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Record W2617161100 · doi:10.4314/ahs.v17i1.29

Where there is no doctor: can volunteer community health workers in rural Uganda provide integrated community case management?

2017· article· en· W2617161100 on OpenAlexafffund
Jennifer L. Brenner, Celestine Barigye, Samuel Maling, Jerome Kabakyenga, Alberto Nettel‐Aguirre, Denise Buchner, Teddy Kyomuhangi, Carolyn Pim, K. A. Wotton, Natukwatsa Amon, Nalini Singhal

Bibliographic record

VenueAfrican Health Sciences · 2017
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsUniversity of Calgary
FundersCanadian Institutes of Health ResearchMbarara University of Science and TechnologyInternational Development Research CentreGovernment of CanadaUNICEF
KeywordsMedicineCommunity health workersIntervention (counseling)MalariaCommunity healthCase managementUnder-fiveRural communityHealth facilityFamily medicineRural healthEnvironmental healthPublic healthPopulationRural areaHealth servicesNursingDemographyImmunology

Abstract

fetched live from OpenAlex

INTRODUCTION: Integrated community case management (iCCM) involves assessment and treatment of common childhood illnesses by community health workers (CHWs). Evaluation of a new Ugandan iCCM program is needed. OBJECTIVES: The objectives of this study were to assess if iCCM by lay volunteer CHWs is feasible and if iCCM would increase proportions of children treated for fever, pneumonia, and diarrhoea in rural Uganda. METHODS: This pre/post study used a quasi-experimental design and non-intervention comparison community. CHWs were selected, trained, and equipped to assess and treat children under five years with signs of the three illnesses. Evaluation included CHW-patient encounter record review plus analysis of pre/post household surveys. RESULTS: 196 iCCM-trained CHWs reported 6,276 sick child assessments (45% fever, 46% pneumonia, 9% diarrhoea). 93% of cases were managed according to algorithm recommendations. Absolute proportions of children receiving treatment significantly increased post-intervention: antimalarial for fever (+24% intervention versus +4% control) and oral rehydration salts/zinc for diarrhoea (+14% intervention versus +1% control). CONCLUSION: In our limited-resource, rural Ugandan setting, iCCM involving lay CHWs was feasible and significantly increased the proportion of young children treated for malaria and diarrhoea.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.409
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.043
GPT teacher head0.355
Teacher spread0.313 · 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

Citations26
Published2017
Admission routes2
Has abstractyes

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