The ability to self-assess is a crucial skill in identifying one's own strengths and weaknesses and in coordinating self-directed learning. The Dunning-Kruger effect occurs when limited knowledge causes individuals to overestimate their competence and underestimate others', leading to poor self-assessment and unrecognized incompetence. To serve as a foundation for developing strategies to improve self-assessment, the self-assessment abilities of first-semester students were assessed.

In the final weeks of the summer 2021, winter 2021/22, and summer 2022 semesters, the academic performance (oral anatomy exam) of first semester students was assessed (0-15 points). Before the exam results were announced, students were asked to self-assess their performance.

Exam scores (M = 10.64, SD = 2.95) and self-assessed scores (M = 10.38, SD = 2.54) were comparable. The absolute difference between them, as a measure of self-assessment ability ranged from - 9 to + 9 points (M = -0.26, SD = 2.59). Among participants (N = 426), 18.5% assessed themselves accurately, 35.5% overestimated, and 46.0% underestimated their performance. The correlation between actual score and self-assessment was ρ = -0.590 (p < 0.001), reflecting the Dunning-Kruger effect. When separated by gender, correlation for females was ρ = -0.591 (p < 0.001), and for males ρ = -0.580 (p < 0.001).

Realistic self-assessment is a challenge for first-semester students. The data indicate that females tend to overestimate their performance while males underestimate theirs. A pronounced Dunning-Kruger effect is evident in both genders, with significant negative correlations between self-assessment and actual performance. There are several reasons for the occurrence of the Dunning-Kruger effect. Considering that the COVID-19 pandemic influenced learning environments, collaborative learning was significantly restricted. The lack of opportunities for comparison could potentially lead to unrealistic self-assessment.

The Dunning-Kruger effect (DKE) is a cognitive bias wherein individuals who are unskilled overestimate their abilities, while those who are skilled tend to underestimate their capabilities. The purpose of this investigation is to determine if the DKE exists among American Board of Emergency Medicine (ABEM) in-training examination (ITE) participants.

This is a prospective, cross-sectional survey of residents in Accreditation Council for Graduate Medical Education (ACGME)-accredited emergency medicine (EM) residency programs. All residents who took the 2022 ABEM ITE were eligible for inclusion. Residents from international programs, residents in combined training programs, and those who did not complete the voluntary post-ITE survey were excluded. Half of the residents taking the ITE were asked to predict their self-assessment of performance (percent correct), and the other half were asked to predict their performance relative to peers at the same level of training (quintile estimate). Pearson's correlation (r) was used for parametric interval data comparisons and a Spearman's coefficient (ρ) was determined for quintile-to-quintile comparisons.

A total of 7568 of 8918 (84.9%) residents completed their assigned survey question. A total of 3694 residents completed self-assessment (mean predicted percentage correct 67.4% and actual 74.6%), with a strong positive correlation (Pearson's r 0.58, p < 0.001). There was also a strong positive correlation (Spearman's ρ 0.53, p < 0.001) for the 3874 residents who predicted their performance compared to peers. Of these, 8.5% of residents in the first (lowest) quintile and 15.7% of residents in the fifth (highest) quintile correctly predicted their performance compared to peers.

EM residents demonstrated accurate self-assessment of their performance on the ABEM ITE; however, the DKE was present when comparing their self-assessments to their peers. Lower-performing residents tended to overestimate their performance, with the most significant DKE observed among the lowest-performing residents. The highest-performing residents tended to underestimate their relative performance.

A career in healthcare is built on the foundations of continuous self-reflection and self-assessment. Previous studies have solely compared student self-assessment to faculty grades in a single discipline. The objective of this study was to investigate whether associations of a student's self-assessment skills exist across multiple disciplines in the predoctoral setting.

Sixty-five students from two class years at the Harvard School of Dental Medicine completed preclinical competency exams in dental anatomy waxing and operative dentistry. The difference between the student's self-assessment score and average faculty grade for each exercise was calculated as the student‒faculty (S-F) gap, which served as a proxy to determine how students evaluate their work. Regression analysis was performed to assess associations between wax-up and preclinical operative S-F gaps.

