<scp>Decision‐Making</scp> Around <scp>COVID</scp>‐19 Public Health Measures and Implications for <scp>Self‐Care</scp> Activities: Experiences of Persons With Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: We aimed to advance understanding of how persons with rheumatoid arthritis (RA) experience decision-making about adopting public health measures during the COVID-19 pandemic. METHODS: Persons living with RA partnered throughout this nested qualitative study. One-to-one semistructured telephone interviews were conducted with participants with RA between December 2020 and December 2021. They were strategically sampled from a randomized controlled trial that was underway to test a physical activity counseling intervention. Analysis was guided by reflexive thematic analysis. RESULTS: Thirty-nine participants (aged 26-86 years; 36 women) in British Columbia, Canada were interviewed. We developed three themes. Participants described how their decision-making about public health measures related to 1) "upholding moral values of togetherness" because decisions were intertwined with moral values of neighborliness and reciprocity. Some adapted their self-care routines to uphold these moral values; 2) "relational autonomy-supports and challenges," because they sometimes felt supported and undermined in different relational settings (eg, by family, local community, or provincial government); and 3) "differing trust in information sources," in which decisions were shaped by the degree of faith they had in various information sources, including their rheumatologists. CONCLUSION: Across themes, experiences of decision-making about public health measures during the pandemic were embedded with moral concepts of solidarity, autonomy, and trust, with implications for how persons with RA chose and sustained their self-care activities. Insights gained help sensitize researchers and clinicians to moral issues experienced by persons with RA, which may inform support for self-care activities during and after the pandemic.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".