Identification of distinct physical activity profiles through adolescence: a longitudinal qualitative description study
Bibliographic record
Abstract
Introduction: We aimed to better understand longitudinal physical activity experiences among initially active adolescents and to identify and describe distinct physical activity profiles. Methods: A sample of 23 physically active participants [52% female; mean age = 12.2 (0.6) years at study inception] were selected from the MATCH study to take part in this nested qualitative descriptive study. Participants were interviewed once a year for six years. Following individual-level analyses, profiles were identified based on similarity of longitudinal experiences. Results: Four profiles captured participants' experiences: Independents (those who progressively seek activities that cater to their pursuit of autonomy); Multitaskers (those who participate in many different sports as an integral part of their lifestyle); Specialists (those who are dedicated to becoming the best they can be at one sport); Undecided (those who take part in physical activity to occupy time). Discussion: The exploration of longitudinal physical activity experiences led to the identification of distinct profiles that could be targets for tailored interventions, theory development, and participation models.
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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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".