The ACSI-28: An examination of the instrument's factorial validity and psychometric structure with adult recreational runners
Bibliographic record
Abstract
The Athletic Coping Skills Inventory-28 (ACSI-28) is a validated psychometric tool used to identify skills to be included in psychological skills training programs, and for predicting sports injuries, clutch performers, and survival in sports. The ACSI-28 has been used with predominantly competitive, team-based athletes. The purpose of this study was to examine the psychometric properties of the ACSI-28 to determine its suitability for use with individual recreational runners (RRs). Our sample included 364 adult runners, of which 308 self assessed themselves as RR and 56 as competitive runners. Overall, they had been running between one to 50 years (M = 10.80, SD = 9.97), and had completed events of various distances ranging from 5km (90%) to full marathon (42.2 km, 43%). Factor analyses of the RR data retained only 4-factors (Goal Setting and Planning, Confidence and Motivation, Freedom From Worry, and Peaking Under Pressure) from the original 7-factor structure, and these were consolidated into the 3-factor ACSI-RR (15, 3) model. Overall the results indicate that the original ACSI-28 may not be as suitable for RRs as the much smaller ACSI-RR (15, 3) model, which offered superior data fit. Implications of these findings and direction for future research will be discussed.
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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 | 0.010 | 0.015 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".