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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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Billieux, J., Van der Linden, M., d'Acremont, M., Ceschi, G., & Zermatten, A. (2007) · Applied Cognitive Psychology · doi:10.1002/acp.1289 · Cited by 218
Speaking Up vs. Being Heard: The Disagreement Around and Outcomes of Employee Voice
Burris, E. R., Detert, J. R., & Romney, A. C. (2012) · Organization Science · doi:10.1287/orsc.1110.0732 · Cited by 231
Psychology-Based Models of Asset Prices and Trading Volume
Barberis, N. (2018) · Handbook of behavioral economics · doi:10.1016/bs.hesbe.2018.07.001 · Cited by 231
Developing and evaluating intercultural competence: Ethnographies of intercultural encounters
Holmes, P., & O’Neill, G. (2012) · International Journal of Intercultural Relations · doi:10.1016/j.ijintrel.2012.04.010 · Cited by 255
Unrealistic optimism about future life events: A cautionary note.
Harris, A. J. L., & Hahn, U. (2010) · Psychological Review · doi:10.1037/a0020997 · Cited by 217
Hacker, D. J., Bol, L., & Bahbahani, K. (2008) · Metacognition and Learning · doi:10.1007/s11409-008-9021-5 · Cited by 213
Schlösser, T., Dunning, D., Johnson, K. L., & Kruger, J. (2013) · Journal of Economic Psychology · doi:10.1016/j.joep.2013.07.004 · Cited by 166
Self-citationAccuracy in student self-assessment: directions and cautions for research
Brown, G. T. L., Andrade, H. L., & Chen, F. (2015) · Assessment in Education Principles Policy and Practice · doi:10.1080/0969594x.2014.996523 · Cited by 186
“, 2010; Hewitt, 2001), and might enhance accuracy if the models are used as benchmarks (Dunning et al., 2004).”
BackgroundInfluentialNesbit, P. (2012) · Human Resource Development Review · doi:10.1177/1534484312439196 · Cited by 245
“Given that people have a tendency to overestimate their own level of performance relative to the views of others (Dunning, Heath, & Suls, 2004), one is likely to experience negative feedback at some point in formal and informal appraisal by others.”
BackgroundFeeling blue or turquoise? Emotional differentiation in major depressive disorder
Demiralp, E., Thompson, R. J., Mata, J., Jaeggi, S. M., Buschkuehl, M., Barrett, L. F., Ellsworth, P. C., Demiralp, M., Hernandez-Garcia, L., Deldin, P. J., et al. (2012) · Psychological Science · doi:10.1177/0956797612444903 · Cited by 205
Beghetto, R. A., Kaufman, J. C., & Baxter, J. A. (2011) · Psychology of Aesthetics Creativity and the Arts · doi:10.1037/a0022834 · Cited by 207
Lane, R. D., Weihs, K. L., Herring, A. M., Hishaw, A., & Smith, R. S. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2015.06.007 · Cited by 220
“Given that the concept of alexithymia originated with the goal of capturing an impairment in experiencing and describing emotions (Nemiah and Sifneos, 1970; Nemiah et al., 1976), difficulties potentially arise when attempting to use a self-report measure to accomplish that (Dunning et al., 2004).”
BackgroundResultChiu, M. M., & Klassen, R. M. (2010) · Learning and Instruction · doi:10.1016/j.learninstruc.2008.11.002 · Cited by 202
Teovanović, P., Lukić, P., Zupan, Z., Lazić, A., Ninković, M., & Žeželj, I. L. (2020) · Applied Cognitive Psychology · doi:10.1002/acp.3770 · Cited by 207
“In fact, knowledge overestimation has been widely documented in the health domain (see Dunning et al., 2004).”
BackgroundMann, K. V., van der Vleuten, C. P. M., Eva, K. W., Armson, H., Chesluk, B., Dornan, T., Holmboe, E. S., Lockyer, J., Loney, E., & Sargeant, J. M. (2011) · Academic Medicine · doi:10.1097/acm.0b013e318226abdd · Cited by 198
Emotional Exhaustion Among US Health Care Workers Before and During the COVID-19 Pandemic, 2019-2021
Sexton, J. B., Adair, K. C., Proulx, J., Profit, J., Cui, X., Bae, J. G., & Frankel, A. S. (2022) · JAMA Network Open · doi:10.1001/jamanetworkopen.2022.32748 · Cited by 213
Exploring the divergence between self-assessment and self-monitoring
Eva, K. W., & Regehr, G. (2011) · Advances in Health Sciences Education · doi:10.1007/s10459-010-9263-2 · Cited by 194
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
About these checks
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.
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