Laurel Austin is an Associate Professor in Management Science. She uses behavioural and decision science methods to study individual decision making under risk and uncertainty. She uses this knowledge to develop communications and other interventions to improve peoples’ decision making and risk management. She is currently studying the shift to digital decision aids and virtual medical care during the COVID-19 pandemic, funded by a Western University Catalyst grant. Funded by SSHRC, she is also examining youth and young adult vaping decisions, currently focused on how the pandemic has impacted vaping behaviours. She teaches courses on decision making and risk management in organizations at the HBA, MSc and MBA levels.
Prior to joining Ivey, Laurel was an Associate Professor of Strategic Decision Making and Risk Management at the Copenhagen Business School in Denmark. She has published research on medical decision making, insurance decisions and behaviour, occupational safety, computer supported group decision making, and adolescent risk decisions. She earned her PhD in Management and Decision Sciences at Carnegie Mellon University, and an MSE in Industrial and Operations Engineering at University of Michigan.
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Kfrerer, M.; Zheng, K. Z.; Austin, L. A., 2024, "From 0 to 50 in pandemic, and then back? A case study of virtual care in Ontario pre, during, and post-COVID-19.", Mayo Clinic Proceedings, March 2(1): 57 - 66.
Abstract: We review the evolution of virtual care (VC) in Ontario. Pre–COVID-19, the primary focus was on patients in remote and underserved areas who went to host sites for care. Ontario’s vision pre-pandemic was for a gradual increase in VC by physicians registered with the Ontario Telemedicine Network (OTN), using OTN-approved video technologies; some accommodated patients and doctors wherever they were. Less than 1% of care was virtual pre-pandemic. We discuss how policies that altered access to in-person care (pandemic lockdowns and guidelines to seek and provide care virtually), compensation policy changes (allowing any Ontario physician to be compensated for VC), and policies allowing common technologies not previously allowed (including, importantly, the telephone), drove and enabled a rapid shift to >50% of care being virtual at the start of the pandemic, leveling off to ∼30% over time. We review policy changes in late 2022 and predict these will result in a drop in VC compared with the policies during the pandemic, particularly for walk-in clinic patients, in a province where 2.2-4.6 million people do not have a primary care doctor and presumably use walk-in clinics. This is because, going forward, physicians will be compensated less for telephone care than for in-person or video care for rostered patients, and because compensation will be less still for telephone or video care provided to walk-in patients. Through this case study we develop a visual model of how these key policy and technology factors influence the provision of VC.
Link(s) to publication:
http://dx.doi.org/10.1016/j.mcpdig.2023.07.004
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Ziebart, C.; Kfrerer, M. L.; Stanley, M.; Austin, L. A., 2023, "A Digital-First Health Care Approach to Managing Pandemics: Scoping Review of Pandemic Self-triage Tools", J Med Internet Res, May 25: e40983 - e40983.
Abstract: Background: During the COVID-19 pandemic, many patient-facing digital self-triage tools were designed and deployed to alleviate the demand for pandemic virus triage in hospitals and physicians’ offices by providing a way for people to self-assess their health status and get advice on whether to seek care. These tools, provided via websites, apps, or patient portals, allow people to answer questions, for example, about symptoms and contact history, and receive guidance on appropriate care, which might be self-care. Objective: This scoping review aimed to explore the state of literature on digital self-triage tools that direct or advise care for adults during a pandemic and to explore what has been learned about the intended purpose, use, and quality of guidance; tool usability; impact on providers; and ability to forecast health outcomes or care demand. Methods: A literature search was conducted in July 2021 using MEDLINE, Embase, Scopus, PsycINFO, CINAHL, and Cochrane databases. A total of 1311 titles and abstracts were screened by 2 researchers using Covidence, and of these, 83 (6.76%) articles were reviewed via full-text screening. In total, 22 articles met the inclusion criteria; they allowed adults to self-assess for pandemic virus, and the adults were directed to care. Using Microsoft Excel, we extracted and charted the following data: authors, publication year and country, country the tool was used in, whether the tool was integrated into a health care system, number of users, research question and purpose, direction of care provided, and key findings. Results: All but 2 studies reported on tools developed since early 2020 during the COVID-19 pandemic. Studies reported on tools that were developed in 17 countries. The direction of care advice included directing to an emergency room, seeking urgent care, contacting or seeing a physician, being tested, or staying at home and self-isolating. Only 2 studies evaluated tool usability. No study demonstrated that the tools reduce demand on the health care system, although at least one study suggested that data can predict demand for care and that data allow monitoring public health. Conclusions: Although self-triage tools developed and used around the world have similarities in directing to care (emergency room, physician, and self-care), they differ in important ways. Some collect data to predict health care demand. Some are intended for use when concerned about health status; others are intended to be used repeatedly by users to monitor public health. The quality of triage may vary. The high use of such tools during the COVID-19 pandemic suggests that research is needed to assess and ensure the quality of advice given by self-triage tools and to assess intended or unintended consequences on public health and health care systems.
