Using the Anxiety Sensitivity Index-3 With Athletes: A Psychometric Evaluation of Factor Structure and Measurement Invariance
Bibliographic record
Abstract
To meaningfully use the Anxiety Sensitivity Index-3 (ASI-3) with athletes, measurement invariance must be established. Thus, we sought to determine appropriate factor structures for the ASI-3 in an athlete sample, assess measurement invariance between an athlete sample and a less active sample, and compare ASI-3 scores between these groups. Two university student samples were recruited: an athlete sample ( n = 216) and a less active control sample ( n = 321). Results supported bifactor and hierarchical factor structures for the ASI-3 overall and in the athlete sample. Measurement invariance of these factor structures was established. ASI-3 score comparisons indicated that the athlete sample had significantly lower levels of global anxiety sensitivity, and lower physical and social concerns. Results support the use of the ASI-3 to address mental health concerns in athletes and permit meaningful comparisons between athletes and nonathletes using the ASI-3 and its subscales.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".