Mean S-F gaps for waxing and preclinical operative procedures were positive (5.7 ± 6.1 and 7.6 ± 6.7, respectively). Additionally, students in the lower quartile tended to overestimate performance to a greater degree than their peers in the upper quartile. Furthermore, the waxing S-F gaps were positively associated with S-F gaps of each operative procedure, particularly with the combined operative exercise S-F gaps, where a statistically significant association was seen (coefficient = 0.28; p = 0.04).

Previously, we identified a negative correlation between students' self-assessment skills (S-F gaps) and their preclinical performance. In this study, we further demonstrated an association of S-F gaps in two fundamental exercises: wax-up and operative dentistry. This underscores the roles of S-F gaps as possible indicators of students' preclinical and clinical performance, and it holds potential to become a widely standardized and applicable calculation that may help evaluate the effectiveness of the dental curricula and optimize student learning.

The purpose of this study is to assess whether the Dunning-Kruger effect occurs in surgical residents when performing laparoscopic cholecystectomy in a porcine model.

Prospective blinded study, which counted with forty PGY-1 general surgery residents who agreed to participate in the study were blindly recruited to perform a laparoscopic cholecystectomy in a porcine model. At the end of the procedure, the participants assigned a score of 0-10 for their own performance and the video of the operation was independently assessed by 2 experienced laparoscopic surgeons using a validated tool.

Participants were divided into groups of 10 individuals according to objective performance and compared. The group with the worst objective result was inferior to the group with the best objective result (3.77 ± 0.44 vs. 8.1 ± 0.44, p < 0.001), but they were similar in self-perception of performance (5.11 ± 1.69 vs. 6.1 ± 1.79, p = 0.999).

In the studied sample, it was possible to demonstrate the presence of the Dunning-Kruger effect.

Overestimation and miscalibration increase with a decrease in performance. This finding has been attributed to a common factor: participants' knowledge and skills about the task performed. Researchers proposed that the same knowledge and skills needed for performing well in a test are also required for accurately evaluating one's performance. Thus, when people lack knowledge about a topic they are tested on, they perform poorly and do not know they did so. This is a compelling explanation for why low performers overestimate themselves, but such increases in overconfidence can also be due to statistical artifacts. Therefore, whether overestimation indicates lack of awareness is debatable, and additional studies are needed to clarify this issue. The present study addressed this problem by investigating the extent to which students at different levels of performance know that their self-estimates are biased. We asked 653 college students to estimate their performance in an exam and subsequently rate how confident they were that their self-estimates were accurate. The latter judgment is known as second-order judgments (SOJs) because it is a judgment of a metacognitive judgment. We then looked at whether miscalibration predicts SOJs per quartile. The findings showed that the relationship between miscalibration and SOJs was negative for high performers and positive for low performers. Specifically, for low performers, the less calibrated their self-estimates were the more confident they were in their accuracy. This finding supports the claim that awareness of what one knows and does not know depends in part on how much one knows.

Competencies related to the evaluation of own cognitive processes, called metacognitive monitoring, are crucial as they help decide whether to persist in or desist from cognitive efforts. One of the most well-known phenomena in this context-the Dunning-Kruger effect-is that less skilled people tend to overestimate their performance. This effect has been reported for various kinds of performance including creativity. More recently, however, it has been suggested that this phenomenon could be a statistical artifact caused by the better-than-average effect and by regression toward the mean. Therefore, we examined the Dunning-Kruger effect in the context of creative thinking performance (i.e., divergent thinking ability) across two studies (Study 1: N = 425; Study 2: N = 317) and applied the classical quartile-based analysis as well as newly recommended, advanced statistical approaches: the Glejser test of heteroscedasticity and nonlinear quadratic regression. We found that the results indeed depended on the employed statistical method: While classical analyses supported the Dunning-Kruger effect across all conditions, it was not consistently supported by the more advanced statistical methods. These findings are in line with recent work challenging certain assumptions of the Dunning-Kruger effect and we discuss factors that undermine accurate self-assessments, especially in the context of creative performance.

