Behavioral, normative and control beliefs underlying low-fat dietary and regular physical activity behaviors for adults diagnosed with type 2 diabetes and/or cardiovascular disease
Bibliographic record
Abstract
Promoting healthy lifestyle behaviors is an important aspect of interventions designed to improve the management of chronic diseases such as Type 2 diabetes and cardiovascular disease. The present study used Ajzen's (1991) theory of planned behavior as a framework to examine beliefs amongst adults diagnosed with these conditions who do and do not engage in low-fat dietary and regular physical activity behaviors. Participants (N = 192) completed a questionnaire assessing their behavioral, normative and control beliefs in relation to regular, moderate physical activity and eating foods low in saturated fats. Measures of self-reported behavior were also examined. The findings revealed that, in general, it is the underlying behavioral beliefs that are important determinants for both physical activity and low-fat food consumption with some evidence to suggest that pressure from significant others is an important consideration for low-fat food consumption. Laziness, as a barrier to engaging in physical activity, also emerged as an important factor. To encourage a healthy lifestyle amongst this population, interventions should address the perceived costs associated with behavioral performance and encourage people to maintain healthy behaviors in light of these costs.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".