Abstract P202: Is There a Relationship Between the Psychological Influence of the Highly Palatable Food Environment and Weight Loss Attempts?
Bibliographic record
Abstract
Background: Research suggests that the degree of food desirability may have an impact on successful weight loss. Defined as susceptibility to eating when presented with environmental stimuli, hedonic hunger is related to increased food consumption. Individuals with higher hedonic hunger may be less able to successfully maintain weight loss and, therefore, may have more weight loss attempts (WLA). The purpose was to examine associations between the number of WLA and the PFS total scale and subscale scores, controlling for race, sex, BMI, and age. Methods: Participants were obese adults enrolled in Heads Up, an insurance-sponsored observational study examining surgical and non-surgical weight loss techniques. Individuals completed the Power of Food Scale (PFS) and demographic information, including the number of WLA. The PFS was developed to assess hedonic hunger when food is: 1) available, 2) present, and 3) tasted. Results: Of the 705 participants, 409 (57.8%) were Caucasian, 597 (84.3%) were female, and had attempted to lose weight 9.13 (SD=9.8) times. The number of WLA significantly predicted PFS total scores and subscale scores except for the “Food Tasted” subscale. The full linear regression models accounted for 4.7%, 4.1%, and 6.2% of the variance in the total PFS, Food Available subscale, and Food Present subscale scores, respectively. Conclusions: Results demonstrate that hedonic hunger may be a factor in repeated WLA. Future research should examine the temporal sequence to fully explain this relationship to provide additional tailoring of behavioral weight loss interventions to address hedonic hunger as a hindrance to successful weight maintenance.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 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".