ABSTRACT
Introduction: Gender-based violence (GBV) is under-reported to the authorities owing to the stigma, shame, and fear of reprisal that surrounds these crimes. To address this, there has been an influx of technologies, including mobile phone and online applications that allow victim-survivors (hereafter, victims) to document and report GBV (hereafter referred to as GBVxTech). We critically analysed the extent to which GBVxTech applications align with the scientific knowledge base on gathering accounts of crimes from victims and witnesses. Methods: We identified 41 reporting and evidence building applications from around the world but found many (n = 19) were no longer accessible. A total of 13 applications met the study criteria and were available for download. We evaluated each application on how well its design and features align with established minimum best practice standards for gathering complete and accurate accounts from witnesses and victims, such as the pre-interview instructions (e.g., setting ground rules), questioning approach (e.g., using open-ended questions), and the adequacy of security features (e.g., password protection). Results and Discussion: We found most applications employ open questions, encourage victims to report information in an independent voice, and seek to elicit information pertinent to a criminal investigation. None of the applications use leading questions. However, most applications do not establish ground rules, and many use forced-choice questions, do not time stamp the information gathered, or document when users change their answers. Many applications have limited security features, potentially compromising users' safety. Further, some applications do not provide information about how to use the app, an informed consent procedure, or data usage information. We discuss the findings and offer recommendations for future GBVxTech development.
ABSTRACT
OBJECTIVES: This study examined patterns of sexual violence against adults and children in Kenya during the COVID-19 pandemic to inform sexual violence prevention, protection, and response efforts. DESIGN: A prospective cross-sectional research design was used with data collected from March to August 2020. SETTING: Kenya. PARTICIPANTS: 317 adults, 224 children. MAIN MEASURES: Perpetrator and survivor demographic data, characteristics of the assault. RESULTS: Bivariate analyses found that children were more likely than adults to be attacked during daytime (59% vs 44%, p<0.001) by a single perpetrator rather than multiple perpetrators (31% vs 13%, p<0.001) in a private as opposed to a public location (66% vs 45%, p<0.001) and by someone known to the child (76% vs 58%, p<0.001). Children were violated most often by neighbours (29%) and family members (20%), whereas adults were equally likely to be attacked by strangers (41%) and persons known to them (59%). These variables were entered as predictors into a logistic regression model that significantly predicted the age group of the survivor, χ2(5, n=541)=53.3, p<0.001. CONCLUSIONS: Patterns of sexual violence against adult and child survivors during the COVID-19 pandemic are different, suggesting age-related measures are needed in national emergency plans to adequately address sexual violence during the pandemic and for future humanitarian crises.
