The interplay of perceived stress, self-determination and school engagement in adolescence
Bibliographic record
Abstract
Currently, many societies are placing a greater onus on academic achievement–resulting in higher levels of stress being observed among adolescent students. Stress can have detrimental repercussions on adolescents’ health and is also associated with anxiety and depression. However, since less is known about how high stress levels affect school engagement, this study examined the interplay of perceived stress and school engagement in a large sample of seventh and eighth grade students ( N = 1088; M Age = 13.7) in secondary schools in Brandenburg, Germany. Based on self-determination theory (SDT), this study also examined if perceived autonomy, relatedness, and competence mediated the association between stress and school engagement in order to identify possible strategies for intervention and prevention. Latent structural equation modeling (SEM) was used to test for the associations between stress, self-determination, and school engagement. Results showed that self-determination acted as a full mediator in the negative association between stress and school engagement. These results suggest that supporting students’ basic psychological needs for autonomy, relatedness, and competence could be an effective starting point for prevention and intervention of stress and its negative association with school engagement. Consequently, SDT has strong implications for both school psychologists as well as teachers.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".