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Record W6902603111 · doi:10.6084/m9.figshare.c.7906156

Health and social service provider perspectives on challenges, approaches, and recommendations for treating long COVID: a qualitative study of Canadian provider experiences

2025· other· en· W6902603111 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueFigshare · 2025
Typeother
Languageen
FieldComputer Science
TopicMultimodal Machine Learning Applications
Canadian institutionsUniversity of TorontoUniversity Health NetworkCentre for Addiction and Mental Health
Fundersnot available
KeywordsMental healthThematic analysisPsychosocialQualitative researchService providerPsychoeducationHealth careIntervention (counseling)

Abstract

fetched live from OpenAlex

Abstract Background Many people who contract the SAR-CoV-2 virus present with multiple persistent and debilitating physical, cognitive and mental health symptoms that endure beyond the acute infection period. This new syndrome – generally referred to as long COVID – negatively affects patients’ emotional wellbeing and quality of life, and presents a major challenge for treatment providers. Considering the lack of evidence-based treatment and supports, this qualitative descriptive study explores the experiences of Canadian health and social service providers working with individuals with long COVID, as well as their suggestions for intervention development. Methods Twenty health and social service providers between the ages of 29 and 57 across Canada completed virtual individual interviews to discuss their care experiences and service recommendations for long COVID. Participants were from a range of service sectors, including primary care, rehabilitation, mental health, and community support. Interviews were recorded, transcribed, and analyzed using codebook thematic analysis. Results Four themes illustrated providers’ the experiences of (1) selecting personalized treatments based on patient presentation and similar conditions amidst uncertainty; and their recommendations for long COVID services, including (2) building an integrated and evidence-based model of care; (3) providing holistic support for patients and families through psychoeducation and daily living resources; and (4) caring for mental health in long COVID. Conclusions Canadian health and social service providers are adopting personalized treatment approaches to address the symptom persistence of long COVID in the face of a considerable knowledge gap. A comprehensive, integrated care pathway is needed to support patients’ physical and psychosocial wellbeing while increasing provider preparedness to treat this complex condition.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.555
Threshold uncertainty score0.903

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.163
GPT teacher head0.394
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it