Care-seeking pathways, care challenges, and coping experiences of rural women living with rheumatoid arthritis in Odisha, India
Bibliographic record
Abstract
AIM: The aim of the study was to explore the care-seeking pathway of rural women living with rheumatoid arthritis (RA) and attending a tertiary health-care facility in Odisha, India. BACKGROUND: RA is the third leading chronic health condition and causes severe pain and immense psychosocial stress. The prevalence of RA is three to four times higher in women than in men. Furthermore, in India, women delay care seeking due to the prevailing sociocultural norms. Women report more severe symptoms and greater disability; however, there is a lack of information on their care-seeking pathways. METHOD: We conducted 113 in-depth interviews among RA patients those who visited specialists at the outpatients' Department of Rheumatology, SCB Medical College Hospital, a tertiary care hospital in Cuttack, Odisha, India. The grounded theory approaches were used for data analysis. FINDINGS: The key findings included physical pain and psychosocial stress in relation to RA, cultural issues in relation to RA, mapping of the health-care providers for RA, the first point of cares and changes in care-seeking pathways, the perceived challenge for seeking health-care, and coping strategies of patients and social supports. This study explored that the RA patients seek care from multiple providers - untrained, trained and specialist without any gatekeeping. However, the primary health centers were the first point of care for maximum patients due to accessibility and affordability. Furthermore, follow-up care is significant to prevent complication among RA patients; the primary health centers are the gateway for keeping RA patients. Hence, the availability of RA trained providers at primary health center including interprofessional care, such as physiotherapy providers, and proper referral system is essential to convalesce care-seeking pathways.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".