The World Bank Economic Review, 39(3), 2025, 614–631 https://doi.org10.1093/wber/lhae039 Article Disclosure of Violence against Women and Girls in Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 Senegal Amber Peterman , Malick Dione, Agnes Le Port , Justine Briaux, Fatma Lamesse, and Melissa Hidrobo Abstract Measures of violence against women and girls (VAWG) are widely collected in surveys, yet estimates are ac- knowledged to be lower bounds of the true prevalence. This study reports on a survey experiment randomly assigning 3,400 women and girls to either face-to-face interviews or audio computer-assisted self-interviews (ACASI), a modality that increases privacy and confidentiality of responses. Results show the ACASI group discloses higher prevalence of lifetime intimate partner violence by 4 to 7 percentage points compared to face- to-face interviews. Differences in disclosure for nonpartner VAWG are even larger, ranging from 6 to 12 per- centage points. Tests for correlates of characteristics that might lead to increased disclosure show few notable patterns. Overall results suggest ACASI are a promising way to encourage disclosure, however trade-offs in- clude limits in the complexity of questions that can be asked and higher time costs associated with development and implementation of surveys. JEL classification: C83, J12, J16 Keywords: violence against women and girls, intimate partner violence, measurement, Senegal Amber Peterman (corresponding author) is a Research Associate Professor in the Department of Public Policy at the University of North Carolina, Chapel Hill, N.C., 27599, United States; her email address is amberpeterman@gmail.com. Malick Dione is a Research Analyst in the Nutrition, Diets, and Health Unit at the International Food Policy Research Institute (IFPRI), Dakar, Senegal; his email address is Malick.Dione@cgiar.org. Agnes Le Port is a Research Fellow at the Montpellier Interdis- ciplinary center on Sustainable Agri-food systems (MoISA), University of Montpellier, CIRAD, CIHEAM-IAMM, INRAE, Institut Agro, IRD, 34394, Montpellier, France; her email address is agnes.leport@ird.fr. Justine Briaux is a Public Health and Nutrition Specialist in the Program Section at United Nations Children’s Fund (UNICEF), West and Central Africa Regional Office (WCARO), Dakar, Senegal; her email address is jbriaux@unicef.org. Fatma Lamesse is a Reproductive Health and Rights Specialist at Carrefour International, Dakar, Senegal; her email address is flamesse@cintl.org. Melissa Hidrobo is a Senior Research Fellow in the Poverty, Gender, and Inclusion Unit at IFPRI, Washington, D.C., 20005, United States; her email address is m.hidrobo@cgiar.org. This work was supported by the Consultative Group for International Agricultural Research (CGIAR) Research Program on Policies, Institutions, and Markets (PIM), the CGIAR Gender Platform, and an Anonymous donor. The authors thank implementing partners, MobiCiné, in particular Ousseynou Thiam, and the Réseau Africain pour l’Education à la Santé (RAES), in particular Mbathio Diaw Ndiaye, Louise Lavabre, Julia Branchat, Clément Boutet, and Alexandre Rideau—who all made essential contributions to the broader evaluation. The authors also thank members of the study team contributing to the overall evaluation and previous survey waves, including Abdou Salam Fall, Jessica Heckert, Moustapha Seye, and Annick Nganya Tchamwa and IFPRI colleagues Nicole Rosenvaigue and Rock Zagre for excellent grant administration and assistance with survey coding. Thanks also go to the interviewers and field team from ASSMOR who managed the data C The Author(s) 2024. Published by Oxford University Press on behalf of the International Bank for Reconstruction and Development / THE WORLD BANK. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. The World Bank Economic Review 615 1. Introduction Violence against women and girls (VAWG) measures are widely collected in surveys and important met- rics for health, human rights, and gender equality, as reflected in Sustainable Development Goals (SDG) targets. VAWG includes, but is not limited to physical, sexual, and psychological violence perpetrated by intimate partners, family, co-workers, acquaintances, or strangers—both in and outside the home. De- Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 spite advancements in data collection methodologies, estimates from household surveys are universally acknowledged to be lower-bound estimates of the true prevalence (Sardinha et al. 2022). While the mag- nitude of under-reporting is thought to vary by data source, target group, and type of violence—evidence suggests under-reporting can be substantial. For example, a cross-country paper examining nationally representative samples in 24 low- and middle-income countries (LMICs) found that only 40 percent of females aged 15 to 49 experiencing physical and/or sexual VAWG had previously disclosed it to anyone, and only 7 percent reported it to a formal source (e.g., health, legal, or social service) (Palermo, Bleck, and Peterman 2014). Administrative data from formal sources is thus widely recognized to represent only the most severe cases, influenced by access to, and trust in, services, perceptions around impunity and financial ability to seek formal assistance, among others. While household surveys are understood to be closer to the true prevalence, disclosure in household survey data collection may be affected by a myriad of factors, including shame and stigma, fear of retaliation, distrust of interviewers, or desire to keep the perpetrator’s identity confidential (Palermo, Bleck, and Peterman 2014; Pereira et al. 2020). Rates of dis- closure have implications for data quality and the understanding of impacts of programs and policies to prevent and respond to VAWG, as well as for directing resources towards the issue as an investment in public health and human rights. Researchers have sought to understand how to accurately capture VAWG measures through different strategies. These include design of survey instruments to capture multiple behaviorally specific and diverse violent