Distributed interactive communication in simulated space-dwelling groups

Distributed interactive communication insimulated space-dwelling groups

Joseph V. Bradya,b,*, Robert D. Hienza,b, Steven R. Hursha,b,c,Leonard C. Ragusac, Charles O. Rouseb, Eric D. Gasiorb

aJohnsHopkinsUniversitySchool ofMedicine,BehavioralBiologyResearchCenter, 5510NathanShockDrive/

Suite 3000, Baltimore, MD 21224, USAbInstitute for Behavior Resources, 2457 Maryland Avenue, Baltimore, MD 21218, USA

cScience Applications International Corporation, 626 Town Center Drive, Joppa, MD 21085, USA

Abstract

This report describes the development and preliminary application of an experimental testbed for modeling human behavior in the context of a computer generated environment toanalyze the effects of variations in communication modalities, incentives and stressful condi-

tions. In addition to detailing the methodological development of a simulated task environ-ment that provides for electronic monitoring and recording of individual and group behavior,the initial substantive findings from an experimental analysis of distributed interactive

communication in simulated space dwelling groups are described. Crews of three memberseach (male and female) participated in simulated ‘‘planetary missions’’ based upon a syntheticscenario task that required identification, collection, and analysis of geologic specimens with arange of grade values. The results of these preliminary studies showed clearly that cooperative

and productive interactions were maintained between individually isolated and distributedindividuals communicating and problem-solving effectively in a computer-generated ‘‘plane-tary’’ environment over extended time intervals without benefit of one another’s physical

presence. Studies on communication channel constraints confirmed the functional inter-changeability between available modalities with the highest degree of interchangeabilityoccurring between Audio and Text modes of communication. The effects of task-related

incentives were determined by the conditions under which they were available with PositiveIncentives effectively attenuating decrements in performance under stressful time pressure.# 2003 Elsevier Ltd. All rights reserved.

Keywords: Communication; Distributed interactive simulation; Synthetic task environment

Computers in Human Behavior 20 (2004) 311–340

www.elsevier.com/locate/comphumbeh

0747-5632/$ - see front matter # 2003 Elsevier Ltd. All rights reserved.

doi:10.1016/j.chb.2003.10.022

* Corresponding author. Tel.: +1-410-550-2779; fax: +1-410-550-2780.

E-mail address: [email protected] (J.V. Brady).

http://www.elsevier.com/locate/comphumbeh/a4.3d

mailto:[email protected]

1. Introduction

Distributed interactive communication between widely dispersed elements will bea common feature of future spaceflight endeavors characterized by dependence uponcomputer technology during extended stays by human groups in extraterrestrialhabitats. Recent advances in technology have made it possible to develop experi-mental test beds for modeling human performance in the context of computer-gen-erated environments to analyze and evaluate variations in communicationmodalities and the effects of environmental conditions on performance effectivenessand psychosocial adaptation. For economic, technical, and psychosocial reasons, itis important to determine the correct mix of communication modalities to maximizeefficiency without over-complicating the information system design. The developingcomputer-automated group support technologies do, however, open the door toenhanced precision of performance measurement both within space-dwelling groupsand between the space-dwellers and Earth-based coordinating centers. Never beforehas it been possible to specify with the highest degree of precision the streamof environmental antecedents and consequences that define the critical determinantsof small group behavioral interactions.Recent developments in computer-based simulation technology have confirmed

the effectiveness of incorporating and quantifying the performance dimensionsof human participation and of extending the emerging technology to the analysis ofcommunication modalities that play an essential role in the behavioral and psycho-social interactions of small dispersed groups (Duffy, 1993; Gillis & Hursh, 1999;Hursh, 1997, 1998; Hursh, Brady, & Hienz, 2003; Hursh & McNally, 1993; Kraemer&King, 1988; Pinsonneault & Kraemer, 1990; Pratt, Pratt, Waldrop, Barham, Ehlert,& Chrislip, 1997). In addition, there have been a number of recent publicationsdescribing the application of simulation techniques to the study of ‘‘virtual teams’’and the importance of communication factors in the coordination among individualswho are geographically and/or organizationally dispersed (Ancona & Caldwell, 1992;Baker, 2002; Dougherty, 1992; Ebadi & Utterback, 1984: Pinto, Pinto, & Prescott,1993; Sarker, Valacich & Sarker, 2003). The extensive study by Baker (2002) forexample, analyzed the decision-making performances of 64 virtual teams using fourdifferent collaborative communication technologies: text-only; audio-only; text-video; and audio-video. A comparison of the groups using text-only communicationwith the groups using audio-only communication showed no significant differencesbut the addition of video to the audio-only communication produced a significantimprovement in the quality of the ‘‘virtual teams’’ strategic decision making.The use of computer-based simulation techniques in problem solving training with

geographically dispersed military groups (Orvis, Wisher, Bonk, & Olson, 2002) aswell as with distributed team tasks (Fiore, Cuevas, Scielzo, & Salas, 2002) has beenthe focus of recent reports that reflect the development of technological softwaresupport for Defense Department distributed interactive simulation operations thatinvolve units from multiple Military Services participating from geographicallyremote stations. The extent of these applications is indicated by the range ofcomputer-based programs represented in the National Air and Space Model (NASM),

