MétaCan
Menu
Back to cohort
Record W3211607441 · doi:10.54434/candj.78

Self-Reported Disability Competency in Naturopathic Medical Students

2021· article· en· W3211607441 on OpenAlexvenueno aff
Sarah Hourston, Doug Hanes, Heather Zwickey

Bibliographic record

VenueCAND Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsnot available
FundersNational Center for Complementary and Integrative Health
KeywordsCronbach's alphaNaturopathyInternal consistencyPsychologyMedicineMedical educationFamily medicinePhysical therapyClinical psychologyAlternative medicinePsychometrics

Abstract

fetched live from OpenAlex

Healthcare providers often feel unprepared to work with patients with disabilities. There have been no assessments or tools developed to evaluate whether naturopathic medical (ND) students also feel adequately prepared to work with patients with disabilities. We created a survey to assess student comfort levels, competency, and training needs. Surveys were completed by 218 ND students. Cronbach's alpha for all composite scores were >0.90, suggesting that the surveys have internal consistency. Student comfort working with patients with disabilities significantly increased by program year (p=0.02). Competency scores increased by program year, but this increase was not significant (p=0.17). Over 70% of students indicated that they would like more training on this topic. We were able to assess ND student self-reported comfort, competency, and desire for training with regard to treatment of patients with disabilities. Additional work should be performed to improve disability education for ND students.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.028
GPT teacher head0.372
Teacher spread0.344 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCAND JournalSame topicComplementary and Alternative Medicine StudiesFrench-language works237,207