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PROCEEDINGS of the HUMAN FACTORS AND ERGONOMICS SOCIETY 47th ANNUAL MEETING—2003

CONSIDERING THE IMPORTANCE OF INDIVIDUAL DIFFERENCES IN HUMAN FACTORS RESEARCH: NO LONGER SIMPLY CONFOUNDING NOISE

Panel Chair and Discussant Waldemar Karwowski Professor and Director Center for Industrial Ergonomics University of Louisville Louisville, KY

Panel Organizer and Co-Chair Haydee M. Cuevas Research Assistant Team Performance Lab - Department of Psychology University of Central Florida Orlando, FL Panelists

Jeanne L. Weaver Assistant Professor, Department of Psychology MURI-OPUS Laboratory Research Director University of Central Florida Orlando, FL Gerald Matthews Professor, Department of Psychology University of Cincinnati Cincinnati, OH

Larry Hettinger Senior Human Factors Engineer Northrop Grumman Information Technology Harvard, MA David A. Washburn Associate Professor, Department of Psychology Director, Language Research Center Georgia State University Atlanta, GA

Krystyna Gielo-Perczak Biomechanics Scientist Liberty Mutual Research Institute for Safety Hopkinton, MA

Peter A. Hancock Provost Distinguished Research Professor Department of Psychology Director, MURI-OPUS Laboratory University of Central Florida Orlando, FL

INTRODUCTION

As such, the panelists’ remarks cover a broad range of topics. The discussion begins with a general argument of why recognizing individual differences in human capabilities and limitations is necessary. Then, the discussion turns to demonstrating the key role of personality factors in human-machine interaction. From the industry perspective, we are presented with a proposed model with which to reduce musculoskeletal injuries followed by suggestions on how to cope with individual differences in system test and evaluation. The next area addressed is how vigilance decrement differs as a function of the operator’s innate attention skills, a critical issue in light of the current emphasis on airport security. And, finally the last panelist draws attention to the need for ‘adaptive’ systems, where the focus is not merely on human-centered, but rather on person-speczjk design. The goal of this panel session will be to attempt to bridge the diverse remarks made by the panelists and identify a common overarching theme for investigating individual differences in human factors research.

Too often, individual differences are treated as a nuisance variable, and are either controlled in the study or covaried out in the statistical analyses of the results. Yet, to truly generate sound and useful human factors guidelines to facilitate the interaction between humans and systems, we need to fully understand how individual differences in aptitudes interact with the varying circumstances found in today’s complex technological environments. As the title of this session indicates, this panel is organized specifically to highlight the importance of individual differences in human factors research. To address this issue, this panel draws upon the knowledge and experience of a representative sample of professionals from both industry and academia that have investigated the role of individual differences across a variety of domains.


PANELIST’S ABSTRACTS Jeanne L. Weaver University of Central Florida Why Are Individual Diferences Important? Within the Human Factors and Ergonomics Society, one of the smaller technical groups (TG) with regard to business meeting attendance and proposal submission is the Individual Differences In Performance (IDIP) technical group. For those of us who do consistently devote time and interest to this technical group, the importance of the TG is obvious and yet we constantly struggle with ways to attract the attention of others in order to convince them as well. This is an interesting state of affairs given that the second “more or less established doctrine that characterizes the human factors profession” listed in Sanders and McCormick’s (1993) Human Factors in Engineering and Design, is “recognition of individual differences in human capabilities and limitations and an appreciation for their design implications . . .’, (p. 5). It appears that this doctrine is far from “established.” If one examines the human factors research published in the top journals of our profession, these variables are rarely considered as more than nuisance variables. One notable exception is age. However, consideration of age has only received the attention of researchers in the relatively recent past and many would likely still take the position that greater awareness of issues related to aging is still needed. So, why examine “individual differences?, It has been argued that individual differences contribute a significant amount of variance to many human factors related situations (cf. Bowers, Weaver, & Morgan, 1996) and yet relatively few human factors studies make an attempt to systematically investigate these variables. This begs the question: why do most researchers either ignore or minimize the role that individual differences contribute? The answer might relate in part to the difficulty in determining what most people believe represents an “individual difference” variable? This has been a continuing topic for consideration within the IDIP technical group. Obviously every possible variable cannot be studied in every situation, thus effort should be devoted to the determination of the most relevant variables within a particular context. Finally, human factors practitioners and researchers might be less willing or feel less capable to incorporate the study of individual differences variables into their work because human factors emphasizes performance. Perhaps we have over-emphasized performance as the dependent variable of interest at the expense of acquiring

