MétaCan
Menu
Back to cohort
Record W2489510843

Understanding issues in primary care: perspectives of primary care physicians

2006· article· en· W2489510843 on OpenAlexaboutno aff
Nelly D. Oelke, Wilfreda E. Thurston, Remo Dipalma, Wendy Tink, Josephine Mazonde, Allan Mak Ba, Gail Armitage

Bibliographic record

VenueQuality in primary care · 2006
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsPrimary careThematic analysisFamily medicineWork (physics)NursingPerceptionPrimary health careMedicineQuality (philosophy)Health careQualitative researchMedical educationPsychologyPolitical scienceSociology
DOInot available

Abstract

fetched live from OpenAlex

Objective To explore and describe the perceptions of family physicians in a large urban centre regarding issues in primary care and to identify those issues that would impact provision of care in a primary care setting.Design Cross-sectional survey using interviews.Setting Urban centre in western Canada.Participants Eighty-two family physicians located in the central core of a large urban centre.Method Semi-structured interviews and thematic analysis were used to collect and analyse the data. Main findings Physicians identified a number of interrelated issues in community family practice including high overheads,time,lifestyle and family commitments,staffin g issues,lack of communication among providers and between providers and the health region,and technology. These issues impacted their quality of work life,caus ing a sense of being overwhelmed,frust rated,isolated,pow erless anddisillusioned. The participants recommended changes that would benefit their practices,family medicine, and primary care reform.Conclusion Family practice is at a crossroads and new models of team-based care and alternative funding strategies are the preferred methods of implementing primary care reform.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
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 head0.103
GPT teacher head0.424
Teacher spread0.321 · 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 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

Citations3
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueQuality in primary careSame topicPrimary Care and Health OutcomesFrench-language works237,207