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Record W2314637778 · doi:10.1080/03670244.2016.1161617

The effectiveness of nutrition education: Applying the Health Belief Model in child-feeding practices to use pulses for complementary feeding in Southern Ethiopia

2016· article· en· W2314637778 on OpenAlexaff
Demmelash Mulualem, Carol J. Henry, Getenesh Berhanu, Susan J. Whiting

Bibliographic record

VenueEcology of Food and Nutrition · 2016
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsAnthropometryNutrition EducationMedicineIntervention (counseling)Health educationBaseline (sea)Environmental healthChild healthHealth belief modelDemographyPediatricsPublic healthGerontologyBiology

Abstract

fetched live from OpenAlex

Complementary foods (CFs) in Ethiopia are cereal based and adding locally grown pulses (legumes) to CF would provide needed nutrients. To assess the effects of nutrition education (NEd) using Health Belief Model (HBM) in promoting pulses for CF, a 6-month quasi-experimental study was conducted in 160 mother-child pairs. Knowledge, attitude, and practice (KAP) questions were given to mothers at baseline, midline, and endline, along with anthropometric measurements of children. NEd involving discussions and recipe demonstrations was given twice monthly for 6 months to the intervention group (n = 80) while control mothers received usual education. At baseline, mothers' KAP scores were low at both sites; at 3 and 6 months of NEd, mean KAP scores of mothers increased (p < 0.05) compared to the control site. Significant improvements in children's mean weight, weight for height, and weight for age occurred in the intervention site only. Nutritional status of children improved after providing mothers with pulse-based NEd.

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)0.001
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 score0.159
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.035
GPT teacher head0.329
Teacher spread0.294 · 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

Citations64
Published2016
Admission routes1
Has abstractyes

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