312 J.V. Brady et al. / Computers in Human Behavior 20 (2004) 311–340

the Joint Simulation System (JSIMS), Warfighter’s Simulation 2000 (WARSIM 2000),Close Contact Tactical Trainer (CCTT), and the development by the Army ResearchInstitute of a model that combines the effects of stressful conditions and fatigue on thedecision-making accuracy of a simulated command entity. Among the range of com-puter-based simulation approaches to such investigative initiatives, the relatively simplenetworked work-station system running under an interactive simulation environment,as described in the Methods and Procedures section of this report, has provendemonstrably effective in the indicated government sponsored applications utilizinga ‘‘tool kit’’ approach based upon affordable but high performance PC components.The present report describes the methods and procedures involved in the devel-

opment of a simulated task environment to provide a computer-based automatedmeans for setting the context of space-dwelling group task performances. In addi-tion to detailing the methodological developments that provide for electronic mon-itoring of behavioral interactions in the simulated task environment, the initialsubstantive findings from an experimental analysis of the effects of variations in thecontext of distributed communication, stressful conditions and task-related incen-tives upon performance effectiveness and psychosocial adaptation are described.

2. Methods and procedures

2.1. Participant volunteers

Male and female volunteers (Fig. 1) were recruited from local university campusesto participate as subjects in the experiments. Pre- and post-doctoral level personswere sought as participants in the interest of approximating comparability betweenthe experimental subject population and potential candidates for future space-dwelling group initiatives. The volunteer participants received remuneration at therate of $15 per hour for their participation, calibrated to the incentive system(see below) in respective experiments. In addition, volunteers received an additional$5 per hour bonus payment for full participation and completion of an experiment.No special skills or training were required to participate in the proposed experimentsas a volunteer but a commitment of availability for recurrent experimentalparticipation over continuous experimental periods was required as necessary.The developmental testing program and experimental studies described in this

report were conducted with 11 groups of 3 crewmembers each (both male, female,and combined male/female groups) participating in a total of 89 pre-experimental‘‘test’’ flights to insure ‘‘hardware’’ and ‘‘software’’ reliability, 57 ‘‘training’’ flightsto establish individual and group ‘‘baseline stability’’, and 33 ‘‘experimentalmissions’’ (99 simulated ‘‘space flights’’) to generate the data described in this report.

2.2. Simulated task environment

Individual group members were located at workstations isolated both physicallyand acoustically from each other and from a remotely located monitoring station

J.V. Brady et al. / Computers in Human Behavior 20 (2004) 311–340 313

(Fig. 2). Each group member workstation was comprised of two personal computerswith two monitors as illustrated in Fig. 3. One computer/monitor stationrepresented the ‘‘navigation system’’ and provided simulated task instructions, aninformation database, a series of standardized questionnaires that supported groupdecisions, and visual images that tracked progress through the scenario. The secondcomputer/monitor station represented the ‘‘communication system’’ providing anelectronic network among the group members and between the space-dwellinggroup and Earth-centered ‘‘mission control’’. The remote mission control monitor-ing station programmed task performance requirements as well as availablecommunication modalities, captured and logged communication information andmaintained records of task performance.Functionally, the experimental setting was based upon a modification of the

MUD (Multi-User Dudgeons) concept with augmented voice and Web cameracapabilities. Audio communication was provided via a headset worn by eachcrewmember; visual images of each crewmember were displayed via the Web cameraat each workstation; and text messages were sent to other crewmembers by typinginto a dialogue box on the communication interface. Depending on the simulationscenario requirements, the Web Camera provided active or frozen images of theother group members. A static background display under a shared white boardmechanism allowed users to define routes and build overlays. A status panel shown

Fig. 1. Typical volunteer simulated spaceflight crew.


in Fig. 4 provided scenario relevant information, such as elapsed time, time untilnext decision, and available resources.

2.3. Simulated task scenarios

Interactive simulation scenarios were developed around resource and time man-agement themes within the context of extended geologic exploration expeditions ona simulated planetary surface. At the start of each scenario, a three-person crew wasassigned the task of collecting geologic specimens of high grade values (see below) tocomplete their mission. One crew member was in a simulated ‘‘Orbiter’’ vehicle thatcircled the planet overhead, provided remotely-sensed geologic information of thesurface, and could provide detailed analyses of any geologic specimen collectedon the surface; a second crew member was on the planetary surface in a ‘‘Rover’’vehicle designed to move across the surface, collect and store specimens, andtransmit collected specimen characteristics to the Orbiter for more detailed analyses(see Fig. 6 below); a third crew member was on the planetary surface in a ‘‘Lander’’vehicle that provided logistic support for the Rover (e.g., additional storage space

Fig. 2. Simulated task laboratory environment.

Fig. 3. Workstations with communication and navigation computer monitors.


for collected specimens, additional fuel for the Rover, and docking abilities tophysically move the Rover to other locations on the simulated planetary surface.The scenario map illustrations shown in Figs. 5 and 6 feature a rectangular surface

area on the navigation system of each crew member (Fig. 5) and display threeregions (Fig. 6) designated by name (e.g., ‘‘Canyon’’, ‘‘Plain’’, and ‘‘Ravine’’).Elevation of each region relative to the intervening planetary space (IPS) could beindependently designated, with elevations ranging from �1 to +1 in 0.5 unit steps(IPS elevation=0). Elevation differences between the IPS and other regions couldnot be directly traversed by the Rover vehicle except via a single ‘‘ramp’’ connectingeach region to the IPS. The Lander vehicle, however, could ‘‘jump’’ across thesearea boundaries without using a ramp. With the scenarios developed for the

Fig. 4. Status panel providing scenario-relevant information regarding available time and resources.


experiments described below, the three 4-sided regions were employed. Theseregions, ramp locations and sizes remained the same throughout any given study.Within each region several geologic specimens were randomly placed. Each

specimen could vary in accordance with the following range of characteristics:

� size (small, medium, or large);� shape (round, oval, triangular, rod, or square);� color (red, green, blue, orange, or yellow);� density (low, medium, or high);� magnetite presence indicator (positive or negative);� biological sign indicator (positive or negative); and� grade value (a number between 0 and 120).

