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Record W4405550013 · doi:10.1186/s12961-024-01243-2

Embedding a culture of research in Canadian community hospitals: a qualitative study

2024· article· en· W4405550013 on OpenAlexafffundabout
Kian Rego, Paige Gehrke, Madelyn Law, Kathryn Halverson, Dominique Piquette, Elaina Orlando, Susan M. Jack, Rosa M. Marticorena, Alexandra Binnie, Jennifer Tsang

Bibliographic record

VenueHealth Research Policy and Systems · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHealth Sciences Research and Education
Canadian institutionsSt. Joseph’s Healthcare HamiltonHealth Sciences CentreSunnybrook Health Science CentreMcMaster UniversityWilliam Osler Health SystemNiagara Health SystemBrock University
FundersCanadian Institutes of Health ResearchPhysicians' Services Incorporated Foundation
KeywordsMentorshipHealth services researchQualitative researchOrganizational cultureThematic analysisHealth administrationNursingHealth careNursing researchMedical educationGeneralizability theoryMedicinePublic relationsSociologyPublic healthPsychologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

BACKGROUND: In Canada, academic hospitals are the principal drivers of research and medical education, while community hospitals provide patient care to a majority of the population. Benefits of increasing community hospital research include improved patient outcomes and access to research, enhanced staff satisfaction and retention and increased research efficiency and generalizability. While the resources required to build Canadian community hospital research capacity have been identified, strategies for strengthening organizational research culture in these settings are not well defined. This study aimed to understand how research culture is experienced and shaped in Canadian community hospitals to provide strategies for strengthening research culture in these settings. METHODS: This qualitative descriptive study, as part of a larger study, explored the underlying dimensions of research culture. Participants were purposefully sampled and included healthcare providers, research staff or hospital administrators from community hospitals across Canada, with non-existent, emerging or established research programs. Data were collected via virtual semi-structured interviews and a demographic questionnaire. Interview transcripts were analyzed using reflexive thematic analysis and Schein's Model of Organizational Culture as a sensitizing framework. Demographic data were analyzed using descriptive statistics. RESULTS: A total of 38 participants from 20 Canadian community hospitals described their experiences of research culture illustrating three key themes. As community hospital research programs matured, participants described a shift in research culture whereby research became more embedded in "the way things are done" within the community hospital. Recommended strategies to achieve an embedded culture of research involve: communications; relationship building; mentorship, training and education opportunities; selecting locally relevant studies; and systems-level support. A top-down approach to embedding research culture was contrasted with a bottom-up approach. CONCLUSIONS: This study described the underlying dimensions of community hospital research culture and targeted strategies for strengthening research culture at different levels of research program maturity. Community hospitals without pre-existing research infrastructure were able to foster a culture of research from the bottom-up by emphasizing the value of embedding research in clinical practice. Although challenging, fostering a culture of research from the bottom-up may be necessary to propel research forward and initiate the process to build research capacity within a community hospital.

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)0.183
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1830.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.006
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.006
Insufficient payload (model declined to judge)0.0000.000

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 head0.787
GPT teacher head0.761
Teacher spread0.026 · 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; both teacher heads agree on what is shown here.

Study designQualitative
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

Citations7
Published2024
Admission routes3
Has abstractyes

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