The Role of Passion and Achievement Goals in Optimal Functioning in Sports
Bibliographic record
Abstract
This study aimed to test the role of passion in the cognitive goals pursued in sport and the level of Optimal Functioning in Society (OFIS) derived from such sport engagement. A total of 184 competitive water polo and synchronized swimming athletes completed a questionnaire assessing their passion for their sport, achievement goals, and various scales assessing their level of OFIS (e.g., subjective well-being, relationship with their coach, sport performance, and intentions to continue in sport). It was hypothesized that harmonious passion (HP) would be positively associated with mastery goals while obsessive passion (OP) would be positively associated with mastery, performance-approach, and performance-avoidance goals. In turn, mastery goals were expected to positively lead to the four components of OFIS, whereas performance-approach and performance-avoidance goals should display less adaptive relationships with OFIS. The results of a path analysis generally supported the proposed model. As hypothesized, these findings suggest that HP leads to a more adaptive cognitive engagement in sport (than OP) that, in turn, fosters higher levels of optimal functioning.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".