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Record W4386821212 · doi:10.1080/22423982.2023.2258025

Adapting the Community Paramedicine at Clinic (CP@clinic) program to a remote northern First Nation community: a qualitative study of community members’ and local health care providers’ views

2023· article· en· W4386821212 on OpenAlexafffundabout
Amelia Keenan, Pauneez Sadri, Francine Marzanek, Melissa Pirrie, Ricardo Angeles, Gina Agarwal

Bibliographic record

VenueInternational Journal of Circumpolar Health · 2023
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsMcMaster UniversityImpact
FundersCanadian Frailty NetworkGovernment of Canada
KeywordsReferralCommunity healthNursingMedicineHealth careCommunity engagementPopulationAdaptation (eye)Qualitative researchPublic healthFamily medicinePsychologyPublic relationsSociologyPolitical scienceEnvironmental health

Abstract

fetched live from OpenAlex

The views of community Elders and health care providers in a rural remote First Nation community in Ontario, Canada on their health care landscape and adapting the Community Paramedicine at Clinic (CP@clinic) Program to their community are presented. Key informant interviews took place between September 2020 and March 2021, and were thematically analysed using the Framework Hierarchical Analysis. There were seven themes that emerged with many subthemes: available services in the community, health care access, health challenges in community, causes of frailty, health care and community appreciations, community-specific benefits of CP@clinic, and CP@clinic program considerations for adaptation. CP@clinic program considerations for adaptation included defining the role of CP, refining referral processes to capture the target population, advertising and promoting, ensuring community awareness, determining clinic setting and composition, focusing on advocacy and timely continuity, adding to the program through time, managing resistance, engaging community and partners, deploying cultural training and language accommodations, leveraging community assets, and ensuring sustainability. Focusing on continuity, engagement, and leveraging available resources may support the success of the CP@clinic program implementation. Findings from this study may be useful to other underserved communities in Canada seeking health programming.

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)0.033
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.226
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0330.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.304
GPT teacher head0.562
Teacher spread0.257 · 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

Citations6
Published2023
Admission routes3
Has abstractyes

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