Toward a better assessment of perceived social influence: The relative role of significant others on young athletes
Bibliographic record
Abstract
The purpose of this three-study paper was to develop and validate the Perceived Social Influence in Sport Scale-2 (PSISS-2) that aimed to resolve the limitations of PSISS-1 in assessing the relative social influence of significant others in youth sport. In Study 1, a pool of 60 items generated from revisiting a qualitative dataset about significant others of young athletes were examined by two expert panel reviews in terms of content validity, clarity, coverage, and age-appropriateness, leading to the development of 16 items of the PSISS-2. In Study 2, multi-group exploratory structural equation model for PSISS-2 was conducted among 904 young athletes, and the results supported a model comprising positive influence (ie, conditional and unconditional positive influence combined), punishment (ie, conditional negative influence), and dysfunction (ie, unconditional negative influence) as three factors. The goodness of fit of the three-factor model was acceptable and invariant across the coach-, father-, mother-, and teammates-versions of PSISS-2. In support of the criterion validity of PSISS-2, the three factors explained substantial variance of young athletes' perceived competence, effort, enjoyment, and trait anxiety in sport. Study 3 examined the relationship between PSISS-2 factors, psychological need support, and controlling behaviors in a subsample of 452 young athletes, and the findings supported the concurrent validity and discriminant validity of the scale. In conclusion, the data are supportive of PSISS-2. The three factors of the scale (ie, positive influence, punishment, and dysfunction) may form a new framework for understanding and comparing the relative role of significant others in youth sport.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".