Link(s) to publication:
https://www.jmir.org/2023/1/e40983
http://dx.doi.org/10.2196/40983
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Austin, L. A.; Kovacs, D.; Thorne, S.; Moody, J. R. K., 2020, "Using grounded theory and mental modeling to understand influences on electricians’ safety decisions: Toward an integrated theory of why electricians work energized", Safety Science, October 130
Abstract: Why people engage in unsafe work practices, especially when advised not to, is an important question about human and organizational behavior. We seek insights into such behavior by examining questions about electricians’ safety decisions, with focus on why electricians work “energized” (or “live” meaning with electrical energy on) even when safety standards call for de-energizing. Using a grounded theory approach augmented by a mental models methodology, we develop from literature and 19 experts an ‘expert model’ of influences on electric worker safety decisions. From 60 in-depth electrician interviews we develop an integrated theory, summarized in a decision tree, describing key influences, decisions and events leading to energized work. Findings show electricians work is cognitively demanding. Working energized is not a simple yes/no choice, but instead is a decision influenced by many task, worksite, individual, organizational, and external factors. Working energized may better be thought of as an outcome arrived at via several pathways, including paths that lead to unknowingly working energized. Each path to knowingly or unknowingly working energized suggests different interventions to reduce risk. Additional key findings include that some electricians omit hazard assessments, perceive that past work by people not trained in electric work increases risk to electricians, and sometimes must negotiate to achieve prioritizing safe work practices over time or production pressures.
Link(s) to publication:
https://authors.elsevier.com/a/1bGP6_L39W~GGF
http://dx.doi.org/10.1016/j.ssci.2020.104826
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Austin, L. A., 2019, "Physician and Non-physician Estimates of Positive Predictive Value in Diagnostic Versus Mass Screening Mammography: An Examination of Bayesian Reasoning", Medical Decision Making, January 39(2): 108 - 118.
Abstract: Background:
The same test with the same result has different positive predictive values (PPVs) for people with different pre-test probability of disease. Representative thinking theory suggests people are unlikely to realize this because they ignore or underweight prior beliefs when given new information (e.g., test results), or due to confusing test sensitivity (probability of positive test given disease) with PPV (probability of disease given positive test). This research examines whether physicians and MBAs intuitively know that PPV following positive mammography for an asymptomatic woman is less than PPV for a symptomatic woman, and if so, whether they correctly perceive the difference.
Design:
60 general practitioners and 84 MBA students were given two vignettes of women with abnormal (positive) mammography tests: one with prior symptoms (diagnostic test), the other an asymptomatic woman participating in mass screening (screening test). Respondents estimated pre-test and post-test probabilities. Sensitivity and specificity were neither provided nor elicited.
Results:
88% of GPs and 46% of MBAs considered base rates and estimated PPV in diagnosis > PPV in screening. On average, GPs estimated a 27-point difference and MBAs an 18-point difference, compared to actual of 55 or more points. 10% of GPs and 46% of MBAs ignored base rates, incorrectly assessing the two PPVs as equal.
Conclusions:
Physicians and patients are better at intuitive Bayesian reasoning than is suggested by studies that make test accuracy values readily available to be confused with PPV. However, MBAs and physicians interpret a positive in screening as more similar to a positive in diagnosis than it is, with nearly half of MBAs and some physicians wrongly equating the two. This has implications for overdiagnosis and overtreatment.
