Evaluating the Acceptability and Feasibility of a Sexual Health–Focused Contraceptive Decision Aid for Diverse Young Adults: User-Centered Usability Study
Bibliographic record
Abstract
BACKGROUND: Young adults with low sexual health literacy levels may find it difficult to make informed decisions about contraceptive methods. We developed and pilot-tested a web-based decision aid-Healthy Sex Choices-designed to support diverse young adults with their contraceptive decision-making. OBJECTIVE: This pilot study aimed to evaluate whether the Healthy Sex Choices decision aid is acceptable and feasible to patients and clinicians. METHODS: We used the Ottawa Decision Support Framework and the International Patient Decision Aid Standards to develop and pilot the decision tool. We first conducted a needs assessment with our advisory panel (5 clinicians and 2 patients) that informed decision aid development. All panelists participated in semistructured interviews about their experience with contraceptive counseling. Clinicians also completed a focus group session centered around the development of sex education content for the tool. Before commencing the pilot study, 5 participants from ResearchMatch (Vanderbilt University Medical Center) assessed the tool and suggested improvements. RESULTS: Participants were satisfied with the tool, rating the acceptability as "good." Interviewees revealed that the tool made contraceptive decision-making easier and would recommend the tool to a family member or friend. Participants had a nonsignificant change in knowledge scores (53% before vs 45% after; P=.99). Overall, decisional conflict scores significantly decreased (16.1 before vs 2.8 after; P<.001) with the informed subscale (patients feeling more informed) having the greatest decline (23.1 vs 4.7; mean difference 19.0, SD 27.1). Subanalyses of contraceptive knowledge and decisional conflict illustrated that participants of color had lower knowledge scores (48% vs 55%) and higher decisional conflict (20.0 vs 14.5) at baseline than their white counterparts. CONCLUSIONS: Participants found Healthy Sex Choices to be acceptable and reported reduced decisional conflict after using the tool. The development and pilot phases of this study provided a foundation for creating reproductive health decision aids that acknowledge and provide guidance for diverse patient populations.
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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 | 0.023 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".