MétaCan
Menu
Back to cohort
Record W4319793713 · doi:10.21203/rs.3.rs-2504570/v1

Implementation framework for Income Generating Activities identified by community heath volunteers: a strategy to reduce CHV attrition rate in Kilifi County Kenya

2023· preprint· en· W4319793713 on OpenAlexfundno aff
Roselyter Monchari Riang’a, Njeri Nyanja, Adélaïde Lusambili, Eunice Muthoni Mwangi, Joshua R. Ehrlich, Paul Clayde, Cyprian M. Mostert, Anthony Ngugi

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsnot available
FundersGovernment of CanadaMitsubishi Electric Research LaboratoriesAga Khan Foundation CanadaAga Khan Foundation
KeywordsFocus groupAttritionStakeholderGovernment (linguistics)Qualitative researchLivelihoodBusinessPublic relationsPolitical scienceMarketingSociologyMedicineGeography

Abstract

fetched live from OpenAlex

Abstract Background Strategy Implementation has increasingly become a focus of scientific studies. Failure of strategy implementation may result in high monetary costs, wasted time and human resources, and reduced community enthusiasm and diminished trust in project sponsors. This study sought to investigate viable modalities for implementing Income Generating Activities (IGAs) for Community Health Volunteers (CHV) in Kilifi County Kenya as a strategy to improve their livelihoods, increase motivation and reduce attrition. Methods: This was an exploratory qualitative research study. Key informant in-depth interviews were conducted among sub-county Ministry officials and multi-lateral stakeholder representatives. A further 10 Focus group discussions with CHVs were conducted. The data were thematically analysed using MAXQDA 20.2 software. Data codding, analysis and presentation was guided by the Okumu’s (2003) Strategy Implementation framework on factors to consider when implementing strategic decisions: 1) Need for Strategy (Income Generating activities) development, 2) Operational process [ (i) IGAs selection strategy, ii) Resources, iii) people & iv) controls. A new variable, however, emerged from the findings; namely, networks. Results: A need for stable income was identified as the driving factor for CHVs seeking IGAs, as their health volunteer work is non-remunerative. Contextualized projects that acknowledged diversity of CHVs in terms of environmental conditions of origin, experience, culture, and market viability, informed their IGA selection strategy. Self-savings through table-banking, seeking funding support through loans xx from government funding agencies (e.g., Uwezo Fund, Women Enterprise fund, Youth Fund), grants from corporate agencies, politicians, and other donors were proposed. Formal registration of IGAs with a Government Ministry, developing a guiding constitution, empowering CHVs with leadership skills, project and group diversity management, and entrepreneurial skills, and connecting them to support agencies, were the control measures proposed by the CHVs & Key Informants to enhance sustainability of IGAs. Group owned and managed IGAs were preferred over individual IGAs. Conclusion: CHVs are in need of IGAs and proposed their own implementation strategies informed by local context. Agencies supporting IGAs should therefore be guided by the modalities proposed by CHVs and local stakeholders.

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)0.010
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.003
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 head0.311
GPT teacher head0.467
Teacher spread0.157 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueResearch SquareSame topicCommunity Development and Social ImpactFrench-language works237,207