Basic Psychological Need Satisfaction as Correlates of Physical Activity Trajectories During Adolescence
Bibliographic record
Abstract
This analysis aimed to (1) identify longitudinal joint trajectories of participation in organized and unorganized physical activity contexts, and level of daily moderate-to-vigorous physical activity (MVPA) and (2) assess whether basic psychological need satisfaction during adolescence differentiates between membership in different physical activity trajectories. Participants (n = 888; 56% girls) reported their involvement in 36 different physical activities, level of MVPA, and their perceived satisfaction of competence, autonomy, and relatedness satisfaction in physical activity up to three times per year, over 8 years (from ages 10 to 17 years). Group-based multi-trajectory models were used to identify longitudinal joint trajectories of physical activity participation. We estimated a multinomial logistic regression model for membership in a physical activity trajectory by including individual-level intercepts and slopes for each psychological need obtained using mixed models over the 24 cycles modelized as natural cubic splines. Five longitudinal trajectory groups emerged: Non-participants, Dropouts, Active in unorganized physical activities, Active in organized physical activities, and Active through a variety of activities. Relative to Non-participants, we identify a dose-response relationship in baseline competence and membership in the higher active trajectory groups. In addition, a positive change in competence in early adolescence predicted membership in all three Active trajectory groups.
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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".