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some general principles about the way that categories of individuals work most effectively relative to other groups under the same circumstances. In summary, this panel has been assembled to discuss issues with regard to what individual differences variables are most amenable to investigation within human factors, how this might vary across contexts, and how human factors professionals might be assisted in obtaining the confidence and/or skills necessary in order to facilitate the study of these variables. Gerald Matthews University of Cincinnati Individual Differences in Performance: A Transactional Perspective Empirical research continues to substantiate the key role of personality factors as predictors of psychophysiological response, information-processing and stress in operational environments. However, the influence of personality on multiple levels of interaction between human and machine is not always appreciated. Matthews (200 1) proposes that the person-machine transaction operates at both biocognitive and cognitiveadaptive levels. The biocognitive transaction refers to the effects of the task environment on parameters of the neural and cognitive architectures, such as resource availability, speed of processing and memory capacities. These processes, in turn, influence the functional capabilities of the operator to influence that environment. For example, research maps the biasing influence of fundamental traits such as extraversion and anxiety across a range of performance indicators. The cognitive-adaptive level refers to the operator’s intentions, situation evaluation and strategies for coping with task demands. Personality traits bias not just basic processing components, but also schemas for personal competence in the task environment, metacognitions and coping preferences. Individual differences in selfknowledge and task strategy are central to contextualized personality traits, referring to stable self-beliefs within a particular (task) environment. Effects of traits linked to vehicle driving on stress responses, performance and safety are mediated by individual differences in appraisal and coping in the traffic environment (Matthews, 2002). The experience of the anxious driver is dominated by themes of danger and personal inadequacy, whereas aggressive drivers inhabit a hostile, confrontational driving world. Biocognitive and cognitive-adaptive biases work together to influence the affordances of the environment for the individual. For example, stress-vulnerable

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individuals such as those high in general or driving anxiety are adapted for avoiding environmental threat, whereas hardy individuals are better prepared to meet threats directly. At a practical level, personality research has two messages for designers. The first is that indices of functional status differ in their validity depending on personality characteristics. Thus, neuroergonomic indices of readiness to perform may need to be appropriately tuned to the individual. For example, high levels of EEG alpha signify alertness in extraverts but impaired functional status in introverts (see Matthews et al., 2000). Thus, predictive validity for diagnostic indicators of status should be established across a range of personality characteristics. Likewise, high levels of distress and worry appear to be more detrimental to anxiety-prone drivers than to those of a calmer disposition, implying that the predictive validity of stress markers is likely to vary with personality (Matthews, 2002). The second message is that the personal significance of the task environment has profound implications for performance and wellbeing, so that successful design requires an understanding of the meanings that the operator will 'read into' the system. Anxiety-prone individuals are especially sensitive to appraisals of negative feedback, and may be liable to attribute difficulties in system operation to personal incompetence rather than system shortcomings. Thus, in these persons, poor design may generate not just primary difficulties in usability, but also worries and negative self-referent thoughts that have the potential to interfere with performance. Conversely, vehicle driving research demonstrates that low-anxiety drivers are vulnerable to over-confidence, and systems that add to this sense of personal invulnerability may have unforeseen and dangerous consequences (Matthews & Desmond, 200 1). Krystyna Gielo-Perczak and Tom Leamon Liberty Mutual Research Institute for Safety An Investigation of the Individual Differences in Geometry of the Glenohumeral Joint on the Maximum Acceptable Workload A model of the glenohumeral joint (shoulder) has been proposed and investigated for its applicability to ergonomic studies. It addressed the important question of what geometric features and relations should be applied for underlayment of individual strength at the glenohumeral joint. The purpose of the study was threefold: 1) theoretically explain the influence of the geometric parameters of the glenohumeral joint on individual strength during abductiodadduction; 2)

