General Practitioners' Perceptions of the Use of Wearable Electronic Health Monitoring Devices: Qualitative Analysis of Risks and Benefits
Bibliographic record
Abstract
BACKGROUND: The rapid diffusion of wearable electronic health monitoring devices (wearable devices or wearables) among lay populations shows that self-tracking and self-monitoring are pervasively expanding, while influencing health-related practices. General practitioners are confronted with this phenomenon, since they often are the expert-voice that patients will seek. OBJECTIVE: This article aims to explore general practitioners' perceptions of the role of wearable devices in family medicine and of their benefits, risks, and challenges associated with their use. It also explores their perceptions of the future development of these devices. METHODS: Data were collected during a medical conference among 19 Swiss general practitioners through mind maps. Maps were first sketched at the conference and their content was later compared with notes and reports written during the conference, which allowed for further integration of information. This tool represents an innovative methodology in qualitative research that allows for time-efficient data collection and data analysis. RESULTS: Data analysis highlighted that wearable devices were described as user-friendly, adaptable devices that could enable performance monitoring and support medical research. Benefits included support for patients' empowerment and education, behavior change facilitation, better awareness of personal medical history and body functioning, efficient information transmission, and connection with the patient's medical network; however, general practitioners were concerned by a lack of scientific validation, lack of clarity over data protection, and the risk of stakeholder-associated financial interests. Other perceived risks included the promotion of an overly medicalized health culture and the risk of supporting patients' self-diagnosis and self-medication. General practitioners also feared increased pressure on their workload and a compromised doctor-patient relationship. Finally, they raised important questions that can guide wearables' future design and development, highlighting a need for general practitioners and medical professionals to be involved in the process. CONCLUSIONS: Wearables play an increasingly central role in daily health-related practices, and general practitioners expressed a desire to become more involved in the development of such technologies. Described as useful information providers, wearables were generally positively perceived and did not seem to pose a threat to the doctor-patient relationship. However, general practitioners expressed their concern that wearables may fuel a self-monitoring logic, to the detriment of patients' autonomy and overall well-being. While wearables can contribute to health promotion, it is crucial to clarify the logic underpinning the design of such devices. Through the analysis of group discussions, this study contributes to the existing literature by presenting general practitioners' perceptions of wearable devices. This paper provides insight on general practitioners' perception to be considered in the context of product development and marketing.
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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 | 0.020 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".