Virtual Reality Applications for the Implementation of Domestic Respiratory Rehabilitation Programs for Patients With Long COVID and Post-COVID Condition: Scoping Review
Bibliographic record
Abstract
BACKGROUND: Due to a high number of patients affected by long COVID or post-COVID condition, an essential step to address the long-term effects of COVID-19 lies in the development and implementation of flexible and accessible rehabilitation programs. Virtual reality (VR) technologies offer the potential to support traditional therapies with individualized at-home programs. OBJECTIVE: This study aims to provide an overview of existing scientific evidence on the development and implementation of VR-assisted respiratory rehabilitation programs for patients with long COVID and post-COVID condition and to synthesize the results. METHODS: We conducted a scoping review of studies from 6 databases. PubMed, CINAHL, Cochrane, ScienceDirect, Web of Science Social Sciences Citation Index, and PEDro were searched using an exploratory search strategy. The search, which was last updated in February 2024, included peer-reviewed studies on immersive VR applications providing respiratory rehabilitation programs for patients with chronic obstructive pulmonary disease and long COVID or post-COVID condition. Exclusion criteria were studies in clinical or inpatient settings, telemedicine, nonimmersive VR applications, and gray literature. Nine publications were included in this review. Findings were extracted and summarized from the studies according to the JBI (Joanna Briggs Institute) method and thematically categorized. Topics covered were study characteristics, physiotherapeutic concept, clinical parameters, as well as usability and acceptability. RESULTS: The 9 publications included in the qualitative analysis were published in 2019-2023. Eight empirical studies were included: 4 followed a mixed methods design, 3 were qualitative studies, and 1 followed a quantitative method. One scoping review was included in the data analyses. Four of the included studies were on patients with chronic obstructive pulmonary disease. The 9 studies demonstrated that VR-supported respiratory rehabilitation programs result in positive initial outcomes in terms of physical as well as psychological parameters. Particularly noteworthy was the increased motivation and compliance of patients. However, adverse effects and lack of usability are the barriers to the implementation of this innovative approach. CONCLUSIONS: Overall, VR is a promising technology for the implementation of individualized and flexible respiratory rehabilitation programs for patients with long COVID and post-COVID condition. Nevertheless, corresponding approaches are still under development and need to be more closely adapted to the needs of users. Further, the evidence was limited to pilot studies or a small number of patients, and no randomized controlled trials or long-term studies were part of the study selection. The included studies were performed by 4 groups of researchers: 3 from Europe and 1 from the United States.
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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 | 0.009 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".