acts, specialized training of enumerators, and modification of data collection protocols to build rapport and create a safe space for disclosure. A set of studies also focus on rigorously testing differ- ent survey-administration techniques to increase disclosure and protect participant confidentiality. These studies typically randomize enumerator-administered face-to-face surveys to audio computer-assisted self- interviewing (ACASI) techniques; however, other comparisons include phone interviewing, sealed enve- lope methods, and qualitative methods (see table S1.1 in the supplementary online appendix for a list of studies).1 The basic assumption across studies is that soliciting responses with methods that provide increased privacy and confidentiality will mitigate response bias by reducing shame, stigma, social de- sirability, and fear of adverse consequences linked to disclosure. Six of the eight studies reviewed find significant differences in prevalence of VAWG in the hypothesized direction, although many studies also show heterogeneity in these differences across different settings or violence outcomes (Assefa et al. 2022; Barr et al. 2017; Cullen 2023; Park et al. 2022; Punjabi et al. 2021; Rathod et al. 2011; Stark et al. 2017; van der Elst et al. 2009). Studies varied in the type of violence analyzed (for example, whether violence was perpetrated by an intimate partner or not), how it was measured (using multiple questions or only one question), and the target sample and size. This variation makes it difficult to draw nuanced lessons across studies and contexts. collection process, as well as the women and adolescent girls interviewed for this study. Participants at the Sexual Violence Research Initiative (SVRI) forum 2022 and the PacDev Conference 2023 provided helpful comments. The views expressed in this article are those of the authors, and do not reflect those of the funding agencies. The data underlying this article and analysis replication files are provided as online supplementary materials. A supplementary online appendix is available at the World Bank Economic Review website. 1 A related group of studies examines differences in reporting with across face-to-face surveys using indirect (versus direct) methods for soliciting responses. For example, studies may use the “list randomization” technique, vignettes, or ask about experiences of neighbors or other community members (Cullen 2023; Lépine et al. 2020; Peterman 2021; Peterman et al. 2018). 616 Peterman et al. The closest to the current study based on geography, methods, and outcomes are Cullen (2023) and Park et al. (2022), who randomize ACASI and face-to-face surveys to collect measures of intimate part- ner violence (IPV) and nonpartner violence in Rwanda, and measures of IPV in Liberia and Malawi. In Rwanda, Cullen (2023) finds that women report higher sexual violence from nonpartners (3 percentage points, pp) using ACASI, but no differences in physical IPV. Likewise, men in Rwanda disclose higher rates of perpetration for some but not all emotional IPV questions using ACASI compared to face-to-face Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 administration. Park et al. (2022) find that women report higher values for all forms of IPV in Malawi when using ACASI (ranging from 5 to 18 pp); however, in Liberia, higher rates are seen only for sexual IPV and controlling behaviors using ACASI. Based on responses to nonsensitive questions, Park et al. (2022) suggest that increased prevalence in ACASI surveys may be in part due to “spurious reporting” driven by inability of participants to correctly key in responses on tablets. However, misuse of ACASI due to low comprehension of how to use tablets may be less of a concern for adolescents and youth. In addition, these challenges may be overcome even in areas with low digital literacy through close training and quality assurance. This paper adds to the literature on the role of survey administration on disclosure of VAWG. The study reports on a survey experiment randomly assigning approximately 3,400 adolescent girls and young women aged 15 to 35 in rural Senegal to either face-to-face interviews or ACASI. Results show participants in the ACASI group disclose higher prevalence of lifetime IPV by 4 to 7 pp compared to face-to-face interviews and these differences are more pronounced for more sensitive types of violence. Differences in reporting for nonpartner VAWG are even larger, ranging from 6 to 12 pp, for physical violence and sexual harassment, respectively. For the preferred measures of any physical and/or sexual violence, these differences equate to a 39 percent increase in prevalence for IPV and a 23 percent increase in prevalence for nonpartner VAWG among participants using ACASI (as compared to face-to-face administration). Results for continuous measures of violent acts and for past-year measures mirror those for lifetime experience. Tests for correlates of characteristics that might lead to increased disclosure show few notable patterns to explain these findings. Results suggest that self-administered surveys are a promising way to encourage disclosure, however acknowledged trade-offs include the limited complexity of questions that can be asked and higher time costs associated with development and implementation of ACASI surveys. This study contributes to existing literature in a number of ways. First, it shows how rates of disclosure vary by survey administration in a rural and conservative setting among a large sample of adolescent girls and young women. Adolescent girls and young women are a key target population for violence prevention, as they are often at higher risk for IPV as compared to older women and simultaneously are important for primary prevention intervention prior to relationship formation (Peterman, Bleck, and Palermo 2015; Sardinha et al. 2022). Second, it examines holistic measures of nonpartner violence, including violence women and girls may experience outside the home, such as sexual harassment. While there is a growing evidence-base on VAWG experienced in public spaces and work