  3.  Descriptive  statistics  for  the  aggregate  attitude  scores  by  model  and  by  disorder  (possible  range  3-­‐20).    

Schizophrenia Major Depressive

Disorder Antisocial Personality

Disorder Biological 12.64 (4.2) (4-20) 11.66 (3.9) (4-20) 10.36 (3.7) (4-20) Behavioural 11.07 (2.5) (4-17) 11.86 (2.4) (4-17) 12.90 (2.7) (4-20)

Cognitive 11.22 (2.8) (4-20) 12.48 (2.6) (4-20) 12.41 (2.7) (4-20)

Psychodynamic 10.41 (3.2) (4-18) 10.85 (3.1) (4-20) 11.55 (3.5) (4-20)

Social Realist 12.86 (3.1) (4-20) 13.81 (2.7) (6-20) 13.87 (2.8) (4-20)

Social Constructionist

11.02 (3.7) (4-20) 11.24 (3.5) (4-20) 11.46 (3.4) (4-20)

Nihilist 6.08 (2.4) (3-15) 6.11 (2.3) (3-15) 6.52 (2.4) (3-15)

Spiritual 7.48 (2.9) (4-17) 7.70 (2.9) (4-16) 7.77 (2.8) (4-15)

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Figure 1. Standardized mean aggregate scores by model and by mental disorder, with a possible range of 4-16. Disorder included; Schizophrenia, MDD as Major Depressive Disorder, and APD as Antisocial Personality Disorder. Models included; Beh- Behavioural, Bio-Biological, Cog- Cognitive, Psych- Psychodynamic, Real-Social Realist, Const- Social Constructionist, Nihl- Nihilist, Spir-Spiritualist.

ANOVA

A  two-­‐way  within-­‐subjects  analysis  of  variance  was  conducted  to  explore  

the  impact  between  mental  illnesses  and  models  of  mental  illness,  as  measured  

by  a  questionnaire  on  professional  attitudes.  Mental  health  illnesses  were  

divided  into  3  levels;  Schizophrenia,  Major  Depressive  Disorder,  and  Antisocial  

personality  disorder.  Mental  health  models  were  divided  into  8  levels;  biological,  

behavioural,  cognitive,  psychodynamic,  social  realist,  social  constructionist,  

nihilist,  and  spiritual.  The dependent variable is the attitude professionals hold

towards mental health models for the three mental health disorders.  

Mauchley’s test for sphericity demonstrated that the assumption of

homogeneity of variances has been violated for mental health illnesses (W=.855, X2

(2)= 2.43, p<.001), mental health models (W=.118, X(27)2=907.50, p<0.001), and the

4

6

8

10

12

14

16

Att

itude

Sco

re

Schizophrenia

MDD

APD

             

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interaction between the two (W=.001, X(104)2=2760.21, p<0.001). Therefore

Greenhouse-Geisser corrections were applied.

The  interaction  effect  between  mental  health  illnesses  and  mental  health  

models  was  statistically  significant,  F  (14,  5978)=  113.13,  p<0.  0005,  indicating  

that  mental  illnesses  are  significantly  associated  with  mental  health  models.  

There  was  a  statistically  significant  main  effect  for  mental  illnesses;  F  (2,  854)=  

98.466,  p<0.0005,  as  well  as  a  statistically  significant  main  effect  for  mental  

health  models;  F  (7,  2989)=  349,14,  p<  0.0005.    

Principal Component Analysis

The same respondents were entered into each Principle component analysis

calculated for each mental illness. Sample descriptive’s for all the analysis can be

therefore be found above in Table 2.

Professional’s attitudes towards mental illnesses

In order to investigate which model factors group together 3 Principal

component analysis were conducted, 1 per mental health disorder. For each PCA, 365

participants were analysed. Participants who did not complete the whole questionnaire

were excluded from all PCA’s, and so for each PCA the average age is 40.26 (range=

19-99), 69.56% of respondents were female, and the remaining 30.44% were male.

Inspection of the scree plot was used to select the number of components for

each analysis. The questions relating to each of the three chosen mental disorders

were included in the principal components analysis to reveal the amount of variance

between the questions, which can be explained by each of the statistically significant

factors found in the initial parallel analysis.

Initial eigenvalues for schizophrenia indicated that the first five factors

explained 29%, 9%, 7%, 4%, and 4% of the variance respectively, totaling 54% of the

total variance. The sixth, seventh, and eighth factors had eigenvalues just over one;

the sixth factors explained 3% of the variance and the seventh and eighth 2%. The

first five factors were individually examined with oblimin rotations of the factor-

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loading matrix. The five-factor solution, explaining 54% of the variance, was favored

due to; previous theoretical backing, the flattening off of the eigenvalues on the scree

plot after the initial three, and the inadequate interpretation and loadings from the

fourth to eighth factors.

Primary eigenvalues for major depressive disorder determined that the initial

six factors explained 23%, 10%, 7%, 4%, 4% and 3%, calculating to explain the

cumulative variance of 51%. The seventh and eighth factors had eigenvalues of up to

1%. Solutions for the first six factors were inspected employing oblimin rotations of

the factor-loading matrix. The six factor solutions explaining 51% of the variance was

endorsed for the same three reasons as used for Schizophrenia. Initiatory eigenvalues

for antisocial personality disorder signified that the initial four factors explained 21%,

10%, 7%, and 5% of the variance, adding up to explain 45% of the total variance. The

following fifth, sixth, seventh and eighth factors had eigenvalues of just over one,

each explaining 3% of the variance. Solutions one to four were examined using

oblimin rotations of the factor-loading matrix. This five-factor solution, explaining

49% of the variance, was selected for the same three reason as the previous two factor

analysis for schizophrenia and major depressive disorder.

