Evaluation of statistical illiteracy in Latin American clinicians and the piloting evaluation of a short course across multiple timepoints.

BACKGROUND: All clinicians require statistical interpretation skills to keep up to date with evidence-based recommendations in their field. However, statistical illiteracy among clinicians is a highly prevalent problem with far-reaching consequences. The few available that report statistical literacy improvements after educational interventions do not measure for how long these benefits last. To estimate statistical illiteracy among Latin-American clinicians across multiple levels of training and to evaluate a 10-h course at multiple timepoints. METHODS: Using an online questionnaire, we evaluated; self-perceived statistical proficiency, scientific literature reading habits and statistical literacy (using an adaptation of the Quick Risk Test). Separately, we evaluated statistical proficiency after a 10-h statistics course in a group of Internal Medicine residents at a tertiary center in Mexico City across multiple time points between November 2020 and February 2021. RESULTS: Data from 392 clinicians from 9 Latin American countries were analyzed. Most clinicians (85%) failed our adaptation of the Quick Risk Test (mean score = 2.6/10, IQR:1.4). The 10-h course significantly improved the scores of the Internal Medicine Residents (n = 16) from 3.8/10, IQR:1.8 to 8.3/10, IQR:1.4 (p < 0.01). However, scores dropped after one and 2 months to 7.7/10, IQR:1.6 and 6.1 / 10, IQR:2.2, respectively. CONCLUSION: Statistical Illiteracy is highly prevalent among Latin American clinicians. Short-term educational interventions are effective but, their benefits quickly fade away. Medical boards and medical schools need to periodically teach and evaluate statistical proficiency to ameliorate these issues.

Illusion of knowledge in statistics among clinicians: evaluating the alignment between objective accuracy and subjective confidence, an online survey.

Healthcare professionals' statistical illiteracy can impair medical decision quality and compromise patient safety. Previous studies have documented clinicians' insufficient proficiency in statistics and a tendency in overconfidence. However, an underexplored aspect is clinicians' awareness of their lack of statistical knowledge that precludes any corrective intervention attempt. Here, we investigated physicians', residents' and medical students' alignment between subjective confidence judgments and objective accuracy in basic medical statistics. We also examined how gender, profile of experience and practice of research activity affect this alignment, and the influence of problem framing (conditional probabilities, CP vs. natural frequencies, NF). Eight hundred ninety-eight clinicians completed an online survey assessing skill and confidence on three topics: vaccine efficacy, p value and diagnostic test results interpretation. Results evidenced an overall consistent poor proficiency in statistics often combined with high confidence, even in incorrect answers. We also demonstrate that despite overconfidence bias, clinicians show a degree of metacognitive sensitivity, as their confidence judgments discriminate between their correct and incorrect answers. Finally, we confirm the positive impact of the more intuitive NF framing on accuracy. Together, our results pave the way for the development of teaching recommendations and pedagogical interventions such as promoting metacognition on basic knowledge and statistical reasoning as well as the use of NF to tackle statistical illiteracy in the medical context.

The jigsaw puzzle of fraudulent health claims: Missing psychological pieces.

Fraudulent health claims have become an inescapable fixture of the contemporary information (or misinformation) landscape. MacFarlane, Hurlstone, and Ecker (2020) provided a five-fold framework for conceptualizing susceptibility to fraudulent health claims, and proposed potential remedies for each driver of these claims. We build on their analysis by arguing that a complete account of fraudulent health claim susceptibility additionally requires a thoroughgoing consideration of (a) individual differences in cognitive styles and personality traits, (b) innumeracy and statistical illiteracy, and (c) persuasive appeals involving logical fallacies and commonplaces. We further contend that dual processing models of cognition may help to synthesize a variety of psychological variables relevant to fraudulent health claim vulnerability. In conjunction with our commentary, MacFarlane's framework underscores the broader point that complex, multifactorial psychological phenomena demand complex, multifactorial psychological explanations and solutions.