Once a geologic specimen had been collected by the Rover, its size, shape, andcolor (‘‘primary’’ characteristics) were displayed in the Rover’s collection tray.The remaining characteristics were known only after the Rover transmitted thespecimen’s data to the Orbiter for a more complete analysis. The results were thentransmitted back to the Rover.Prior to each experimental session, a software program generated a ‘‘scenario file’’

that specified all specimen grade values and specimen characteristics for that session.The program generated semi-random specimen characteristics and grade values

Fig. 5. Rectangular scenario map of planetary surface area displayed on navigation system.


based upon input values that specified (1) the number of specimens to occur in allregions, (2) the grade value (points per specimen) associated with each specimen,and (3) the number and type of ‘‘rules’’ predictive of those specimens with non-zerograde values. For the experiments described below, there were available five rules forthe occurrence of non-zero grade value specimens within each region, and the ruleswere one-dimensional, two-dimensional, and/or three-dimensional. A one-dimen-sional rule specified that a particular grade value (e.g., 20) was associated with asingle value of a primary characteristic (e.g., for color, a red specimen); a two-dimensional rule specified that a particular grade value (e.g., 40) was associated witha single value of two of the primary characteristics (e.g., for size and color, a‘‘small’’, ‘‘orange’’ specimen); a three-dimensional rule specified that a particulargrade value (e.g., 80) was associated with a single value of each of the three primarycharacteristic (e.g., a small, green, oval specimen). For all specimens with a zerograde value, the primary characteristics were assigned randomly, as long as thosecharacteristics did not match any of those already specified by one of the ruleswithin a region.Several additional restrictions were also imposed upon the generation of each new

scenario. First, no more than five rules of one type (1-, 2-, or 3-dimensional) couldoccur across all three regions, although more than one type could occur within a

Fig. 6. Regional map of planetary surface area designated for geologic specimen collection and analysis

by Rover, Lander, and Orbiter.


region. Second, the same rule could not occur twice in the same region, but couldoccur again in a different region. Third, if a 1-dimensional rule occurred in a region,no 2- or 3-dimensional rule containing that 1-dimensional rule could occur withinthe same region (e.g., if a rule exists for blue specimens, then no other rule couldhave blue as a characteristic). Fourth, if a 2-dimensional rule occurred in a region,no 3-dimensional rule containing that 2-dimensional rule could occur within thesame region (e.g., if a rule existed for round, green specimens, then no 3-dimensionalrule could have round, green specimens). Fifth, no randomly-generated specimens ofgrade value zero could have characteristics that match any of the rules within aregion. Sixth, the actual number of specimens of each rule type within each regionwas randomly varied to minimize the use of specimen frequency as an extra clue indecoding the rules of a region, with a specimen frequency randomization factor of�13 employed for the present experiments. Seventh, actual grade values were alsorandomly varied about a specified mean value (e.g., a grade value of 40, �20) tominimize the use of grade value as an added clue for decoding the rules within aregion, with a randomization factor of �20 employed for the experiments to bedescribed.For these experiments, all generated scenarios contained three geographic regions,

and a total of 252 geologic specimens were randomly positioned and equally dis-tributed within the three regions. Approximately one-third of the specimens (N=84)had positive grade values assigned to them, while the remainder (N=168) had a zerograde value. Assigned grade values were 20 (N=17), 40 (N=17), 60 (N=17), 80(N=17), and 100 (N=17), resulting in a total possible grade value of 5000. Addi-tionally, the actual number of specimens of each rule type within the overall scenariowas randomly varied to minimize the use of a fixed sample frequency as an extraclue in decoding the rules of a region. A specimen frequency randomization factor of�13 was employed for the present study; that is, the number of specimens of a givenrule type could vary between 3 and 30. The frequency of zero-valued specimens,however, was adjusted to keep the total sample constant at a value of N=252.Actual grade values were also randomly varied about their specified mean value by agrade value randomization factor of �20 to minimize the use of fixed grade valuesas added clues for decoding the rules within a region. All non-zero grade valuespecimens were required, however, to have a grade value of at least 1.

2.4. Communication monitoring, recording, and analysis

The modality, frequency, duration, and content of all communication via text,audio, and video among crewmembers and between crewmembers and ‘‘missioncontrol’’ center were monitored and recorded for analysis. Relevant data was alsoprovided by the logbook entries required of each crewmember and by the text(Fig. 7) included on the communication screen.Following each test session as well, all subjects completed a debriefing ques-

tionnaire requiring them to rate the importance of and their satisfaction with rele-vant aspects of the group interaction and the simulation system that occasioned andsupported their interactions. The descriptive and predictive value of a computerized


content analysis scoring system for logbook entries and debriefing questionnaireswas evaluated by the use of the PCAD 2000 software program (GB Software). Thissoftware reliably scored speech transcriptions on Content Analysis Scales includingsubscales for Hostility, Social Alienation, Cognitive Impairment, Hope andDepression (Gottschalk & Gleser, 2000). The program assigned scores on user-selected scales to each clause in the speech transcription sample, and reported scoresummaries for each scale as compared to established norms for a subject’s demo-graphic group. Analysis results are considered reliable on input samples as small as85–90 words, and the reliability and accuracy of the system improve with the lengthof the sample. The software also provided a statement of the significance andimplication of the scores.Each crewmember also completed a computerized adaptation of the Revised NEO

