The potential use of social media and other internet-related data and communications for child maltreatment surveillance and epidemiological research: Scoping review and recommendations

Abstract

Collecting child maltreatment data is a complicated undertaking for many reasons. As a result, there is an interest by child maltreatment researchers to develop methodologies that allow for the triangulation of data sources. To better understand how social media and internet-based technologies could contribute to these approaches, we conducted a scoping review to provide an overview of social media and internet-based methodologies for health research, to report results of evaluation and validation research on these methods, and to highlight studies with potential relevance to child maltreatment research and surveillance. Many approaches were identified in the broad health literature; however, there has been limited application of these approaches to child maltreatment. The most common use was recruiting participants or engaging existing participants using online methods. From the broad health literature, social media and internet-based approaches to surveillance and epidemiologic research appear promising. Many of the approaches are relatively low cost and easy to implement without extensive infrastructure, but there are also a range of limitations for each method. Several methods have a mixed record of validation and sources of error in estimation are not yet understood or predictable. In addition to the problems relevant to other health outcomes, child maltreatment researchers face additional challenges, including the complex ethical issues associated with both internet-based and child maltreatment research. If these issues are adequately addressed, social media and internet-based technologies may be a promising approach to reducing some of the limitations in existing child maltreatment data.

Exploring the ethical issues in research using digital data collection strategies with minors: A scoping review

“…Some researchers [25] stressed that the various ethical issues at stake when handling digitally derived data depended on whether the data was actively, or passively, collected. For Schwab-Reese et al [25], active data collection methods closely aligned with traditional data collection methods as they consist of direct interaction with research participants, even if the interaction is facilitated through electronic means [25]. Active data collection methods required participants to actively engage in the data collection process; in direct conversation with the researcher, or in responding to survey questions.…”

“…For example, a researcher may ask a series of questions in real-time through a social media app to which a participant can give an immediate response. Alternatively, passive data collection methods aligned with secondary data analysis as they do not require direct interaction with participants, but rather, aggregate and analyze large sets of existing data [25]. For example, a researcher may monitor the number of hours a participant spends on a certain app, like Twitter, and therefore does not need to be in direct contact with the participant to collect that data in real-time.…”

“…Since a researcher would have direct contact with participants when using active data collection methods, informed consent or assent processes follow suit as standard practice [25]; the participant would be made aware that whatever data they produced in that given research context would be given over to the researcher for analysis. Examples of active digital data collection methods include crowdsourcing (i.e., most commonly done through websites where an open call for participation is issued for users to complete a short survey), or, online recruitment (i.e., most commonly done through websites or social media).…”

“…However, passive data collection methods proved to be more ethically challenging for researchers [25] when considering users' privacy expectations about their digital data. Since passive data collection methods, according to Schwab-Reese et al [25], are predicated on analyzing existing data, this means researchers may not have to necessarily seek out consent or assent from users which could be considered ethically problematic (e.g., does the user consider their digital data on a social media platform, like Twitter, private or public information?).…”

Shedding the Constraints of Formal Systems in Research on Child Maltreatment Through High-Quality Measurement and Broad Population Surveys

“…Until that goal is achieved, smaller-scale, community-based samples with high-quality measures and research designs would allow for aggregation across studies, which would improve our certainty of the findings. In addition, Several additional considerations may also improve data quality, including triangulation of multiple data sources and other novel approaches to data collection, such as trends in Internet search query or disclosures in social media (Schwab-Reese et al 2018;Schwab-Reese et al 2019). These approaches should be carefully validated to ensure they are culturally appropriate and create data that represent the experiences of children.…”