environments, there is less understanding of the role of stigma and potential for low disclosure (Borker 2021; Folke and Rickne 2022). This study examines how disclosure rates vary with different levels of severity, but also by type of VAWG and prox- imity (closeness) to perpetrators. Previous experimental studies on the role of survey administration have focused on IPV or on other specific forms of violence against children (e.g., school violence), often with limited outcome indicators, rather than holistic scales. This study avoids limitations from previous stud- ies, which have examined either fewer questions or single types of VAWG, thus limiting generalizability of findings. Third, analysis is conducted to show if disclosure varies by characteristics hypothesized to influ- ence participant’s ability and willingness to report VAWG. These include examination of logistical factors encountered in survey work, as well as validated scales capturing violence attitudes and norms. While few factors stood out as being strong correlates, in theory these factors can help unpack which groups are more or less likely to under-report in typical household surveys or in response to a particular inter- vention. Finally, the study highlights lessons from development and implementation of the ACASI, with The World Bank Economic Review 617 implications for future survey efforts aiming to conduct similar data collection efforts. Key evidence gaps for future research are discussed, focusing on the role of survey administration to increase the accuracy of VAWG measures, while implementing data collection in a participant-focused and ethical manner. 2. Context Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 Acceptability and Prevalence of VAWG in Senegal The setting of this study, Senegal, ranks as having high levels of gender inequality (139 out of 166 coun- tries on the Gender Development Index) (United Nations 2021). Senegal’s 1999 revision of the Penal Code includes a clause criminalizing acts of domestic violence, defined as “wounding, striking or physical abuse against partners,” punishable with up to 5 years in prison (and 20 years for domestic homicide) (OECD 2014). However, the law does not recognize marital rape, or other forms of sexual or emotional IPV, and few women seek formal legal action, possibly in part because police and other actors in the justice system are perceived to be lenient on perpetrators. Analysis of nationally representative data shows that approx- imately half of women in Senegal have attitudes justifying physical IPV; however, this percentage is higher at 64 percent in rural areas (Zegeye et al. 2021). Another analysis of a rural demographic surveillance site (Niakhar) shows similar levels of IPV acceptability among men and women at 61 percent—with highest levels for scenarios when a women refuses sex, goes out without telling her husband, or neglects children (Sandberg et al. 2021). Despite the high acceptance of IPV, official levels of IPV in Senegal are well be- low regional averages in West Africa. A global review using data from 366 studies across 161 countries estimates lifetime rates of sexual and/or physical IPV in West Africa at 27 percent (uncertainty levels: 22–33 percent) and past-year estimates at 15 percent (uncertainty levels: 12–19 percent) (Sardinha et al. 2022). However, the most recent Senegalese Demographic and Health Survey (DHS), collected in 2019, estimates these same figures to be approximately 13 and 6 percent for lifetime and past-year, respectively (ANSD and ICF 2020). Thus, official IPV prevalence for Senegal can be considered low for the region, raising questions as to whether Senegal is truly an outlier or if IPV is substantially underreported in official statistics. Qualitative Evidence on Acceptability and Disclosure of VAWG in Study Sample The study took place across two regions of Senegal—Kaolack in central Senegal, and Kolda in the south. These regions are both geographically and culturally distinct, with Kaolack composed mainly of Wolof ethnicity, and Kolda composed mainly of Fulakunda ethnicity (belonging to the Pular ethnic group). Qual- itative narratives among women and community health volunteers in study communities collected as part of a process evaluation, show that acceptability VAWG varies widely across the study sample.2 VAWG, particularly physical violence, was viewed as unacceptable in some communities and warranted interven- tion by both community leadership (or elders) and bystanders. In other communities it was normalized, despite community members being aware of violence, dominant narratives promoted silence to avoid “meddling in family affairs." These two quotes are characteristic of the range of contexts: These days, if you hurt your wife in the home and someone knows about it, people can file a complaint—and they will see how to find a solution so that it will stop … The community will never sit back “fold their arms” on cases of violence happening in this village. —Focus group married women, Kaolack 2 Data comes from 10 focus group discussions among women, 8 individual in-depth-interviews, and 4 key informant interviews with community health volunteers (who are often the first point of contact for women experiencing violence), stratified by region. Additional information regarding methodology and protocols related to the qualitative data collection can be found in Le Port et al. 2022. 