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Record W2437252869 · doi:10.3138/ptc.2015-50

Factors Associated with Reduced Perceived Access to Physiotherapy Services among People with Low Back Disorders

2016· article· en· W2437252869 on OpenAlexaffvenue
Brenna Bath, Megan Jakubowski, Darren R. Mazzei, Jessica McRae, Natalie McVittie, Sarah Stewart, Stacey Lovo

Bibliographic record

VenuePhysiotherapy Canada · 2016
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsCanadian Physiotherapy AssociationEmissions Reduction AlbertaRegina Qu'Appelle Health RegionUniversity of Saskatchewan
Fundersnot available
KeywordsPhysical therapyPhysical medicine and rehabilitationMedicinePsychology

Abstract

fetched live from OpenAlex

Purpose: To explore which socio-demographic, clinical, and other factors are associated with reduced perceived access to physiotherapy among people with low back disorders. Methods: A cross-sectional study design was used to evaluate perceived access to physiotherapy services in a convenience sample of 111 people with low back disorders presenting to a spinal triage service. Participants were asked whether they felt that they had reduced access to physiotherapy as a result of cost, wait time, or location. Bivariate and multivariate logistic regression were used to explore the association between perceived access to physiotherapy and a range of socio-demographic, clinical, and other factors. Results: Overall reduced perceived access to physiotherapy was reported by 27.9% of the sample; 13.5% reported reduced access resulting from cost, 9.9% from wait time, and 10.8% from location. A variety of socio-demographic and clinical variables were found to be associated with reduced perceived access, including the presence of other health conditions, rural residence, and no prior physiotherapy use. Conclusion: Perceived access to physiotherapy among people with low back disorders may be associated with a diverse range of factors. Further research is required to determine the relationship between these variables and actual use of physiotherapy services.

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 score0.571
Threshold uncertainty score0.726

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.266
Teacher spread0.259 · 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

Citations24
Published2016
Admission routes2
Has abstractyes

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