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Record W2177487349 · doi:10.3148/cjdpr-2015-034

Practice-based Research Program Promotes Dietitians' Participation in Research

2015· article· en· W2177487349 on OpenAlexafffundvenueabout
Frances Johnson, Agnes Black, Jiak Chin Koh

Bibliographic record

VenueCanadian Journal of Dietetic Practice and Research · 2015
Typearticle
Languageen
FieldHealth Professions
TopicDietetics, Nutrition, and Education
Canadian institutionsProvidence Health Care
FundersProvidence Health Care
KeywordsCompetence (human resources)Health careNursingMedicineMedical educationHealth professionalsWork (physics)PsychologyPolitical science

Abstract

fetched live from OpenAlex

Barriers to dietitians' participation in research include lack of time, self-perceived competence, confidence, administrative support, and funding. Providence Health Care, a multi-site health care organization in Vancouver, British Columbia implemented the Practice-based Research Challenge (RC), a 1-year research program, to support interdisciplinary teams of nurses and allied health professionals to conduct practice-relevant research projects. Funding, mentoring, and research education were provided to research teams. From 2011 to 2015, 37% of all dietitians in the organization were involved in the RC in 4 cohorts of the 1-year program. An online survey was conducted to understand these dietitians' interest and experience in the RC. The survey results indicated that the major reasons for participating in the program were to increase knowledge, improve patient care, and to work on a project of interest. Respondents thought they gained knowledge, enhanced professional development, and improved patient care. A majority stated they would likely conduct future research. The RC enabled and supported dietitians' participation in research; infrastructure supports for research and enabling a culture of research participation are key contributors to promoting dietitians involvement in research.

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)0.060
metaresearch head score (Gemma)0.081
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0600.081
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0080.003
Scholarly communication0.0050.003
Open science0.0030.013
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0120.004

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 head0.684
GPT teacher head0.656
Teacher spread0.028 · 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

Citations11
Published2015
Admission routes4
Has abstractyes

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Same venueCanadian Journal of Dietetic Practice and ResearchSame topicDietetics, Nutrition, and EducationFrench-language works237,207