Tailoring of Health-Promotion Video Messaging for Reproductive-Aged Women at Risk for Developing Cardiometabolic Disease: Qualitative Focus-Groups Study
Bibliographic record
Abstract
BACKGROUND: Targeting reproductive-aged women at high risk for type 2 diabetes (T2D) provides an opportunity for prevention earlier in the life course. A woman's experiences during her reproductive years may have a large impact on her future risk of T2D. Her risk is 7 to 10 times higher if she has had gestational diabetes (GDM). Despite these risks, T2D is preventable. Evidence-based programs, such as the National Diabetes Prevention Program (DPP), can reduce the risk of developing T2D by nearly 60%. However, only 0.4% of adults with prediabetes have participated in the DPP to date and reproductive-aged women are 50% less likely to participate than older women. In prior work, our team developed a mobile 360° video to address diabetes risk awareness and promote DPP enrollment among at-risk adults; this video was not designed, however, for reproductive-aged women. OBJECTIVE: This study aims to obtain feedback from reproductive-aged women with cardiometabolic disease risk about a 360° video designed to promote enrollment in the DPP, and to gather suggestions about tailoring video messages to reproductive-aged women. METHODS: Focus groups and a qualitative descriptive approach were used. Women with at least 1 previous pregnancy, aged 18 to 40 years, participated in one of three focus groups stratified by the following health risks: (1) a history of GDM or a hypertensive disorder of pregnancy, (2) a diagnosis of prediabetes, or (3) a BMI classified as obese. Focus-group questions addressed several topics; this report shared findings regarding video feedback. The 3 focus-group discussions were conducted via Zoom and were recorded and transcribed for analysis. Deductive codes were used to identify concepts related to the research question and inductive codes were created for novel insights shared by participants. The codes were then organized into categories and themes. RESULTS: The main themes identified were positive feedback, negative feedback, centering motherhood, and the importance of storytelling. While some participants said the video produced a sense of urgency for health-behavior change, all participants agreed that design changes could improve the video's motivating effect on health-behavior change in reproductive-aged women. Participants felt a tailored video should recognize the complexities of being a mother and how these dynamics contribute to women's difficulty engaging in healthy behaviors without stirring feelings of guilt. Women desired a video with a positive, problem-solving perspective, and recommended live links as clickable resources for practical solutions promoting health behavior change. Women suggested using storytelling, both to describe how complications experienced during pregnancy impact long-term health and to motivate health behavior change. CONCLUSIONS: Reproductive-aged women require tailored lifestyle-change messaging that addresses barriers commonly encountered by this population (eg, parenting or work responsibilities). Moreover, messaging should prioritize a positive tone that harnesses storytelling and human connection while offering realistic solutions.
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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 | 0.017 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".