Experiences of physiotherapists working with adults living with Long COVID in Canada: a qualitative study
Bibliographic record
Abstract
ABSTRACT Objectives To explore experiences of physiotherapists working with adults living with Long COVID in Canada. Design Cross-sectional descriptive qualitative study involving online semi-structured interviews. Participants We recruited physiotherapists in Canada who self-identified as having clinically treated one or more adults living with Long COVID in the past year. Data collection Using an interview guide, we inquired about physiotherapists’ knowledge of Long COVID, assessment and treatment experiences, perspectives on physiotherapists’ roles, contextual and implementation factors influencing rehabilitative outcomes, and their recommendations for Long COVID rehabilitation. Interviews were audio-recorded, transcribed verbatim, and analyzed using a group-based thematic analytical approach. We administered a demographic questionnaire to describe sample characteristics. Results Thirteen physiotherapists from five provinces participated; most were women (n=8;62%) and practised in urban settings (n=11;85%). Participants reported variable amounts of knowledge of existing guidelines and experiences working with adults living with Long COVID in the past year. Physiotherapists characterized their experiences working with adults living with Long COVID as a dynamic process involving: 1) a disruption to the profession (encountering a new patient population and pivoting to new models of care delivery), followed by 2) a cyclical process of learning curves and evolving roles of physiotherapists working with persons living with Long COVID (navigating uncertainty, keeping up with rapidly-emerging evidence, trial and error, adapting mindset and rehabilitative approaches, and growing prominence of roles as advocate and collaborator). Participants recommended the need for education and training, active and open-minded listening with patients, interdisciplinary models of care, and organizational- and system-level improvements to foster access to care. Conclusions Physiotherapists’ experiences involved a disruption to the profession followed by a dynamic process of learning curves and evolving roles in Long COVID rehabilitation. Not all participants demonstrated an in-depth understanding of existing Long COVID rehabilitation guidelines. Results may help inform physiotherapy education in Long COVID rehabilitation. STRENGTHS AND LIMITATIONS OF THIS STUDY To our knowledge, this is one of the first qualitative studies to explore experiences of physiotherapists working with patients living with Long COVID in Canada. Our qualitative approach, involving online semi-structured interviews, enabled an in-depth exploration into Canadian physiotherapists’ perceived roles in Long COVID care, experiences with assessment and treatment, knowledge acquisition, and facilitators and barriers to delivery of rehabilitation services. Our team-based analytical approach and partnership with physiotherapists living with Long COVID as part of our process provided valuable collaboration, guidance, and advice for refining the interview guide and demographic questionnaire and fostering student researcher interview skills to increase the quality of the study. The diversity of participants’ characteristics working in different practice settings across five Canadian provinces and the variability in the number of individuals with Long COVID treated by participants were strengths of the study. However, as most participants practised in urban settings in Canada, transferability to other geographical contexts including rural settings and other countries may be limited, especially those with larger differences in healthcare systems.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.023 | 0.011 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".