A systematic review of dropout from organized sport among children and youth
Bibliographic record
Abstract
Leisure constraints theory was used as a framework to systematically review factors associated with dropout of organized sport among children and adolescents. Keyword searches for the population, context and construct of interest (i.e. dropout) identified articles from the entire contents of the following databases: Academic Search Complete, ERIC, MEDLINE, PsycINFO and SPORTDiscus. The initial search yielded 557 studies, and 43 met the selection criteria. Most studies focused solely on adolescents, and 89% of participants were male. Most studies were cross-sectional using quantitative approaches. Almost 30 different sports were included in the reviewed studies; however, the most represented sports were soccer, swimming, gymnastics and basketball. Findings from this review indicated that intrapersonal and interpersonal constraints are more frequently associated with dropping out of sport than structural constraints. Although many discrete factors associated with dropout were identified, five major areas emerged: lack of enjoyment, perceptions of competence, social pressures, competing priorities and physical factors (maturation and injuries). Rarely were the interrelationships between factors or the underlying dimensions of factors examined. Future research would benefit from mixed-methods and prospective approaches. These approaches would allow children and youth to explain how their experience of sport shaped their motives to dropout and allow researchers to probe the extent to which affordances and motives for participation aligned with athletes’ reasons for dropping out.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.020 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".