Prediction of Leisure‐time Physical Activity Among Obese Individuals
Bibliographic record
Abstract
The aims of this study were to identify (i) what cognitions predict leisure-time physical activity and (ii) the moderators of cognition-behavior relationships among obese individuals. A sample of 91 adults (BMI >or=30 kg/m(2)) completed a baseline questionnaire assessing variables of the theory of planned behavior (TPB). Biological measures and socio-demographic variables were also obtained. Behavior was assessed 3 months later. Multiple hierarchical regression analyses indicated that significant variables predicting behavior were past behavior (beta = 0.39; P = 0.0001), intention (beta = 0.27; P = 0.03), and the interaction term "perceived behavioral control (PBC) x perceived built environment" (beta = 0.17; P = 0.05). The PBC-behavior relation was better when the built environment was perceived as favorable to physical activity. The model explained 41% of variance in behavior. The determinants explaining intention were PBC (beta = 0.55; P < 0.0001), anticipated regret (beta = 0.26; P = 0.0007), and past behavior (beta = 0.22; P = 0.005), accounting for 59% of variance. Participation in leisure-time physical activity is explained primarily by a person's intentions to perform this behavior. The results also suggest that people are more able to translate their perception of control into action if they perceive the built environment as favorable, although this additional gain in prediction is small relative to intention. Nonetheless, both cognitions and aspects of the built environment should be given consideration in the promotion of leisure-time physical activity among obese individuals.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".