Stages of Change for Healthy Eating in Diabetes
Bibliographic record
Abstract
OBJECTIVES: To identify diabetes-related characteristics of individuals at different stages of readiness to change to healthy, low-fat eating. RESEARCH DESIGN AND METHODS: Stage-based differences in demographic, eating-related, health care utilization, and psychosocial factors were examined in a sample of 768 overweight (BMI >27 kg/m(2)) individuals with diabetes enrolled in a randomized behavioral intervention trial. RESULTS: Stage-based differences occurred for type 1 diabetic participants on percent of calories from fat and number of daily vegetable servings. For type 2 diabetic participants, sex, disease-specific quality of life, percent calories from fat, and number of daily vegetables servings differed across stages. Those in action stages were more likely to be female and have a better quality of life and healthier eating habits. Type 2 diabetic insulin-requiring participants in action stages were more likely to be married. Social support was highest for those in the contemplation stage and lowest for those in the action stage. Type 2 diabetic participants on pills in the action stages were older, had a lower BMI, ate more fruit, were nonsmokers, recently attended diabetes education, had a better quality of life and social support, and had less stress. One anomalous finding for type 2 diabetic participants was that precontemplators scored similarly to those in action stages. CONCLUSIONS: These data validate the Transtheoretical Model, where those in the action stages displayed healthier eating. They also indicate that demographic and psychosocial factors may mediate readiness to change diet. Precontemplators were a heterogeneous group and may need individually tailored interventions.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".