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Record W4394855791 · doi:10.3390/children11040477

Using Implementation Research to Inform Scaling of Parenting Programs: Independently Conducted Case Studies from Zambia and Bhutan

2024· article· en· W4394855791 on OpenAlexaff
Frances E. Aboud, Karma Choden, Given Hapunda, Francis Sichimba, Ania Chaluda, Rafael Contreras Gomez, Rachel Hatch, Sara Dang, Karma Dyenka, Cecilia Banda, Carina Omoeva

Bibliographic record

VenueChildren · 2024
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsMcGill University
FundersLEGO FoundationStrongFHI 360UNICEF
KeywordsWorkforceAttendanceAttritionWorkloadGovernment (linguistics)Scale (ratio)Focus groupChristian ministryResource (disambiguation)Medical educationQuality (philosophy)Implementation researchNursingMedicinePsychologyBusinessPolitical sciencePsychological interventionGeographyComputer scienceMarketing

Abstract

fetched live from OpenAlex

Two case studies of parenting programs for parents of children 0 to 36 months of age, developed and implemented by Save the Children/Ministry of Health/Khesar Gyalpo University in Bhutan and UNICEF Zambia, were conducted by an independent research group. The focus was on how program delivery and scale-up were revised on the basis of feedback from implementation research. Feedback on workforce delivery quality was based on observations of deliveries using a monitoring form, as well as survey and interview data collected from the workforce. In-depth interviews with the resource team during the fourth year of implementation revealed how the feedback was used to address horizontal and vertical scaling. Delivery quality was improved in some cases by revising the delivery manual, offering refresher courses, and instituting regular monitoring. Scaling challenges in Zambia included slow progress with regard to reaching families in the two districts, which they addressed by trialing group sessions, and stemming workforce attrition. The challenges in Bhutan were low attendance and reducing the workload of providers. Vertical scaling challenges for both countries concerned maintaining demand through continuous advocacy at community and government levels to sustain financing and to show effectiveness in outcomes.

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 score0.483
Threshold uncertainty score0.460

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.197
GPT teacher head0.481
Teacher spread0.284 · 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
Published2024
Admission routes1
Has abstractyes

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