Virtual care exercise interventions in multidisciplinary chronic pain clinics: a qualitative study of perspectives of adults living with chronic pain
Bibliographic record
Abstract
PURPOSE: Chronic pain affects 1 in 4 Canadians and is a leading contributor of disability. Although virtual care has become more prevalent, it is unclear how adults living with chronic pain perceive virtual delivery of exercise interventions within multidisciplinary chronic pain clinics (MCPC). This study explores the perspectives of adults living with chronic pain regarding their perceived barriers and facilitators and recommendations when implementing virtual care exercise interventions within MCPCs. METHODS: We conducted an interpretive description qualitative study based on semi-structured interviews with adults (age ≥18 years) living with chronic pain from a MCPC in Toronto, Canada, between March 1 and April 30, 2021. RESULTS: = 15) interviews of adults living with chronic pain. We identified eight themes that addressed the study objectives: 1) virtual care supplements in-person care, 2) virtual care improves accessibility, 3) impact of technology on participation, 4) navigating the home environment, 5) impact of pain on participation, 6) impact of supervision and feedback, 7) the need for tailored care, and 8) the need for preparation and additional support. CONCLUSION: Our results reveal that adults living with chronic pain view virtual care exercise interventions positively however, the implementation of these interventions must be carefully considered within MCPCs. Specifically, virtual care was considered an excellent adjunct to in-person care but should not replace it completely.Implications for RehabilitationChronic pain is a leading contributor of disability.Exercise interventions are recommended component of comprehensive pain management.Virtual delivery of exercise interventions are becoming more prevalent.Adults living with chronic pain view virtual care exercise interventions positively as they can supplement in-person care and improve access to this type of care.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".