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Flawed Self-Assessment: Implications for Health, Education, and the Workplace
Open accessAbstract
Research from numerous corners of psychological inquiry suggests that self-assessments of skill and character are often flawed in substantive and systematic ways. We review empirical findings on the imperfect nature of self-assessment and discuss implications for three real-world domains: health, education, and the workplace. In general, people's self-views hold only a tenuous to modest relationship with their actual behavior and performance. The correlation between self-ratings of skill and actual performance in many domains is moderate to meager—indeed, at times, other people's predictions of a person's outcomes prove more accurate than that person's self-predictions. In addition, people overrate themselves. On average, people say that they are “above average” in skill (a conclusion that defies statistical possibility), overestimate the likelihood that they will engage in desirable behaviors and achieve favorable outcomes, furnish overly optimistic estimates of when they will complete future projects, and reach judgments with too much confidence. Several psychological processes conspire to produce flawed self-assessments. Research focusing on health echoes these findings. People are unrealistically optimistic about their own health risks compared with those of other people. They also overestimate how distinctive their opinions and preferences (e.g., discomfort with alcohol) are among their peers—a misperception that can have a deleterious impact on their health. Unable to anticipate how they would respond to emotion-laden situations, they mispredict the preferences of patients when asked to step in and make treatment decisions for them. Guided by mistaken but seemingly plausible theories of health and disease, people misdiagnose themselves—a phenomenon that can have severe consequences for their health and longevity. Similarly, research in education finds that students' assessments of their performance tend to agree only moderately with those of their teachers and mentors. Students seem largely unable to assess how well or poorly they have comprehended material they have just read. They also tend to be overconfident in newly learned skills, at times because the common educational practice of massed training appears to promote rapid acquisition of skill—as well as self-confidence—but not necessarily the retention of skill. Several interventions, however, can be introduced to prompt students to evaluate their skill and learning more accurately. In the workplace, flawed self-assessments arise all the way up the corporate ladder. Employees tend to overestimate their skill, making it difficult to give meaningful feedback. CEOs also display overconfidence in their judgments, particularly when stepping into new markets or novel projects—for example, proposing acquisitions that hurt, rather then help, the price of their company's stock. We discuss several interventions aimed at circumventing the consequences of such flawed assessments; these include training people to routinely make cognitive repairs correcting for biased self-assessments and requiring people to justify their decisions in front of their peers. The act of self-assessment is an intrinsically difficult task, and we enumerate several obstacles that prevent people from reaching truthful self-impressions. We also propose that researchers and practitioners should recognize self-assessment as a coherent and unified area of study spanning many subdisciplines of psychology and beyond. Finally, we suggest that policymakers and other people who makes real-world assessments should be wary of self-assessments of skill, expertise, and knowledge, and should consider ways of repairing self-assessments that may be flawed.
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“Learning about notions of quality through assessing the work of peers may reduce the effect of cognitive biases directed towards the self when undertaking self-assessment (Dunning et al. 2004).”
From Developing evaluative judgement: enabling students to make decisions about the quality of work (2018) · cites this paper as Dunning et al. 2004
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“human beings do show a tendency to leap to conclusions about themselves, other people, and the world based on limited information and misperceptions about the extent and generalizability of prior knowledge and experiences (Dunning, Heath, & Suls, 2004).”
From Psychological flexibility as a fundamental aspect of health (2010) · cites this paper as Dunning, Heath, & Suls, 2004
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“Feedback helps students make sense of their learning and compare their performance against a recognized standard. 1-3”
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Nonlinear Dynamics of Team Performance and Adaptability in Emergency Response
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Mynttinen, S., Sundström, A. E., Koivukoski, M., Hakuli, K., Keskinen, E., & Henriksson, W. (2008) · Transportation Research Part F Traffic Psychology and Behaviour · doi:10.1016/j.trf.2008.09.002 · Cited by 47
Negotiation based adaptive learning sequences: Combining adaptivity and adaptability
Chou, C., Lai, K.-H. R., Chao, P.-Y., Lan, C. H., & Chen, T.-H. (2015) · Computers & Education · doi:10.1016/j.compedu.2015.05.007 · Cited by 46
Munyewende, P. O., Levin, J., & Rispel, L. C. (2016) · Global Health Action · doi:10.3402/gha.v9.32486 · Cited by 46
“The higher self-rating scores by the PHC nursing managers were also found in another study (26), where employees overestimated their skills, making it difficult to give meaningful feedback (55).”
