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Record W4392818450 · doi:10.1101/2024.03.07.24303745

Pilot Randomised Controlled Trial - Nurture Early for Optimal Nutrition (NEON) Study: Community facilitator-led participatory learning and action (PLA) women’s groups to improve infant feeding, care and dental hygiene practices in South Asian infants aged < 2 years in East London

2024· preprint· en· W4392818450 on OpenAlexaff
Logan Manikam, Priyanka Patil, Tala El Khatib, Subarna Chakraborty, Delaney Douglas- Hiley, S. Fujita, Joanna Dwardzweska, Oyinlola Oyebode, Clare Llewellyn, Kelley Webb-Martin, Carol Irish, Mfon Archibong, Jenny Gilmour, Phoebe Kalungi, Neha Batura, Kalpita Shringarpure, Monica Lakhanpaul, Michelle Heys

Bibliographic record

VenuemedRxiv · 2024
Typepreprint
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsCentre for Global Health Research
FundersNIHR Great Ormond Street Hospital Biomedical Research CentreNational Institute for Health and Care Research
KeywordsAttendancePsychological interventionMedicineFacilitatorRandomized controlled trialIntervention (counseling)Family medicineNursingPsychologySocial psychology

Abstract

fetched live from OpenAlex

Abstract Background The first 1000-days of life are a critical window and can result in adverse-health consequences due to inadequate nutrition. South-Asian (SA) communities face significant health-disparities, particularly in maternal and child-health. Community-based-interventions, often employing Participatory-Learning-and-Action (PLA) approaches, have effectively addressed health-inequalities in lower-income-nations. The aim of this study was to assess the feasibility of implementing a PLA-intervention to improve infant-feeding and care-practices in SA communities in London. Methods Comprehensive-analyses were conducted to assess the feasibility/fidelity of this pilot-randomised-controlled-trial. Summary-statistics were computed to compare key-metrics (participant consent-rates, attendance, retention, intervention-support, perceived-effectiveness) against predefined-progression-rules guiding towards a definitive-trial. Secondary-outcomes were analysed, drawing insights from sources, such as The-Children’s-Eating-Behaviour-Questionnaire (CEBQ), Parental-Feeding-Style-Questionnaires (PFSQ), 4-Day-Food-diary, and the Equality-Impact-Assessment (EIA) tool. Video-analysis of children’s mealtime behaviour trends was conducted. Feedback-interviews were collected from participants. Results Process-outcome measures met predefined-progression-rules for a definitive-trial which deemed the intervention as feasible. The secondary-outcomes analysis revealed no significant changes in children’s BMI z-scores. This could be attributed to the abbreviated follow-up period of 6-months, reduced from 12-months, due to COVID-19-related delays. CEBQ analysis showed increased food-responsiveness, along with decreased emotional-over/undereating. A similar trend was observed in PFSQ. The EIA-tool found no potential discrimination areas, and video-analysis revealed a decrease in force-feeding-practices. Participant-feedbacks revealed improved awareness and knowledge-sharing. Conclusion The study validates the feasibility of a community-oriented, co-adapted Participatory-Learning-and-Action approach for optimising infant-care among South-Asians in high-income countries. It underscores the potential of such interventions in promoting health-equity and improving health-outcomes. Further research is required to evaluate their wider impact.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.014
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0150.002

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 head0.037
GPT teacher head0.328
Teacher spread0.292 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreProtocol

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

Citations1
Published2024
Admission routes1
Has abstractyes

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