Predicting dropout in male youth soccer using the theory of planned behavior
Bibliographic record
Abstract
This investigation prospectively predicted dropout among young soccer players, using the theory of planned behavior (TPB). First, behavioral beliefs required to develop a TPB-questionnaire were elicited from 53 male soccer players, aged 13-15 years. Second, at the beginning of the soccer season, 354 different male soccer players aged 13-15 years completed this questionnaire, thereby assessing direct dimensions (intention, attitude, subjective norm, perceived control) and indirect dimensions (attitudinal, normative and control beliefs) derived from TPB. Nine months later--upon termination of the soccer season--these players were classified into 323 perserverers and 31 dropouts, with TPB being applied prospectively to predict these two groups. For both direct and indirect dimensions, between-group comparisons revealed significant differences in favor of the perseverers. Discriminant analyses revealed five measures (intention, attitude, subjective norm, a normative belief, and a control belief), which enabled a 22.1% a priori dropout prediction when used within a suitable equation. In conclusion, TPB may have a promising application to prospectively discriminate dropouts from perseverers, providing a potential predictive a priori classification model for sport participation.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".