Ethical issues experienced by persons with rheumatoid arthritis in a wearable‐enabled physical activity intervention study
Bibliographic record
Abstract
INTRODUCTION: Using wearables to self-monitor physical activity is a promising approach to support arthritis self-management. Little is known, however, about the context in which ethical issues may be experienced when using a wearable in self-management. We used a relational ethics lens to better understand how persons with rheumatoid arthritis (RA) experience their use of a wearable as part of a physical activity counselling intervention study involving a physiotherapist (PT). METHODS: Constructivist grounded theory and a relational ethics lens guided the study design. This conceptual framework drew attention to benefits, downsides and tensions experienced in a context of relational settings (micro and macro) in which participants live. Fourteen initial and eleven follow-up interviews took place with persons with RA in British Columbia, Canada, following participation in a wearable-enabled intervention study. RESULTS: We created three main categories, exploring how experiences of benefits, downsides and tensions when using the intervention intertwined with shared moral values placed on self-control, trustworthiness, independence and productivity: (1) For some, using a wearable helped to 'do something right' by taking more control over reaching physical activity goals. Some, however, felt ambivalent, believing both there was nothing more they could do and that they had not done enough to reach their goal; (2) Some participants described how sharing wearable data supported and challenged mutual trustworthiness in their relationship with the PT; (3) For some, using a wearable affirmed or challenged their sense of self-respect as an independent and productive person. CONCLUSION: Participants in this study reported that using a wearable could support and challenge their arthritis self-management. Constructing moral identity, with qualities of self-control, trustworthiness, independence and productivity, within the relational settings in which participants live, was integral to ethical issues encountered. This study is a key step to advance understanding of ethical issues of using a wearable as an adjunct for engaging in physical activity from a patient's perspective. PATIENT OR PUBLIC CONTRIBUTION: Perspectives of persons with arthritis (mostly members of Arthritis Research Canada's Arthritis Patient Advisory Board) were sought to shape the research question and interpretations throughout data analysis.
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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 | 0.022 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.010 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| 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".