propose a method of geometrical description of the glenoid fossa and head of the humerus; and, 3) provide strength tests with the subjects for whom MRI measurements of glenohumeral joint geometries had been collected. Frontal MRI images of the glenohumeral joint of the right arm were obtained from 12 healthy men. The participants' mean age [and standard deviation] was 40.5 f 8 years, with an average height of 178 f 7.09 cm and body weight of 81.54 f 15.60 kg. The geometric data of the glenoid concavity, the deltoid muscle attachment and the radius of the humeral head of the group were collected. A method of geometrical description of a joint and the term Maximum Acceptable Workload (MAW) were proposed. The MAW of each element of a glenohumeral joint can be calculated individually as a function of the external load, and the geometry of the articulating surfaces, the muscles and the ligaments. The calculations have been performed for the different joints and loading, and the results reveal that the individual differences in geometry have the greatest influence on the Maximum Acceptable Workload. Strength tests were performed with the 12 subjects as a complimentary study to the MRI study of subject glenohumeral geometry. The strength measurements confirmed the theoretical findings that the subjects with the deeper glenoid fossa were stronger than those with a flatter shape. The attachment of the lateral part of the deltoid muscle was also a factor. For the strongest subject, the distance of the muscle attachment to the glenoid fossa was the longest in the group (18 mm) and for the weakest subjects the distances were the shortest (3.8 and 5.6 mm). There was a strong correlation among all distinguished geometric parameters. The study explains theoretically the influence of glenoid concavity and deltoid muscle attachment on the stability of a joint. The geometrical description of the glenohumeral joint will help to anticipate musculoskeletal disorders before the injuries can occur. These theoretical mechanical variations can provide a better biomechanical basis for joint modeling and lead to consideration of articular geometry during workplace design. With this glenohumeral model, it is possible to reduce musculoskeletal injuries by assessing individual acceptable loads during different work activities. This method can be useful for minimizing incompatibilities between the individual worker's physical capabilities and job demands towards preventing work-related shoulder injuries.


Larry Hettinger Northrop Grumman Information Technology Coping with Individual Differences in System Test and Evaluation Most major Department of Defense procurements are now required to demonstrate an adequate approach to “human-systems integration” (HSI). While this represents a positive development for the integration of human factors and ergonomics into major design efforts, the dominant systems engineering culture often still regards HSI as an empirically suspect domain. This is particularly true for test and evaluation - an area of vital concern to HSI practitioners. Systems engineers are accustomed to analyzing components whose performance shows little variability. For example, an aircraft’s landing gear deploys at essentially the same speed every time, regardless of weather conditions, time of day, etc. The fact that humans often show significant intra- and inter-operator variability in performance not only creates difficulties in the interpretation of test data, but in the very willingness of the system engineering culture to acknowledge its validity. My talk will focus on this problem area, as well as possible solutions. David A. Washburn Georgia State University Individual Differences and Group Differences: Asking the Right Questions The balance between producing generalized principles of behavior on the one hand and the appreciating individual differences on the other is vital to psychology and human engineering. The caricature of our disciplines is that the answer to every interesting question-“How does memory work?, “Can people perform multiple tasks concurrently?” “What is the effect of caffeine on performance?” and countless others-is “It depends” or something equally tentative. Although such hedging compromises our ability to sell behavioral science as valuable to the lay community, to industry, and so forth, “It depends” is often a fully accurate characterization of individual differences in performance. Consider for example the pregnant question, “How does the threat-detection performance of airport security screeners change as a function of time-on-task?, or the more applied version, “What is the ideal shift-length for security screeners?” To answer these questions, one might look to the substantial vigilance literature for general findings on target detection across watchperiods. The standard and general answer would include

