Procrastination in medical students: a systematic review
Bibliographic record
Abstract
Background: The purpose of this systematic review was to understand the implications of procrastination on medical students' lives and well-being by examining its conceptualization in the medical education literature, the contexts in which it has been studied, and with which variables it has been associated. These areas were investigated to propose practical solutions to reduce medical students' procrastination tendencies. Methods: This systematic review was completed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses and the guidelines of the Association for Medical Education in Europe. We searched the PubMed, ERIC (ProQuest), and PsycINFO (OVID) databases. A total of 243 articles were identified and screened independently by two authors. Results: Based on a set of inclusion criteria, 26 articles were kept and analyzed in the review. We found that medical students' procrastination was most often conceptualized as the voluntary delay of a given task. Medical students' procrastination was examined in two different contexts: academic procrastination and bedtime procrastination. Procrastination was negatively related to variables such as academic achievement, metacognition, and self-esteem, and positively related to other variables such as stress, anxiety, and mobile phone addictions. Conclusions: Medical students' procrastination is most frequently described as the intentional or voluntary postponement of a given task with the expectation of negative consequences and is most often evaluated in academic settings alongside mental health and affective variables. Future research should focus on promoting students' awareness of their procrastination and emotional states through targeted and goal-oriented interventions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".