Personality Inventory (NEO PI-R) and the Brief Symptom Inventory (BSI). TheNEOPI-R is a 240-item questionnaire measure of the five major domains ofpersonality: Neuroticism, Extroversion, Openness to Experience, Agreeableness, andConscientiousness. Responses were made on a five-point Likert scale ranging from‘‘Strongly Disagree’’ to ‘‘Strongly Agree’’. Raw scores were converted to T-scoresthat were based on normative data from census-matched adults and collegestudents. Numerous publications (Costa & McCrae, 1995, 1997; Costa & Widiger,1994) have documented the extensive construct validity of the NEO PI-R domainand facet scales including such criteria as most major personality inventories and

Fig. 7. Communication screen displaying video and text messaging modalities.


measures of coping and defense, somatic complaints, psychological well-being,interpersonal characteristics, needs and motives, interests and attitudes, as well ascognitive styles. The BSI is a psychological self-report scale that consists of a 53-itemquestionnaire. The BSI was developed from its longer parent instrument, the SCL-90-R, and has been documented as an acceptable short alternative to the completescale (Derogatis & Melisaratos, 1983). The symptom scales include Somatization,Obsessive-Compulsive, Interpersonal Sensitivity, Depression, Anxiety, Hostility,Phobic Anxiety, Paranoid Ideation, Psychoticism, and three Global Indices—theGlobal Severity Index, the Positive Symptom Distress Index, and the PositiveSymptom Total. The BSI instrument has been considered especially appropriate insituations that result in reduced attention and endurance, in research with limitedinterview schedules, and in situations where testing procedures demand brevity.The BSI instrument has also been frequently used in measuring progress duringinterventions or in the assessment of performance outcomes.

2.5. Experimental session parameters

Each experimental session consisted of a ‘‘Mission’’ composed of 3 separate‘‘Flights’’, each approximately 1 h in duration. At the beginning of each Flight, thecrew was directed by ‘‘Mission Control’’ (Fig. 8) to explore a specific region of thesimulated planetary surface for the duration of that Flight. The ‘‘planetary mission’’

Fig. 8. Operations center for simulated ‘‘Mission Control’’.


simulated task environment required that the crew locate, identify, collect, andanalyze geologic specimens with a range of graded values. Typically, each 3- to-4 hMission consisted of multiple Flights of approximately 60 min in duration. Baselineconditions provided for the availability of all communication modalities (i.e., textmessaging, drawing on a shared ‘‘white board’’, active video images, and audiovocal exchanges) and for the measurement of total geologic specimen grade valuesduring control flights. The extent to which the interacting crewmembers could opti-mize their performances during the simulated space flights was dependent upon uti-lization of the distributed communication modalities to exchange information aboutthe location, identifying characteristics, storage, and analysis of the grade-valued geo-logic specimens. The total specimen grade values accumulated during each flight, minusthe ‘‘damage’’ points accrued during that Flight (see ‘‘Stressful Conditions’’ experimentsbelow), comprised the overall performance effectiveness score for that Flight.

2.6. Baseline stability and performance measurements

Repeated acquisition and performance trials were required during the preliminaryinstructional and training phase for each crew. Learning the scenarios was facilitatedby the method of approximation with each group initially exposed to simplifiedscenarios designed to increase familiarity with the various performance require-ments. Performance effectiveness measures were based upon successful accumu-lation of specimen grade values (Fig. 9) and data derived from the flight log whichprovided a minute by minute record of all quantifiable activity values throughout allphases of every mission (Fig. 10). The effects of experimental manipulations (e.g.,communication modalities, incentive conditions, stressful interventions) werequantitatively assessed in the context of these baseline measures. In addition,psychosocial adaptation and performance effectiveness evaluations were providedby an analysis of communication patterns involving the frequency, duration, andcontent of exchanges among the crewmembers as well as between the flight crew and‘‘Mission Control’’ in the course of simulation scenario operations.

2.7. Experimental manipulation of communication modalities

The contribution of different communication modalities to the effectiveness of theindicated distributed interactive performances was investigated by selectivelyeliminating one or more modes of communication during specific Missions andFlights. The following conditions were studied experimentally: ‘‘Audio Out’’, ‘‘TextMessaging Out’’, ‘‘Whiteboard Communication Out’’, ‘‘Audio and Text Out’’, and‘‘Audio and Whiteboard Out’’. Typically, these studies were conducted utilizing atraditional ‘‘ABA’’ experimental design in which the ‘‘A’’ or baseline condition withall communication modalities available was programmed to occur during the firstand third flights of a three-flight mission. The selected ‘‘test’’ or ‘‘experimental’’mode of communication was eliminated during the second flight (the ‘‘B’’ condition)of the mission to permit a comparative assessment of the performance effectsproduced by the communication restraint (‘‘A’’ to ‘‘B’’ change) as well as reversal of


the performance effect by reinstatement of the eliminated modality (‘‘B’’ to ‘‘A’’baseline recovery). Selected flights were also conducted in accordance with an‘‘AAB’’ design in which the experimentally manipulated communication mode waspresent during the first and second flights but eliminated during the third flight ofthe Mission.

2.8. Experimental manipulation of incentive conditions

Under ‘‘appetitive’’ (i.e., positive) incentive conditions, crew performances thatexceeded a predetermined total grade value standard resulted in proportionalmonetary additions to a group ‘‘bonus’’ account (+$0.05 per grade value unit).

