Clinician Perspectives on Long-COVID Rehabilitation: 21 Interviews
by Jack M. Reeves·Updated 2d ago
39.2 KB2files
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Description
A qualitative study based on semi-structured interviews with 21 clinicians involved in Long-COVID rehabilitation. The data, published by Jack M. Reeves on figshare, includes perspectives from physiotherapists, exercise physiologists, clinical psychologists, and physicians. The interviews, conducted until thematic saturation was reached, explore challenges in diagnosis, management, and exercise therapy for the condition.
Use Cases
Thematic analysis of clinician-reported challenges in Long-COVID care based on the four identified overarching themes.
Studying semantic discordance and terminology use in medical communication based on the subthemes concerning naming and framing Long-COVID.
Investigating variability in rehabilitation approaches for novel conditions based on the theme 'Management of a novel condition – Who knows what to do?'.
Strengths
Includes interviews with 21 clinicians from diverse specialties, including physiotherapists, exercise physiologists, and physicians.
Thematic analysis identified four overarching themes and multiple subthemes, providing structured qualitative insights.
Data collection continued until thematic saturation was reached on physical rehabilitation approaches.
Limitations
The dataset is a 39.2 KB DOCX file, indicating a very limited textual scope, likely a summary or article rather than raw interview transcripts.
Row count and column-level documentation are absent; the structure and granularity of the underlying data are unknown.
The geographic origin of the interviewed clinicians is not specified, which may limit generalizability.
Provenance
Source
figshare
Collection Method
Clinicians were recruited via email and interviewed using a semi-structured approach. Interviews were recorded, deidentified, transcribed, and analyzed using reflexive thematic analysis.
Freshness
Last updated 2026-06-04 16:27:39; freshness should be verified.
License is CC-BY-4.0, requiring attribution. The primary data format is DOCX, which may require specific software for access.