Schizophrenia

According to the Pattern Matrix produced by PCA (found in Appendix 7), a

significant proportions of the variance was explained by 5 components, KMO= .913,

p<.001. The first component included a substantially large degree of significant

questions; 15, 23, 8, 12, 38, 22, 20, 33, 19, 35, 29, 9, 11. The most supported

statements were found in questions 15, 23, 8 and 12; these were all biological

statements such as “the appropriate study of the disorder involves discovery of

biological markers and the effects of biological interventions” (question

15). However, questions 38, 22, 20, 33, 19, 35, 29, 9, and 11 were also clustered into

this component. These questions encompassed the social realist model, with

statements such as “social factors such as prejudice, poor housing and unemployment

are the main causes of the disorder” (question 20). This leads to a single component

incorporating a biological and social realism dimension, whereby professionals are

             

18  

most likely to endorse certain sides of the component. However, as we can see from

the pattern matrix, the biological explanations are negatively correlated with

underlying factor, and the social realist explanations are positively correlated. This

indicated that the degree to which people go for biological models are less inclined to

support social realist explanations, and this is one of the main ways to account for the

variation between people’s views in this data set.

The principal component analysis formed a second component consisting of

questions 13, 26, 25, 17, 21, and 37, reflecting a cognitive and behavioural model

of schizophrenia e.g. “the disorder should be treated by challenging and

restructuring maladaptive thoughts and beliefs”. The next component formed

consisted of questions 36, 27, 31, 14, 32, 34, 28, and 24. The first group of

questions from 36, 27, 31, and 14 were statements endorsing the spiritual model,

such as “adherence to religious or spiritual practice is the most effective way of

treating the disorder” (question 27). The following questions of 32, 34, 28 and

24, included statements regarding the psychodynamic model, such as “the disorder

results from the failure to successfully complete developmental psychic stages”

(question 32). This component therefore reflects a spiritual and psychodynamic

model. The fourth component consisted of questions, which referred to the social

realist and nihilist models of schizophrenia, and the last significantly endorsed

component reflected the social constructionist and nihilist models.

 

Parallel analysis revealed 5 components. PCA- KMO = .913 Bartlett’s<.001

àassumptions met.

Overall variance explained by all components = 54.41%

Component 1- Bio, Social Real.

Component 2- Cognitive, Behav

Component 3 Spirit, PsychoD

Component 4- Soc Real, Nihi

Component 5- Soc Const, Nihi.

29.2% 9.31% 7.14% 4.49% 4.17%  

Major Depressive Disorder

According to the Pattern Matrix produced in the MDD PCA, a significant

proportions of the variance was explained by 6 components, KMO= .913, p<.001. It

was shown that the most significantly agreed with component consisted of questions

                                                                                                                                          19  

pertaining to the social realist model of MDD. The cognitive and behavioral models

of major depressive disorder appeared to be the second component; containing

questions such as 13 “The disorder should be treated by challenging and restructuring

maladaptive thoughts and beliefs” as well as questions 26, 21, 17, endorsing cognitive

explanations and treatments. Questions 36, 27, 31, and 14 clustered together to form

the third component, reflecting a significantly endorsed spiritual model, as seen by

question 36 “The disorder is better understood through religious or spiritual insights”.

The fourth supported component formed the psychodynamic model, containing

questions 24, 34, 32, and 28. The social constructionist and nihilist models of

schizophrenia then followed to cluster as the fifth component, containing questions

18, 29, 22, 33, 19, and 16 e.g. “mental health professionals have no ‘expertise’ of the

disorder over and above anyone else”. The last component consisted of questions 15,

8, 23, 27 and 12. These questions consisted of statements such as “The appropriate

study of the disorder involves discovery of biological markers and the effects of

biological interventions” (Question 15), allowing for the potential interpretation that

the least prominent and supported model of major depressive disorder is the

biological model.

Parallel analysis = 6 components PCA- KMO = .874 Bartlett’s <.001 à

meets assumptions

Overall variance explained by all components = 51%

Component 1- Social Realist

Component 2- Cog, Behav

Component 3- Spiritual

Component 4- Psychodynamic

Component 5- Social C, Nihi

Component 6- Biological

23.38% 10.57% 7.69% 4.91% 4.43% 3.8% Antisocial Personality Disorder

By viewing the Pattern Matrix from the APD PCA, we can see that a

significant proportions of the variance was explained by 4 components, KMO= .913,

p<.001. The first component outlined questions 18, 22, 33, 29, and 19, which referred

to the social constructionist model, as well as questions pertaining to the nihilist

model, forming a social constructionist and nihilist component. A cognitive and

behavioural dimension followed second with questions 13, 25, 26 and 17. The third

component was clustered into questions 23, 15, 8 and 12; reflecting a biological vs.

social realist model i.e. professionals endorsing biological models do not tend to

             

20  

endorse social realist explanations. Questions 36, 27, 31, and 14, as well as questions

24, 34, 32, and 28 clustered together to form the last spiritual and psychodynamic

component of antisocial personality disorder.

Parallel analysis = 4 components PCA- KMO =.848 Bartlett’s <.001 à

meets assumptions

Overall variance explained by all components = 45.15%

 Component 1- Social C, Nihi

Component 2- Cognitive, Behavioural

Component 3- Bio, Social Realist

Component 4- Spiritual, PsychoD.

21.39% 10.53% 7.74% 5.48%  

                                                                                                                                          21  

Discussion

Main Findings

The results of this study support the belief that mental health professionals do

significantly endorse certain models more than others, and this seems to occur

specifically for each mental illness. However, the more specific propositions

regarding individual model endorsement per mental illness were not accurately

supported by the findings, which were unexpected. For instance, it was found that

professional attitude towards Schizophrenia most significantly supported a biological

versus social realist interpretation of the disorder.

The results exhibited several important findings, which might have significant

implications on clinical practice and research. Firstly, the diversity of professions

within the participant pool shows that there is a general consensus amongst

professionals regarding which models are valuable. This can most notably be seen in

the lowest mean for the nihilist model in Table 3, and in Figure 1 showing the lowest

mean for all illnesses in comparison to the other models of the illnesses. This could

imply that mental health professionals are moving away from any critical psychiatry

models, and generally towards a disorder specific and dual-dimension interpretation

of psychiatric illnesses. Without further analysis on separated professions, it could

also be argued that the profession of mental health is not yet moving towards a more

unified classification and interpretation of psychiatry which may lead to better quality

treatment through well refined multi-model concepts. For example, for many years

the nature vs. nurture argument has prevailed, and the findings for schizophrenia

propose this dispute still exists i.e. the biological model (nature) and social realist

model (nurture) were found to be at odds with each other.

