Evaluating the Acceptability and Feasibility of a Sexual Health–Focused Contraceptive Decision Aid for Diverse Young Adults: User-Centered Usability Study (Preprint)
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 | 0.027 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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) | 0.002 | 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".