How do patients with systemic autoimmune rheumatic disease perceive the use of their medications: a systematic review and thematic synthesis of qualitative research
Bibliographic record
Abstract
Pharmacotherapy is paramount to the management of systemic autoimmune rheumatic diseases (SARDs), yet there is sub-optimal adherence and limited adherence interventions. To understand how to better support patients’ medication use, our two-fold objectives were: 1) to conduct a systematic review of qualitative research studies of medication taking among SARD patients; and 2) to thematically synthesize qualitative research studies to obtain SARD patients’ perspectives and experiences with medication use. We conducted a search of MEDLINE, EMBASE, Cumulative Index to Nursing and Allied Health Literature, and Social Sciences Citation Index databases to identify qualitative research studies exploring views on medication use among patients with SARDs, their healthcare providers, or caregivers. We used thematic synthesis to combine data from selected studies, and identify analytical themes on SARD patients’ perspectives and experiences with medication use. Our systematic review identified 18 studies. Thematic synthesis identified seven analytical themes: 1) effects of medications on emotional and social well-being, 2) impacts of healthcare provider relationships on treatment, 3) gaining control over treatment, 4) fear and concern with side effects of treatment, 5) understanding the importance of treatment, 6) practical barriers to taking medication, and 7) motivation towards adherence to treatment. This systematic review and thematic synthesis contributes to better understanding of SARDs patients’ perspectives on medication use. Given the paucity of existing adherence interventions targeting this patient population, our study has certain practical implications for care, namely the need to address emotional and social impacts of medication use and the necessity of establishing a meaningful and trusting professional relationship with patients.
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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 | 0.082 | 0.159 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.005 |
| 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".