A qualitative study of older adult trauma survivors’ experiences in acute care and early recovery
Bibliographic record
Abstract
BACKGROUND: Older adults (aged ≥ 65 yr) account for a substantial proportion of hospital admissions for severe injury, yet little is known about their care experiences and views regarding outcomes. We sought to characterize the acute care and early recovery experiences of older adults who had been discharged after traumatic injury, with a long-term goal to inform the selection of patient-centred process and outcome measures in geriatric trauma. METHODS: From June 2018 to September 2019, we conducted telephone interviews with adults aged 65 years or older who had been discharged after traumatic injury within 6 months from Sunnybrook or London Health Sciences Centres in Ontario, Canada. Using interpretive description and thematic analysis, we drew on social science theories of illness and aging for data interpretation. We analyzed data to the point of theoretical saturation. RESULTS: We interviewed 25 trauma survivors aged 65-88 years. Most were injured in a fall. Four themes characterized participants' experiences, as follows: "I don't feel like a senior" (i.e., participants disliked being viewed as a senior or as needing senior-specific care); "don't bother telling him anything" (i.e., participants perceived ageist assumptions and treatment in acute care processes); getting back to normal (i.e., participants emphasized their active lifestyles and functional recovery as goals of care); "I have lost control of my life" (i.e., substantial social and personal losses linked to participants' experiences and adaptations to aging generally). INTERPRETATION: Findings suggest that older adults experience social and personal loss after injury, and underscore how implicit age bias may influence care experiences and outcomes. This can inform improvements in injury care and guide providers in the selection of patient-centred outcome measures.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".