Wishful Thinking? Inside the Black Box of Exposure Assessment

Background: Decision-making processes used by experts when undertaking occupational exposure assessment are relatively unknown, but it is often assumed that there is a common underlying method that experts employ. However, differences in training and experience of assessors make it unlikely that one general method for expert assessment would exist. Therefore, there are concerns about formalizing, validating, and comparing expert estimates within and between studies that are difficult, if not impossible, to characterize. Heuristics on the other hand (the processes involved in decision making) have been extensively studied. Heuristics are deployed by everyone as short-cuts to make the often complex process of decision-making simpler, quicker, and less burdensome. Experts’ assessments are often subject to various simplifying heuristics as a way to reach a decision in the absence of sufficient data. Therefore, investigating the underlying heuristics or decision-making processes involved may help to shed light on the ‘black box’ of exposure assessment. Methods: A mixed method study was conducted utilizing both a web-based exposure assessment exercise incorporating quantitative and semiqualitative elements of data collection, and qualitative semi-structured interviews with exposure assessors. Qualitative data were analyzed using thematic analysis. Results: Twenty-five experts completed the web-based exposure assessment exercise and 8 of these 25 were randomly selected to participate in the follow-up interview. Familiar key themes relating to the exposure assessment exercise emerged; ‘intensity’; ‘probability’; ‘agent’; ‘process’; and ‘duration’ of exposure. However, an important aspect of the detailed follow-up interviews revealed a lack of structure and order with which participants described their decision making. Participants mostly described some form of an iterative process, heavily relying on the anchoring and adjustment heuristic, which differed between experts. Conclusion: In spite of having undertaken comparable training (in occupational hygiene or exposure assessment), experts use different methods to assess exposure. Decision making appears to be an iterative process with heavy reliance on the key heuristic of anchoring and adjustment. Using multiple experts to assess exposure while providing some form of anchoring scenario to build from, and additional training in understanding the impact of simple heuristics on the process of decision making, is likely to produce a more methodical approach to assessment; thereby improving consistency and transparency in expert exposure assessment.

[1]  Sue Ziebland,et al.  Analysing qualitative data , 2000, BMJ : British Medical Journal.

[2]  C MacLeod,et al.  Memory accessibility and probability judgments: an experimental evaluation of the availability heuristic. , 1992, Journal of personality and social psychology.

[3]  Richard E. Boyatzis,et al.  Transforming Qualitative Information: Thematic Analysis and Code Development , 1998 .

[4]  Annemarie Money,et al.  Agreement of experts and non-experts in a desktop exercise evaluating exposure to asthmagens in the cotton and textile, and other industries. , 2015, The Annals of occupational hygiene.

[5]  A. Lieblich,et al.  Narrative Research: Reading, Analysis, and Interpretation , 1998 .

[6]  W. Edwards Behavioral decision theory. , 1961, Annual review of psychology.

[7]  J. Klayman Varieties of Confirmation Bias , 1995 .

[8]  Maria Jirwe,et al.  Analysing qualitative data. , 2011, Nurse researcher.

[9]  B. Fischhoff,et al.  Reasons for confidence. , 1980 .

[10]  E. Brunswik,et al.  The Conceptual Framework of Psychology , 1954 .

[11]  A. Povey,et al.  Personal exposure to inhalable dust and the specific latex aero-allergen, Hev b6.02, in latex glove manufacturing in Thailand. , 2014, The Annals of occupational hygiene.

[12]  Kai Yu,et al.  Inside the black box: starting to uncover the underlying decision rules used in a one-by-one expert assessment of occupational exposure in case-control studies , 2012, Occupational and Environmental Medicine.

[13]  G. Benke,et al.  Retrospective assessment of occupational exposure to chemicals in community-based studies: validity and repeatability of industrial hygiene panel ratings. , 1997, International journal of epidemiology.

[14]  Clifford R. Mynatt,et al.  Confirmation Bias in a Simulated Research Environment: An Experimental Study of Scientific Inference , 1977 .

[15]  Robert T. Clemen,et al.  Toward an Improved Methodology to Construct and Reconcile Decision Analytic Preference Judgments , 2013, Decis. Anal..

[16]  R. Hogarth,et al.  BEHAVIORAL DECISION THEORY: PROCESSES OF JUDGMENT AND CHOICE , 1981 .

[17]  Adrian P. Banks,et al.  Expert Decision Making in a Complex Engineering Environment , 2011 .

[18]  R. Nickerson Confirmation Bias: A Ubiquitous Phenomenon in Many Guises , 1998 .

[19]  Gurumurthy Ramachandran,et al.  Effect of Training on Exposure Judgment Accuracy of Industrial Hygienists , 2012, Journal of occupational and environmental hygiene.

[20]  N. Gale,et al.  Using the framework method for the analysis of qualitative data in multi-disciplinary health research , 2013, BMC Medical Research Methodology.

[21]  D. Fourney Commentary , 2011, Evidence-based spine-care journal.