Fig. 9. Geologic specimen collection tray display.


Under ‘‘aversive’’ (i.e., negative/punitive) conditions, crew performances that failedto reach a predetermined total grade value standard resulted in proportionalsubtractions from the group bonus account (�$0.05 per grade value unit). Grouptotal grade value standards were based on the mean total crew grade values (i.e.,accrued total crew grade values minus accrued ‘‘damage’’ units) over the precedingsix baseline flights. Under appetitive or positive incentive conditions, the groupstandard was set at the mean minus 1 standard deviation. Under aversive or punitiveincentive conditions, the group standard was set at the mean plus 1 standarddeviation. When a negative or aversive incentive condition was programmed beforeaccrual of a crew bonus account, a bonus was awarded at the beginning of the flightequal to two standard deviations worth of grade values multiplied by $0.05. Adeduction of $0.05 was made from this bonus amount for each point below thegroup standard at the end of the flight to insure that if the crew performed at theiraverage level, the two incentive conditions would yield an identical payment to thegroup bonus account. The proceeds of each group bonus account were distributedequally among the crewmembers at the completion of an experiment.A self-report procedure, the Visual Analogue Scale (VAS), provided an additional

measure of the behavioral and psychosocial adaptation effects of incentive conditionexperimental manipulations. The VAS (Kelly, Foltin, Emurian, & Fischman, 1993;Kelly, Taylor, Heishman, & Crouch, 1998) used a computer display to present‘‘feeling’’ words (e.g., ‘‘lethargic’’, ‘‘happy’’, ‘‘frustrated’’) above a line labeled ‘‘notat all’’ on the left end and ‘‘extremely’’ on the right end with instructions to movethe ‘‘mouse’’ indicator to the place best describing the crewmember’s ‘‘feeling’’ atthe time. Quantitative scores were derived from measures of the distance betweenthe left endpoint (‘‘not at all’’ anchor point) of the 100 unit analog line and thepoint on the line selected by the crewmember. The response time for each wordand for completion of the list was also recorded electronically for subsequentanalysis.

Fig. 10. Flight log minute-by-minute display of scenario events and simulated crew activity.


2.9. Experimental manipulation of stressful conditions

Investigations of the effects of stressful time pressure manipulations upon perfor-mance effectiveness and psychosocial adaptation in the simulated task environmentwere based upon a method for reducing the available on-task time by programmingan unscheduled intrusive performance requirement to be completed before sched-uled geologic specimen collection and evaluation activities could be continued.Emergency drill requirements to avoid such hazardous events as ‘‘radiation storms’’are likely to be among the more realistic time-consuming intrusions characterizinglong duration space expeditionary missions. As integrated into the scenarios of thecurrently ongoing simulated task environment studies, detection of such a hazardrequired the crew to initiate emergency procedures that involved discontinuation ofcurrent work and institution of a standard protocol to shut down sensitive equip-ment (sensors, antennae, etc.). The crew was required to remain in this mode until itwas safe to resume work. After the emergency, the crew was required to execute asecond drill to restart equipment in order to resume their interrupted tasks. Theduration and frequency of these simulated radiation storms determined the degree oftime pressure on the on-going performance tasks. Under normal (‘‘baseline’’) con-ditions, three radiation storms were scheduled to occur within each flight. Eachstorm sequence consisted of a 30-s warning period (to allow for proper shutdown ofequipment), and an 80-s storm, following which all equipment could be re-deployed.If any equipment remained on during a radiation storm, ‘‘damage’’ points wereaccrued by the crewmember at the rate 5/s until the equipment was turned off, or thestorm ended, whichever came first. To increase time pressure stress, additionalradiation storms were programmed. For example, when nine storms were insertedinto the approximately one hour duration flights, they effectively reduced the avail-able time by some 10–11 min compared with baseline, amounting to approximatelya 17% reduction in available on-task time.

3. Results

The results to be described in this report focus primarily upon the contribution ofthe different modes of communication to performance in the context of the simu-lated scenarios and the effects of incentive conditions and stressful interventionsupon both performance effectiveness and psychosocial adaptation. The data to bepresented is based upon the performances of three of the eleven groups participatingin the research as described in Section 2.1 above, Participant Volunteers. The threegroups, composed of three crewmembers each (both male and female), participatedin a total of 25 simulated ‘‘planetary missions’’ (75 experimental flights) based upona simulation scenario task that required the identification, collection, and analysis ofgeologic specimens with a range of graded values that were designated by fivedifferent rules in each of the regions explored.Fig. 11 summarizes graphically a typical Baseline Performance for Crew AG

following a combination of eight training and baseline missions (24 flights). These


326

Fig. 11. Baseline utilization of communication modalities by group (upper section) and individual crewmember performances (lower section).

J.V.Bradyetal./Computers

inHumanBehavior20(2004)311–340

results illustrate the characteristic stability of group baseline utilization ofcommunication modalities (upper section) and individual crewmember perfor-mances as well as total crew grade values (lower section) both within and across allthree Flights of the simulated Mission. In addition, these results confirmedthe maintenance of cooperative and productive performance interactions betweenindividually isolated and dispersed members of simulated spaceflight crews commu-nicating and problem solving effectively over extended time intervals without benefitof one another’s physical presence.