618 Peterman et al. Abuse a woman, the community says nothing … The elders of this village, they won’t say anything, because not everyone interferes with the lives of others. Of course, your parents might come to you to talk about it, but otherwise, you’ll stay in this marriage until the end of your days. —Focus group married women, Kolda Despite this variation, most women interviewed as part of the qualitative data collection believed some form of IPV was normal in partnerships, as well as violence from in-laws or originating from extended family structures. Most women also mentioned disclosing violence to confidants and soliciting support Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 or advice (including mothers, uncles, aunts, brothers, or in-laws). Community health volunteers reported similar views, indicating that violence was a normal part of life in most villages. In addition, community health volunteers explained that few options existed for women in rural areas for support or assistance— several mentioning that they explicitly advise women not to take action if they experience violence: What I advise them to do is as I did: be patient, pray for a long life, and know that sooner or later things will get better … here you can’t come and tell someone to go to the police, file a complaint, as there’s no follow-up … there are no social services, you cannot even talk to a social worker! —Community Health Volunteer, Kaolack As is the case for all couples, there may be problems—but, as they say: “dirty laundry is washed at home”—so their intimate problems, they can settle internally. They won’t need to tell me. —Community Health Volunteer, Kolda However, some community health volunteers mentioned they acted to counsel families and spoke with men about violence to resolve it and keep it from escalating to more serious (and fatal) outcomes. Taken together, qualitative data suggests that although VAWG is common in study communities, there are a few formal support services or resources for women outside their network. While qualitative data are illustrative only, this study hypothesizes that the tendency for violence to be viewed as a family issue in the target population motivates the consideration of methodologies to increase disclosure within household survey efforts. In addition, wide variation in acceptability and community response to VAWG may drive variability in disclosure—thus motivating the analysis of correlates included in the current study. 3. Study Design Data Collection and the Measurement Experiment This study experimentally tests the role of survey administration within the endline survey of an edu- tainment evaluation designed as a cluster randomized control trial (cRCT) in 117 rural villages across Kaolack and Kolda (fig. S1.1in the supplementary online appendix).3 The study targeted adolescent and young adult women aged 14 to 34 at baseline, fluent in the dominant local language, and living up to two-kilometer radius to the village primary school. The endline survey took place from December 2020 to January 2021 led by the International Food Policy Research Institute (IFPRI) Dakar and ASSMOR con- sulting. At endline, women were approximately 15 to 35 years old. Of the 3,968 adolescent and young adult women interviewed at baseline just over 12 months prior, 86 percent (or 3,430) were successfully interviewed at endline. A companion impact evaluation paper shows no evidence of differential or overall attrition from baseline to endline with respect to aggregate VAWG attitude or behavior outcomes (Dione et al. 2023). The survey experiment was embedded in an enumerator administered survey, lasting on average 55 minutes and consisting of multitopic modules related to knowledge, attitudes, and behaviors on maternal and child health, sexual and reproductive health and VAWG. The surveys took place at or around the 3 Companion impact and process evaluation papers provide further information on the broader evaluation (Dione et al. 2023; Le Port et al. 2022). This includes information on the edutainment intervention which focused on health and gender themes. The current survey experiment was balanced across intervention arms (the percentages assigned to the edutain- ment intervention were 67 percent and 66 percent in the ACASI and face-to-face survey experiment arms, respectively; p-value from test of difference is 0.414) and there was no differential impact of the intervention across survey experiment arms. The World Bank Economic Review 619 Figure 1. Assignment of Survey Administration Mode (Face-to-Face versus Audio Computer-Assisted Self-Interviews, ACASI) Intent-to-treat analysis group Ability to be Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 interviewed Face-to-face Yes alone? interview Face-to-face randomization [44%, 1,505] 1/3 [34%, 1,155] 3,430 No females [2%, 20] [16%, 370] [15-35 No years] ACASI 2/3 randomization Pass test [66%, 2,275] ACASI questions & Yes interview tablet comfort* [56%, 1,925] Source: Authors’ representation based on experimental design of primary data collection in Senegal. Note: Three test questions resulted in a pass rate of 94 percent to 98 percent per question—for example, “Is Macky Sall the present of Senegal?” (correct answer: Yes). respondent’s homes, or alternatively in a nearby location in the community. The last module of the survey was on VAWG experiences and included an individual-level randomized assignment to either face-to-face (one-third of the sample) or ACASI (two-thirds of the sample) administration (fig. 1). These probabilities were chosen due to the anticipated higher reported rates of violence from ACASI interviews, thus a larger ACASI proportion would increase the ability to detect effects on VAWG in the primary cRCT. However, if respondents failed to demonstrate they understood how to operate the tablet, or if they voiced preference for not using the tablet, they were reassigned to face-to-face interviews (16 percent of the ACASI group, or n = 370). Conversely, for face-to-face interviews, enumerators screened participants based on their ability to be interviewed in private, out of earshot from individuals over the age of two years old. If enumerators were unable to secure privacy, participants were reassigned to ACASI interviews (2 percent of the face-to- face group, or n = 20). The final modality distribution was 44 percent face-to-face and 56 percent ACASI interviews. The entire survey, including the ACASI portion was coded using SurveyCTO, and the ACASI module was developed and tested based on an iterative process. First, experienced enumerators who had ad- ministered VAWG modules previously were selected to collaboratively develop local language scripts (in Wolof and Pular). Thereafter, all questions and scripts were recorded into audio clips and validated