MétaCan
Menu
Back to cohort
Record W3184460659 · doi:10.1136/bmjopen-2020-048209

Development of a primary care pandemic plan informed by in-depth policy analysis and interviews with family physicians across Canada during COVID-19: a qualitative case study protocol

2021· article· en· W3184460659 on OpenAlexafffundabout
Maria Mathews, Sarah Spencer, Lindsay Hedden, Emily Gard Marshall, Julia Lukewich, Leslie Meredith, Dana Ryan, Richard Buote, Tiffany Liu, Emily Volpe, Paul Gill, Bridget Ryan, Gordon B. Schacter, Jamie Wickett, Thomas R. Freeman, Shannon L. Sibbald, Eric Wong, M. Heather McKay, Rita McCracken, Judith Belle Brown

Bibliographic record

VenueBMJ Open · 2021
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversity of British ColumbiaNova Scotia HospitalMemorial University of NewfoundlandUniversity of TorontoDalhousie UniversityBritish Columbia Academic Health Science NetworkProvidence Health CareSimon Fraser UniversityThames Valley Children's CentreWestern University
FundersCanadian Institutes of Health Research
KeywordsPandemicSnowball samplingMedicineQualitative researchPublic healthResearch ethicsHealth policyFamily medicineNursingPublic relationsCoronavirus disease 2019 (COVID-19)Political scienceDiseaseSociologyInfectious disease (medical specialty)Social science

Abstract

fetched live from OpenAlex

INTRODUCTION: Given the recurrent risk of respiratory illness-based pandemics, and the important roles family physicians play during public health emergencies, the development of pandemic plans for primary care is imperative. Existing pandemic plans in Canada, however, do not adequately incorporate family physicians' roles and perspectives. This policy and planning oversight has become increasingly evident with the emergence of the novel coronavirus disease, COVID-19, pandemic. This study is designed to inform the development of pandemic plans for primary care through evidence from four provinces in Canada: British Columbia, Newfoundland and Labrador, Nova Scotia, and Ontario. METHODS AND ANALYSIS: We will employ a multiple-case study of regions in four provinces. Each case consists of a mixed methods design which comprises: (1) a chronology of family physician roles in the COVID-19 pandemic response; (2) a provincial policy analysis; and (3) qualitative interviews with family physicians. Relevant policy and guidance documents will be identified through targeted, snowball and general search strategies. Additionally, these policy documents will be analysed to identify gaps and/or emphases in existing policies and policy responses. Interviews will explore family physicians' proposed, actual and potential roles during the pandemic, the facilitators and barriers they have encountered throughout and the influence of gender on their professional roles. Data will be thematically analysed using a content analysis framework, first at the regional level and then through cross-case analyses. ETHICS AND DISSEMINATION: Approval for this study has been granted by the Research Ethics of British Columbia, the Health Research Ethics Board of Newfoundland and Labrador, the Nova Scotia Health Authority Research Ethics Board and the Western University Research Ethics Board. Findings will be disseminated via conferences and peer-reviewed publications. Evidence and lessons learnt will be used to develop tools for government ministries, public health units and family physicians for improved pandemic response plans for primary care.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.066
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.198
GPT teacher head0.564
Teacher spread0.366 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations47
Published2021
Admission routes3
Has abstractyes

Explore more

Same venueBMJ OpenSame topicCOVID-19 and Mental HealthFrench-language works237,207