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Record W4385157102 · doi:10.1093/tbm/ibad040

Supporting meaningful research partnerships: an interview study applying behavior change theory to develop relevant recommendations for researchers

2023· article· en· W4385157102 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueTranslational Behavioral Medicine · 2023
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsToronto Rehabilitation InstituteUniversity of TorontoSpinal Cord Injury BCUniversity of ManitobaUniversity of SaskatchewanUniversity of AlbertaUniversity of British ColumbiaInternational Collaboration On Repair DiscoveriesUniversity of British Columbia, Okanagan Campus
Fundersnot available
KeywordsGeneral partnershipPsychological interventionPsychologyIntervention (counseling)Descriptive statisticsMedical educationKnowledge translationApplied psychologyKnowledge managementNursingMedicineComputer scienceBusiness

Abstract

fetched live from OpenAlex

Research partnerships, while promising for ensuring translation of relevant and useable findings, are challenging and need support. This study aimed to apply behavior change theory to understand and support researchers' adoption of a research partnership approach and the Integrated Knowledge Translation (IKT) Guiding Principles for conducting and disseminating spinal cord injury (SCI) research in partnership. Using an IKT approach, SCI researchers across Canada and the USA completed a survey (n = 22) and were interviewed (n = 13) to discuss barriers and facilitators to deciding to partner and follow the IKT Guiding Principles. The Behaviour Change Wheel, Theoretical Domains Framework (TDF), and Mode of Delivery Ontology were used to develop the survey, interview questions, and guided analyses of interview data. COM-B and TDF factors were examined using descriptive statistics and abductive analyses of barriers and facilitators of decisions to partner and/or use the IKT Guiding Principles. TDF domains from the interview transcripts were then used to identify intervention, content, and implementation options. 142 factors (79 barriers, 63 facilitators) related to deciding to partner, and 292 factors (187 barriers, 105 facilitators) related to deciding to follow the IKT Guiding Principles were identified. Barriers to partnering or use the IKT Guiding Principles were primarily related to capability and opportunity and relevant intervention options were recommended. Interventions must support researchers in understanding how to partner and use the IKT Guiding Principles while navigating a research system, which is not always supportive of the necessary time and costs required for meaningful research partnerships.

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.

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
gptMetaresearch
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativemedium
models agreeAgreement compares identical category sets and study designs across arms.

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)0.056
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0560.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.978
GPT teacher head0.803
Teacher spread0.176 · 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