‘It’s not a diet, it’s a lifestyle’: a longitudinal, data-prompted interview study of weight loss maintenance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Objective: To advance understanding of the individual and environmental factors underpinning weight loss maintenance. Design: Semi-structured, data-prompted interviews were conducted with twelve overweight adult participants (three men, nine women) who had lost over 5% of their body weight in the year before baseline. Participants gathered daily data through wireless scales, activity monitors (Fitbit™), ecological momentary assessment and experience sampling (taking photographs, writing notes). They were interviewed at 3- and 6-months post baseline. Interview stimuli included personal data of weight and activity graphs, correlations of psychological factors, and self-generated notes and photographs. Interview data were analysed using the Framework Method, applying pre-specified maintenance-relevant theoretical themes. Results: The theoretical Framework provided a good fit for the narratives, with five main themes underpinning successful weight loss maintenance: sustained motivation, effective self-regulation, plentiful resources, habit formation and a supportive environment. Additionally, participants reported an identity shift from being a dieter to accepting a new healthy lifestyle. Goal prioritising and allowing for occasional controlled lapses enhanced weight loss maintenance. Conclusions: This study successfully used the novel method of data-prompted interviews to explore weight loss maintenance experiences with new explanations emerging from the data. Future research should further develop behaviour change maintenance theory and data-prompted interview method.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 it