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Record W1977274128 · doi:10.12927/whp.2013.23580

Factors Influencing Motivation and Retention of Primary Healthcare Workers in the Rural Areas of Oyo State, Nigeria

2013· article· en· W1977274128 on OpenAlexvenueno aff
Ayodele Samuel Jegede, Prisca Olabisi Adejumo, Boniface Ayanbekongshie Ushie

Bibliographic record

VenueWorld health & population · 2013
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsnot available
Fundersnot available
KeywordsIncentiveRural areaLogistic regressionWork (physics)Health careRural healthMedicineEnvironmental healthSocioeconomicsNursingEconomic growthSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Limited data exist on retention of primary healthcare (PHC) staff in rural areas, crippling the already fragile healthcare systems in Nigeria. This study investigated why PHC staff would or would not want to work in rural areas and how they could be retained. METHODS: Four hundred and twelve (412) health workers and caregivers, and 21 key informants were interviewed in Ona-Ara LGA. Logistic regression statistics was used to analyse quantitative data and narrative for qualitative data. RESULTS: There was no significant factor influencing health workers' unwillingness to work in rural areas and, relationship between their demographic characteristics and perceived reasons to do so. Combined factors influencing PHC workers' willingness to work in rural areas influenced use of PHC. CONCLUSION: Financial and non-financial incentives are responsible for workers' motivation to work in rural areas. The mal-distribution of health facilities and health workers between urban and rural areas must be addressed.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.032
GPT teacher head0.294
Teacher spread0.262 · 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

Citations6
Published2013
Admission routes1
Has abstractyes

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