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Record W4362458472 · doi:10.1080/10749357.2023.2195590

A qualitative pilot study exploring clients’ and health-care professionals’ experiences with aquatic therapy post-stroke in Ontario, Canada

2023· article· en· W4362458472 on OpenAlexafffundabout
Andresa R. Marinho-Buzelli, Abirami Vijayakumar, Elizabeth Linkewich, Catherine Gareau, Hasnain Mawji, Zoe Li, Sander L. Hitzig

Bibliographic record

VenueTopics in Stroke Rehabilitation · 2023
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsHealth Sciences CentreSunnybrook HospitalUniversity of TorontoQueen's UniversityToronto Rehabilitation InstituteSunnybrook Health Science Centre
FundersCanadian Institutes of Health Research
KeywordsNonprobability samplingThematic analysisQualitative researchHealth careMedicineStroke (engine)RehabilitationNursingPsychologyPhysical therapyEnvironmental healthPopulationSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Aquatic therapy is beneficial for people post-stroke, as it improves their physical function, well-being, and quality of life. There is a lack of description of users' experiences and perspectives toward aquatic therapy that could elucidate contextual factors for aquatic therapy implementation. OBJECTIVES: To explore participants' experiences with aquatic therapy post-stroke as part of a participatory design project to develop an education tool-kit to address the users' needs for aquatic therapy post-stroke. METHODS: A qualitative descriptive study was employed using a purposive sampling. Letters were sent to stroke and aquatic therapy organizations. Individual interviews were conducted either by phone or Zoom with nine participants in the chronic phase of stroke and 14 health-care professionals. All transcripts were coded and analyzed independently by two researchers. Inductive thematic analysis was used to identify the main themes. RESULTS: = 3). From the interviews, two organizing themes were identified: (1) Importance of aquatic therapy (e.g. experiences, benefits, and program approaches); and (2) Aquatic therapy education (e.g. knowledge gaps, sources of learning and communication). CONCLUSIONS: Health-care professionals and clients reported numerous benefits of aquatic therapy post-stroke including, but not limited to, improvements in mobility, balance, wellbeing, and socialization. Lack of formal and informal education and communication as participants' transition from rehab to community were viewed as barriers to aquatic therapy use post-stroke. Developing education material and communication strategies may improve the uptake of aquatic therapy post-stroke.

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 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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.340
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.093
GPT teacher head0.377
Teacher spread0.284 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations5
Published2023
Admission routes3
Has abstractyes

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