GoKawiilEthical approval
The Disrupting Harm Survey was reviewed and approved by a global institutional review board (HML IRB Research and Ethics). Moreover, ethics approval was obtained from national or institutional ethics review bodies in each of the 12 participating countries. These included the National Commission for Science, Technology and Innovation (Kenya); Makerere University School of Public Health and the Uganda National Council of Science and Technology (Uganda); the Cambodia National Council for Children and the Ministry of Interior (Cambodia); the Ministry of Health, National Committee on Bioethics for Health (Mozambique); the Medical Research and Ethics Committee (Malaysia); the Health Research Ethics Committee, National Institute of Health Research and Development (Indonesia); the Ministry of Health and Social Services Ethical Review Board (Namibia); the Ministry of Labour, Invalids and Social Affairs (Vietnam); the Philippine Social Science Council Ethical Review Board (the Philippines); the Ethiopian Society of Sociologists, Social Workers and Anthropologists (Ethiopia); and multiple bodies in Tanzania: the National Institute of Medical Research, National Bureau of Statistics and the President’s Office–Regional Administration and Local Government, with permits from the Tanzania Commission for Science and Technology and additional approvals from the Zanzibar Health Research Institute. In Thailand, the study was reviewed by a special panel at Mahidol University’s Institute of Human Rights and Peace Studies, as no formal government ethics review process exists for social research.
Dataset and participants
Disrupting Harm child survey
This survey was conducted between 2020 and 2021 across 12 countries in Eastern and Southern Africa and Southeast Asia and was designed to be representative of each country’s digitally connected population. A random-probability clustered-sample design was used to ensure all households had an equal chance of being sampled, while accounting for some countrywide variation. Ipsos Mori collected the data using a combination of face-to-face household interviews and online interviews (possibly due to the COVID-19 pandemic restrictions) to ensure maximum national coverage of the total population that had the probability of being included in the survey. The total sample size was approximately 1,000 children and caregivers in each country (Cambodia, n = 992; Ethiopia, n = 1,000; Indonesia, n = 995; Kenya, n = 1,014; Malaysia, n = 995; Mozambique, n = 999; Namibia, n = 994; the Philippines, n = 950; Tanzania, n = 996; Thailand, n = 967; Uganda, n = 1,016; Vietnam, n = 994), including some of the regions with the highest rates of violence against children in the world13 (Supplementary Table 1 for data collection timelines). The sampling strategy was further implemented in three stages: (1) 100 primary sampling units (PSUs) with a probability proportional to population size, region and urbanity were selected; (2) random samples of household units within each PSU were undertaken; and (3) children (and caregivers) within each eligible household unit were identified by a local enumerator. Field coverage varied slightly between countries owing to inaccessibility because of conflict-affected or remote areas. Kenya, Namibia, Cambodia and Mozambique had 100% coverage, while Indonesia had the lowest national coverage at 76% given its dispersed geography (Supplementary Fig. 1). Once PSUs were identified, the selection of household units was done using random walk methods, which included a random starting point, usually a landmark area (for example, church, mosque, bridge). To be included, children needed to have used the internet at least once in the past 3 months. Gender matching between interviewer and interviewee was encouraged and informed consent was provided by children and their caregivers.
We analysed data from the 11,912 children aged 12–17 years (full sample, 23,824 including parents), including 6,044 (51%) boys and 5,868 (49%) girls, 3,112 (26%) 12–13-year-old children, 3,954 (33%) 14–15-year-old children and 4,846 (40%) 16–17-year-old children (survey-weighted; unweighted counts in Supplementary Table 39). Gender-specific estimates were calculated among internet-using adolescents from the Disrupting Harm child survey. We could not construct comparable gender-specific population denominators because harmonised data on internet use by age (12–17 years) and gender are not consistently available across all study countries, including from the International Telecommunication Union (ITU) statistics (Supplementary Fig. 12).
The inclusion of rural and peri-urban children in LMICs is a particular strength of this dataset. 6,586 (55%) of the children were living in rural areas, 1,177 (10%) were living in peri-urban areas and 4,149 (35%) were living in urban areas (see Supplementary Table 32 for the full-weighted sample demographics, Supplementary Table 38 for children who experienced one or more forms of technology-facilitated CSEA, and Supplementary Table 39 for survey-weighted prevalence by demographic subgroup with unweighted counts and 95% CIs). A detailed pre-analysis plan was time-stamped and archived on the Open Science Framework (OSF) before data analysis (15 April 2022; https://osf.io/3tpqa/files/osfstorage?view_only=5f02ad5dcbbe4d2ab2b161ce9a00ccfb).
Disrupting Harm household survey (internet exposure)
In each country, the Disrupting Harm household survey (2020–2021) visited a nationally representative sample of approximately 1,500–10,000 households depending on connectivity. At each household, enumerators established whether any children aged 12–17 years lived in the household and, if so, whether those children used the internet (through any device and at any location). These exposure data were collected regardless of whether a child from the household completed the separate CSEA interview, thereby avoiding selection on child interview participation. Aggregating responses across sampled households yielded the national proportion of 12–17-year-old children who are internet users for each country. For validation, we compared these estimates with ITU youth internet-use indicators (typically ages 15–24 years, nearest available year; Supplementary Fig. 13). As ITU data differ in age band and reference period, we retained the Disrupting Harm household data as our primary exposure source (Supplementary Fig. 11).
Measures
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