Swept under the carpet: a qualitative study of patient perspectives on Long COVID, treatments, services, and mental health
Bibliographic record
Abstract
BACKGROUND: A constellation of often disabling long-term physical symptoms enduring after an acute SARS-COV-2 infection is commonly referred to as Long COVID. Since Long COVID is a new clinical entity, research is required to clarify treatment needs and experiences of individuals affected. This qualitative descriptive study aimed to provide insight into Long COVID treatment and service experiences and preferences of individuals experiencing Long COVID and the intersections with mental health. METHODS: The study was conducted out of a tertiary care mental health hospital, with online recruitment from the community across Canada. A total of 47 individuals (average age = 44.9) participated in one of 11 focus groups between June and December 2022. Five focus groups were conducted with participants who had pre-existing mental health concerns prior to contracting SARS-CoV-2, and six were with people with Long COVID but without pre-existing mental health concerns. A semi-structured interview guide asked about service experiences and service preferences, including mental health and well-being services. Discussions were recorded, transcribed, and analyzed using codebook thematic analysis. RESULTS: When accessing services for Long COVID, patients experienced: (1) systemic barriers to accessing care, and (2) challenges navigating the unknowns of Long COVID, leading to (3) negative impacts on patient emotional well-being and recovery. Participants called for improvements in Long COVID care, with a focus on: (1) developing Long COVID-specific knowledge and services, (2) enhancing support for financial well-being, daily living, and building a Long COVID community, and (3) improving awareness and the public representation of Long COVID. CONCLUSIONS: Substantial treatment barriers generate considerable burden for individuals living with Long COVID. There is a pressing need to improve treatment, social supports, and the social representation of Long COVID to create integrated, accessible, responsive, and ongoing support systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".