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Record W1977651201 · doi:10.7224/1537-2073-14.3.132

Barriers and Facilitators Related to Participation in Aquafitness Programs for People with Multiple Sclerosis

2012· article· en· W1977651201 on OpenAlexaffabout
Cara L. Brown, K. Kitchen, K Nicoll

Bibliographic record

VenueInternational Journal of MS Care · 2012
Typearticle
Languageen
FieldMedicine
TopicAutoimmune and Inflammatory Disorders Research
Canadian institutionsWinnipeg Regional Health Authority
Fundersnot available
KeywordsPsychosocialThematic analysisFocus groupMedicineQuality of life (healthcare)GerontologyQualitative researchQualitative propertyMedical educationFamily medicineNursingPsychiatrySociology

Abstract

fetched live from OpenAlex

Exercise and leisure activities provide physical and psychosocial benefits to people with multiple sclerosis (MS) and can enhance their quality of life. In Winnipeg, Manitoba, Canada, people with MS have reported barriers to their participation in local MS-specific aquafitness (AF) programs. Therefore, a formal exploration of the accessibility of local AF programs for people with MS was undertaken. The purpose of this phenomenological study was to identify factors that facilitate or impede participation in AF programs by individuals with MS living in Winnipeg. Qualitative data were collected from a total of eight participants through one focus group (n = 7) and one in-depth interview (n = 1). The sample consisted of individuals with MS who were currently participating in AF programming as well as those who were not. Data were audio-recorded and transcribed verbatim, and thematic analysis was completed. Seven themes emerged regarding factors affecting participation in local AF programs. Barriers to participation included inadequate transportation, lack of one-on-one support, environmental inaccessibility, and fears associated with participation in the programs. Facilitators of participation included a knowledgeable instructor and experiencing physical and psychosocial benefits from the program. Information from this study was used locally to advocate for people with MS in order to increase participation in local AF programming.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.210

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.026
GPT teacher head0.325
Teacher spread0.298 · 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

Citations29
Published2012
Admission routes2
Has abstractyes

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