User-Centered Development of a Patient Decision Aid for Choice of Early Abortion Method: Multi-Cycle Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: People seeking abortion in early pregnancy have the choice between medication and procedural options for care. The choice is preference-sensitive-there is no clinically superior option and the choice depends on what matters most to the individual patient. Patient decision aids (PtDAs) are shared decision-making tools that support people in making informed, values-aligned health care choices. OBJECTIVE: We aimed to develop and evaluate the usability of a web-based PtDA for the Canadian context, where abortion care is publicly funded and available without legal restriction. METHODS: We used a systematic, user-centered design approach guided by principles of integrated knowledge translation. We first developed a prototype using available evidence for abortion seekers' decisional needs and the risks, benefits, and consequences of each option. We then refined the prototype through think-aloud interviews with participants at risk of unintended pregnancy ("patient" participants). Interviews were audio-recorded and documented through field notes. Finally, we conducted a web-based survey of patients and health care professionals involved with abortion care, which included the System Usability Scale. We used content analysis to identify usability issues described in the field notes and open-ended survey questions, and descriptive statistics to summarize participant characteristics and close-ended survey responses. RESULTS: A total of 61 individuals participated in this study. Further, 11 patients participated in think-aloud interviews. Overall, the response to the PtDA was positive; however, the content analysis identified issues related to the design, language, and information about the process and experience of obtaining abortion care. In response, we adapted the PtDA into an interactive website and revised it to include consistent and plain language, additional information (eg, pain experience narratives), and links to additional resources on how to find an abortion health care professional. In total, 25 patients and 25 health care professionals completed the survey. The mean System Usability Scale score met the threshold for good usability among both patient and health care professional participants. Most participants felt that the PtDA was user-friendly (patients: n=25, 100%; health care professionals: n=22, 88%), was not missing information (patients: n=21, 84%; health care professionals: n=18, 72%), and that it was appropriate for patients to complete the PtDA before a consultation (patients: n=23, 92%; health care professionals: n=23, 92%). Open-ended responses focused on improving usability by reducing the length of the PtDA and making the website more mobile-friendly. CONCLUSIONS: We systematically designed the PtDA to address an unmet need to support informed, values-aligned decision-making about the method of abortion. The design process responded to a need identified by potential users and addressed unique sensitivities related to reproductive health decision-making.
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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 | 0.056 | 0.064 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| 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".