Listening with a narrative ear
Bibliographic record
Abstract
Objective To determine the value of adding a patient narrative to the clinical assessment of falls in the elderly. Design Qualitative study of interviews. Setting A fall prevention clinic in Calgary, Alta. Participants Fifteen older adults on a wait list for assessment by the fall clinic and the physiotherapists who assessed them. Methods Participants’ stories were audiorecorded and later transcribed and summarized. Stories were collected using open-ended questions, first inviting participants to tell the interviewer about themselves, and then the circumstances of their falls and their reflections on them. In a subsequent visit, transcriptions or summaries were returned to patients for member checking. Narratives were read and analyzed by all 4 investigators using a narrative approach and a close-reading technique. With the patients’ additional consent, stories were shared with the fall prevention team for their insights and reactions. Interviews with physiotherapists were audiorecorded and transcribed. Main findings The narrative analysis provided new insights into the attitudes about and perceptions of the causes of falls, their effects, and rehabilitation. Close reading exposed presentation of self, locus of control, and underlying social and emotional issues. Conclusion The addition of patient narratives to clinical assessments offers clinicians an understanding of patients’ perspectives, which can be used to better engage patients in rehabilitation.
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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 | 0.000 |
| 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 | 0.001 |
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".