Interpretations and Implications

Alternatively, some would argue that this multi-modal representation has

developed due to professional acknowledgement of the inadequate effects that anti-

psychotic medication has on many patients suffering from Schizophrenia (Harrow,

Jobe, & Faull, 2014, and Steingard, 2013), and evidence base suggesting

schizophrenia to be a complex multi-factorial disorder (Maccabe et al, 2006).

Potentially this has been aided by the development and rise of the biopsychosocial

             

22  

model (Engel, 1977), as well as recent models of psychosis such as Robin Murray’s

integrated model, which has increased in use (Frankel, Quill, & McDaniel, 2003), and

is now adopted for practice by many services, for example the Early Intervention in

Psychosis services (Borrell-Carrio, Suchman, & Epstein, 2004). This would fit in with

the current research finding of a joint cognitive and behavioural component falling

second to a biological and social constructionist component.  

Current research might be highlighting professional’s additional lack of

confidence in anti-depressant medication, a subject that has been actively debated in

the academic world (Kirsch, et al, 2008, Moncrieff, Wessely, & Hardy, 2004, Hetrick

et al, 2007). This can be concluded from the finding that professionals placed the least

significance on the biological model of MDD. Indeed there is an abundance of

literature citing a ‘crisis of confidence’ in anti depressant medication (Nierenberg et

al, 2011) with some claiming antidepressants might be expensive and overused

placebos. However research simultaneously asserts that in 2008 1 out of 12

Americans aged 12 and over were taking antidepressant medication, mounting to 11%

of the population and 2.7% of youths between 12-17 (Pratt, Brody, & Gu, 2011).

Although this is a complex debate, with some empirical findings in strong

support of anti-depressant use (Levkovitz et al, 2011), especially for depressed

patients with heart disease or other chronic illness (Pizzi et al, 2011), the current

research findings display professional opinion to place the least significance on a

biological model for MDD, this would include placing little importance on

antidepressant medication as a biological treatment for MDD. The discrepancy

between belief and practice, as antidepressants are still routinely prescribed (Mojtabai

& Olfson, 2010), could potentially be explained through lack of alternative

treatments. For example; light therapy, exercise, massage, acupuncture, yoga and

meditation, and even nutritional changes (Fobbester et al, 2004), are some of the

holistic alternatives to antidepressants, but their effect on depression (especially

MDD) has found to be severely lacking (Luberto et al, 2013, Albanese et al, 2012),

and small effects are only found when used in combination with antidepressants

(Talaei et al, 2015, and Ravindran et al, 2013).

Research by Howell (2013) and Black & O’Sullivan (2012) agree with this

                                                                                                                                          23  

lack of alternatives, despite investments to address potential issues such as social

disadvantage (Pleasence, Balmer, and Hagell, 2015). Social disadvantages are vast

and not easy to individually link to mental health, however research by Barry (2010)

proposed demographic factors such as age, gender, and ethnicity as important

determinants of social disadvantage. Friedli (2009) and Marmot (2010) argued

structural and environmental factors lead to susceptibility to mental health disorders,

alternatively McCulloch and Goldie (2010) grouped social determinants of mental

health into four sections; societal, community, family, and individual elements, each

containing 6 factors (see Appendix. 6 for comprehensive breakdown). Although

social determinants and disadvantages of mental health might be challenging to

define, research still strongly suggests these factors play an important role in mental

illness. The results of the current research may actually be showing that mental health

professionals are becoming aware of these social factors, and hoping it might provide

an alternative to other treatments, such as anti depressant medication.

The value professionals place on social factors, that the current findings have

highlighted, may potentially be demonstrating the explanatory model that

professionals are proposing for each mental illness. In this way, the results might

indicate whether professionals place an increased amount of responsibility for the

disorder on the individual themselves or alternative mechanisms. For instance, if

professionals are placing significance on social factors for Schizophrenia and MDD

then we could determine that the same factors are responsible for the disorder onset

and it’s symptoms. This could be a meaningful finding for individuals facing criminal

convictions for crimes committed whilst presenting with a mental health diagnosis.

For many years academics have hotly debated the liability individuals face for their

actions whilst unwell (MacDonald, Hucker, and Hebert, 2010), with courts of law

even placing guilt on individuals for not taking their medication (harrow, Jobe &

Faull, 2012). This is especially prominent in APD, associated with a lack of sense of

responsibility for ones own actions (Harpur, Hare, & Hakstian, 1989). Therefore the

current finings could be used in several forums to illustrate mental health

professional’s true beliefs in causes of mental illness, and this could have serious

repercussions for individuals within the criminal justice system.

Furthermore, if professionals are moving away from single model explanations and

             

24  

towards a multi-modal account of mental illness, this could precipitate (or

alternatively have followed) a reduction in stigmatizing attitudes. When using

individual models, professionals may choose to view diagnosed individuals in only

that framework, for instance viewing individuals with schizophrenia in only a

biological model, when this occurs it might feed into society who believe that the

individual has something innately wrong with them, making them instinctively erratic

and in some cases dangerous. For example Read and Harre (2001) confirmed that

biological beliefs of mental illness are correlated with increased negative attitudes,

Kingdon and Young (2007) and Angermeyer et al (2005) believed biological models

worsened stigma, and over half of the UK population believe schizophrenia is

biologically based rather than a combination of social and biological causes (Kingdon

et al, 2004). In actuality there is a very wide variety of research proposing just this,

for example Read, Harlam, Sayce and Davies (2006) conducted a systematic review

on the effect of prejudice and schizophrenia through different approaches. The

research aimed to evaluate the effectiveness of the anti-stigma programme ‘mental

illness is an illness like any other’ approach, in relation to schizophrenia. The

researchers discovered that society prefers psychosocial models of schizophrenia in

comparison to biogenetic ones, as the latter cause diagnostic labelling and are

positively related to fear and a desire for social distance. Thus the multi-modal

approach enhances public understanding of schizophrenia and reduces prejudice.

