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Background Populations in low-resource settings with high childhood morbidity and mortality increasingly are being selected as beneficiaries for interventions using passive sensing data collection through digital technologies. However, these populations often have limited familiarity with the processes and implications of passive data collection. Therefore, methods are needed to identify cultural norms and family preferences influencing the uptake of new technologies. Objective Before introducing a new device or a passive data collection approach, it is important to determine what will be culturally acceptable and feasible. The objective of this study was to develop a systematic approach to determine acceptability and perceived utility of potential passive data collection technologies to inform selection and piloting of a device. To achieve this, we developed the Qualitative Cultural Assessment of Passive Data collection Technology (QualCAPDT). This approach is built upon structured elicitation tasks used in cultural anthropology. Methods We piloted QualCAPDT using focus group discussions (FGDs), video demonstrations of simulated technology use, attribute rating with anchoring vignettes, and card ranking procedures. The procedure was used to select passive sensing technologies to evaluate child development and caregiver mental health in KwaZulu-Natal, South Africa, and Kathmandu, Nepal. Videos were produced in South Africa and Nepal to demonstrate the technologies and their potential local application. Structured elicitation tasks were administered in FGDs after showing the videos. Using QualCAPDT, we evaluated the following 5 technologies: home-based video recording, mobile device capture of audio, a wearable time-lapse camera attached to the child, proximity detection through a wearable passive Bluetooth beacon attached to the child, and an indoor environmental sensor measuring air quality. Results In South Africa, 38 community health workers, health organization leaders, and caregivers participated in interviews and FGDs with structured elicitation tasks. We refined the procedure after South Africa to make the process more accessible for low-literacy populations in Nepal. In addition, the refined procedure reduced misconceptions about the tools being evaluated. In Nepal, 69 community health workers and caregivers participated in a refined QualCAPDT. In both countries, the child’s wearable time-lapse camera achieved many of the target attributes. Participants in Nepal also highly ranked a home-based environmental sensor and a proximity beacon worn by the child. Conclusions The QualCAPDT procedure can be used to identify community norms and preferences to facilitate the selection of potential passive data collection strategies and devices. QualCAPDT is an important first step before selecting devices and piloting passive data collection in a community. It...

Background: The International Study of Movement Behaviours in the Early Years, SUNRISE, was initiated to assess the extent to which young children meet movement behaviour guidelines (physical activity, sedentary behaviour, screen time, sleep). Objective: The South African SUNRISE pilot study assessed movement behaviours in preschool children from two low-income settings, and associations between these movement behaviours, adiposity, motor skills and executive function (EF). Methods: Preschool child/parent pairs (n = 89) were recruited from preschools in urban Soweto and rural Sweetwaters. Height and weight were measured to assess adiposity. Physical activity was assessed using accelerometers while sedentary behaviour, screen time and sleep were assessed via parent report. Fine and gross motor development were measured using the Ages and Stages Questionnaire-3, and EF was assessed using the Early Years Toolbox. Results: The proportion of children meeting the physical activity guideline was 84% , 66% met the sleep guideline ,48% met the screen time guideline , and 26% met all three guidelines. Rural children were more active, but spent more time on screens compared to urban children. Most children were on track for gross (96%) and fine motor (73%) development, and mean EF scores were in the expected range for all EF measures. EF was negatively associated with screen time, and gross motor skills were positively associated with physical activity. Conclusion: The South African SUNRISE study contributes to the growing literature on 24-hour movement behaviours in SA preschool children, and highlights that these behaviours require attention in this age group.

Background: In 2018, South Africa developed 24-hour movement behavior guidelines for children from birth to 5 years. This study reports on the stakeholder consultation as part of this development process. Methods: An online survey was completed by 197 participants; 9 focus groups (with parents/caregivers, early childhood development practitioners, and community health workers, total n = 70) were conducted, and a meeting with stakeholders from government and nongovernment organizations (n = 15) was held. Results: In the online survey, stakeholders overwhelmingly agreed with the guidelines (97.0%) and recognized the benefit of putting the guidelines into practice (88.8%). Most online survey respondents (88.3%) reported that the guidelines would benefit all South African children equally. Responses to open-ended questions in the online survey and focus group discussions revealed issues including safety and nutrition of children, perceived parental barriers to using the guidelines, and education. Training and provision of educational materials were identified from all stakeholders as key in the dissemination and implementation of the guidelines. Conclusions: The findings informed the development of the South African 24-hour movement behavior guidelines and revealed several important factors to address in the dissemination and implementation of the guidelines to ensure that they are applicable and equitable in South Africa.

There has been a recent increase in debates on the ethics of social media research, passive sensor data collection, and big data analytics. However, little evidence exists to describe how people experience and understand these applications of technology. This study aimed to passively collect data from mobile phone sensors, lapel cameras, and Bluetooth beacons to assess people’s understanding and acceptance of these technologies. Seven households were purposefully sampled and data collected for 10 days. The study generated 48 hr of audio data and 30,000 images. After participant review, the data were destroyed and in-depth interviews conducted. Participants found the data collected acceptable and reported willingness to participate in similar studies. Key risks included that the camera could capture nudity and sex acts, but family review of footage before sharing helped reduce concerns. The Emanuel et al. ethics framework was found to accommodate the concerns and perspectives of study participants.

BACKGROUND Populations in low-resource settings with high childhood morbidity and mortality increasingly are being selected as beneficiaries for interventions using passive sensing data collection through digital technologies. However, these populations often have limited familiarity with the processes and implications of passive data collection. Therefore, methods are needed to identify cultural norms and family preferences influencing the uptake of new technologies. OBJECTIVE Before introducing a new device or a passive data collection approach, it is important to determine what will be culturally acceptable and feasible. The objective of this study was to develop a systematic approach to determine acceptability and perceived utility of potential passive data collection technologies to inform selection and piloting of a device. To achieve this, we developed the Qualitative Cultural Assessment of Passive Data collection Technology (QualCAPDT). This approach is built upon structured elicitation tasks used in cultural anthropology. METHODS We piloted QualCAPDT using focus group discussions (FGDs), video demonstrations of simulated technology use, attribute rating with anchoring vignettes, and card ranking procedures. The procedure was used to select passive sensing technologies to evaluate child development and caregiver mental health in KwaZulu-Natal, South Africa, and Kathmandu, Nepal. Videos were produced in South Africa and Nepal to demonstrate the technologies and their potential local application. Structured elicitation tasks were administered in FGDs after showing the videos. Using QualCAPDT, we evaluated the following 5 technologies: home-based video recording, mobile device capture of audio, a wearable time-lapse camera attached to the child, proximity detection through a wearable passive Bluetooth beacon attached to the child, and an indoor environmental sensor measuring air quality. RESULTS In South Africa, 38 community health workers, health organization leaders, and caregivers participated in interviews and FGDs with structured elicitation tasks. We refined the procedure after South Africa to make the process more accessible for low-literacy populations in Nepal. In addition, the refined procedure reduced misconceptions about the tools being evaluated. In Nepal, 69 community health workers and caregivers participated in a refined QualCAPDT. In both countries, the child’s wearable time-lapse camera achieved many of the target attributes. Participants in Nepal also highly ranked a home-based environmental sensor and a proximity beacon worn by the child. CONCLUSIONS The QualCAPDT procedure can be used to identify community norms and preferences to facilitate the selection of potential passive data collection strategies and devices. QualCAPDT is an important first step before selecting devices and piloting passive data collection in a community. It is especially important for work with caregivers and young children for whom cultural beliefs and shared family environments strongly determine behavior and potential uptake of new technology.