Measuring real-time violence exposure and its impact on intimate partner violence perpetration among adolescents

Intimate partner violence (IPV) has dire health consequences. To intervene, it is critical that we first understand why young men perpetrate IPV. One theory is that men who experience violence are more likely to perpetrate violence. We used real-time data to examine how daily and repeated experiences of violence affect IPV behaviors. We enrolled 498 males aged 15-19 years in South Africa. We collected data through weekly mobile phone surveys (n=12,603) delivered over a year. Generalized linear mixed effect models were used to fit IPV perpetration as a function of past-24-hour violence victimization; models included indicators for between-person and within-person components of victimization. In at least one survey submitted, 13% of boys reported perpetrating physical IPV, and 5% perpetrating sexual IPV. Any victimization in the past 24 hours significantly increased the odds of physical (OR 4.00) and sexual violence perpetration (OR 2.45). When examined individually, sexual violence victimization had the strongest association (OR of 7.96 for physical and 4.88 for sexual IPV perpetration). We also examined the between-person influence of victimization. Boys who experienced more violence on average (a higher person-centered mean exposure) were substantially more likely to perpetrate both physical IPV and sexual IPV as compared to boys with overall low levels of victimization. Adolescent boys who experience violence are more likely to use violence against their partners the same day. To break this cycle, it will be critical to understand the mechanisms by which proximal victimization triggers onward violence perpetration. Both the current findings and the next steps highlight the importance of real-time, repeated data collection. This dataset contains the data required to replicate analyses in Kidman et al, "Measuring real-time violence exposure and its impact on intimate partner violence perpetration among adolescents." Data collection is described in the paper. Data have been recoded where appropriate to create the categories (e.g., age, race) used in the paper's analyses. Data are stored in .csv and can be uploaded and analyzed in any standard statistical software. Data are in "long" format: weekly surveys (survey_week) are nested within participants (randomID). Missing data is indicated as NA, and refused data is indicated as 99. A .csv file containing the dataset is attached. # Measuring real-time violence exposure and its impact on intimate partner violence perpetration among adolescents [doi.org](doi.org) This dataset contains the data required to replicate analyses in Kidman et al, "Measuring real-time violence exposure and its impact on intimate partner violence perpetration among adolescents." Data collection is described in more detail in the paper. Briefly, the study focuses on adolescent boys aged 15-19 who were living in South Africa. After consent/assent, adolescent participants used a tablet computer to complete a baseline survey in their preferred choice of English, isiZulu, or Sesotho. Demographics in the attached dataset are derived from such. The remaining data were collected through mobile phone surveys that included brief measures of violence exposure, partner interaction, and IPV perpetration. Mobile surveys were delivered once a week over 52 weeks. Only surveys received within 24 hours of the prompt were considered valid and included in this dataset. Data are stored in MobileIPVdata_18Oct24.csv and can be uploaded and analyzed in any standard statistical software. Data are in "long" format: weekly surveys (survey_week) are nested within participants (randomID). The random ID is different from that used in the study to ensure anonymity. Missing data is indicated as NA, and refused data is indicated as 99. Variables: * randomID: Randomly assigned participant ID (numeric format)  * HIV_status: Participant HIV status (0 = negative; 1 = positive)  * age_cat: Participant age, categorical (0 = 15-17; 1 = 18+)  * race: Participant race (0 = Black African; 1 = Other) * school: Participant school enrollment status (0 = not in school; 1 = enrolled in school) * survey_week: The number corresponding to the survey week (e.g., 1 = the first weekly survey, 40 = the 40th weekly survey) * witness_week: Whether the participant witnessed violence in the community in the past week (0 = No; 1 = Yes; 99 = Refused)  * witness_day: Whether the participant witnessed violence in the past 24 hours (0 = No; 1 = Yes; 99 = Refused) * physical_week: Whether the participant experienced physical victimization in the past week (0 = No; 1 = Yes; 99 = Refused)  * physical_day: Whether the participant experienced physical victimization in the past 24 hours (0 = No; 1 = Yes; 99 = Refused)  * physical_perpetrator_1: Perpetrator type: Girlfriend/wife * physical_perpetrator_2: Perpetrator type: Boyfriend/husband * physical_perpetrator_3: Perpetrator type: Female casual partner * physical_perpetrator_4: Perpetrator type: Male casual partner * physical_perpetrator_5: Perpetrator type: Family member * physical_perpetrator_6: Perpetrator type: Peer * physical_perpetrator_7: Perpetrator type: Female stranger * physical_perpetrator_8: Perpetrator type: Male stranger  * physical_perpetrator_99: Perpetrator type: Refused  * verbal_week: Whether the participant experienced verbal victimization in the past week (0 = No; 1 = Yes; 99 = Refused) * verbal_day: Whether the participant experienced verbal victimization in the past 24 hours (0 = No; 1 = Yes; 99 = Refused) * verbal_perpetrator_1: Perpetrator type: Girlfriend/wife  * verbal_perpetrator_2: Perpetrator type: Boyfriend/husband  * verbal_perpetrator_3: Perpetrator type: Female casual partner  * verbal_perpetrator_4: Perpetrator type: Male casual partner  * verbal_perpetrator_5: Perpetrator type: Family member  * verbal_perpetrator_6: Perpetrator type: Peer  * verbal_perpetrator_7: Perpetrator type: Female stranger  * verbal_perpetrator_8: Perpetrator type: Male stranger  * verbal_perpetrator_99: Perpetrator type: Refused  * sexual_week: Whether the participant experienced sexual victimization in the past week (0 = No; 1 = Yes; 99 = Refused) * sexual_day: Whether the participant experienced sexual victimization in the past 24 hours (0 = No; 1 = Yes; 99 = Refused) * sexual_perpetrator_1: Perpetrator type: Girlfriend/wife  * sexual_perpetrator_2: Perpetrator type: Boyfriend/husband  * sexual_perpetrator_3: Perpetrator type: Female casual partner  * sexual_perpetrator_4: Perpetrator type: Male casual partner  * sexual_perpetrator_5: Perpetrator type: Family member  * sexual_perpetrator_6: Perpetrator type: Peer  * sexual_perpetrator_7: Perpetrator type: Female stranger  * sexual_perpetrator_8: Perpetrator type: Male stranger  * sexual_perpetrator_99: Perpetrator type: Refused  * any_victim_week: Whether the participant experienced any victimization in the past week (0 = No; 1 = Yes; 99 = Refused) * any_victim_day: Whether the participant experienced any victimization in the past 24 hours (0 = No; 1 = Yes; 99 = Refused) * saw_partner: Whether the participant saw their intimate partner in the past 24 hours (0 = No; 1 = Yes; 99 = Refused) * physical_IPV: Whether the participant perpetrated physical violence against their partner in the past 24 hours (0 = No; 1 = Yes; 99 = Refused) * sexual_IPV: Whether the participant perpetrated sexual violence against their partner in the past 24 hours (0 = No; 1 = Yes; 99 = Refused) ## Human subjects data Participants were identified by a unique anonymous study ID number in all electronic surveys and forms to maintain subject confidentiality. The random ID used in the dryad dataset is different from the anonymous study ID to ensure anonymity. The dataset is further limited to only those variables relevant to this paper.