Exploring occupational disruption among women after onset of rheumatoid arthritis
Bibliographic record
Abstract
OBJECTIVE: To portray experiences of women engaging in everyday tasks, activities, and occupations, from symptom onset to 12 months after diagnosis with rheumatoid arthritis (RA), and to explore the meanings attributed to their activities and occupations. METHODS: A secondary analysis of qualitative data, guided by phenomenography, explored the stories of 37 women with early RA. The original study used in-depth interviews to explore the help-seeking process from first symptom to diagnosis, and results indicated unexplored impacts on activity, stimulating the present analysis. Transcripts were read and coded by 3 investigators and then debated by the full team with this new research objective in mind. Descriptive categories were formed through a systematic, iterative approach with a focus on how early RA impacted daily routines and participation in occupation. RESULTS: Participants recounted a range of experiences characterized by changes in the way they engaged in occupations as a result of RA symptoms. Four interrelated categories were identified: uncertainties associated with good days, bad days, and worse days; experiencing activity disruption; doing things differently, which was perceived both positively and negatively; and changing views of self, as participants developed identities as individuals living with RA. CONCLUSION: Daily activities and occupational identity can be profoundly impacted in the first 12 months after diagnosis with RA, resulting in significant life changes. Health professionals are encouraged to identify disrupted activities, facilitate participation in valued occupations, and create environments that enable patients to explore changes in identity to prevent negative life consequences.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".