Link(s) to publication:
http://dx.doi.org/10.1177/0272989X18823757
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Austin, L. A.; Reventlow, S.; Sandøe, P.; Brodersen, J., 2013, "The Structure of Medical Decisions: Probability, Uncertainty and Risk in Five Common Choice Situations", Health, Risk & Society, April 15(1): 27 - 50.
Abstract: Increasingly, medical choices involve deciding whether to look for evidence of undetected, asymptomatic conditions, or increased risk of future conditions (i.e. screening). Those who screen at sufficiently high risk face decisions about interventions to prevent or postpone the onset of possible, but not certain, future symptomatic conditions. Other preventive decisions include whether or not to accept population-based intervention, such as vaccination. Using decision trees, we model the normative structures and associated uncertainties that underlie five medical decision situations, each of which involves assessing the probabilistic hypothesis that a person has, or will in the future have, a given symptomatic condition. The probability estimate that results from assessment becomes an input into predicting treatment benefit, with the probability of benefit decreasing as that of the symptomatic condition decreases. The five situations identified in this paper involve assessing: (1) a symptomatic patient (2) an asymptomatic individual for an undetected condition (3) an individual for risk of a future condition (4) an individual for multiple risks simultaneously (shotgun assessment) and (5) an individual for a population-based intervention. Analysis of these situations facilitates examination of intuitive probabilistic reasoning. Drawing on evidence in related literature, we discuss some implications of decision-makers imposing the wrong structure or probabilistic reasoning when making medical choices. In particular, we discuss (1) overestimation of expected benefit due to systematic underestimation of uncertainty in a given decision (2) overconfidence in probabilistic test results and (3) failure to understand the implications of cumulative probabilities when shot-gun’ testing.
Link(s) to publication:
http://dx.doi.org/10.1080/13698575.2012.746286
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Austin, L. A.; Fischhoff, B., 2012, "Injury Prevention Risk Communication: A Mental Models Approach", Injury Prevention, November 18(2): 124 - 129.
Abstract: Individuals' decisions and behaviour can play a critical role in determining both the probability and severity of injury. Behavioural decision research studies peoples' decision-making processes in terms comparable to scientific models of optimal choices, providing a basis for focusing interventions on the most critical opportunities to reduce risks. That research often seeks to identify the 'mental models' that underlie individuals' interpretations of their circumstances and the outcomes of possible actions. In the context of injury prevention, a mental models approach would ask why people fail to see risks, do not make use of available protective interventions or misjudge the effectiveness of protective measures. If these misunderstandings can be reduced through context-appropriate risk communications, then their improved mental models may help people to engage more effectively in behaviours that they judge to be in their own best interest. If that proves impossible, then people may need specific instructions, not trusting to intuition or even paternalistic protection against situations that they cannot sufficiently control. The method entails working with domain specialists to elicit and create an expert model of the risk situation, interviewing lay people to elicit their comparable mental models, and developing and evaluating communication interventions designed to close the gaps between lay people and experts. This paper reviews the theory and method behind this research stream and uses examples to discuss how the approach can be used to develop scientifically validated context-sensitive injury risk communications.
Link(s) to publication:
http://dx.doi.org/10.1136/injuryprev-2011-040079
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Austin, L. A.; Fischhoff, B., 2010, "Consumers’ Collision Insurance Decisions: A Mental Models Approach to Theory Evaluation", Journal of Risk Research, October 13(7): 895 - 911.
