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Record W2154121053 · doi:10.1007/s13142-013-0231-2

Assessing the research use and needs of organizations promoting healthy living for adults with disabilities

2013· article· en· W2154121053 on OpenAlexafffund
Shane N. Sweet, Amy E. Latimer‐Cheung, Christopher Bourne, Kathleen A. Martin Ginis

Bibliographic record

VenueTranslational Behavioral Medicine · 2013
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsMcMaster UniversityCanadians Living with HIVQueen's UniversityMcGill University
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health Research
KeywordsMedical educationReading (process)Action researchPsychologyMedicineKnowledge managementPolitical scienceComputer sciencePedagogy

Abstract

fetched live from OpenAlex

The uptake of research in community-based organizations (CBOs) is low and still unknown in CBOs that promote active and healthy living in adults with a disability. Using the knowledge to action framework, the objectives of this study were to determine if a gap exists regarding the use of research in CBOs, to learn about the preferred method to receive/read research evidence and to identify the barriers and facilitators of research use. Sixty-two employees of CBOs answered an online questionnaire. A research use gap was found as only 53 % of employees indicated they often or always use research. Conferences, emails and short research summaries were the favoured method of receiving/reading research information. Education, time and financial resources were important barriers to research use, while attitudes, intentions and self-efficacy were facilitators. More efforts are needed to develop tools to help CBOs use 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)0.049
metaresearch head score (Gemma)0.142
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 score0.049
Threshold uncertainty score0.258

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0490.142
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0040.003
Open science0.0010.005
Research integrity0.0020.002
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 head0.724
GPT teacher head0.682
Teacher spread0.042 · 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

Citations1
Published2013
Admission routes2
Has abstractyes

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