for sound quality as well as accuracy and fidelity to the original scripts in French. Audio recordings were then preloaded onto the SurveyCTO platform, coded alongside visual images representing answers to questions. A green circle indicated “Yes,” a red square indicated “No,” and an outline of a star indicated “Refusal or do not know” (fig. S1.2). ACASI scripts and functionality were further tested during enu- merator training and piloting, including iterative cognitive interviews with approximately 40 participants selected during the piloting of the entire survey (undertaken once in urban Dakar and once in a rural area outside Dakar). Pilots showed that participants were able to respond to the ACASI module, under- stood the questions, and the vast majority preferred ACASI as compared to enumerator administered violence questions. Based on the pilots, small changes to audio recordings and to the tablet screening and 620 Peterman et al. functionality were made to increase participants’ understanding of the module before the primary data collection. During actual implementation of the VAWG module, for the ACASI arm, enumerators keyed in the local language of choice, introduced the ACASI, and explained to participants how to listen to questions using headsets, how to repeat them if needed, and how to enter responses and advance the module. Participants then undertook three test questions with the enumerator watching. These test questions were structured Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 such that all participants should both know the answer and either pick “Yes” or “No”—for example: “Is Macky Sall the president of Senegal?” (answer: Yes). Correct responses included both “Yes” and “No” answers, so that participants were not biased towards only one response option. At the end of the practice session, enumerators asked if participants were comfortable undertaking the module. Enumerators sat nearby while women completed ACASI in case there were any questions or need for intervention, for example, to explain to other household members that women and girls should be left alone to complete the survey if interruptions occurred. Table S1.2 gives details on the screening questions administered, showing that high levels of women answered the test questions correctly—in total 89 percent of the sample answering all three correctly. Violence Against Women and Girls Measures The study focuses on two primary groups of VAWG measures. The first set of questions were modeled after the Senegalese DHS to capture past-year and lifetime IPV using a modified conflict tactics scale following the WHO multicountry study on domestic violence (ANSD and ICF 2020; Garcia-Moreno et al. 2006). These questions were asked only to women and girls who were currently partnered or partnered in the previous 12 months, including noncohabiting and dating partners. Specific questions include those related to emotional IPV (5 questions, e.g., partner said something to humiliate you in front of others), physical IPV (7 questions, e.g., partner tried to choke you or burn you on purpose), and sexual IPV (3 questions, e.g., partner physically forced you to have sexual intercourse with him when you did not want to). The second set of questions combines validated instruments for nonpartner domestic violence, sexual harassment, and community violence, as no single common instrument is routinely used to cover a diverse set of perpetrators, locations, and types of violence. These questions also asked about lifetime and past- year experience related to emotional VAWG (6 questions, e.g., spread false rumors about you or one of your children), physical VAWG (4 questions, e.g., forced you to work excessively against your will), and sexual harassment and violence (8 questions, e.g., made unwelcome attempts to establish a romantic or sexual relationship with you, despite your efforts to discourage it). The second set of questions was asked to all participants, with the caveat that items pertained to all possible perpetrators (both male or female) except current or previous romantic partner. Table S1.3 gives detailed descriptions of questions and indicators used for violence outcomes, including the coding of missing observations across items used to construct aggregate scores.4 In addition to the main behavioral outcomes, auxiliary violence indicators are also analyzed: (1) if the respondent would hypothetically intervene in the case of a neighbor’s physical IPV (full sample), (2) if she has told anyone about her own experience of IPV in the last 12 months (including friends, family, etc.), and (3) if she has tried to get help to stop IPV from happening to her in the last 12 months (latter two indicators for the ever-partnered sample only). The study hypothesizes that the same factors potentially driving under-reporting for experience measures would operate for these measures as well. For example, if 4 Due to the coding of “don’t know/refuse” answers, the total sample sizes for each aggregate are slightly different. For example, for binary outcomes (such as any violence) the entire aggregate is coded as missing if at least one of the items is missing, and none of the other responses are affirmative (as this means the entire aggregate could be “Yes” or “No”), but as nonmissing if at least one item is coded as affirmative. This strategy ensures that the overall VAWG aggregate is not biased downward because of missing responses. For continuous outcomes, each act of violence that is nonmissing is summed and a standardized z-score is created of the sum in relation to the comparison group (face-to-face administration). The World Bank Economic Review 621 IPV is thought to be a “family” issue or accepted within spousal relationships, women are unlikely to view intervening to stop abuse as an acceptable action in the case of a neighbor’s situation. In addition, there may be shame or stigma attached to discussing IPV outside the couple, or seeking help, as social norms may dictate that women should tolerate violence or keep discussion or disclosure of violence within the family. Ethical