Patient perspectives on engagement in decision-making in early management of non-ST elevation acute coronary syndrome: a qualitative study
Bibliographic record
Abstract
BACKGROUND: Surveys of patients suggest many want to be actively involved in treatment decisions for acute coronary syndromes. However, patient experiences of their engagement and participation in early phase decision-making have not been well described. METHODS: We performed a patient led qualitative study to explore patient experiences with decision-making processes when admitted to hospital with non-ST elevation acute coronary syndrome. Trained patient-researchers conducted the study via a three-phase approach using focus groups and semi-structured interviews and employing grounded theory methodology. RESULTS: Twenty patients discharged within one year of a non-ST elevation acute coronary syndrome participated in the study. Several common themes emerged. First, patients characterized the admission and early treatment of ACS as a rapidly unfolding process where they had little control. Participants felt they played a passive role in early phase decision-making. Furthermore, participants described feeling reduced capacity for decision-making owing to fear and mental stress from acute illness, and therefore most but not all participants were relieved that expert clinicians made decisions for them. Finally, once past the emergent phase of care, participants wanted to retake a more active role in their treatment and follow-up plans. CONCLUSIONS: Patients admitted with ACS often do not take an active role in initial clinical decisions, and are satisfied to allow the medical team to direct early phase care. These results provide important insight relevant to designing patient-centered interventions in ACS and other urgent care situations.
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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 | 0.019 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".