ReviewBMJ open2023
An in-depth review of the UNICEF NutriDash platform, lessons learnt and future perspectives: a mixed-methods study.
Review in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Challenges and strategies for maintaining nutrition services in the Democratic Republic of Congo during COVID-19: a qualitative study.Frontiers in health services · 2025Article
- Human factors methods in the design of digital decision support systems for population health: a scoping review.BMC public health · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesRobust data on nutrition are essential to realise the right to nutrition for every child. Created in 2009, UNICEF's Nutrition Dashboard (NutriDash) collects nutrition programme information from 125 countries. An in-depth review of NutriDash was conducted to understand its strengths and identify key actions to increase its effectiveness and efficiency.
methodsAdapting the Centres for Disease Control and Prevention updated guidelines for evaluating public health surveillance systems, a mixed-methods approach was used. A questionnaire was designed to capture information on key attributes of NutriDash and disseminated to UNICEF country offices for quantitative feedback on user experiences. Structured key informant interviews were held with internal and external stakeholders to gain qualitative perceptions on data generated from NutriDash. Analysis involved producing frequency distributions for the questionnaire data and performing thematic analyses on interview data.
resultsA total of 53 respondents completed the questionnaire (42% response rate), representing 48 countries and good regional geographic representation. Most respondents (96%) worked in UNICEF country offices. The percentages of participants who agreed or strongly agreed with each attribute of the NutriDash system were as follows: acceptability: 71%, stability: 68%, simplicity; 63%, data quality: 60%, flexibility: 58% and usefulness: 43%. Internal and external stakeholders commented on the value of NutriDash; its use ranging from nutrition global trend monitoring for programme planning to producing reports and dashboards. Key themes derived from this review as areas for improvement included communication, access to data and data quality.
conclusionsThis review has identified key themes that will inform improvements to NutriDash and form a baseline for future periodic reviews to continuously enhance the system to improve availability of timely quality nutrition programme data. UNICEF will continue to engage with countries, key partners and governments to improve the NutriDash data value chain and ensure the right to nutrition for every child.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.