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Record W4295088749 · doi:10.1089/jicm.2022.0637

Canadian Naturopathic Doctor Engagement, Preparedness, and Perceptions of Evidence-Based Practice: A National Cross-Sectional Study

2022· article· en· W4295088749 on OpenAlexaffabout
Matthew Leach, Monique Aucoin, Kieran Cooley

Bibliographic record

VenueJournal of Integrative and Complementary Medicine · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsCanadian College of Naturopathic Medicine
Fundersnot available
KeywordsPreparednessNaturopathyCross-sectional studyEvidence-based practiceMedicineFamily medicineComputer-assisted web interviewingPsychologyNursingMedical educationAlternative medicinePolitical science

Abstract

fetched live from OpenAlex

Background: Despite the reported benefits of evidence-based practice (EBP), there are concerns that some practitioners, including naturopathic doctors (NDs), may be cautious about its use. The objective of this study was to explore Canadian ND perceptions, preparedness, and engagement in EBP, and the barriers and enablers to EBP uptake. Methods: The study was a national cross-sectional survey. NDs practicing in Canada were invited to complete the validated 84-item Evidence-Based Practice Attitudes and Utilization Survey between February and May 2020. Results: A total of 252 Canadian NDs were recruited. Participant attitudes toward EBP were predominantly positive, with three-quarters of participants indicating that >50% of their practice was informed by clinical research evidence. One-half of participants self-reported a medium-high to high level of skill across most EBP-related activities. Notable barriers to EBP uptake were lack of clinical evidence in naturopathy, and lack of time. Access to the internet and online databases were identified as useful enablers to improving EBP engagement. Conclusions: By shedding light on Canadian ND engagement with, preparedness for, and perceptions of EBP, the findings will help guide the development of strategies to support EBP uptake in NDs with the expectation of improving quality of care.

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)0.009
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.293
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.346
GPT teacher head0.584
Teacher spread0.238 · 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.

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

Citations9
Published2022
Admission routes2
Has abstractyes

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