[22]  Tony Fletcher,et al.  Assessing Exposure Misclassification by Expert Assessment in Multicenter Occupational Studies , 2003, Epidemiology.

[23]  Schneider,et al.  All Frames Are Not Created Equal: A Typology and Critical Analysis of Framing Effects. , 1998, Organizational behavior and human decision processes.

[24]  A. Tversky,et al.  Judgment under Uncertainty: Heuristics and Biases , 1974, Science.

[25]  Gurumurthy Ramachandran,et al.  Exposure Modeling in Occupational Hygiene Decision Making , 2009, Journal of occupational and environmental hygiene.

[26]  G. Northcraft,et al.  Experts, amateurs, and real estate: An anchoring-and-adjustment perspective on property pricing decisions , 1987 .

[27]  F. Agnoli Development of judgmental heuristics and logical reasoning: Training counteracts the representativeness heuristic , 1991 .

[28]  N. Epley,et al.  The Anchoring-and-Adjustment Heuristic , 2006, Psychological science.

[29]  M. Lorentzon Doing Qualitative Research , 1993 .

[30]  J. Spinelli,et al.  Statistical Modeling of Occupational Exposure to Polycyclic Aromatic Hydrocarbons Using OSHA Data , 2015, Journal of occupational and environmental hygiene.

[31]  Patricia A Stewart,et al.  Comparison of ordinal and nominal classification trees to predict ordinal expert-based occupational exposure estimates in a case-control study. , 2015, The Annals of occupational hygiene.

[32]  A. Olshan,et al.  Occupational exposure assessment in case–control studies: opportunities for improvement , 2002, Occupational and environmental medicine.

[33]  Lin Fritschi,et al.  Triaging jobs in a community-based case-control study to increase efficiency of the expert occupational assessment method. , 2012, The Annals of occupational hygiene.

[34]  K. Straif,et al.  Exposure to inhalable dust and its cyclohexane soluble fraction since the 1970s in the rubber manufacturing industry in the European Union , 2007, Occupational and Environmental Medicine.

[35]  G Gigerenzer,et al.  Reasoning the fast and frugal way: models of bounded rationality. , 1996, Psychological review.

[36]  T. Kauppinen Exposure assessment--a challenge for occupational epidemiology. , 1996, Scandinavian journal of work, environment & health.

[37]  I. Levin,et al.  A New Look at Framing Effects: Distribution of Effect Sizes, Individual Differences, and Independence of Types of Effects , 2002 .

[38]  Patricia A Stewart,et al.  Comparison of two expert-based assessments of diesel exhaust exposure in a case–control study: programmable decision rules versus expert review of individual jobs , 2012, Occupational and Environmental Medicine.

[39]  Igor Burstyn,et al.  The ghost of methods past: exposure assessment versus job–exposure matrix studies , 2010, Occupational and Environmental Medicine.

[40]  Gary Klein,et al.  Sources of Power: How People Make Decisions , 2017 .

[41]  A. Tversky,et al.  The weighing of evidence and the determinants of confidence , 1992, Cognitive Psychology.

[42]  R. Radner,et al.  Decision and Organization. A Volume in Honor of Jacob Marschak. Edited by C.B. Mc Guire and Roy Radner. Studies in Mathematical and Managerial Economics, volume 12. Amsterdam, London, North-Holland Publishing Company, 1972 X p. 361 p., fl. 63.00. , 1973, Recherches économiques de Louvain.

[43]  Wei Lu,et al.  Validity and reliability of exposure assessors' ratings of exposure intensity by type of occupational questionnaire and type of rater. , 2011, The Annals of occupational hygiene.

[44]  C. C. Johnson,et al.  Intra- and inter-rater agreement in the assessment of occupational exposure to metals. , 1998, International journal of epidemiology.

[45]  Daniel M. Oppenheimer,et al.  Heuristics made easy: an effort-reduction framework. , 2008, Psychological bulletin.

[46]  R A Riedmann,et al.  Sensitivity Analysis, Dominant Factors, and Robustness of the ECETOC TRA v3, Stoffenmanager 4.5, and ART 1.5 Occupational Exposure Models , 2015, Risk analysis : an official publication of the Society for Risk Analysis.

[47]  Melissa C. Friesen,et al.  OccIDEAS: Retrospective Occupational Exposure Assessment in Community-Based Studies Made Easier , 2009, Journal of environmental and public health.

[48]  Sudipto Banerjee,et al.  Desktop Study of Occupational Exposure Judgments: Do Education and Experience Influence Accuracy? , 2011, Journal of occupational and environmental hygiene.

[49]  D. M. Grether,et al.  Bayes Rule as a Descriptive Model: The Representativeness Heuristic , 1980 .

[50]  Gary Klein,et al.  Expert decision making , 1999 .

[51]  P. Gustafson,et al.  What do measures of agreement (κ) tell us about quality of exposure assessment? Theoretical analysis and numerical simulation , 2013, BMJ Open.