Perfectionism and depression in sport. Are we as clear as in clinical practice? A systematic review
Bibliographic record
Abstract
Abstract Depression is among the most prevalent mental disorders globally, and the athletic population is not exempt from its impact. Research has identified perfectionism as a personality trait strongly associated with depressive symptoms in athletes, often characterized by elevated levels of rumination and intrusive thoughts following high-pressure situations such as competitive events. The current study aimed to review the relationship between perfectionism and depression in the sports context, describing which vulnerability factors (both predisposing and maintenance) have been linked in scientific literature. A total of 1,046 publications were initially identified, of which 13 met the established inclusion criteria. This review describes the instruments used to assess perfectionism and depression in sport settings (describing their rigor and clinical value), outlines the sociodemographic characteristics of the athlete populations in which this variable combination is most frequently observed. Finally, additional variables associated with perfectionism and depression, such as anxiety, burnout, and coping strategies, are also discussed. The findings of this review may help reorient empirical approaches that seek to explain, from a coherent clinical perspective, the intense and extreme relationship between perfectionistic tendencies and the emergence of depressive symptoms in high-performance sport. Also, the results may support the valuable scientific effort to inform coaches, other sport professionals, or family members to identify, address, and support athletes (or themselves), positively impacting their psychosocial resources and individual capacities for healthy adaptation and/or athletic effectiveness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".