An appreciative inquiry into older adults’ pain experience in long term care facilities: a pain education initiative
Bibliographic record
Abstract
Background: The prevalence of pain in older adults living in long-term care homes is as high as 80% in developed countries. A Pain Initiative was implemented to improve the pain experience of older adults in two care homes in Vancouver, Canada. This initiative consisted of education and coaching to strengthen the staff teams’ competence and confidence in pain management, although it was not evaluated for effectiveness. \nAim: A clinical research team explored the lived experiences of older adults and professional caregivers participating in the Pain Initiative. The two research questions were: what were the experiences of participating in the Pain Initiative of older adults, professional caregivers and nurse supervisors? and what are enabling factors for positive changes in older adults’ pain experiences? \nMethods: We used appreciative inquiry to identify enabling factors for effective pain management, staying consistent with the tradition of this method to focus on the strengths within an organisation. Older adults and nurse supervisors participated in one-to-one interviews, and professional caregivers participated in focus groups. Inductive thematic analysis was used to analyse the data. \nFindings: Enhanced awareness of older adults’ pain led to increased empathy in professional caregivers. Ongoing coaching, education and resources were enabling factors for effective pain management. The findings illustrate that person-centred practices for pain management in long-term care homes were enhanced through getting to know the older adult, teamwork, non-pharmacological solutions and effective clinical and team processes. \nConclusions and implications for practice: \nPain management is enhanced with ongoing multidisciplinary education, and coaching \nOlder adults’ life stories affect their experiences of pain. Care teams should seek personal knowledge about the older adults as a priority of care \nIncreased frequency of pain discussions results in changing assumptions about pain as a normal part of ageing and encourages empathic practice
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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 | 0.022 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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".