Getting airtime: Exploring how patients shape the stories they tell health practitioners
Bibliographic record
Abstract
INTRODUCTION: Effective communication during health encounters is known to decrease patient complaints, increase patient adherence and optimise health outcomes. While the aim of patient-centred care is to find common ground, health practitioners tend to drive the encounter, often interrupting patients within the first minute of the clinical conversation. Optimal care for people with chronic illnesses requires individuals to interact with health practitioners regarding their health concerns, but given these constraints, we know little about how patients strategise conversations with their care providers. This understanding may further our efforts to educate health practitioners and trainees to learn and practice patient-centred care. METHODS: A constructivist grounded theory approach with iterative data collection and analysis was used to explore the processes patients use to present and shape their stories for interactions with health practitioners. Twenty-one patients (n = 16 female; 5 male) representing a variety of chronic illnesses participated in semi-structured interviews. Using the constant comparative method of analysis, salient themes were ascertained. RESULTS: Patients engage in extensive strategic preparations for productive health encounters. From the data, we identified four related elements comprising patients' process of planning, preparing, and strategising for health encounters: deciding to go, organising to get airtime, rehearsing a game plan, and anticipating external forces. By focusing on the extensive preparatory work patients engage in, our study expands the dimensions of how we understand illness-related work. Assembling personal health information, gathering disease information and achieving equanimity represent the dimensions of this 'health interaction work'. CONCLUSION: The work patients engage in for health encounters is noteworthy yet often invisible. And work that is unseen may also be undervalued. Acknowledging, illuminating and valuing patients' preparatory work for health encounters add to how we understand patient-centred care, and this offers new targets for us to effectively teach and deliver it.
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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 | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.001 | 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".