A Smartphone App Designed to Empower Patients to Contribute Toward Safer Surgical Care: Qualitative Evaluation of Diverse Public and Patient Perceptions Using Focus Groups
Bibliographic record
Abstract
BACKGROUND: MySurgery is a smartphone app designed to empower patients and their caregivers to contribute toward safer surgical care by following practical advice to help reduce susceptibility to errors and complications. OBJECTIVE: The aim of this study is to evaluate service users' perceptions of MySurgery, including its perceived acceptability, the potential barriers and facilitators to accessing and using its content, and ideas about how to facilitate its effective implementation. The secondary aim is to analyze how the intended use of the app might differ for diverse patients, including seldom-heard groups. METHODS: We implemented a diversity approach to recruit participants from a range of backgrounds with previous experience of surgery. We aimed to achieve representation from seldom-heard groups, including those from a Black, Asian, and minority ethnic (BAME) background; those with a disability; and those from the lesbian, gay, bisexual, transgender, queer (LGBT+) community. A total of 3 focus groups were conducted across a 2-month period, during which a semistructured protocol was followed to elicit a rich discussion around the app. The focus groups were audio recorded, and thematic analysis was carried out. RESULTS: In total, 22 individuals participated in the focus groups. A total of 50% (n=11) of the participants were from a BAME background, 59% (n=13) had a disability, and 36% (n=8) were from the LGBT+ community. There was a strong degree of support for the MySurgery app. The majority of participants agreed that it was acceptable and appropriate in terms of content and usability, and that it would help to educate patients about how to become involved in improving safety. The checklist-like format was popular. There was rich discussion around the accessibility and inclusivity of MySurgery. Specific user groups were identified who might face barriers in accessing the app or acting on its advice, such as those with visual impairments or learning difficulties and those who preferred to take a more passive role (eg, some individuals because of their cultural background or personality type). The app could be improved by signposting further specialty-specific information and incorporating a calendar and notes section. With regard to implementation, it was agreed that use of the app should be signposted before the preoperative appointment and that training and education should be provided for clinicians to increase awareness and buy-in. Communication about the app should clarify its scientific basis in plain English and should stress that its use is optional. CONCLUSIONS: MySurgery was endorsed as a powerful tool for enhancing patient empowerment and facilitating the direct involvement of patients and their caregivers in maintaining patient safety. The diversity approach allowed for a better understanding of the needs of different population groups and highlighted opportunities for increasing accessibility and involvement in the app.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".