Quality Improvement Pilot Study of the Living Your Best Weight Program: A Health at Every Size Approach
Bibliographic record
Abstract
Purpose: Living Your Best Weight (LYBW) is an outpatient program based on Health at Every Size (HAES) principles for adults interested in managing their weight. The purpose of this pilot study was to determine perceptions of participants and their satisfaction with the LYBW program. Methods: A survey was developed to determine participant satisfaction of the LYBW program. Fifty-six participants who completed the LYBW program from June 2017 to February 2018 were contacted via telephone and invited to participate in the study. Forty-five participants agreed to receive the survey by mail or email. Results: Thirty-four participants completed the survey for a response rate of 61%. The average age of respondents was 52 years. Seventy-nine percent of respondents agreed that the program helped them to focus on health instead of weight. Eighty-two percent agreed that the program helped them respond to internal cues of hunger and fullness, and 94% were satisfied with the program. Conclusion: Participants reported that they were satisfied with the LYBW program and perceived improvements in their health. Future programming may benefit from using a HAES-based approach with adults.
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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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".