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Record W3103998334 · doi:10.1016/j.heliyon.2020.e05326

Perspectives of health care workers and village health volunteers on community-based Integrated Management of Childhood Illness in Madagascar

2020· article· en· W3103998334 on OpenAlexaff
Tomomi Kitamura, Pamela Fergusson, Arison Nirina Ravalomanda, Florentine Soanarenina, Angeline Thérése Raveloarivony, René Rasamoelisolonjatovo, Raymond Rakotoarimanana, Mitsuaki Matsui

Bibliographic record

VenueHeliyon · 2020
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsToronto Metropolitan University
FundersNational Center for Global Health and Medicine
KeywordsIntegrated Management of Childhood IllnessNursingMedicinePublic healthHealth carePoliticsChristian ministryEconomic growthSocioeconomicsPopulationSociologyPolitical scienceEnvironmental healthPrimary health careLaw

Abstract

fetched live from OpenAlex

The Ministry of Health and Family Planning of Madagascar introduced Integrated Management of Childhood Illness (IMCI) strategy in 2006, and community-based IMCI (c-IMCI), in Mahajanga II District in 2007. Following the 2009 political crisis, foreign organisations' suspension of development aid until 2012 significantly affected the implementation of c-IMCI. This study aimed to elucidate the perspectives of village health volunteers (VHVs) and public health officers (PHO) on c-IMCI. Semi-structured in-depth interviews with all VHVs working in three communes and PHOs working at central, district, and health centre levels were conducted in 2013. Textual data, created from transcripts, were translated into English and French. Data management involved analysis of sections of translated transcripts, which were marked, coded, and linked with similar experiences, challenges, and opinions; these were categorised into words and phrases to discover meaningful relationships between emerging themes. From all interviews of 30 VHV in three Mahajanga II communes and 4 PHOs, 3 themes emerged: 1) benefits of c-IMCI to the community and for VHVs, 2) challenges to continue c-IMCI, and 3) motivation to continue c-IMCI. Although all respondents considered c-IMCI as beneficial, they stated it was difficult to continue. The health system and implementation of c-IMCI should be strengthened to enable programme survival beyond the initial phase, especially during times of political instability.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.015
GPT teacher head0.282
Teacher spread0.267 · 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

Citations5
Published2020
Admission routes1
Has abstractyes

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