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details about the vigilance decrement in which performance declines predictably with time-on-task, and could link this behavioral outcome richly to cognitive constructs (e.g., sustained attention, boredom), physiological states (e.g., arousal), and cortical functions (e.g., the “alert” network). However, the actual shape of the vigilance decrement may vary markedly across participants, reflecting the “noise around the mean” mentioned in the title of this panel discussion. As illustrated with laboratory data, some participants show stable performance across time, and others actually improve in the speed of target detection across a 40-minute vigil. (Of course, the shape and nature of this vigilance decrement would depend on numerous parametric variables that are both reasonable and beyond the scope of this talk.) The point is that one is faced with a choice between answering the target question with the group average, which may not be characteristic of any particular individual, or with the individual differences, which may not yield a general principle. But there is middle ground, and many researchers have examined the utility of performance-based groupings of participants that may illuminate the subtleties of the relation between variables. For example, when individuals are profiled according to the attention skills that they bring to performance and grouped according to these profiles, one can see reliable differences between relatively homogeneous subgroups that reflect both the variables of interest (e.g., time-ontask, detection accuracy) and the individual differences observed in performance. This will be illustrated with data from threat detection in x-ray images across time. This strategy is not new, but it bears emphasis. The problem is not with our answers. The problem is the questions. “How does threat detection change across time?” is the wrong question to ask. We must do a better job of instructing those in industry, security, education, and (yes) academia to ask questions in the way that reflects both individual and group differences. Peter A. Hancock University of Central Florida Individuation: Not Merely Human-Centered but Person-Specific Design In the nineteenth century, it was possible at the beginning of the industrial revolution to consider the individual as a part or a component. Essentially without life and character, the ‘elan vital’ was extracted from the worker and thus the product also could be ‘mass produced’ in order to be produced for the ‘mass.’ It has taken many decades for humanity to recover what it

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possessed in the eighteenth century but lost in the nineteenth - individuality. The twentieth century saw this renaissance initially expressed in shadows such as ‘percentiles’ in which we sought to capture first the physical ‘measure of man’ only to be followed by its cognate companion. In the last few decades, we have advocated for ‘adaptive’ systems, based on generalized profiles of activity, but systems in which individual concerns have been raised to a higher level. I claim this is part of an evolution in which the single individual will be reified in design. The leitmotif might well be ‘one size fits none.’ Not merely simple adjustments or variations on limited themes, we shall see a true, life-span concern for the particular person. Since I hope to buy a new set of golf clubs soon, I hope this ethos is enacted in the very near future. ACKNOWLEDGEMENTS The views herein are those of the authors and do not necessarily reflect those of the organizations with which the authors are affiliated. Address correspondence to Haydee M. Cuevas, Team Performance Lab, 12424 Research Parkway, Room 408, Orlando, FL 32826 or via email at ha65 1622@ ucf.edu.

REFERENCES Bowers, C. A., Weaver, J. L., & Morgan, B. B. (1996). Moderating the performance effects of stressors. In J. E. Driskell & E. Salas (Eds.), Stress and human performance (pp. 163-192). Mahwah, NJ: LEA. Matthews, G. (2001). Levels of transaction: A cognitive science framework for operator stress. In P.A. Hancock & P.A. Desmond (Eds.), Stress, workload and fatigue (pp. 5-33). Mahwah, N.J.: Lawrence Erlbaum. Matthews, G. (2002). Towards a transactional ergonomics for driver stress and fatigue. Theoretical Issues in Ergonomics Science, 3, 19521 1. Matthews, G., Davies, D.R., Westerman, S.J., & Stammers, R.B. (2000). Human performance: Cognition, stress and individual dflerences. London: Psychology Press. Matthews, G., & Desmond, P.A. (2001). Stress and driving performance: Implications for design and training. In P.A. Hancock & P.A. Desmond (Eds.), Stress, workload and fatigue (pp. 2 1 1-231). Mahwah, N.J.: Lawrence Erlbaum. Sanders, M. S. & McCormick, E. J. (1993). Human factors in engineering and design (7’ Ed.). New York, NY: McGraw-Hill.