Action Control of Exercise Behavior: Evaluation of Social Cognition, Cross-Behavioral Regulation, and Automaticity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Intention is considered the proximal determinant of behavior in many popular theories applied to understanding physical activity, yet intention-behavior discordance is high. Thus, an understanding of constructs that facilitate or inhibit the successful translation of intentions into behavior is both timely and important. The action control approach of dividing the intention-behavior relationship into quadrants of successful/unsuccessful intenders has shown utility in the past by demonstrating the magnitude of intention-behavior discordance and allowing for an outcome variable to test predictors. The purpose of this article was to evaluate automaticity and cross-behavioral regulation as predictors of exercise action control, in conjunction with other more standard social cognitive predictors of perceived behavioral control and affective and instrumental attitudes. Participants were a random sample of 263 college students who completed predictor measures at time one, followed by exercise behavior two weeks later. Participants were classified into three intention-behavior profiles: (1) nonintenders (14.1%; n = 31), (2) unsuccessful intenders (35.5%; n = 78), and (3) successful intenders (48.6%; n = 107). Affective attitude, perceived behavioral control, automaticity, and cross-behavioral regulation were predictors of action control. The results demonstrate that automaticity and cross-behavioral regulation, constructs not typically used in intention-based theories, predict intention-behavior discordance.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 it