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Record W2386448667 · doi:10.4314/ahs.v16i1.12

A demonstration of mobile phone deployment to support the treatment of acutely ill children under five in Bushenyi district, Uganda

2016· article· en· W2386448667 on OpenAlexaff
Jerome Kabakyenga, Celestine Barigye, Jennifer L. Brenner, Samuel Maling, Denise Buchner, Alberto Nettle-Aquirre, Nalini Singhal, Teddy Kyomuhangi, David Tumusiime, Janet Finch, Stuart MacLeod

Bibliographic record

VenueAfrican Health Sciences · 2016
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsUniversity of British ColumbiaChild and Family Research InstituteUniversity of Calgary
Fundersnot available
KeywordsMobile phoneMedicinePhoneSoftware deploymentQualitative researchFocus groupmHealthPopulationMedical emergencyNursingFamily medicineEnvironmental healthPsychological interventionBusinessComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Benefits of mobile phone deployment for children <5 in low-resource settings remain unproven. The target population of the current demonstration study in Bushenyi District, Uganda, presented with acute fever, pneumonia, or diarrhoea and were treated by community health workers (CHWs) providing integrated community case management (iCCM). METHODS: An observational study was conducted in five parishes (47 villages) served by CHWs well versed in iCCM with supplemental training in mobile phone use. Impact was assessed by quantitative measures and qualitative evaluation through household surveys, focus group discussions, and key informant interviews. RESULTS: CHWs in targeted sites improved child healthcare through mobile phone use coupled with iCCM. Of acutely ill children, 92.6% were correctly managed. Significant improvements in clinical outcomes compared to those obtained by CHWs with enhanced iCCM training alone were unproven in this limited demonstration. Nonetheless, qualitative evaluation showed gains in treatment planning, supply management, and logistical efficiency. Provider confidence and communications were enhanced as was ease and accuracy of record keeping. CONCLUSION: Mobile phones appear synergistic with iCCM to bolster basic supportive care for acutely ill children provided by CHWs. The full impact of expanded mobile phone deployment warrants further evaluation prior to scaling up in low-resource settings.

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)0.002
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 score0.443
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.051
GPT teacher head0.410
Teacher spread0.359 · 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

Citations30
Published2016
Admission routes1
Has abstractyes

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