3.1. Experimental analysis of communication modalities

Fig. 12 shows the effects on communication modality utilization and geologicspecimen Grade Value performance of eliminating text messaging during the secondFlight of the Mission (striped bars) but with all modes of communication availableduring the 1st and 3rd flights. The data have been ‘‘normalized’’ with the average

Fig. 12. Effects of text messaging constraints on communication modality utilization and crew total grade

value performance.


value at the beginning of the Mission (Flight 1) taken as the 100% value (100 on thegraphs) and the subsequent values plotted relative to the first value. Although thepercentage of Audio Messages can be seen to have increased slightly (20%) duringthe 2nd flight, there was virtually no effect of text messaging removal upon crewGrade Value performance. Fig. 13 by contrast, shows the marked increase in thepercentage of text messages (150%) observed during the 3rd flight of the Mission(striped bar) with audio messaging eliminated and all modes of communicationavailable during the 1st and 2nd flights. Again, however, there was virtually no effectof audio messaging removal upon crew Grade Value performance. The resultsillustrated in Figs. 12 and 13 can thus be seen to provide strong support for thefunctional interchangeability of at least these two modes of communication underthe distributed interactive simulation conditions described.Fig. 14 shows the marked reduction in crew Grade Value (approximating 65%)

observed following the simultaneous combined elimination of both audio and textmessaging during the 2nd Flight (striped bars) of the Mission with all communication

Fig. 13. Effects of audio messaging constraints on communication modality utilization and crew total

grade value performance.


modalities available during the 1st and 3rd flights (solid black bars). Fig. 14 alsoshows that there was more than a three-fold increase in whiteboard messagingduring the 2nd flight (striped bars) with both audio and text messaging eliminated.The increased utilization of this alternative communication modality however, failedto compensate for the marked reduction in performance effectiveness reflected in thebetter than three-fold decrease in crew Grade Values observed under the indicatedcommunication mode constraints.

3.2. Experimental analysis of incentive conditions

Fig. 15 shows the effect of introducing the Positive Incentive condition during the2nd flight (striped bar) of a three-flight baseline Mission with 3 ‘‘radiation storm’’emergency drills programmed during each of the three flights. The Positive Incentiveproduced but a small increase (10%) in performance effectiveness by comparison ofthe 2nd flight Grade Values with those observed during the preceding 1st Flight

Fig. 14. Effects of combined audio and text messaging constraints on communication modality utilization

and crew total grade value performance.


without the Positive Incentive condition. The consistency of this small effecthowever, was called into question by the evident further increase in crew GradeValues during the subsequent 3rd flight after the Positive Incentive condition hadbeen removed. In addition, there was no consistent change in communicationpatterns accompanying these effects.

3.3. Experimental analysis of incentive interactions with stressful conditions

Fig. 16 compares the effects of nine ‘‘radiation storm’’ emergency drills on crewGrade Values during the middle flight (light striped bars) of two 3-Flight Missions inthe absence of Positive Incentive conditions (upper section) with the effects of nine‘‘storms’’ on crew Grade Values during the middle flight (heavy striped bars) of two3-Flight Missions under Positive Incentive Conditions (lower section). Comparingthe 1st and 3rd Flights of the two Non-incentive Missions (upper section of Fig. 16)with only three ‘‘radiation storm’’ emergency drills programmed in each Flight,there was a 10–20% decrease in the crew Grade Values produced by introduction ofthe stressful time pressure condition during the 2nd flight of each mission. Bycontrast, the bottom two panels of Fig. 16 illustrate the effects on total crew GradeValues of an added Positive Incentive during the two middle flights with the nineprogrammed ‘‘radiation storm’’ emergency drills. By comparison with the 1st and3rd flights of these two Missions in the absence of Incentive conditions and onlythree ‘‘storms’’, the decline in crew Grade Values observed with nine ‘‘storms’’without Positive Incentive shown in the upper two panels of Fig. 16 was attenuated.In these latter two Missions (lower section of Fig. 16) with both the nine ‘‘radiationstorm’’ emergency drills and the Positive Incentive condition in the middle flights(heavy-striped bars), there was no consistent decline in total crew Grade Value ofgeologic specimens compared with the first and third flights of the Missions.

Fig. 15. Effects of Positive Incentive conditions on baseline crew total grade value performance.


Fig. 17 summarizes the differential effects of the stressful ‘‘radiation storms’’intervention in the presence and absence of Positive Incentive conditions. The datafrom the two Non-incentive Flights under stressful conditions (upper section,Fig. 16) were combined (upper bar graph, Fig. 17) and the data from the twoPositive Incentive flights under stressful conditions (lower section, Fig. 16) werecombined (lower bar graph, Fig. 17). The data shown in Fig. 17 was also ‘‘normal-ized’’ with the average value at the beginning of the Mission (i.e., the first ‘‘A’’ flight)taken as the 100% value (100 on the graphs) and the subsequent values (i.e., Flight‘‘B’’ and the third ‘‘A’’ Flight) plotted relative to the first value. Compared to theeffect of the nine ‘‘radiation storm’’ stressful condition without Positive Incentiveproducing better than a 30% decrease in Total Crew Grade Value (striped bar,

Fig. 16. Effects of stressful time pressure on crew total grade value performance during two missions in

the absence of incentive conditions (upper two bar graphs) and during two missions with positive

incentives (lower two bar graphs).


upper graph, Fig. 17), there was an attenuation of the nine-storm stressful conditioneffect decreasing Grade Values (approximately 10%) with the Positive Incentiveduring the ‘‘B’’ flight (striped bar, lower graph, Fig. 17).Fig. 18 compares the interacting effects of Incentive and Stressful Conditions

upon the utilization of communication modalities during a three-flight Missionunder combined Stressful and ‘‘Positive’’ Incentive conditions (left column of bargraphs) and a three-Flight Mission under combined Stressful and ‘‘Negative’’Incentive Conditions (right column of bar graphs). When Stressful Conditions werepaired with Positive Incentives during the second flight of the three-Flight Mission(striped bars, left column of graphs), there were minimal changes in the utilization of

Fig. 17. Normalized data representation of differential stressful time pressure effects upon crew total

grade value performance under Positive Incentive conditions (lower bar graph) and in the absence of

incentive conditions (upper bar graph).


