PREVIEW study—influence of a behavior modification intervention (PREMIT) in over 2300 people with pre-diabetes: intention, self-efficacy and outcome expectancies during the early phase of a lifestyle intervention
Bibliographic record
Abstract
Purpose: Onset of type 2 diabetes (T2D) is often gradual and preceded by impaired glucose homeostasis. Lifestyle interventions including weight loss and physical activity may reduce the risk of developing T2D, but adherence to a lifestyle change is challenging. As part of an international T2D prevention trial (PREVIEW), a behavior change intervention supported participants in achieving a healthier diet and physically active lifestyle. Here, our aim was to explore the influence of this behavioral program (PREMIT) on social-cognitive variables during an 8-week weight loss phase. Methods: PREVIEW consisted of an initial weight loss, Phase I, followed by a weight-maintenance, Phase II, for those achieving the 8-week weight loss target of ≥ 8% from initial bodyweight. Overweight and obese (BMI ≥25 kg/m2) individuals aged 25 to 70 years with confirmed pre-diabetes were enrolled. Uni- and multivariate statistical methods were deployed to explore differences in intentions, self-efficacy, and outcome expectancies between those who achieved the target weight loss (“achievers”) and those who did not (“non-achievers”). Results: At the beginning of Phase I, no significant differences in intentions, self-efficacy and outcome expectancies between “achievers” (1,857) and “non-achievers” (163) were found. “Non-achievers” tended to be younger, live with child/ren, and attended the PREMIT sessions less frequently. At the end of Phase I, “achievers” reported higher intentions (healthy eating χ 2 (1) =2.57; P <0.008, exercising χ 2 (1) =0.66; P <0.008), self-efficacy (F (2; 1970) =10.27, P <0.005), and were more positive about the expected outcomes (F (4; 1968) =11.22, P <0.005). Conclusion: Although statistically significant, effect sizes observed between the two groups were small. Behavior change, however, is multi-determined. Over a period of time, even small differences may make a cumulative effect. Being successful in behavior change requires that the “new” behavior is implemented time after time until it becomes a habit. Therefore, having even slightly higher self-efficacy, positive outcome expectancies and intentions may over time result in considerably improved chances to achieve long-term lifestyle changes. Keywords: diabetes mellitus, weight loss, goals, habits, cognition
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".