The adoption of physical activity and eating behaviors among persons with obesity and in the general population: the role of implicit attitudes within the Theory of Planned Behavior
Bibliographic record
Abstract
Obesity can be prevented by the combined adoption of a regular physical activity (PA) and healthy eating behaviors (EB). Researchers mainly focused on socio-cognitive models, such as the Theory of Planned Behavior (TPB), to identify the psychological antecedents of these behaviors. However, few studies were interested in testing the potential contribution of automatic processes in the prediction of PA and EB. Thus, the main objective of this study was to explore the specific role of implicit attitudes in the pattern of prediction of self-reported PA and EB in the TPB framework, among persons with obesity and in adults from the general population. One hundred and fifty-three adults participated to this cross-sectional study among which 59 obese persons (74% women, age: 50.6 ± 12.3 years, BMI: 36.8 ± 4.03 kg m–²) and 94 people from the general population (51% women; age: 34.7 ± 8.9 years). Implicit attitudes toward PA and EB were estimated through two Implicit Association Tests. TPB variables, PA and EB were assessed by questionnaire. Regarding to the prediction of PA, a significant contribution of implicit attitudes emerged in obese people, β = .25; 95%[CI: .01, .50]; P = .044, beyond the TPB variables, contrary to participants from the general population. The present study suggests that implicit attitudes play a specific role among persons with obesity regarding PA. Other studies are needed to examine which kind of psychological processes are specifically associated with PA and EB among obese people.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".