An Exploratory Investigation of the Relationship between Proxy Efficacy, Self-efficacy and Exercise Attendance
Bibliographic record
Abstract
The purpose of the study was to examine the relationship between perceptions of self-efficacy, proxy efficacy, and exercise class attendance of participants involved in a 10-week structured group fitness program. At week 3, 127 females completed measures of self-efficacy and proxy efficacy and their class attendance was monitored for the subsequent four weeks. Self-efficacy was assessed through measures of exercise, scheduling, and barrier self-efficacy. Proxy efficacy was assessed through a measure of fitness instructor efficacy defined as participants' confidence in their fitness instructors' communication, teaching, and motivating capabilities. Results revealed positive correlations between self-efficacy variables and proxy efficacy. Hierarchical multiple regression analyses indicated that among those who were classified as exercise initiates (n = 33), self-efficacy and proxy efficacy accounted for 34 percent of the variance in exercise class attendance with the latter variable explaining a unique 12 percent. Consistent with theorizing, these preliminary findings indicate that for instructor-led, group physical activities such as aerobics classes, proxy efficacy perceptions are related to self-efficacy and may also be an important predictor of exercise behavior.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".