Limitations

However, although interesting to speculate what can be extrapolated from the

results, the research methodology might suffer several flaws, which limit the value of

any interpretations based on it. For example, the anonymous and online nature of the

survey meant that the majority of respondents began filling in their responses but

withdrew with ease. This severely reduced the number of respondents for the main

bulk of the attitude questions, reducing the overall sample size and limiting the

generalizability of the results. From this, and the use of a convenience sample, we

could question how representative the findings are to the general population of mental

health professionals both within the UK and internationally. Potential respondents

were only approached within the UK, although the online setting allowed for a much

wider potential scope and did actually reap a group of overseas respondents. Besides

                                                                                                                                          25  

issues with attrition, the sampling bias concerns were worsened due to the personal

circulation of the research questionnaire by the researchers. The leading researchers

personally disseminated the questionnaire amongst colleagues and acquaintances that

they believed would complete the research, rather than focusing on extending the

research to all professions and fields of mental health. This may have caused for the

response pool to be biased towards the professions and attitudes that the researchers

maintained, thus producing a selection bias and reducing the results ability to capture

current professional true attitudes.

The attitude questionnaire used was adapted from Harland et al (2009), and so

it was believed that internal consistency verification was not needed. However

Harland et al (2009) acknowledge that due to their sample size the analysis they

conducted was based on the belief that participants would endorse the illnesses for

each model equally, but before analyzing their raw data they assessed item correlation

between and within paradigms, not a formal method of testing internal consistency. It

was observed that the question regarding cognitive treatment correlated stronger with

items of other models than models within the cognitive model. Harland and

colleagues concluded that this might have occurred due to the acceptance of cognitive

behavioural therapy across disorders even though these disorders may not be

principally interpreted using cognitive models (NICE, 2008). Regardless of whether

this can potentially be explained, the questionnaire did not entirely show internal

consistency, and so using it without conducting more rigorous internal consistency

testing severely limited the validity of the results. In comparison to Harland et al

(2009), the current research similarly showed significant endorsement of a biological

model of schizophrenia, but this was found to be at odds with an equally significant

social explanation, and was apparent for mental health professionals as a group unit

rather than solely psychiatrists.

Of additional concern is the feedback the online survey received through

Question 45, which allowed respondents to comment on any aspect of the research.

The majority of feedback outlined concerns about the difficulty participants felt in

completing the questionnaire. A large volume of the feedback outlined the issue of

questions being too definitive implying absolutes i.e. the disorder is either biological

or spiritual, allowing for only one answer to each question per illness. Respondents

             

26  

felt that a lot of the models are not mutually exclusive but have several variables in

play at once, especially when considering individual cases. This caused offence to

some respondents, causing many participants to dropout, which lead to a high level of

attrition. Many respondents also claimed to fundamentally disagree with the

terminology used, for example the term ‘disorder’ was deemed offensive, as it

assumes there is something fundamentally at fault with the individual. Some

respondents also claimed to not know what the illnesses were, potentially a definition

of each disorder could have allowed for better understanding and increased quality

results. The most prominent issue reported was the desire for respondents to answer

the questions according to the biopsychosocial model, as well as a person-centered

approach, which coincides with much of the feedback protesting the simplicity of the

questions. Respondents claimed that due to the single available answers that the

results rendered will be misleading, and not representative of their true attitude,

causing many to chose neutral responses for the majority of questions.

Strengths

Although this research has its critiques, it also has several strengths that

enhance the validity of our results. For instance, even though the dropout rates were

observable the main section containing the attitude questions received a high amount

of responses, allowing for a good effect and sample size, increasing the

generalizability of results. The online setting and ability to further distribute the

questionnaire link meant that the questionnaire reached many different mental health

professionals in a variety of settings, both academic and clinical, and of many

different ages and ethnicities. This widened the participant pool by profession, mental

health disorder industry, and geographical location, further increasing the

generalizability of results, an aspect which previous research in the same field has

failed to do. The online nature of the research provided complete anonymity as well

as the ability to dropout with no duress.

 

Further Research

There are many directions further research on this topic could take. For

instance, the same questionnaire could be used in the same setting and method, but

the difference between treatment and explanatory model significance could be

differentiated, allowing for a thorough investigation of whether professional attitudes

                                                                                                                                          27  

differ between what they believe explains the onset of the disorder and what treatment

will effectively benefit patients. A contradictory finding in the current research

showed the biological treatment was the least significantly endorsed component for

MDD, yet NICE (2009) still recommend drug treatments, allowing for many

professionals to also endorse it as a treatment. Therefore further research into the

cause of this discrepancy would highlight why professionals are endorsing a treatment

that they do not believe effective. Future research might also look into the specific

aspects of social factors that have significant affects on mental health. Current

evidence cannot adequately inform the development of social capital interventions,

but by looking at what exact factors professionals believe to have the most prominent

affects on mental health, policy makers can use this to increase social support and

reduce rates of diagnosis and relapse.

As discussed earlier, professional interpretation of mental illnesses has a

prominent effect on stigma, an area that needs further research to develop programs to

increase understanding. For example Read and Harre (2001) found that increased

personal contact with an individual receiving psychiatric treatment corresponded with

positive attitudes towards psychiatric illnesses, whereas Schomerus et al (2011)

conducted a systematic review and meta-analysis of public attitudes to mental illness

and found that increasing public knowledge on biological aspects of mental illness did

not increase social acceptance of mental illness. Therefore future research could aim

to further understand what aspects of social contact increase positive attitudes, or

develop programs to effectively allow this. Another field that may help to reduce gaps

could be the development of a unifying philosophy amongst mental health

professionals, which would guide clinical practice. Norman and Peck (1999) and

Hannigan (1999) acknowledged the division amongst the professions and the

emphasis placed on different elements of the biopsychosocial model by professions,

claiming that incompatible frameworks don’t allow for a functioning

multidisciplinary team, therefore further research is needed to understand how the

professions are unified, what inherently divides them, and if service standards can be

improved through unification.

