Sustained behaviour change in healthy eating to improve obesity outcomes: It is time to abandon willpower to appreciate wanting
Bibliographic record
Abstract
The purpose of this study was to report on a nationally representative survey of the experience of Canadian adults regarding food cravings and the impact of these cravings on behaviour and quality of life. A total of 1532 respondents (16% of members of an online panel emailed an invitation and link) completed a nationally distributed survey. Almost two-thirds of the sample reported experiencing cravings, with women being more likely to report cravings than men. Of those with cravings, 83.1% reported moderate or strong cravings. Cravings impacted eating behaviours and quality of life, especially for those with strong cravings. Cravings were associated with being bored, emotional or watching TV. Those who identified themselves as overweight or as trying to lose weight were more likely to have cravings. Of those reporting to be overweight and trying to lose weight few experienced distress because of lack of access to help and rates of interest in being guided by healthcare professionals were low, except in those with strong cravings. These results reinforce the notion that eating behaviour may differ from other behaviours in that there is a strong drive to eat that is difficult to control for many individuals. Behavioural interventions targeting healthy eating should be developed to address this construct of drive to eat, that is, food cravings.
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 | 0.012 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".