The Value of Patient Narratives in the Assessment of Older Patients Presenting with Falls
Bibliographic record
Abstract
BACKGROUND PURPOSE: Falls are a common and serious health problem experienced by older persons. The perception and interpretation of the fall experience can influence the long-term consequences of the event. In this pilot study, we explored whether there would be additional value in obtaining a patient narrative as part of the assessment of an older person who had fallen. METHODS: We conducted narrative interviews on a convenience sample of five older patients referred to the Calgary Fall Prevention Clinic (CFPC). Phenomena from the narratives were generated using original audio recordings. A focus group of four CFPC health professionals discussed similarities and differences between the narratives and the CFPC assessments conducted on these subjects without access to the narratives. RESULTS: Patient narratives revealed additional information about the person's emotional response to their falls and overall health status, their strengths that could be utilized in implementing a care plan, and what they had done personally to prevent further falls. CONCLUSIONS: Including patient narratives within standard fall-risk assessments could aid in understanding the emotional impact of falls on older patients and how they might respond to interventions. A challenge would be incorporating this within the time restraints of routine clinical practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".