Environmental and behavioral factors are responsible for 12.6 million deaths annually and contribute to 25% of deaths and chronic diseases worldwide. Through the One Health initiative, the World Health Organization and other international health organizations plan to improve these indicators to create healthier environments by 2030. To meet this challenge, training primary care professionals should be the priority of national policies. General practitioners (GPs) are ready to become involved but need in-depth training to gain and apply environmental health (EH) knowledge to their practice. In response, we designed the Primary Care Environment and Health (PCEH) online course in partnership with the Occitanie Regional Health Agency in France. This course was used to train GP residents from the Montpelier-Nimes Faculty of Medicine in EH knowledge. The course was organized in 2 successive parts: (1) an asynchronous e-learning modular course focusing on EH knowledge and tools and (2) 1 day of face-to-face sessions.

This study assessed the impact of the e-learning component of the PCEH course on participants' satisfaction, knowledge, and behavior changes toward EH.

This was a pilot before-and-after study. Four modules were available in the 6-hour e-learning course: introduction to EH, population-based approach (mapping tools and resources), clinical cases, and communication tools. From August to September 2021, we recruited first-year GP residents from the University of Montpellier (N=130). Participants' satisfaction, knowledge improvements for 19 EH risks, procedure to report EH risks to health authorities online, and behavior change (to consider the possible effects of the environment on their own and their patients' health) were assessed using self-reported questionnaires on a Likert scale (1-5). Paired Student t tests and the McNemar χ2 test were used to compare quantitative and qualitative variables, respectively, before and after the course.

A total of 74 GP residents completed the e-learning and answered the pre- and posttest questionnaires. The mean satisfaction score was 4.0 (SD 0.9) out of 5. Knowledge scores of EH risks increased significantly after the e-learning course, with a mean difference of 30% (P<.001) for all items. Behavioral scores improved significantly by 18% for the participant's health and by 26% for patients' health (P<.001). These improvements did not vary significantly according to participant characteristics (eg, sex, children, place of work).

The e-learning course improved knowledge and behavior related to EH. Further studies are needed to assess the impact of the PCEH course on clinical practice and potential benefits for patients. This course was designed to serve as a knowledge base that could be reused each year with a view toward sustainability. This course will integrate new modules and will be adapted to the evolution of EH status indicators and target population needs.

The American College of Obstetricians and Gynecologists recommends all pregnant people be offered genetic screening and diagnostic testing regardless of risk factors. Previous studies have demonstrated disparities in referrals for genetic testing by race outside of pregnancy, but limited data exist regarding genetic counseling practices during pregnancy.

This study aimed to describe how patient, provider, and practice demographics influence the offering of diagnostic prenatal genetic testing by outpatient prenatal care providers.

This was a multicenter anonymous survey study conducted between October 2021 and March 2022. Outpatient prenatal care providers, including family medicine and obstetrics attendings, residents, maternal-fetal medicine fellows, nurse practitioners, physician assistants, and midwives, were surveyed about their genetic counseling practices and practice demographics. The primary outcome was the proportion of respondents who answered "yes, all patients" to the survey question "Do you offer diagnostic genetic testing to all patients?" The secondary outcomes included the association between patient and practice demographics and offering diagnostic testing. Diagnostic testing was defined as chorionic villus sampling or amniocentesis. Screening genetic tests were defined as sequential screen, quadruple screen, cell-free DNA screening, or "other." The chi-square test or Fisher exact test was used as appropriate. For the outcome answers of diagnostic testing, logistic regression was performed to assess the association between the answer of diagnostic genetic testing and the current training level of providers, race and ethnicity, and insurance status variables. Multivariable analysis was performed to adjust for confounders.

