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评估 Mbiotisho:一款用于从难以接触的人群中收集高频健康和营养数据的智能手机应用程序。

Assessing Mbiotisho: A smartphone application used to collect high-frequency health and nutrition data from difficult-to-reach populations.

机构信息

Sustainable Livestock Systems, International Livestock Research Institute, Nairobi, Kenya.

Nutrition Sensitive Agriculture, Food, Agriculture and Natural Resources Policy Analysis, Pretoria, South Africa.

出版信息

Matern Child Nutr. 2023 Jul;19(3):e13496. doi: 10.1111/mcn.13496. Epub 2023 Mar 6.

DOI:10.1111/mcn.13496
PMID:36876924
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10262886/
Abstract

There is an urgent need for improved and timely health and nutrition data. We developed and tested a smartphone application that caregivers from a pastoral population used to measure, record and submit high-frequency and longitudinal health and nutrition information on themselves and their children. The data were assessed by comparing caregiver-submitted measurements of mid-upper arm circumference (MUAC) to several benchmark data sets, including data collected by community health volunteers from the participating caregivers during the project period and data generated by interpreting photographs of MUAC measurements submitted by all participants. We found that the caregivers participated frequently and consistently over the 12-month period of the project; most of them made several measurements and submissions in at least 48 of the 52 weeks of the project. The evaluation of data quality was sensitive to which data set was used as the benchmark, but the results indicate that the errors in the caregivers' submissions were similar to that of enumerators in other studies. We then compare the costs of this alternative approach to data collection through more conventional methods, concluding that conventional methods can be more cost-effective for large socioeconomic surveys that value the breadth of the survey over the frequency of data, while the alternative we tested is favoured for those with objectives that are better met by high-frequency observations of a smaller number of well-defined outcomes.

摘要

目前迫切需要改进和及时的健康与营养数据。我们开发并测试了一个智能手机应用程序,供牧民群体的照顾者使用,以便他们能够测量、记录并提交自己和孩子的高频次和纵向健康与营养信息。通过将照顾者提交的上臂中部周长(MUAC)测量值与几个基准数据集进行比较,对数据进行了评估,这些数据集包括项目期间参与的照顾者由社区卫生志愿者收集的数据,以及所有参与者提交的 MUAC 测量照片解释生成的数据。我们发现,在项目的 12 个月期间,照顾者频繁且持续地参与;他们中的大多数人在项目的 52 周中至少有 48 周进行了多次测量和提交。数据质量评估对用作基准的数据集很敏感,但结果表明,照顾者提交的数据中的错误与其他研究中的计数员相似。然后,我们将这种替代数据收集方法与更传统方法的成本进行了比较,得出的结论是,对于重视调查广度而不是数据频率的大型社会经济调查来说,传统方法可能更具成本效益,而我们测试的替代方法则更适合那些通过对少数明确界定的结果进行高频观察来更好地实现目标的情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba19/10262886/4702a070c774/MCN-19-e13496-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba19/10262886/0cd5755163ad/MCN-19-e13496-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba19/10262886/c96d87808dae/MCN-19-e13496-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba19/10262886/22f5a3c15c4b/MCN-19-e13496-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba19/10262886/4702a070c774/MCN-19-e13496-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba19/10262886/0cd5755163ad/MCN-19-e13496-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba19/10262886/c96d87808dae/MCN-19-e13496-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba19/10262886/22f5a3c15c4b/MCN-19-e13496-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba19/10262886/4702a070c774/MCN-19-e13496-g002.jpg

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Feasibility of engaging caregivers in at-home surveillance of children with uncomplicated severe acute malnutrition.
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