“I Had to Know About It, I Had to Find It, I Had to Know How to Access it”: Experiences of Access to Rehabilitation Services Among People Living with Long COVID
Bibliographic record
Abstract
Purpose: The aim of this qualitative study is to understand the need for, access to, and quality of rehabilitation services for people living with Long COVID. Little is known about the experiences of people living with Long COVID accessing rehabilitation services. Therefore, we explored health concerns leading people living with Long COVID to seek help to address functional concerns and their experiences with accessing and participating in rehabilitation. Method: Interpretive description guided exploration of participants' experiences with Long COVID rehabilitation in Alberta, Canada. Semi-structured interviews were completed with 56 participants recruited from: three publicly funded Long COVID clinics, a specialized private physiotherapy clinic, a telephone-based rehabilitation advice line, and a Workers' Compensation Board-funded Long COVID rehabilitation program. Recruitment through mass media coverage allowed us to include people who did not access rehabilitation services. Data analysis was informed by Braun and Clarke's reflexive thematic analysis. Results: Four themes were identified: (1) the burden of searching for guidance to address challenges with functioning and disability; (2) supportive relationships promote engagement in rehabilitation; (3) conditions for participation in safe rehabilitation; and (4) looking forward - provision of appropriate interventions at the right time. Conclusions: Our findings highlight the experiences of accessing rehabilitation services for people living with Long COVID. Results suggest approaches to Long COVID rehabilitation should be accessible, multi-disciplinary, flexible, and person-centred.
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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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.017 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| 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".