Determinants and Reasons for Dropout in Swimming —Systematic Review
Bibliographic record
Abstract
The present research aims to systematically review the determinants and reasons for swimming dropout. The systematic review was conducted through electronic searches on the Web of Knowledge and PsycInfo databases from 2 February to 29 July 2015, using the keywords dropout, withdrawal, motives, reasons, sport, framework-theories, motivation, swim*, review, attrition and compliance. Fifteen studies were found and six were fully reviewed and its data extracted and analysed. Most studies were undertaken in Canada and in the United States of America (USA), and one study was conducted in Spain. Most participants were female (65.74%), and the main reasons for dropout were 'conflicts with their trainers', 'other things to do', 'competence improvements' failure', 'parents, couples or trainers' pressure', 'lack of enjoyment' and 'get bored'. This review contributes to the present knowledge on the understanding of dropout in swimming. However, it is necessary to continue researching on this topic, validating measurement instruments and studying the motivational processes related to dropout and persistence.
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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 | 0.017 | 0.077 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".