FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3127570983> ?p ?o ?g. }

• W3127570983 endingPage "e23154" @default.
• W3127570983 startingPage "e23154" @default.
• W3127570983 abstract "Background Multimodal approaches have been shown to be a promising way to collect data on child development at high frequency, combining different data inputs (from phone surveys to signals from noninvasive biomarkers) to understand children’s health and development outcomes more integrally from multiple perspectives. Objective The aim of this work was to describe an implementation study using a multimodal approach combining noninvasive biomarkers, social contact patterns, mobile surveying, and face-to-face interviews in order to validate technologies that help us better understand child development in poor countries at a high frequency. Methods We carried out a mixed study based on a transversal descriptive analysis and a longitudinal prospective analysis in Malawi. In each village, children were sampled to participate in weekly sessions in which data signals were collected through wearable devices (electrocardiography [ECG] hand pads and electroencephalography [EEG] headbands). Additionally, wearable proximity sensors to elicit the social network were deployed among children and their caregivers. Mobile surveys using interactive voice response calls were also used as an additional layer of data collection. An end-line face-to-face survey was conducted at the end of the study. Results During the implementation, 82 EEG/ECG data entry points were collected across four villages. The sampled children for EEG/ECG were 0 to 5 years old. EEG/ECG data were collected once a week. In every session, children wore the EEG headband for 5 minutes and the ECG hand pad for 3 minutes. In total, 3531 calls were sent over 5 weeks, with 2291 participants picking up the calls and 984 of those answering the consent question. In total, 585 people completed the surveys over the course of 5 weeks. Conclusions This study achieved its objective of demonstrating the feasibility of generating data through the unprecedented use of a multimodal approach for tracking child development in Malawi, which is one of the poorest countries in the world. Above and beyond its multiple dimensions, the dynamics of child development are complex. It is the case not only that no data stream in isolation can accurately characterize it, but also that even if combined, infrequent data might miss critical inflection points and interactions between different conditions and behaviors. In turn, combining different modes at a sufficiently high frequency allows researchers to make progress by considering contact patterns, reported symptoms and behaviors, and critical biomarkers all at once. This application showcases that even in developing countries facing multiple constraints, complementary technologies can leverage and accelerate the digitalization of health, bringing benefits to populations that lack new tools for understanding child well-being and development." @default.
• W3127570983 created "2021-02-15" @default.
• W3127570983 creator A5015964241 @default.
• W3127570983 creator A5020744129 @default.
• W3127570983 creator A5025361750 @default.
• W3127570983 creator A5026397944 @default.
• W3127570983 creator A5040235344 @default.
• W3127570983 creator A5063360427 @default.
• W3127570983 creator A5069885186 @default.
• W3127570983 creator A5084405627 @default.
• W3127570983 date "2021-03-05" @default.
• W3127570983 modified "2023-09-26" @default.
• W3127570983 title "Combining Wearable Devices and Mobile Surveys to Study Child and Youth Development in Malawi: Implementation Study of a Multimodal Approach" @default.
• W3127570983 cites W1782270568 @default.
• W3127570983 cites W1956101870 @default.
• W3127570983 cites W1957305559 @default.
• W3127570983 cites W1967457283 @default.
• W3127570983 cites W1975855420 @default.
• W3127570983 cites W1995364830 @default.
• W3127570983 cites W2037356999 @default.
• W3127570983 cites W2037923840 @default.
• W3127570983 cites W2080883821 @default.
• W3127570983 cites W2082047925 @default.
• W3127570983 cites W2083434126 @default.
• W3127570983 cites W2085273941 @default.
• W3127570983 cites W2099696079 @default.
• W3127570983 cites W2125190735 @default.
• W3127570983 cites W2132515061 @default.
• W3127570983 cites W2158222386 @default.
• W3127570983 cites W2159492200 @default.
• W3127570983 cites W2166660524 @default.
• W3127570983 cites W2245488506 @default.
• W3127570983 cites W2247700344 @default.
• W3127570983 cites W2266982813 @default.
• W3127570983 cites W2395289406 @default.
• W3127570983 cites W2413075748 @default.
• W3127570983 cites W2527516304 @default.
• W3127570983 cites W2528342610 @default.
• W3127570983 cites W2535461225 @default.
• W3127570983 cites W2556443505 @default.
• W3127570983 cites W2557695132 @default.
• W3127570983 cites W2557883384 @default.
• W3127570983 cites W2580263176 @default.
• W3127570983 cites W2591841133 @default.
• W3127570983 cites W2594761667 @default.
• W3127570983 cites W2611898996 @default.
• W3127570983 cites W2672759822 @default.
• W3127570983 cites W2726678038 @default.
• W3127570983 cites W2739350828 @default.
• W3127570983 cites W2755014019 @default.
• W3127570983 cites W2761296717 @default.
• W3127570983 cites W2792699808 @default.
• W3127570983 cites W2808514730 @default.
• W3127570983 cites W2893706655 @default.
• W3127570983 cites W2893814198 @default.
• W3127570983 cites W2907072092 @default.
• W3127570983 cites W2913129088 @default.
• W3127570983 cites W2945202129 @default.
• W3127570983 cites W2952391360 @default.
• W3127570983 cites W2956197914 @default.
• W3127570983 cites W2962825251 @default.
• W3127570983 cites W2965534548 @default.
• W3127570983 cites W2966663785 @default.
• W3127570983 cites W2981223444 @default.
• W3127570983 cites W3003442787 @default.
• W3127570983 cites W3004162060 @default.
• W3127570983 doi "https://doi.org/10.2196/23154" @default.
• W3127570983 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7980111" @default.
• W3127570983 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33536159" @default.
• W3127570983 hasPublicationYear "2021" @default.
• W3127570983 type Work @default.
• W3127570983 sameAs 3127570983 @default.
• W3127570983 citedByCount "7" @default.
• W3127570983 countsByYear W31275709832021 @default.
• W3127570983 countsByYear W31275709832022 @default.
• W3127570983 countsByYear W31275709832023 @default.
• W3127570983 crossrefType "journal-article" @default.
• W3127570983 hasAuthorship W3127570983A5015964241 @default.
• W3127570983 hasAuthorship W3127570983A5020744129 @default.
• W3127570983 hasAuthorship W3127570983A5025361750 @default.
• W3127570983 hasAuthorship W3127570983A5026397944 @default.
• W3127570983 hasAuthorship W3127570983A5040235344 @default.
• W3127570983 hasAuthorship W3127570983A5063360427 @default.
• W3127570983 hasAuthorship W3127570983A5069885186 @default.
• W3127570983 hasAuthorship W3127570983A5084405627 @default.
• W3127570983 hasBestOaLocation W31275709831 @default.
• W3127570983 hasConcept C105795698 @default.
• W3127570983 hasConcept C118552586 @default.
• W3127570983 hasConcept C133462117 @default.
• W3127570983 hasConcept C138885662 @default.
• W3127570983 hasConcept C149635348 @default.
• W3127570983 hasConcept C150594956 @default.
• W3127570983 hasConcept C15744967 @default.
• W3127570983 hasConcept C2777421447 @default.
• W3127570983 hasConcept C2778707766 @default.
• W3127570983 hasConcept C33923547 @default.
• W3127570983 hasConcept C41008148 @default.
• W3127570983 hasConcept C41895202 @default.

• next