Multiple symptoms and health anxiety in primary care: a qualitative study of tensions and collaboration between patients and family physicians
Bibliographic record
Abstract
BACKGROUND: Patients with multiple, persistent symptoms and health anxiety often report poor health outcomes. Patients who are difficult to reassure are challenging for family physicians. The therapeutic alliance between a physician and a patient can influence the prognosis of these patients. Optimising the quality of the physician-patient alliance may depend on a better understanding of the interpersonal processes that influence this relationship. OBJECTIVE: The purpose of this study is to understand the experiences of patients who experience multiple persistent symptoms or high health anxiety and their physicians when they interact. DESIGN, PARTICIPANTS AND SETTING: A qualitative study was conducted using grounded theory of 18 patients, purposively sampled to select patients who reported high physical symptom severity, high health anxiety or both, and 7 family physicians in the same clinic. This study was conducted at a family medicine clinic in a teaching hospital. RESULTS: A model of interpersonal tension and collaboration for patients and physicians in primary care was developed. Helpful attitudes and actions as well as troublesome topics influence crucial dilemmas between patients and physicians. These dilemmas include if patients feel heard and validated and the alignment of goals and mutual respect of expertise and experience between patients and physicians. These experiences contribute to a constructive collaboration and in turn positive outcomes. CONCLUSIONS: This model of patient-physician interaction may facilitate providers to turn their attention away from the contentious topics and towards actions and attitudes that promote beneficial outcomes.
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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 | 0.014 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.011 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| 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".