             

28  

Conclusions Mental health professionals are most committed to combination models of

mental illnesses, coinciding with the movement of the biopsychosocial model.

However some of the endorsed models do not correspond with clinical practice, for

instance the biological model of MDD was the least significantly endorsed model, but

drug therapies are often used to treat this disorder. The research findings have several

implications; on professional attitudes towards disorder responsibility, stigmatization,

and changes to treatment regimes, for example; the importance professionals place on

social elements could be met with changes in treatments and social support

programmes.

Authors’ Contributions JM was responsible for the respective write-up of the current research

paper, as well as the circulation of the online questionnaire link amongst University

departments and particular academic staff. JM and SJ contributed to the

development of the research objectives and methods. KD, SJ, VB, and JM were

responsible for the alterations and development of the questionnaire and online

survey, and all jointly invested in circulating the research questionnaire to

professionals for participation. VB helped with data analysis, statistical support,

and draft approval.

Acknowledgements This study was supported by the University College London, Division of

Psychiatry, as well as Professor Sonia Johnson and Dr Vaughan Bell.

                                                                                                                                          29  

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Appendix 1

Breakdown of all BSc, MSc, PhD, & DClinPsych courses for every University contacted with a request for staff to complete and circulate the link amongst the course department.  Nursing    1)  Glasgow   2)  East  Anglia   3)  Kings  College  

London  4)  Portsmouth  

5)  Nottingham   6)  West  of  England   7)  Swansea   8)  Brighton  9)  Bedfordshire   10)  Salford   11)  Bradford   12)  Cumbria  13)  City   14)  Bolton   15)  Leeds  Beckett   16)  Canterbury  

Christ  Church  17)  Worcester   18)  Essex   19)  Surrey   20)  Edinburgh  21)  Cardiff   22)  York   23)  Manchester  

Metropolitan  24)  Ulster  

25)  De  Monfort   26)  Birmingham   27)  Hull   28)  Chester  29)  Edge  Hill   30)  Stirling   31)  Glasgow  

Caledonian  32)  Staffordshire  

33)  Glyndwr   34)  Kingston-­‐  St  George’s  

35)  Suffolk   36)  Buckinghamshire  New  

37)  Birmingham   38)  Sheffield   39)  Southampton   40)  Bangor  41)  Northumbria   42)  Brunel   43)  Huddersfield   44)  Oxford  Brookes  45)  Brunel   46)  Huddersfield   47)  Bournemouth   48)  Northampton  49)  Hertfordshire   50)  Anglia-­‐Ruskin   51)  Lincoln   52)  South  London  

Bank  53)  Robert  Gordon   54)  West  London   55)  Edinburgh  

Napier  56)  West  of  Scotland  

57)  Liverpool   58)  Leeds   59)  Keele   60)  Manchester  61)  Queen  Margaret   62)  South  Wales   63)  Coventry   64)  Queens  Belfast  65)  Teeside   66)  Liverpool  John  

Moores  67)  Sheffield  Hallam  

68)  Derby  

69)  Central  Lancashire  

70)  Plymouth   71)  Greenwich     72)  Dundee  

73)  Abertay   74)  Middlesex            Social  Work    1)  Lancaster   2)  Birmingham   3)  Glasgow   4)  Stirling  5)  Bath   6)  Strathclyde   7)  Robert  Gordon   8)  Swansea  9)  Queens  Belfast   10)  UWE  Bristol   11)  Nottingham   12)  East  Anglia  13)  Leeds   14)  Sussex   15)  Warwick   16)  York  17)Glasgow  Caledonian  

18)  Portsmouth   19)  Teesside   20)  Dundee  

21)  Edinburgh   22)  Brunel   23)  Kent   24)  Keele  

                                                                                                                                          35  

25)  Manchester  Metropolitan  

26)  Huddersfield   27)  Middlesex   28)  Lincoln  

29)  De  Monfort   30)  Coventry   31)  Ulster   32)  Oxford  Brookes  33)  Hull   34)  Northumbria   35)  Suffolk   36)  Liverpool  Hope  37)  Bournemouth   38)  Salford   39)  Anglia  Ruskin   40)  South  Wales  41)  West  of  London   42)  Central  

Lancashire  43)  Bradford   44)  London  South  

bank  45)  Southampton  Solent  

46)  Cardiff  Metropolitan  

47)  Birmingham  City  

48)  Liverpool  John  Moores  

49)  Goldsmiths   50)  Hertfordshire   51)  Kingston  St  Georges  

52)  Winchester  

53)  Plymouth   54)  Sunderland   55)  Nottingham  Trent  

56)  Sheffield  Hallam  

57)  Chester   58)  West  London   59)  East  London   60)  Northampton  61)  Greenwich   62)  Gloucestershire   63)  London  

Metropolitan  64)  Derby  

65)  Buckinghamshire  New  

66)  Bradfordshire   67)  Leeds  Beckett   68)  Staffordshire  

69)  Brighton   70)  St  Mark  &  St  John  

71)  Chichester   72)  Glyndwr  

73)  Trinity  Saint  David  

74)  Cumbria   75)  Edge  Hill   76)  Canterbury  Christ  Church  

77)  Worcester          Occupational  Therapy    1)  London  South  Bank  

2)  York  St  John   3)  Plymouth   4)  Northampton  

5)  South  Wales   6)  Derby   7)  Oxford  Brookes   8)  Worcester  9)  Teesside   10)  Brunel   11)  Cardiff   12)  UEA  13)  Glasgow  Caledonian  

14)  Ulster   15)  Liverpool   16)  Bournemouth  

17)  Salford   18)  Leeds  Beckett   19)  Southampton   20)  Cumbria  21)  Robert  Gordon   22)  Coventry   23)  Huddersfield   24)  Sheffield  

Hallam  25)  Northumbria   26)  Essex   27)  Glyndwr   28)  Queen  Margaret  29)  Canterbury   30)  Bradford   31)  Brighton   32)  London  