Protocol Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 Ethics approval for the study was granted by the Comité National d’Ethique pour la Recherche en Santé in Senegal (#00000929 MSAS/DPRS/DR) and by IFPRI’s Institutional Review Board (#00007490). These included amendments for implementing surveys during COVID-19 and ensuring safety and equipment protocols were in place for enumerators and participants. Standard protocols set out by the WHO were implemented to ensure the safety of participants and enumerators while collecting violence data (World Health Organization 2001). All interviews were carried out by female enumerators, matched by language group (Wolof, the dominant language in Kaolack, or Pular, the dominant language in Kolda), who un- derwent specialized training on interviewing for VAWG topics, with preference in recruitment given to enumerators who had experience collecting sensitive data. During interviews, written informed consent was obtained from all participants at the start of the survey. For minors, written assent was obtained, along with written informed consent from the legal guardian. The study followed best practice during interviews by ensuring privacy (except for children under the age of two), implementing graduated in- formed consent, allowing women to skip questions voluntarily and advertising the survey as related to health and wellbeing—rather than linked explicitly to VAWG. All participants, regardless of disclosure, were given a card with de-identified local referral sources (as well as a toll-free national hotline), unless they indicated they could not safely keep the card without others, including partners, discovering it. In this case, enumerators orally discussed referral options and provided hotline information. Enumerators also offered direct referrals, whereby regional service providers would seek out women and girls directly for acute cases or upon request of participants. Acute cases were monitored to ensure proper and timely response. Both de-identified and direct referrals were offered to women regardless of whether they re- sponded to questions face-to-face or via ACASI. Enumerators were offered access to the same services and assistance as survey participants to cope with vicarious trauma or own experiences with violence. Analysis Two main analyses are presented. First, simple mean comparisons of VAWG outcomes among participants randomized to ACASI versus face-to-face interviews are reported. In addition, the coefficient of being assigned to ACASI are reported from unadjusted linear probability regressions with standard errors clus- tered at the village level. Standard errors are clustered at the village level due to the high intercluster corre- lation typically observed for VAWG measures; however, results are virtually unchanged using robust stan- dard errors (without clustering). A variety of sensitivity analysis are also conducted, controlling for addi- tional background characteristics of participants and their households, as well as enumerator fixed effects, which may influence the quality of the survey implementation. Background characteristics include age splines, levels of educational achievement, ethnicity indicators, household size, and an indicator of whether the participant has ever been partnered.5 As not all participants ultimately completed the survey modality to which they were assigned, this analysis is akin to an intent-to-treat (ITT) analysis. Results are presented for lifetime VAWG measures; however, they replicate results for the 12-month measures as a robustness check. In addition, following evidence showing that conceptually using continuous measures capturing 5 A small number of observations are missing for both background characteristics (education level, household size) and for heterogenous effects (crowding and cohabitation with partner), totaling 2.8 percent of the sample. These missing observations are replaced with means and binary indicators for missing are included in regression analysis. However, because missing observations are few and balanced across the face-to-face and ACASI groups, this results in very little change to results. Results are also robust to imputing missings instead of mean replacement. 622 Peterman et al. the number or frequency of distinct acts of VAWG is distinct from binary outcomes, and may result in dif- ferent conclusions, summary counts are analyzed of different violent acts constructed as z-scores, for each type of VAWG category (Boyer et al. 2022; Peterman et al. 2022). Finally, results are estimated for actual administration of ACASI versus face-to-face using an instrumental variable approach (akin to treatment- on-the-treated or TOT analysis) using the indicator for randomization to ACASI as the instrument. Second, heterogeneous effects are analyzed to explore possible factors that may explain differences in Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 reporting, by adding indicators of interest to the regression and interacting them with the ACASI indi- cator. Two groups of indicators are explored: (1) logistical factors hypothesized to discourage disclosure and (2) attitudes and norms justifying VAWG. The first group of indicators includes (a) an indicator in- dicating if her spouse or partner is cohabiting (as partners migrate for work in this setting, set to 0 if the participant is not currently partnered), (b) an indicator of crowding (number of household members / number of sleeping rooms), and (c) an index of the number of times the interview had to be stopped due to an interruption (by a partner or other male adult) during the violence module. These logistical factors may make women less likely to disclose in face-to-face surveys due to fear of partners or other house- hold members overhearing, especially if there is high interest or attention to the interview. The second group of factors are motivated by qualitative work in study locations and include 2 indices of individual attitudes and perceived community norms justifying IPV and sexual violence aggregating 17 questions answered on Likert scales (Perrin et al. 