Assessing and Promoting Cardiovascular Health for Adolescent Women: User-Centered Design Approach
Bibliographic record
Abstract
BACKGROUND: Cardiovascular disease (CVD) is the leading cause of death among women in the United States. A considerable number of young women already have risk factors for CVD. Awareness of CVD and its risk factors is critical to preventing CVD, yet younger women are less aware of CVD prevalence, its risk factors, and preventative behaviors compared to older women. OBJECTIVE: The purpose of this study is to assess CVD awareness among adolescent and young adult women and develop a lifestyle-based cardiovascular risk assessment tool for the promotion of CVD awareness among this population. METHODS: This study used a 3-phase iterative design process with young women and health care practitioners from primary care and reproductive care clinics in Atlanta, Georgia. In phase 1, we administered a modified version of the American Heart Association Women's Health Survey to young women, aged 15-24 years (n=67), to assess their general CVD awareness. In phase 2, we interviewed young women, aged 13-21 years (n=10), and their health care practitioners (n=10), to solicit suggestions for adapting the Healthy Heart Score, an existing adult cardiovascular risk assessment tool, for use with this age group. We also aimed to learn more about the barriers and challenges to health behavior change within this population and the clinical practices that serve them. In phase 3, we used the findings from the first 2 phases to create a prototype of a new online cardiovascular risk assessment tool designed specifically for young women. We then used an iterative user-centered design process to collect feedback from approximately 105 young women, aged 13-21 years, as we adapted the tool. RESULTS: Only 10.5% (7/67) of the young women surveyed correctly identified CVD as the leading cause of death among women in the United States. Few respondents reported having discussed their personal risk (4/67, 6%) or family history of CVD (8/67, 11.9%) with a health care provider. During the interviews, young women reported better CVD awareness and knowledge after completing the adult risk assessment tool and suggested making the tool more teen-friendly by incorporating relevant foods and activity options. Health care practitioners emphasized shortening the assessment for easier use within practice and discussed other barriers adolescents may face in adopting heart-healthy behaviors. The result of the iterative design process was a youth-friendly prototype of a cardiovascular risk assessment tool. CONCLUSIONS: Adolescent and young adult women demonstrate low awareness of CVD. This study illustrates the potential value of a cardiovascular risk assessment tool adapted for use with young women and showcases the importance of user-centered design when creating digital health interventions.
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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 | 0.054 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".