Exploring older adults’ perceptions of a patient-centered education manual for hip fracture recovery: “everything in one place”
Bibliographic record
Abstract
Karen Tsui,1,2,* Lena Fleig,1,3,4,* Dolores P Langford,2,5 Pierre Guy,1,2,6 Valerie MacDonald,7,8 Maureen C Ashe1,31Centre for Hip Health and Mobility, The University of British Columbia, 2Vancouver Coastal Health, 3Department of Family Practice, The University of British Columbia, Vancouver, BC, Canada; 4Health Psychology, Freie Universität Berlin, Berlin, Germany; 5Department of Physical Therapy, The University of British Columbia, 6Department of Orthopaedics, 7School of Nursing, The University of British Columbia, Vancouver, 8Fraser Health Authority, Surrey, BC, Canada*These authors contributed equally to this workPurpose: To describe older adults’ perspectives on a new patient education manual for the recovery process after hip fracture.Materials and methods: The Fracture Recovery for Seniors at Home (FReSH) Start manual is an evidence-based manual for older adults with fall-related hip fracture. The manual aims to support the transition from hospital to home by facilitating self-management of the recovery process. We enrolled 31 community-dwelling older adults with previous fall-related hip fracture and one family member. We collected data using a telephone-based questionnaire with eight five-point Likert items and four semi-structured open-ended questions to explore participants’ perceptions on the structure, content, and illustration of the manual. The questionnaire also asked participants to rate the overall utility (out of 10 points) and length of the manual. We used content analysis to describe main themes from responses to the open-ended interview questions.Results: Participants’ ratings for structure, content, and illustrations ranged from 4 to 5 (agree to highly agree), and the median usefulness rating was 9 (10th percentile: 7, 90th percentile: 10). Main themes from the content analysis included: ease of use and presentation; health literacy; illustration utility; health care team delivery; general impression, information support from hospital to home; emotional and decision-making support; and the novelty of the manual.Conclusion: The FReSH Start manual was perceived as comprehensive in content and acceptable for use with older adults post-fall-related hip fracture. Participants expressed a need for delivery and explanation of the manual by a health care team member.Keywords: falls, patient education, health literacy, self-management, discharge planning
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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 | 0.005 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".