Metropolitan  33)  Liverpool   34)  Bradford          Clinical  Psychology  Doctorate      1)  Bangor   2)  Bath   3)  Birmingham   4)  Warwick  5)  East  Anglia   6)  East  London   7)  Edinburgh   8)  Essex  9)  Exeter   10)  Glasgow   11)  Hertfordshire   12)  KCL  13)  Lancaster   14)  Leeds   15)  Leicester   16)  Liverpool  17)  Manchester   18)  Newcastle   19)  North  Thames   20)  Oxford  21)  Plymouth   22)  Royal  Holloway   23)  Salomon’s   24)  Sheffield  25)  Southampton   26)  South  Wales   27)  Staffordshire   28)  Surrey  

             

36  

29)  Teesside   30)  Lincoln  Trent   31)  Nottingham  Trent  

 

 Psychology      1)  Cambridge   2)  Bath   3)  Oxford   4)  UCL  5)  Glasgow   6)  Durham   7)  St  Andrews   8)  Birmingham  9)  Bristol   10)  Exeter   11)  Southampton   12)  Cardiff  13)  Surrey   14)  York   15)  Kent   16)  Newcastle  17)  Nottingham   18)  Warwick   19)  Lancaster   20)  Strathclyde  21)  RHUL   22)  Edinburgh   23)  Leeds   24)  Loughborough  25)  Sussex   26)  Aberdeen   27)  Stirling   28)  East  Anglia  29)  Reading   30)  Heriot-­‐Watt   31)  Sheffield   32)  Bangor  33)  Dundee   34)  Swansea   35)  Manchester   36)  Aston  37)  Portsmouth   38)  Leicester   39)  Essex   40)  Lincoln  41)  Liverpool   42)  Queens  Belfast   43)  City   44)  Goldsmiths  45)  Nottingham.  T   46)  Queen  Margaret   47)  Keele   48)  Plymouth  49)  York  St  John   50)  Coventry   51)  Abertay   52)  Hull  53)  Queen  Mary’s   54)  Manchester.  M   55)  West  of  Scot.     56)  Oxford  Brookes  57)  Northumbria   58)  Brunel   59)  Middlesex   60)  De  Montfort  61)  Chester   62)  Roehampton   63)  Bath  Spa   64)  Glyndwr  65)  Central  Lancashire  

66)  Teesside   67)  Edge  Hill   68)  Hertfordshire  

69)  Westminster   70)  Glasgow  Caledonian  

71)  West  London   72)  Bradford  

73)  Buckingham   74)  Edinburgh  Napier  

75)  Brighton   76)  Bournemouth  

77)  Salford   78)  Liverpool  John  Moores  

79)  Winchester   80)  Greenwich  

81)  Sunderland   82)  Bolton   83)  East  London   84)  Ulster  85)  Huddersfield   86)  Chichester   87)  Derby   88)  Staffordshire  89)  UWE  Bristol   90)  Aberystwyth   91)  Leeds  Trinity   92)  Leeds  Beckett  93)  Liverpool  Hope   94)  Kingston   95)  Anglia  Ruskin   96)  South  Wales  97)  Worcester   98)  Bedfordshire   99)  Canterbury   100)  Birmingham.  C  101)  Wolverhampton  

102)  London  South  Bank  

103)  Cumbria   104)  London  Metropolitan  

105)  Sheffield  Hallam  

106)  Bishop  Grosseteste  

107)  Southampton  Solent  

108)  Newman  

109)  St  Mary’s   110)  Gloucester   111)  Cardiff  Metropolitan  

112)  Suffolk  

113)  Trinity  Saint  David  

114)  Buckinghamshire    

   

 Psychiatry    1)  School  of  Central  Medicine  

2)  Nottingham   3)  KCL   4)  Aberdeen  

5)  Essex   6)  Edinburgh   7)  Birmingham   8)  Cardiff  9)  Royal  College  of  Psychiatrists  

10)  Liverpool   11)  Leicester   12)  Southampton  

13)  Manchester   14)  Oxford   15)  Cambridge    

                                                                                                                                          37  

 

Appendix 2 Write-in option for individuals who did not fit into the available options of Psychiatry, Clinical or Counselling Psychology, Mental Health Nursing, Occupational Therapy, Social Work, Art Therapies, Non Applicable. Last choice text input Early years psychotherapist Approved Mental Health Professional Peer Worker Speech & Language Therapy AMHP Cbt CBT working towards clinical doctorate Education Systemic family psychotherapy CBT Therapist CBT & IPT psychotherapy Neurology Computer science 4 / 83 Clinical neuropsychology Psychodynamic Psychotherapeutic Counselling Counsellor in Secondary care/psychological therapist Educational Psychology Educational Psychology RGN Systemic Psychotherapy CBT Post Grad Dip mental health nursing and social work Family Therapy Counselling OT arts therapist, CAT practitioner Research Psychology CBT School nurse children with disabilities Educational psychology Physiotherapist pharmacist cognitive analytic therapy Support services Physiotherapist Peer Support Specialist psychotherapy social work and arts psychotherapist psychology and nursing Nursing and education counsellor Sport psychology and counselling psychology Speech & Language Therapy Cognitive and Behavioural Psychotherapist mental health officer (Scottish equivalent of AMHP I have a BA in Psych. I am getting a MSW and I am a CRSS, WRAP facilitator and trainor and MHFA

             

38  

trainor Educational psychology CBT therapist PhD Certified peer recovery coach

Appendix 3 The demographic questions placed at the beginning of the questionnaire once the participants had begun.

1. Number of years working in mental health:

2. Do you have a recognised mental health qualification (e.g. in psychiatry, clinical psychology, mental health nursing)? Please choose one of the options.

Qualified professional (e.g. clinical psychologist, mental health nurse, occupational therapist, social worker, other qualified therapist)

Currently training for a professional qualification

Working in mental health research/academia, not clinically qualified

Working in mental health care, not clinically qualified (e.g. support worker, assistant psychologist)

Post-graduate student in area related to mental health (not currently training for professional qualification)

Undergraduate student in area related to mental health (not currently training for professional qualification)

3. For qualified professionals and trainees, which profession are you qualified/training in?

Psychiatry

Clinical or Counselling Psychology

Mental Health Nursing

Occupational Therapy

Social Work

Arts Therapies

                                                                                                                                          39  

Not applicable

Other, please describe:

4. Where do you mainly work? Please tick all that apply

In a healthcare setting

In research/academia

Other, please describe:

5. Are you currently engaged in research?

Yes

No

6.

