2022
DOI: 10.3389/fpubh.2022.972177
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Using wearable devices to generate real-world, individual-level data in rural, low-resource contexts in Burkina Faso, Africa: A case study

Abstract: BackgroundWearable devices may generate valuable data for global health research for low- and middle-income countries (LMICs). However, wearable studies in LMICs are scarce. This study aims to investigate the use of consumer-grade wearables to generate individual-level data in vulnerable populations in LMICs, focusing on the acceptability (quality of the devices being accepted or even liked) and feasibility (the state of being workable, realizable, and practical, including aspects of data completeness and plau… Show more

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Cited by 17 publications
(20 citation statements)
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References 60 publications
(55 reference statements)
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“…In 2020, five weather stations were installed across the Nouna CHEERS site to represent various agro-ecological zones. A sensor-based sub-cohort, stratified by age and gender, collected data on daily activity, sleep, heart rate, indoor temperature, and humidity [refer to ( 41 , 42 )]. Remote sensing approaches, including agricultural yield models, were employed to estimate crop productivity ( 43 , 44 ).…”
Section: Methodsmentioning
confidence: 99%
“…In 2020, five weather stations were installed across the Nouna CHEERS site to represent various agro-ecological zones. A sensor-based sub-cohort, stratified by age and gender, collected data on daily activity, sleep, heart rate, indoor temperature, and humidity [refer to ( 41 , 42 )]. Remote sensing approaches, including agricultural yield models, were employed to estimate crop productivity ( 43 , 44 ).…”
Section: Methodsmentioning
confidence: 99%
“…The term RWD refers to health data that are collected during the course of disease, including treatment and outcome data [45]. These may be derived from individual patient records or registry‐based studies and may also include data collected via health apps or by wearables [46, 47]. Such data reflect to a certain extent the reality of treatment and associated outcomes outside the context of clinical studies which—by design and intentionally—carefully control numerous parameters and factors.…”
Section: Evidence Generation—innovative Precision Oncology Trials And...mentioning
confidence: 99%
“…In contrast, data brokers accumulate large amounts of data and use it to create products for surveillance and marketing [8] . In addition to privacy, creating machine learning models that work effectively for individuals from different backgrounds is inhibited by the inaccessibility of inclusive datasets to researchers [9] .…”
Section: Introductionmentioning
confidence: 99%