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
Maija Huttunen-Lenz,1 Sylvia Hansen,1 Pia Christensen,2 Thomas Meinert Larsen,2 Finn Sandø-Pedersen,2 Mathijs Drummen,3 Tanja C Adam,3 Ian A Macdonald,4,5 Moira A Taylor,5 J Alfredo Martinez,6–8 Santiago Navas-Carretero,6–8 Svetoslav Handjiev,9 Sally D Poppitt,10 Marta P Silvestre,10 Mikael Fogelholm,11 Kirsi H Pietiläinen,12,13 Jennie Brand-Miller,14 Agnes AM Berendsen,15 Anne Raben,2 Wolfgang Schlicht1 1Department of Exercise and Health Sciences, University of Stuttgart, Stuttgart, Germany; 2Department of Nutrition, Exercise and Sports, Faculty of Science, University of Copenhagen, Copenhagen, Denmark; 3Department of Nutrition and Movement Sciences, Maastricht University, Maastricht, the Netherlands; 4MRC/ARUK Centre for Musculoskeletal Ageing Research, National Institute for Health Research (NIHR) Nottingham Biomedical Research Centre, School of Life Sciences, University of Nottingham, Nottingham, UK; 5School of Life Sciences, University of Nottingham Medical School, Nottingham, UK; 6Center for Nutrition Research at the University of Navarra, Pamplona, Spain; 7Madrid Institute of Advanced Studies (IMDEA Food), Madrid, Spain; 8Biomedical Research Centre Network in Physiopathology of Obesity and Nutrition (CIBERobn), Carlos III Institute, Madrid, Spain; 9Department of Pharmacology and Toxicology, Medical University – Sofia, Sofia, Bulgaria; 10Human Nutrition Unit, School of Biological Sciences, University of Auckland, Auckland, New Zealand; 11Department of Food and Nutrition, University of Helsinki, Helsinki, Finland; 12Obesity Research Unit, Research Program Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland; 13Abdominal Center, Endocrinology, Helsinki University Central Hospital, University of Helsinki, Helsinki, Finland; 14Charles Perkins Centre and School of Life and Environmental Biosciences, University of Sydney, Camperdown, NSW, Australia; 15Division of Human Nutrition & Health, Wageningen University & Research, Wageningen, the Netherlands 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 χ2(1)=2.57; P <0.008, exercising χ2(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
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".