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Record W4392731862 · doi:10.1136/bmjopen-2023-074412

Insight into Private General Physicians’ Practices: an Exploratory Qualitative Study in a Rural District of Pakistan

2024· article· en· W4392731862 on OpenAlexaff
Nousheen Akber Pradhan, Tahani Zaidi, Sameen Siddiqi

Bibliographic record

VenueBMJ Open · 2024
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsMedicineExploratory researchGlobal Positioning SystemQualitative researchPsychological interventionNursingEnforcementHealth careFamily medicineEconomic growth

Abstract

fetched live from OpenAlex

OBJECTIVE: The study aimed to assess private general physicians'(GPs) healthcare practices, identifying perceived malpractices, the support they receive, and barriers they experience in providing healthcare services. DESIGN: Qualitative exploratory study. SETTING: Rural district, Thatta in Province of Sindh, Pakistan. PARTICIPANTS: 15 GPs. RESULTS: Our results include increased motivation among GPs for continued professional development, the high influence of pharmaceutical companies on providers' prescribing practices, perceived malpractices by GPs, and the prevalence of quackery and ineffective regulatory mechanisms for private GPs in a rural district. CONCLUSION: Our findings have implications for the capacity building of GPs by academic institutions, enforcement of regulatory measures by the authorities, and the introduction of measures to curb practices by unqualified practitioners. Finally, more research will be needed to further understand the perceptions of GPs, their needs and the service delivery interventions that will enhance the quality of care they provide.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.274
GPT teacher head0.616
Teacher spread0.342 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2024
Admission routes1
Has abstractyes

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