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Record W2956272989 · doi:10.1071/hc18092

Community engagement in general practice: a qualitative study

2019· article· en· W2956272989 on OpenAlexaff
Nick Rowe, Rāwiri Keenan, Leon Lack, Nancy Malloy, Roger Strasser, Ross Lawrenson

Bibliographic record

VenueJournal of Primary Health Care · 2019
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsNOSM UniversityLakehead University
FundersFlinders University
KeywordsCommunity engagementQualitative researchPublic engagementPublic relationsPsychologyBest practiceSociologyPolitical scienceSocial science

Abstract

fetched live from OpenAlex

BACKGROUND Community engagement is believed to be an important component of quality primary health care. We aimed to capture specific examples of community engagement by general practices, and to understand the barriers that prevent engagement. METHODS We conducted 20 distinct interviews with 31 key informants from general practice and the wider community. The interviews were semi-structured around key relevant topics and were analysed thematically. RESULTS Key themes identified from the interview transcripts included an understanding of 'community', examples of community engagement and the perceived benefits and barriers to community-engaged general practice. We particularly explored aspects of community engagement with Māori. CONCLUSIONS General practices in the study do not think in terms of communities, and they do not have a systematic framework for engagement. Although local champions have generated some great initiatives, most practices seemed to lack a conceptual framework for engagement: who to engage with, how to engage with them, and how to evaluate the results of the engagement.

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)0.018
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0180.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.005
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 head0.143
GPT teacher head0.549
Teacher spread0.406 · 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 teacher head, not a consensus.

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

Citations4
Published2019
Admission routes1
Has abstractyes

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