A total of 635 outpatient prenatal care providers across 7 sites were sent the survey. Overall, 419 providers responded for a total response rate of 66%. Of the providers who responded, most were attendings (44.9%), followed by residents (37.5%). Providers indicated the race, insurance status, and primary language of their patient population. Screening genetic testing was offered by 98% of providers. Per provider report, 37% offered diagnostic testing to all patients, 18% did not offer it at all, and 44% only offered it if certain patient factors were present. Moreover, 54.8% of attendings reported universally offering diagnostic testing. On univariable analysis, residents were less likely to offer diagnostic testing than attendings (odds ratio, 0.18; 95% confidence interval, 0.11-0.30). Providers who serve non-Hispanic Black, Hispanic Black, and other Hispanic patients were less likely to report offering diagnostic testing than other patient populations. Providers who served non-Hispanic Whites were more likely to offer diagnostic testing (odds ratio, 2.26; 95% confidence interval, 1.51-3.39). Patient populations who were primarily privately insured were more likely to be offered diagnostic testing compared with primarily publicly insured patients (odds ratio, 6.25; 95% confidence interval, 3.60-10.85). Providers who served a primarily English-speaking population were more likely to offer diagnostic genetic testing than other patient populations (odds ratio, 0.43; 95% confidence interval, 0.26-0.69). On multivariable analysis, the factors that remained significantly associated with offering diagnostic testing included level of training (resident odds ratio, 0.33; 95% confidence interval, 0.17-0.62; P=.0006; advanced practice provider odds ratio, 0.34; 95% confidence interval, 0.15-0.82; P=.02), having at least one-third of the patient population identify as "other Hispanic" (odds ratio, 0.42; 95% confidence interval, 0.23-0.77; P=.005), and having private insurance instead of public insurance (primarily private insured odds ratio, 2.84; 95% confidence interval, 1.20-6.74; P=.02).

Although offering genetic screening and diagnostic testing to all patients is recommended, no provider group universally offers diagnostic testing. Providers who serve populations from a racial and ethnic minority, those with public insurance, and those whose primary language is not English are less likely to report universally offering diagnostic genetic testing.

Artificial intelligence (AI) is changing the way we create and evaluate information, and this is happening during an infodemic, which has been having marked effects on global health. Here, we evaluate whether recruited individuals can distinguish disinformation from accurate information, structured in the form of tweets, and determine whether a tweet is organic or synthetic, i.e., whether it has been written by a Twitter user or by the AI model GPT-3. The results of our preregistered study, including 697 participants, show that GPT-3 is a double-edge sword: In comparison with humans, it can produce accurate information that is easier to understand, but it can also produce more compelling disinformation. We also show that humans cannot distinguish between tweets generated by GPT-3 and written by real Twitter users. Starting from our results, we reflect on the dangers of AI for disinformation and on how information campaigns can be improved to benefit global health.

Although researchers have begun to consider metacognitive insight during face matching, little is known about the underlying mechanism. Here, I investigated whether objective ability, as well as self-assessed ability, were able to predict metacognitive performance, that is, the ability to differentiate correct and incorrect responses in terms of confidence. In addition, I considered whether a training intervention resulted in improvements to both face matching performance and metacognitive insight.

In this experiment (N = 220), participants completed a face matching task, with either a diagnostic feature training course or a control course presented at the halfway point. In addition, a second face matching task, as well as a self-report questionnaire regarding ability, were completed to provide measures of objective and self-assessed ability respectively.

Higher self-assessed ability with faces, as well as higher objective ability with face matching, predicted better metacognitive performance, i.e., greater confidence in correct, in comparison with incorrect, responses. This pattern of results was evident both when objective ability was measured through performance on the same task used to measure metacognitive insight and when a different task was used. Finally, the training intervention failed to produce improvements in face matching performance and showed no evidence of altering metacognitive ability.

The current work begins to address the mechanism underlying individual differences in metacognitive insight during face matching. Although support was provided for a competence-based account, where better face matchers showed greater performance on the task and were more successful in monitoring their performance, further work might focus on decoupling task performance and competence in order to more conclusively explain why some people are more insightful than others.