MétaCan
Menu
Back to cohort
Record W2465018965 · doi:10.3138/ptc.2015-63

Knowledge, Attitudes, and Current Practices of Canadian Physiotherapists in Preventing and Managing Diabetes

2016· article· en· W2465018965 on OpenAlexaffvenueabout
Karly Doehring, Scott Durno, Catherine Pakenham, Bashir Versi, Vincent DePaul

Bibliographic record

VenuePhysiotherapy Canada · 2016
Typearticle
Languageen
FieldMedicine
TopicDiabetes Management and Education
Canadian institutionsSt. Joseph’s Healthcare HamiltonQueen's UniversityUniversity Health NetworkToronto Rehabilitation InstituteMcMaster University
Fundersnot available
KeywordsMedicineDemographicsFamily medicinePatient educationGerontologyNursingMedical educationDemographySociology

Abstract

fetched live from OpenAlex

Purpose: To describe the knowledge, attitudes, and current practices of Canadian physiotherapists in preventing and managing diabetes. Methods: Members of the Canadian Physiotherapy Association were recruited by email to participate in a Web-based survey. The survey contained 40 items in four domains: demographics and education, attitudes and beliefs, current practices, and knowledge of diabetes. A descriptive analysis was completed for all the response variables from the survey. Results: A total of 401 physiotherapists from 10 provinces and 2 territories participated. Respondents were most confident in providing education about exercise and had decreasing confidence in providing education about managing secondary complications, weight management, blood sugar control, and nutrition, respectively. Only 32.4% of participants offered diabetes management counselling, citing lack of training. Knowledge was generally good, except for activity guidelines. Conclusions: A significant proportion of physiotherapists lack confidence in providing key aspects of care to patients with diabetes. Gaps in clinical practice and knowledge of activity guidelines were also observed. This study highlights the need to review entry-level physiotherapy training and to develop continuing educational opportunities in this area.

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 score0.333
Threshold uncertainty score0.328

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 head0.017
GPT teacher head0.321
Teacher spread0.304 · 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

Citations11
Published2016
Admission routes3
Has abstractyes

Explore more

Same venuePhysiotherapy CanadaSame topicDiabetes Management and EducationFrench-language works237,207