What is your country of birth?

7.

In which country do you currently reside?

             

40  

Appendix 4

The adapted version of the MAQ questionnaire used in the current research for data collection.

Professionals' Understanding of Mental Health Problems

Thank you very much for your interest. This study looks at how different groups of people working or studying in the field of mental health or mental health research understand mental health problems (for example, depression and anxiety).

While taking this survey, you will be asked to complete a questionnaire which should take no more than 15 minutes of your time. You will be asked for some information regarding your professional and cultural background, and will be asked some questions about the way you understand certain mental health problems.

Please note: To be consistent with past research, this survey uses standard ICD-10 diagnoses to describe mental health problems. We recognise that people have differing opinions with regard to the appropriateness of these terms, but please complete the survey with regard to the problems that these diagnoses describe.

Please attempt to answer each question.

All of your responses are collected anonymously. However, there is an option to leave an email address at the end of this survey if you would like to be informed about the results of this study. If you choose to do so, this information will be stored confidentially and in accordance with the Data Protection Act 1998.

This study has been approved by the University College London (UCL) Research Ethics Committee. It is being conducted by:

Kira Dormann, MSc Student, UCL: kira.dormann.14@ucl.ac.uk

Jasmine Martinez, MSc Student, UCL, jasmine.martinez.14@ucl.ac.uk

Prof Sonia Johnson, UCL: s.johnson@ucl.ac.uk

Dr Vaughan Bell, UCL: vaughan.bell@ucl.ac.uk

Dr Niall Boyce, Editor of the Lancet Psychiatry: n.boyce@elsevier.com

                                                                                                                                          41  

Dr Matthew Broome, Oxford University: matthew.broome@psych.ox.ac.uk

Please click 'Start' if you consent to participate in this survey.

1. 1. Number of years working in mental health:

2. Do you have a recognised mental health qualification (e.g. in psychiatry, clinical psychology, mental health nursing)? Please choose one of the options.

Qualified professional (e.g. clinical psychologist, mental health nurse, occupational therapist, social worker, other qualified therapist)

Currently training for a professional qualification

Working in mental health research/academia, not clinically qualified

Working in mental health care, not clinically qualified (e.g. support worker, assistant psychologist)

Post-graduate student in area related to mental health (not currently training for professional qualification)

Undergraduate student in area related to mental health (not currently training for professional qualification)

3. For qualified professionals and trainees, which profession are you qualified/training in?

Psychiatry

Clinical or Counselling Psychology

Mental Health Nursing

Occupational Therapy

Social Work

Arts Therapies

Not applicable

Other, please describe:

4. Where do you mainly work? Please tick all that apply

In a healthcare setting

In research/academia

Other, please describe:

             

42  

5. Are you currently engaged in research?

Yes

No

6. What is your country of birth?

7. In which country do you currently reside?

The following questions will explore your understanding of different mental health problems. There are no right or wrong answers. Please answer every question.

8. The disorder results from brain dysfunction.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

9. The disorder arises as a consequence of social circumstances or conditions

                                                                                                                                          43  

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

10. The disorder is best approached through the study of abnormal behaviour.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

11. The research into the disorder should focus on the identification of causative social factors

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

12. The ideal classification of the disorder would be a pathophysiological one.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

13. The disorder should be treated by challenging and restructuring maladaptive thoughts and beliefs.

             

44  

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

14. Neglecting the spiritual or moral dimension of life leads to the disorder.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

15. The appropriate study of the disorder involves discovery of biological markers and the effects of biological interventions.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

16. Treatment of the disorder should be based on whatever folk treatments and models are accepted as appropriate by the patient and their local community.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

                                                                                                                                          45  

17. Studying the associations between antecedents and consequences in patients’ behaviour is the best basis for modification of the disorder.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

18. Mental health professionals have no ‘expertise’ of the disorder over and above anyone else.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

19. The disorder can only be understood in the context of local meanings and these meanings cannot be extrapolated to universal classifications.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

20. Social factors such as prejudice, poor housing and unemployment are the main causes of the disorder.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

             

46  

21. Maladaptive thoughts and beliefs are normally distributed in the population and it is the extreme ends of this distribution that accounts for the disorder.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

22. There is no universal classification of disorder, only culturally relative classifications.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

23. Treatment of the disorder should be directed at underlying biological abnormalities.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

24. The disorder is due to unconscious factors (as defined psychodynamically).

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

                                                                                                                                          47  

25. The behavioural problems in the disorder are best modified by associating new responses to a given stimulus.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

26. The study of the disorder should concentrate on understanding cognitive distortions and reasoning errors.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

27. Adherence to religious or spiritual practice is the most effective way of treating the disorder.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

28. The structure of the disordered psyche and its unconscious mechanisms is best understood by a study of individual cases.

Strongly disagree Disagree Neutral Agree Strongly agree

             

48  

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

29. Attempts to scientifically explain the disorder have resulted in no significant knowledge.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

30. The disorder is nothing other than the sum of maladaptive thoughts, belief and behaviours.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

31. Consulting a spiritual authority can give a better understanding of the disorder than psychiatry.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

32. The disorder results from the failure to successfully complete developmental psychic stages

Strongly disagree Disagree Neutral Agree Strongly agree

                                                                                                                                          49  

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

33. All classifications and ‘treatments’ of the disorder are myths.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

34. Treatment of the disorder requires resolution of disturbed early object relationships.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

35. Government policies to reduce prejudice, poor housing and unemployment are the way to eradicate the disorder.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

36. The disorder is better understood through religious or spiritual insights.

Strongly disagree Disagree Neutral Agree Strongly agree

             

50  

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

37. The disorder results from maladapted associative learning.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

38. The disorder is a culturally determined construction that reflects the interests and ideology of socially dominant groups.