ResultMurphy, J., Kurland, L., Rådestad, M., Magnusson, S., Ringqvist, T., & Rüter, A. (2021) · International Emergency Nursing · doi:10.1016/j.ienj.2021.101019 · Cited by 46
Weiner, B. L. (2010) · Elsevier eBooks · doi:10.1016/b978-0-08-044894-7.00600-x · Cited by 46
A Statistical Explanation of the Dunning-Kruger Effect
Magnus, J. R., & Peresetsky, A. A. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2022.840180 · Cited by 53
Recognition of home injury risks by novice parents of toddlers
Gaines, J., & Schwebel, D. C. (2009) · Accident Analysis & Prevention · doi:10.1016/j.aap.2009.06.010 · Cited by 45
Binning, K. R., & Browman, A. S. (2020) · Social Issues and Policy Review · doi:10.1111/sipr.12066 · Cited by 51
Oosten, E. B. V., McBride-Walker, S. M., & Taylor, S. N. (2019) · Consulting psychology journal · doi:10.1037/cpb0000141 · Cited by 46
Toward a General Framework of Biased Reasoning: Coherence-Based Reasoning
Simon, D., & Read, S. J. (2023) · Perspectives on Psychological Science · doi:10.1177/17456916231204579 · Cited by 47
“People tend to rate themselves as being above average across a wide range of domains (Cross, 1977; Dunning et al., 2004; Svenson et al., 1985) and inflate outside evaluations of their performance and rate their own performance even higher (Alicke, 1985).”
Biases in social comparisons: Optimism or pessimism?
Menon, G., Kyung, E. J., & Agrawal, N. (2008) · Organizational Behavior and Human Decision Processes · doi:10.1016/j.obhdp.2008.05.001 · Cited by 44
Judgments of physics problem difficulty among experts and novices
Fakcharoenphol, W., Morphew, J., & Mestre, J. P. (2015) · Physical Review Special Topics - Physics Education Research · doi:10.1103/physrevstper.11.020128 · Cited by 44
Data management and sharing: Practices and perceptions of psychology researchers
Borghi, J., & Gulick, A. E. V. (2021) · PLoS ONE · doi:10.1371/journal.pone.0252047 · Cited by 46
“It is possible that this trend simply reflects a well-known phenomenon of participants rating themselves as above average across a range of characteristics [49], but it is also possible that a study, which was explicitly advertised as being about data management practices in psychology, disproportionately attracted ps…”
BackgroundFastré, G., van der Klink, M. R., & van Merriënboer, J. J. G. (2010) · Advances in Health Sciences Education · doi:10.1007/s10459-009-9215-x · Cited by 52
The role of interest and images in slideware presentations
Tangen, J. M., Constable, M., Durrant, E., Teeter, C., Beston, B. R., & Kim, J. A. (2010) · Computers & Education · doi:10.1016/j.compedu.2010.10.028 · Cited by 47
The Other Side of Method Bias: The Perils of Distinct Source Research Designs
Kammeyer‐Mueller, J. D., Steel, P., & Rubenstein, A. L. (2010) · Multivariate Behavioral Research · doi:10.1080/00273171003680278 · Cited by 44
Change one can believe in: Adding learning to computational models of self-regulation
Vancouver, J. B., Weinhardt, J. M., & Vigo, R. (2014) · Organizational Behavior and Human Decision Processes · doi:10.1016/j.obhdp.2013.12.002 · Cited by 43
“Our model implies, and research supports (Roy, Christenfeld, & McKenzie, 2005) the notion that this underestimation problem might be a primary source of the prevalence of overconfidence (Dunning et al., 2004) and the planning fallacy (Buehler, Griffin, & Ross, 1994).”
ResultHelping Skills Training for Undergraduate Students
Hill, C. E., Anderson, T., Kline, K. V., McClintock, A. S., Cranston, S., McCarrick, S. M., Petrarca, A., Himawan, L. K., Pérez‐Rojas, A. E., Bhatia, A., et al. (2015) · The Counseling Psychologist · doi:10.1177/0011000015613142 · Cited by 43
Metadata
- Authors
- Dunning, D., Heath, C., & Suls, J. M.
- Affiliations
- Cornell University (US)
- Stanford University (US)
- University of Iowa (US)
- Venue
- Psychological Science in the Public Interest
- Publisher
- SAGE Publications
- Published
- 2004-12
- Volume
- 5
- Issue
- 3
- Pages
- 69-106
- ISSN
- 1539-6053 (ISSN-L)
- 1529-1006
- OpenAlex
- W2139736795
- Cited by
- 1,865
- References
- 310
- Citations by year
- 2026: 107 · 2025: 89 · 2024: 104 · 2023: 76 · 2022: 104 · 2021: 103 · 2020: 110 · 2019: 114 · 2018: 113 · 2017: 98 · 2016: 102 · 2015: 111 · 2014: 99 · 2013: 82 · 2012: 90
- FWCI
- 35.81
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Gothic.net (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Science Foundation (9910592)
- National Institute of Mental Health (RO1 56072)
- Topics
- Social Sciences › Psychology › Clinical Psychology › Personality Traits and Psychology
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Education › Student Assessment and Feedback
- Keywords
- self-assessment, overconfidence, above-average effect, self-prediction, self-efficacy, health risk perception, self-diagnosis, student self-assessment, skill retention, massed practice, CEO overconfidence, management decision-making, feedback, self-knowledge, self-regulation, self-monitoring
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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