Strategies to Optimize Participation in Diabetes Prevention Programs following Gestational Diabetes: A Focus Group Study
Bibliographic record
Abstract
OBJECTIVE: We performed a qualitative study among women within 5 years of Gestational Diabetes (GDM) diagnosis. Our aim was to identify the key elements that would enhance participation in a type 2 diabetes (DM2) prevention program. RESEARCH DESIGN AND METHODS: Potential participants received up to three invitation letters from their GDM physician. Four focus groups were held. Discussants were invited to comment on potential facilitators/barriers to participation and were probed on attitudes towards meal replacement and Internet/social media tools. Recurring themes were identified through qualitative content analysis of discussion transcripts. RESULTS: Among the 1,201 contacted and 79 eligible/interested, 29 women attended a focus group discussion. More than half of discussants were overweight/obese, and less than half were physically active. For DM2 prevention, a strong need for social support to achieve changes in dietary and physical activity habits was expressed. In this regard, face-to-face interactions with peers and professionals were preferred, with adjunctive roles for Internet/social media. Further, direct participation of partners/spouses in a DM2 prevention program was viewed as important to enhance support for behavioural change at home. Discussants highlighted work and child-related responsibilities as potential barriers to participation, and emphasized the importance of childcare support to allow attendance. Meal replacements were viewed with little interest, with concerns that their use would provide a poor example of eating behaviour to children. CONCLUSIONS: Among women within 5 years of a GDM diagnosis who participated in a focus group discussion, participation in a DM2 prevention program would be enhanced by face-to-face interactions with professionals and peers, provision of childcare support, and inclusion of spouses/partners.
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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 | 0.013 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| 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".