Strongly disagree Disagree Neutral Agree Strongly agree

1 2 3 4 5

Schizophrenia

Major Depression

Antisocial Personality Disorder

39. Which mental health problems or disabilities are the people you see in your clinical practice mainly experiencing? Please tick all that apply.

Child Mental Health

Dementia

Depression and Anxiety

Eating Disorders

Intellectual and / or Neurodevelopmental Disability

Personality Disorder

                                                                                                                                          51  

Psychosis

Substance Misuse

Not applicable

Other:

40. Which mental health problems or disabilities is your research mainly concerned with? Please tick all that apply.

Child Mental Health

Dementia

Depression and Anxiety

Eating Disorders

Intellectual and / or Neurodevelopmental Disability

Personality Disorder

Psychosis

Substance Misuse

Not applicable

Other:

41. Age

42. Sex

Female

Male

43. Please indicate your ethnic group. Choose one option which best describes your ethnic group or background. If mixed or not included in list please describe in box below.

White: British

             

52  

White: Irish

White: Other

Asian/Asian British: Indian

Asian/Asian British: Pakistani

Asian/Asian British: Bangladeshi

Asian/Asian British: Other

Black/Black British: Caribbean

Black/Black British: African

Black/Black British: Other

Mixed: White and Black Caribbean

Mixed: White and Black African

Mixed: White and Asian

Mixed: Other

Any other, please descibe:

44. Religious beliefs of parents and respondent. If parents have different beliefs please choose as many as appropriate.

Respondent Parents

Agnostic

Atheist

Christian

Muslim

Jewish

Hindu

Buddhist

Sikh

Other:

                                                                                                                                          53  

             

54  

Appendix 5 Participants information sheet.

                                                                                                                                          55  

Appendix 6

Examples of determinants of mental health (McCulloch and Goldie, 2010)

             

56  

Appendix 7 Pattern Matrix produced from the PCA on Models of Schizophrenia

Pattern Matrixa

Component

1 2 3 4 5

Q23Bio_Schizo -.806 Q15Bio_Schizo -.801 Q8Bio_Schizo -.797 Q12Bio_Schizo -.785 Q26Cog_Schizo .751 Q13Cog_Schizo .720 Q25Behav_Schizo .656 Q17Behav_Schizo .534 Q21Cognitive_Schizo .501 Q37Behav_Schizo .446 .382 Q10Behav_Schizo -.310 .374 Q36Spirit_Schizo .893 Q27Spirit_Schizo .856 Q31Spirit_Schizo .763 Q14Spirit_Schizo .631 Q32PsychoD_Schizo .540 Q34PsychoD_Schizo .409 .460 Q28PsychoD_Schizo .308 -.507 Q9SR_Schizo .354 .477 Q20SR_Schizo .395 .441 Q35SR_Schizo .333 .356 .430 Q24PsychoD_Schizo .369 -.400 Q11SR_Schizo Q18Nihi_Schizo .704

Q22SC_Schizo .538

Q33Nihi_Schizo .315 .528

Q29Nihi_Schizo .519

Q19SC_Schizo .512

Q16SC_Schizo .508

Q38SC_Schizo .325 .338 .353

Q30Cog_Schizo .315 .324 Extraction Method: Principal Component Analysis. Rotation Method: Oblimin with Kaiser Normalization.a a. Rotation converged in 21 iterations.  

Appendix 8

                                                                                                                                          57  

Pattern Matrix produced from the PCA on Models of Major Depressive Disorder

Pattern Matrixa

Component

1 2 3 4 5 6

Q20SR_MDD .685 Q9SR_MDD .638 Q35SR_MDD .630 Q11SR_MDD .586 Q21Cognitive_MDD .435 .330 Q26Cog_MDD .652 Q30Cog_MDD .643 -.372

Q25Beh_MDD .584 Q13Cog_MDD .582 Q17Behav_MDD .510 Q37Behav_MDD .458 -.300 Q10Behav_MDD .403 Q36Spirit_MDD .884 Q27Spirit_MDD .832 Q31Spirit_MDD .805 Q14Spirit_MDD .448 -.309 Q24PsychoD_MDD -.780 Q34PsychoD_MDD -.740 Q32PsychoD_MDD -.699 Q28PsychoD_MDD -.597 Q18Nihi_MDD .773 Q29Nihi_MDD .570 Q16SC_MDD .516 Q19SC_MDD .513 Q22SC_MDD .331 .490 Q33Nihi_MDD .477 Q38SC_MDD .319 .314 .335 Q15Bio_MDD .800

Q8Bio_MDD .794

Q23Bio_MDD .779

Q12Bio_MDD .728 Extraction Method: Principal Component Analysis. Rotation Method: Oblimin with Kaiser Normalization.a a. Rotation converged in 20 iterations.

Appendix 9

             

58  

Pattern Matrix produced from the PCA on Models of Antisocial Personality Disorder

Pattern Matrixa

Component

1 2 3 4

Q22SC_APD .701 Q38SC_APD .659 Q35SR_APD .653 Q20SR_APD .610 Q19SC_APD .606 Q16SC_APD .530 Q33Nihi_APD .517 Q18Nihi_APD .426 Q13Cog_APD .688 Q26Cog_APD .662 Q17Behav_APD .642 Q25Behav_APD .629 Q37Behav_APD .456 -.338

Q21Cognitive_APD .426 .447 Q10Behav_APD -.353 .405 Q30Cog_APD .343 Q23Bio_APD .797 Q15Bio_APD .766 Q8Bio_APD .743 Q12Bio_APD .623 Q9SR_APD -.449 Q11SR_APD .314 -.379 Q29Nihi_APD -.334 Q36Spirit_APD .304 -.660

Q27Spirit_APD -.652

Q24PsychoD_APD -.639

Q32PsychoD_APD -.629

Q34PsychoD_APD -.622

Q31Spirit_APD .383 -.564

Q14Spirit_APD -.554

Q28PsychoD_APD -.539 Extraction Method: Principal Component Analysis. Rotation Method: Oblimin with Kaiser Normalization.a a. Rotation converged in 11 iterations.