Middle-aged women’s decisions about body weight management
Bibliographic record
Abstract
OBJECTIVE: This study aims to assess middle-aged women's needs when making body weight management decisions and to evaluate a knowledge translation tool for addressing their needs. METHODS: A mixed-methods study used an interview-guided theory-based survey of professional women aged 40 to 65 years. The tool summarized evidence to address their needs and enabled women to monitor actions taken. Acceptability and usability were reported descriptively. RESULTS: Sixty female participants had a mean body mass index of 28.0 kg/m(2) (range, 17.0-44.9 kg/m(2)), and half were premenopausal. Common options for losing (82%) or maintaining (18%) weight included increasing physical activity (60%), eating healthier (57%), and getting support (40%). Decision-making involved getting information on options (52%), soliciting others' decisions/advice (20%), and being self-motivated (20%). Preferred information sources included written information (97%), counseling (90%), and social networking websites (43%). Five professionals (dietitian, personal trainer, occupational therapist, and two physicians) had similar responses. Of 53 women sent the tool, 27 provided acceptability feedback. They rated it as good to excellent for information on menopause (96%), body weight changes (85%), and managing body weight (85%). Most would tell others about it (81%). After 4 weeks of use, 25 women reported that the wording made sense (96%) and that the tool had clear instructions (92%) and was easy to use across time (88%). The amount of information was rated as just right (64%), but the tool had limited space for responding (72%). CONCLUSIONS: When making decisions about body weight management, women's needs were "getting information" and "getting support." The knowledge translation tool was acceptable and usable, but further evaluation is required.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| 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".