Fig. 18. The interacting effects of incentives and time pressure stress on communication modality

utilization under Positive Incentive conditions (left column of bar graphs) and under Negative Incentive

conditions (right column of bar graphs).


audio, text, or white board ‘‘Scribbles’’ communication modalities. In contrast,there was a consistent decline in the utilization of all three communication modeswhen Stressful Conditions were paired with Negative Incentives during the secondflight of the three-flight Mission (striped bars, right column of graphs).Fig. 19 compares the interacting effects of Incentive and Stressful Conditions

upon individual and crew Performance during a three-flight Mission under com-bined Stressful and ‘‘Positive’’ Incentive Conditions (left column of bar graphs) anda three-flight Mission under combined Stressful and ‘‘Negative’’ Incentive Condi-tions (right column of bar graphs). When Stressful Conditions were paired withPositive Incentives during the second flight of the 3-flight Mission (striped bars, leftcolumn of graphs), there was a small (approximately 10%) but consistent decreasein the Rover Collection rate (top left graph), the Orbiter Analysis rate (middle leftgraph), and the Crew Total Grade Value (bottom left graph) compared with thebaseline values (100) of the first ‘‘Control’’ flight. When Stressful Conditions werepaired with Negative Incentives during the second flight of the three-flight Mission(striped bars, right column of graphs), however, the decreases in Rover CollectionRate (top graph, right column), Orbiter Analysis Rate (middle graph, right column),and Crew Total Grade Value (bottom graph, right column) were approximately20% below the ‘‘100’’ baseline values of the first ‘‘Control’’ Flight. This decrease inperformance levels under Stressful Conditions with Negative Incentives was twice asgreat as the decrease in performance under Stressful Conditions with PositiveIncentives.Fig. 20 summarizes the results obtained with the self-report Visual Analogue Scale

(VAS) under ‘‘baseline’’ performance conditions (i.e., all communication modalitiesavailable, standard simulation task scenario) with No Incentives (white bars),Negative Incentives (shaded bars), and Positive Incentives (black bars). The‘‘normalized’’ data is based upon averages across multiple conditions and across allcrewmembers with the value at the beginning of the Mission (FL #1) taken as 100%(1.0 on the graphs) and the subsequent values plotted relative to the first value. Forall of the graphs, the Incentive Condition manipulation (i.e., Positive, Negative, orNo Incentive) was programmed to occur during FL #2 (the ‘‘B’’ flight in the ‘‘ABA’’flight sequence). The top two graphs show that the ‘‘Fatigued’’ and ‘‘Sleepy’’ ratingsincrease systematically during FL #2 and FL #3 of the Mission with ‘‘No Incentive’’(white bars) and somewhat less systematically during ‘‘Negative Incentive’’ condi-tions (gray bars). By contrast, no increase in the ‘‘Fatigue’’ and ‘‘Sleepy’’ ratings wasobserved during FL #2 and FL #3 of the Mission with the ‘‘Positive Incentive’’condition (black bars).The middle two graphs of Fig. 20 show that ‘‘Stressed’’ and ‘‘Anxious’’

ratings increase progressively across FL #2 and FL #3 of the Mission with NoIncentives (white bars) but that both ‘‘Positive’’ (black bars) and ‘‘Negative’’(gray bars) Incentives attenuate that increase to at least some extent. And thebottom two graphs show that the systematic decrease across FL #2 and FL #3in ‘‘Stimulated’’ and ‘‘Happy’’ ratings with No Incentive (white bars) is virtuallyeliminated under both ‘‘Negative’’ (gray bars) and ‘‘Positive’’ (black bars) IncentiveConditions.


Fig. 19. The interacting effects of incentives and time pressure stress on individual crewmember and crew

total grade value performances under Positive Incentive conditions (left column of bar graphs) and under

Negative Incentive conditions (right column of bar graphs).


Fig. 20. The effect of Incentive conditions on Visual Analogue Scale self-report ratings.


4. Discussion

The results of this research and development show clearly that cooperative andproductive interactions can be maintained between individually isolated anddistributed members of simulated spaceflight crews communicating and problem-solving effectively in a computer-generated ‘‘planetary’’ environment over extendedtime intervals without benefit of one another’s physical presence. In addition, thesestudies have provided the basis for a preliminary experimental analysis of communi-cation channel constraints and interactions between stressful and incentive conditionsas well as their effects upon performance effectiveness and psychosocial adaptation.From a methodological perspective, the results of the developmental program andinitial experimental findings provide further support for the effective research appli-cation of technological software designed for distributed interactive simulation oper-ations that involve units from multiple sites participating from geographicallyseparate locations. Among the range of computer-based simulation techniques avail-able for such investigative initiatives, the relatively simple networked work-stationsystem running under an interactive simulation environment has provendemonstrably effective in the current application utilizing a ‘‘tool kit’’ approach withhigh-performance but affordable PC components.The focus of the initial experimental studies on communication channel