Abstract: Using interviews with 74 drivers, we elicit and analyze how people think about collision insurance coverage and decide whether to buy coverage, and if so, what deductible level to carry. We compare respondents’ judgments and behaviors to predictions of three models: baseline expected utility (EU) theory, which predicts that insurance is an inferior good, meaning more wealthy people buy less a modified EU model, which incorporates income constraints and suggests that property insurance is a normal good, meaning more wealthy people buy more and a mental accounting model which predicts that consumers budget income across consumption categories. The results suggest they purchase insurance as a normal good, guided by a cognitive model that emphasizes budget constraints. Verbal reports reveal a desire to balance two conflicting goals in deductible decisions: keeping premiums affordable’ and keeping deductible level affordable.’ Thus, wealth does not distinguish people by risk aversion, but by ability to pay. In other words, the behavior of less wealthy people is not driven by greater risk aversion, but by their lesser ability to pay, both now and later. We find that a simple heuristic using only vehicle value accounts for most decisions of whether to purchase optional collision coverage: out of 45 respondents who did not have loans on their vehicles, 90% of those with vehicles worth more than 1000 carried collision coverage, while less than 30% of those with lower-valued vehicles did.
Link(s) to publication:
http://dx.doi.org/10.1080/13669871003703278
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Austin, L. A.; Liker, J.; McLeod, P., 1993, "Who Controls the Technology in Group Support Systems? Determinants and Consequences", Human-Computer Interaction, September 8(3): 217 - 236.
Abstract: Student groups completed a rank-ordering task in a "low-structure" computerized meeting room where all group members had equal access to a shared computer with a large monitor. Strategies used by the groups to distribute control over the public monitor, determinants of which members took control, and the consequences of control strategies were examined. Groups adopted either a dedicated-scribe strategy, in which one member had control throughout the session, or a non-dedicated-scribe strategy, in which control of the public monitor passed among members. Groups with at least one member who had low proficiency with the technology were very likely to adopt a dedicated-scribe strategy. Social influence within the group, proficiency with the computer system, and gender predicted which group members would take control of the public monitor. The results suggest that a group's social structure may be altered by the use of low-structure computer support, depending on the distribution of technical proficiency in the group. Dedicated-scribe groups had marginally better task performance but reported less increase in satisfaction (over previous work together) than non-dedicated-scribe groups. The implications of this research for the design and use of group computer support are discussed.
Link(s) to publication:
http://dx.doi.org/10.1207/s15327051hci0803_2
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Beyth-Marom, R.; Austin, L. A.; Fischhoff, B.; Palmgren, C.; Jacobs-Quadrel, M., 1993, "Perceived consequences of risky behaviors: Adults and adolescents.", Developmental Psychology, May 29(3): 549 - 563.
Abstract: Adult and adolescent Ss were asked to list possible consequences of either accepting or declining opportunities to engage in various potentially risky behaviors (e.g., drinking and driving, skipping school to go to a mall). Response patterns were quite similar for these adults and adolescents, indicating shared beliefs about the possibilities. Although taking and avoiding a risk are logically complementary actions, they did not prove to be psychologically complementary. Other comparisons showed systematic differences in the consequences produced for 1-time and regular (or repeated) versions of the same behaviors, as well as open-ended and closed-ended response modes. These results are discussed in terms of their methodological implications for studying risk perceptions, their practical implications for influencing adolescents' risk behaviors, and their theoretical implications for understanding intellectual development.
Link(s) to publication:
http://dx.doi.org/10.1037/0012-1649.29.3.549
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Horton, M.; Rogers, P.; Austin, L. A.; McCormick, M., 1991, "Exploring the Impact of Face-to-Face Collaborative Technology on Group Writing", Journal of Management Information Systems, December 8(3): 27 - 48.
Abstract: This experimental study examines the impact of face-to-face collaborative technology on group writing. We conducted a comparative analysis of small work groups writing managerial memoranda with the collaborative technology of the Capture Lab and with conventional writing tools. We find that the technology significantly alters the writing process, resulting in less initial group planning, more individual work and more revising, compared to when conventional tools are used. The minimal group planning in the technology condition appears to impact the group processes of negotiations and consensus-reaching. The technology also influences group interactions patterns, resulting in more individual tool use, less speech and less group focus. User feedback suggests the technology can have both positive and negative effects on communication among group members. We found no general effects of the technology on document quality, although preliminary evidence suggests that writing with technology can enhance writers’ audience adaptiveness. We also present some comparisons of how different groups used the technology and how these patterns may have influenced document quality. The final sections discuss suggestions for effective use of collaborative technology and future research.
Link(s) to publication:
http://dx.doi.org/10.1080/07421222.1991.11517928
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