Appropriating and asserting power on inflammatory arthritis teams: A social network perspective
Bibliographic record
Abstract
BACKGROUND: Therapeutic interventions for people with inflammatory arthritis (IA) increasingly involve multidisciplinary teams and strive to foster patient-centred care and shared decision making. Participation in health-care decisions requires patients to assert themselves and negotiate power in encounters with clinicians; however, clinical contexts often afford less authority for patients than clinicians. This disadvantage may inhibit patients' involvement in their own health care. OBJECTIVE: To identify communication attributes, IA patients use to influence and negotiate their treatment with members of their health-care network. METHOD: A qualitative social network approach was used to analyse data from a larger study that investigated IA patients' overall experiences of multidisciplinary care. Fourteen patients with IA attended individual semi-structured interviews. Researchers used thematic analysis to identify patterns of assertiveness and influence in the data. RESULTS: Participants experienced loss of identity, control and agency in addition to the physical symptoms of IA. However, they had a sense of personal responsibility for managing their health care. Perceptions of health-care team support enhanced patients' influence in treatment negotiations. Notably, there appeared to be an underlying tension between being empowered or disempowered. DISCUSSION AND CONCLUSIONS: The findings have significant implications for treatment decision communication approaches to IA care. A social network perspective may provide a pathway for clinicians to better understand the complexities of communication with their patients. This approach may reduce unequal power dynamics that occur within clinician/patient interactions and afford people with IA agency, control and affirmation of identity within their health-care network.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".