ReviewJournal of general internal medicine2025
What Type of Self-Assessment Is Best for Your Educational Activity? A Review of Pre-Post, Now-Then, and Post-Only Designs.
Review in Journal of general internal medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed.
- Educational impact of a simulation-based renal biopsy workshop for medical students during nephrology clerkship.BMC medical education · 2026Article
- Learning gain of an ATLSEuropean journal of trauma and emergency surgery : official publication of the European Trauma Society · 2026Article
- An Interactive Workshop to Enhance Teaching Skills Through Understanding Teaching Styles.MedEdPORTAL : the journal of teaching and learning resources · 2026Article
- Measurement properties of self-assessment instruments for disaster nursing competencies: a systematic literature review.BMC nursing · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In medical education, learner self-assessments are standard methods used to evaluate the impact of curricula and workshops. Due to the subjective nature of self-assessment, these measures are prone to known biases including framing, recall, social desirability, and response-shift bias. These biases can contribute to floor and ceiling effects of measurement, which can lead to false conclusions about whether the intended learning objectives were achieved. Ideal assessments of skills-based educational activities would include standardized tests and structured observations of learners demonstrating skill use before and after the educational intervention. However, educators often lack the necessary resources, time, and expertise to routinely conduct these appraisals and rely on self-assessment as a pragmatic approach to obtaining curriculum feedback and evaluation data. In this review, we describe three common designs for self-assessments: the pre-post, now-then, and post-only designs. We then give recommendations for choosing between each design to minimize bias. The choice of the best design is based on alignments with four considerations: (1) the educational objectives (e.g., demonstrate skill competency and/or change in skill level); (2) participants' prior experience and shared understanding of levels of skill performance; (3) the nature of the educational activity; and (4) available resources. For each design, we review strengths, weaknesses, and known biases and discuss examples to highlight trade-offs between options. We also discuss the use of control groups and follow-up surveys to measure retention over time as additional methods to address bias and related confounding. The guidance presented here is intended to raise educators' awareness of common pitfalls in self-assessment; minimize the impact of known biases when possible; provide evidence, examples, and rationales for optimal design choices; and increase the rigor of self-assessment evaluations.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.