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Record W2134149543 · doi:10.1093/fampra/cmu094

Providing care to vulnerable populations: a qualitative study among GPs working in deprived areas in Montreal, Canada

2015· article· en· W2134149543 on OpenAlexafffundabout
Christine Loignon, Martin Fortin, Christophe Bedos, David L. Barbeau, Alexandrine Boudreault‐Fournier, Thomas Gottin, Eric Goulet, E. Laprise, Jeannie Haggerty

Bibliographic record

VenueFamily Practice · 2015
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsMcGill UniversityUniversity of VictoriaUniversité de MontréalUniversité de Sherbrooke
FundersCanadian Institutes of Health Research
KeywordsMedicinePovertyGlobal Positioning SystemHealth careNursingGerontologyEnvironmental healthEconomic growth

Abstract

fetched live from OpenAlex

BACKGROUND: Communication barriers between persons living in poverty and healthcare professionals reduce care effectiveness. Little is known about the strategies general practitioners (GPs) use to enhance the effectiveness of care for their patients living in poverty. OBJECTIVE: The aim of this study was to identify strategies adopted by GPs to deliver appropriate care to patients living in poverty. METHODS: We conducted in-depth semi-structured interviews with 35 GPs practising in Montreal, Canada, who regularly provide care to underprivileged patients in primary care clinics located in deprived urban areas. Analysis consisted of interview debriefing, transcript coding, thematic analysis and data interpretation. RESULTS: GPs develop specific skills for caring for these patients that are responsive to their complex medical needs and challenging social context. Our respondents used three main strategies in working with their patients: building a personal connection to overcome social distance, aligning medical expectations with patients' social vulnerability and working collaboratively to empower patients. With these strategies, the physicians were able to enhance the patient-physician relationship and to take into account the impact of poverty on illness self-management. CONCLUSIONS: Our results may help GPs improve the health and care experience of their vulnerable patients by adopting these strategies. The strategies' impacts on patients' experience of care and health outcomes should be evaluated as a prelude to integrating them into primary care practice and the training of future physicians.

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)0.004
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.217
GPT teacher head0.496
Teacher spread0.279 · 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 designObservational
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

Citations35
Published2015
Admission routes3
Has abstractyes

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