constraints, performance effectiveness, and psychosocial adaptation provided for apreliminary analysis of the extent to which there was functional interchangeabilitybetween modes within the range of available communication modalities. The highestdegree of functional interchangeability observed under the synthetic task perfor-mance conditions of the present computer-generated planetary environment wasbetween Audio and Text modes of communication. Not only was there a compen-satory reciprocal increase in the utilization of each modality when the other wasunavailable (i.e., ‘‘equipment failure’’) but there was no change in performanceeffectiveness (i.e., ‘‘Crew Total Grade Values’’) following removal of either audio ortext communication modes alone. The simultaneous removal of both audio andtext modalities in contrast, did produce a change in performance effectivenesscharacterized by a four-fold decrease in Total Crew Grade Values. There was also amarked increase in white board utilization when both audio and text modalitieswere unavailable, suggesting a degree of functional interchangeability involving thismode of communication as well. But the extent of the interchangeability betweenwhite board scribbles and the combined audio and text modalities was clearlyinsufficient to compensate for the resulting performance decrements.The results of these experimental communication modality manipulations are also

generally consistent with the findings reported by Baker (2002) in an extensiveanalysis of decision making performances with 64 ‘‘virtual teams’’ using differentcollaborative communication technologies. As in the present distributed interactivesimulation study, there were no significant differences between the performances ofgroups using text-only communication and the performances of groups using audio-only communication. Although the Baker report described a significant improve-ment in performance (i.e., strategic decision making) following the addition of video


to the audio-only communication condition, this differential effect could not bereplicated systematically in the present study since active video images were availableto the crew members at all times via the network web cameras at each work station.The results obtained with the preliminary exploration of Incentives under the

simulation scenarios studied indicate that the effectiveness of such interventions arelikely to be determined by the conditions under which they are made available. Underbaseline in the absence of stressful conditions (Fig. 15) for example, the introductionof Positive Incentives during the 2nd Flight in the Mission was accompanied by anapproximately 10% increase in Crew Total Grade Values compared with the 1st flightin the Mission. But the continued increase in Crew Total Grade Values during the 3rdflight without an Incentive suggests either that the observed small effect lacked con-sistency (i.e., was unreliable) or that there was a persistence of its motivationaleffects even after the Incentive conditions were no longer in effect.When Positive Incentive conditions were introduced in conjunction with the

stressful time pressure of nine ‘‘radiation storm’’ emergency drills during the 2ndflight of a three-flight Mission however, the effects on crew performance were morereliable. Compared to Crew Total Grade Values under stressful time pressureconditions in the absence of Positive Incentives (upper sections, Figs. 16 & 17), therewas a consistent attenuation of the decrement in performance when Positive Incen-tive conditions were in effect during the 2nd flight with nine emergency drills (lowersections, Figs. 16 & 17). This general preservation of performance by the introduc-tion of the Positive Incentive ‘‘countermeasure’’ in the presence of the stressful timepressure condition is of particular interest considering that this number of nine‘‘radiation storm’’ emergency drills reduces the time available to collect and analyzegeologic specimens by 17%. These findings suggest that the application of PositiveIncentive countermeasures may be most effective under conditions like thoserepresented in this simulated ‘‘planetary’’ environment that require enhancedperformance levels (e.g., working more quickly) to offset the loss in time available tomeet synthetic task requirements.The preliminary studies on communication modality utilization and performance

effectiveness with varying incentives under stressful conditions (Figs. 18 & 19) indi-cate that these measures may reflect the differential effects of Positive and NegativeIncentives. Compared to Missions with nine storms and Positive Incentives combined,there was a consistent reduction in the utilization of all three communication modalities(i.e., audio, text, and white board messaging) when the stressful time pressureconditions were combined with Negative Incentives. Similarly, the measures of bothindividual crewmember and group performance effectiveness (i.e., Rover SpecimenCollection, Orbiter Specimen Analysis, and Crew Total Grade Value) under stressfultime pressure conditions with Negative Incentives were consistently lower than thesesame performance measures under stressful conditions with Positive Incentives.The self-report VAS results (Fig. 20) generally confirm the incentive effects

obtained under both baseline and stressful time pressure conditions. The differentialeffects of Positive and Negative Incentives are reflected most clearly in the ‘‘Fatigue’’ratings that under Positive Incentive conditions showed a marked attenuation of theprogressive increase observed over the three-flight Mission both in the absence of


incentives and under Negative Incentive conditions. And the consistent effect ofincentive conditions, both Positive and Negative, in attenuating the progressivechanges in ‘‘Anxious’’, ‘‘Stimulated’’, and ‘‘Happy’’ ratings observed over the three-flight Mission in the absence of incentives is clearly evident. These findings indicatethat such self-report measures may provide a useful and reliable reflection ofpsychosocial adaptation under conditions of distributed interactive communicationbetween distributed elements of operational groups.The present report represents an initial step in a behavioral engineering approach

built upon an empirical technology of behavioral management and programmingemerging from laboratory science-based analysis (Bernstein & Brady, 1986; Brady,1990, 1992; Emurian, Brady, Meyerhoff, & Mougey, 1981; Emurian, Brady, Ray,Meyerhoff, & Mougey, 1984; Guerin, 1994). In this approach, experimentally-derived principles provide for the construction of laboratory models with applic-ations involving research analysis under human operational conditions incontinuously programmed environments. The research methodology brings withinthe laboratory a broad range of complex and naturalistic units of behavior forexperimental analysis, permits programming, monitoring, objective recording, andquantitative measurement of behavioral interactions, and provides for controlledstudy (e.g., experimental manipulation) of conditions and processes of far greaterduration than the typical short-term behavioral experiment.

Acknowledgements

This research was supported by NASA cooperative agreement NCC 9-58 with theNational Space Biomedical Research Institute.

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