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Record W4220776865 · doi:10.29390/cjrt-2021-074

SingStrong—A singing and breathing retraining intervention for respiratory and other common symptoms of long COVID: A pilot study

2022· article· en· W4220776865 on OpenAlexvenueno aff
Róisín Cahalan, Ciara Meade, Sarah Mockler

Bibliographic record

VenueCanadian Journal of Respiratory Therapy · 2022
Typearticle
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePhysical therapyIntervention (counseling)RetrainingCoronavirus disease 2019 (COVID-19)Internal medicinePsychiatryDisease

Abstract

fetched live from OpenAlex

Background Management of Long COVID (LC) is hugely challenging for clinicians. This pilot study evaluated a breathing retraining and singing programme (SingStrong for LC) to address common LC symptoms. The study hypothesized that this intervention would improve symptoms impacting disordered breathing and participant wellbeing. Methods The 10-week, bi-weekly online programme was comprised of a 45-min class of mindfulness, breathing retraining, vocal exercises, and singing. Sessions were recorded for non-attenders and conducted by a trained vocal coach experienced in respiratory cohorts. Persons with a confirmed COVID-19 diagnosis and persisting symptoms were invited to participate. Demographic and COVID-19 data were collected, and the DePaul Symptom Questionnaire Short Form (DSQ- SF) and COVID-19 Yorkshire Rehab Screen questionnaires were administered. Post-intervention focus groups were also conducted. Results Of 27 (F = 23(85%)) participants recruited, data from 21 who completed at least 10 (50%) classes were analysed. Participants showed significant pre--post-intervention improvements in all breathlessness symptoms (at rest: P \< 0.001; dressing: P = 0.01; stairs: P \< 0.001), fatigue (P = 0.03), usual activities (P = 0.04), pain/disability (P = 0.03), voice quality (P = 0.01), and communication/cognition (P = 0.04). Pre--post number of instances meeting DSQ-SF criteria for myalgic encephalomyelitis (ME) and chronic fatigue syndrome (CFS) decreased by a net of nine cases (14.3%). No association between COVID-19 hospitalisation status and diagnosis of ME/CFS was identified. Qualitative feedback from eight participants was overwhelmingly positive with all reporting improvements in breathing and general well-being. Conclusion The SingStrong programme shows promise as a viable treatment option for LC sufferers. Future studies are required to further investigate the efficacy of this intervention.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.045
GPT teacher head0.327
Teacher spread0.282 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations37
Published2022
Admission routes1
Has abstractyes

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