When Passion Does Not Change, but Emotions Do: Testing a Social Media Intervention Related to Exercise Activity Engagement
Bibliographic record
Abstract
Grounded in self-determination theory and the dualistic model of passion, the present study tested whether a social media intervention could promote harmonious passion and positive emotions related to exercise activities. A four-week intervention managed through an Instagram account was designed to promote more harmonious passion and less obsessive passion, as well as more positive emotions and less negative emotions related to participants’ favourite exercise activities. A web-based questionnaire was distributed to 518 young adults (mean age 26.5) before and after the intervention. Participants were randomly assigned to an intervention group (N = 226) or control group (N = 292). The intervention did not predict change in passion for the activity. However, the intervention predicted more positive emotional outcomes from the activity, statistically controlled for emotions reported at baseline and negative emotions reported at follow-up. Results indicate that digital platforms may be relevant in promoting more physical activity in the population, through the facilitation of more positive emotions related to exercise.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".