2019). The study hypothesizes that participants facing logistical constraints to disclosure will be both more likely to experience VAWG on average, and more likely to disclose when administered ACASI as compared to face-to-face modules (thus one would expect interac- tion terms to be positive). In addition, if VAWG is accepted and normalized, participants may be more likely to experience VAWG on average, but with less stigma attached to it, thus this sample is less likely to drive increased disclosure (thus one would expect interaction terms to be negative) (Humbert et al. 2021). For both sets of factors, indices are transformed into z-scores, standardized to the face-to-face group for ease of interpretation. Table S1.3 provides a more detailed description of these indicators and details on aggregation.6 Summary Statistics and Balance Tests Table 1 shows balance by randomization to ACASI or face-to-face administration by background char- acteristics of participants. The sample is approximately 24 years old, with the largest age group among adolescents aged 15 to 19 (31 percent) and the remaining age groups with 21 to 24 percent of the sample. Approximately 45 percent of the sample has never attended school, and the majority ethnicity is Pular, followed by Wolof and Serer. The average household size is 11 members, and 85 percent of the sample is ever partnered (including both marital and nonmarital partners). Across the 20 variables represent- ing background characteristics and factors affecting disclosure, only one indicator (age between 30–35 years) is marginally significant at the p < 0.10 level. Based on these results, the randomization to survey administration mode appears successful, and the experiment is likely to have high internal validity. 4. Results Figure 2 summarizes mean differences in reporting between face-to-face (dark grey bars) and ACASI (light grey bars) methods, showing means and 95 percent confidence intervals. Results indicate that in all cases ACASI disclosure of VAWG is significantly higher than face-to-face methods; these differences range from 6 Ex-ante power calculations were not conducted for this survey experiment; however, the ex-post minimal detectable effect size for any physical and/or sexual IPV is 4.9 pp and for any physical and/or sexual VAWG is 5.5 pp. However, it is likely the study is underpowered to detect correlates of disclosure via interaction terms; thus this analysis should be interpreted with caveats. The World Bank Economic Review 623 Table 1. Balance in Background Variables and Predictors between ACASI and Face-to-Face Samples All ACASI Face-to-face p-value from difference Age splines (1) (2) (3) (2)-(3) Age 15–19 years 0.309 0.313 0.302 0.512 Age 20–24 years 0.244 0.239 0.255 0.280 Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 Age 25–29 years 0.211 0.205 0.223 0.258 Age 30–35 years 0.235 0.243 0.220 0.082 Education level Never attended school 0.445 0.444 0.446 0.918 Completed or some primary 0.279 0.281 0.275 0.763 Completed or some secondary 0.276 0.275 0.279 0.838 Ethnicity Wolof 0.306 0.301 0.316 0.343 Pular 0.451 0.450 0.454 0.823 Serer 0.153 0.154 0.151 0.760 Other 0.090 0.095 0.080 0.140 Demographics Currently or previously partnered 0.852 0.847 0.862 0.196 Household size 11.166 11.175 11.147 0.876 Factors affecting disclosure Logistical factors discouraging disclosure (z-score) − 0.033 − 0.047 − 0.004 0.202 Partner is currently cohabiting 0.571 0.571 0.573 0.880 Crowding (household size/rooms) 2.792 2.771 2.832 0.135 Interruptions due to partner or other adult male (0–4) 0.096 0.092 0.104 0.408 Attitudes and norms justifying VAWG (z−score) 0.033 0.049 0.002 0.210 Attitudes justifying VAWG 13.477 13.569 13.295 0.203 Norms justifying VAWG 14.658 14.738 14.500 0.403 Sample size 3,430 2,275 1,155 Source: Authors’ calculations based on primary data collection in Senegal. Note: ACASI = Audio computer-assisted self-interviews; VAWG = Violence against women and girls; p-values are reported from Wald tests on the equality of means of randomization to either ACASI or face-to-face interviews for each variable. Standard errors are clustered at the village level. See table S1.3 for full descriptions of indicators. Figure 2. Mean Differences in Reporting between ACASI and Face-to-Face Administered Violence Indicators *** *** 4.9 pp 10.7 pp *** *** *** 7.2 pp *** 9.8 pp 7.0 pp 11.7 pp Prevalence Prevalence *** 3.7 pp *** 6.1 pp Emotional IPV Physical IPV Sexual IPV Physical Emotional VAWG Physical VAWG Sexual Physical and/or and/or sexual harassment or sexual VAWG IPV VAWG IPV experience (lifetime) Violence experience by non-partners (lifetime) Face-to-face ACASI Source: Authors’ calculations based on primary data collection in Senegal. Note: ACASI = Audio computer-assisted self-interviews; IPV = intimate partner violence; VAWG = Violence against women and girls; bars are mean value with 95 percent confidence interval bars; differences are reported from regression analysis of randomization to ACASI for each outcome with clustered standard errors at the village level. ∗ = p < 0.10, ∗ ∗ = p < 0.05, ∗∗∗ = p < 0.01. Standard errors are clustered at the village level. See table 2 for detailed statistics and table S1.3 for full descriptions of indicators. 624 Peterman et al. 3.7 pp (sexual) to 7.2 pp (physical and/or sexual) for IPV and from 6.1 pp (physical) to 11.7 (sexual harassment or violence) for VAWG measures. While categories are not directly comparable, in general prevalence is higher for VAWG measures than in relation to those for IPV, which reflects a broader set of perpetrators and environments where violence may occur. For the preferred measures of any physical and/or sexual violence, these differences equate to a 39 percent higher prevalence of IPV and a 23 percent higher in prevalence of nonpartner VAWG among participants using ACASI. Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 Table 2 gives details underlying these figures, showing that differences in disclosure between ACASI and face-to-face are highly statistically significant even when controlling for enumerator fixed effects and a broader set of control variables (columns 6a/6b). In most cases, differences decrease slightly when addi- tional controls are added—indicating that these factors may explain some of the differences in disclosure between the two modalities. For example, differences are smaller for any IPV (5.6 pp versus 7.2 pp) and any VAWG (8.3 pp versus 9.8 pp) in the adjusted model. Across groups of measures, the differences in disclosure across the ACASI and face-to-face groups are largest among the least common type of violence. For example, ACASI disclosure is 18 percent higher than face-to-face for lifetime emotional IPV, but 58 percent higher for lifetime sexual IPV. This may be because women react to privacy and confidentiality of the ACASI method by disclosing more stigmatizing information, rather than simply responding at equally higher rates each survey question. Table S1.4 illustrates how the 15 individual questions aggregated to create the indicator of any physical and/or sexual IPV contribute to these disclosure differences. While most individual indicators are signifi- cant, this is not always the case, particularly when control variables are added. In addition to the study’s primary questions, table 2 also reports auxiliary violence questions around help-seeking and bystander intervention. Similar to the main experience measures, the analysis shows significantly higher disclosure for all measures in the ACASI sample. Participants are more likely to indicate willingness to intervene in the case of a neighbor’s physical IPV (73 percent versus 69 percent), have previously told someone else about their own IPV experiences (23 percent versus 12 percent), and have tried to get help for their own IPV experiences (17 percent versus 3 percent) when assigned to ACASI administration. Table S1.5 in the supplementary online appendix replicates these results for continuous violence mea- sures and table S1.6 for 12-month measures. Both tables show very similar patterns, whereby ACASI disclosure is significantly higher than face-to-face reporting. Table S1.5 shows that participants random- ized to ACASI report anywhere from 0.150 to 0.275 standard deviation (SD) higher prevalence of violent acts as compared to face-to-face measures. The measure of combined physical and/or sexual IPV acts show differences of approximately 0.266 SDs in unadjusted models, and approximately 0.222 SDs in adjusted models, which are similar to magnitudes for physical and/or sexual VAWG. Figure S1.3 shows the distribution of combined acts for IPV and VAWG as cumulative distribution plots—showing that for each “count” of violent acts, the distribution of the ACASI sample shifted right in comparison to the face-to-face sample (signaling a higher cumulative distribution of acts). Table S1.6 shows that 12-month prevalence of violence is substantially lower than lifetime violence; however; the main results mirror those presented in table 2, except for emotional IPV (where differences in disclosure are not significant). Finally, table S1.7 shows TOT results, instrumenting actual completion of the ACASI module with the random- ized assignment. Results show differences are slightly larger than those show in table 2: for any IPV (any VAWG), unadjusted differences are 8.9 pp (12.0 pp). Table 3 reports results from analysis exploring factors hypothesized to be correlated with disclosure, focusing on lifetime measures of physical and/or sexual IPV and VAWG. For each group of factors, over- all measures are reported (followed by disaggregated components), including both the coefficient of the variables alongside the coefficient of the interaction term with ACASI from separate regressions. While overall factors show significant correlations with lifetime violence outcomes (columns 1a and 2a), in no case are interaction terms significant (columns 1b and 2b). Although results confirm that participants facing logistical constraints and those who live in settings with attitudes and norms justifying VAWG are Table 2. Differences in Disclosure of Lifetime VAWG in ACASI and Face-to-Face Samples Sample means Regression analysis of differences (ACASI) The World Bank Economic Review N All Face-to-face ACASI Coefficient [unadjusted] p-value Coefficient [adjusted] p-value Intimate partner violence (ever partnered sample) (1) (2) (3) (4) (5a) (5b) (6a) (6b) Emotional IPV 2,892 0.312 0.279 0.328 0.049 0.004 0.042 0.016 Physical IPV 2,895 0.219 0.173 0.243 0.070 0.000 0.055 0.001 Sexual IPV 2,896 0.088 0.064 0.101 0.037 0.001 0.029 0.014 Physical and/or sexual IPV 2,891 0.237 0.189 0.262 0.072 0.000 0.056 0.001 Nonpartner violence against women (full sample) Emotional VAWG 3,393 0.594 0.523 0.630 0.107 0.000 0.086 0.000 Physical VAWG 3,405 0.229 0.189 0.250 0.061 0.000 0.050 0.001 Sexual harassment or VAWG 3,401 0.455 0.377 0.494 0.117 0.000 0.104 0.000 Physical and/or sexual VAWG 3,398 0.494 0.428 0.527 0.098 0.000 0.083 0.000 Auxiliary violence measures Would intervene in the case of neighbors’ physical IPV 3,430 0.720 0.694 0.733 0.038 0.030 0.040 0.017 Told anyone about own IPV (12 months) 2,915 0.190 0.118 0.228 0.110 0.000 0.107 0.000 Tried to get help to stop own IPV (12 months) 2,915 0.122 0.032 0.169 0.137 0.000 0.131 0.000 Source: Authors’ calculations based on primary data collection in Senegal. Note: ACASI = Audio computer-assisted self-interviews; IPV = intimate partner violence; VAWG = Violence against women and girls; Reported coefficients and p-values are reported from separate regressions of violence outcomes on an indicator for being randomized to ACASI. Standard errors are clustered at the village level. Control variables used in columns (6a/6b) are age splines, education levels, ethnicity indicators, household size, and enumerator fixed effects. See table S1.3 for full descriptions of indicators. 625 Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 626 Peterman et al. Table 3. Factors Correlated with Increased Reporting of Lifetime VAWG Measures in ACASI Physical and/or sexual IPV Physical and/or sexual VAWG Coefficient Coefficient control Coefficient Coefficient control × control variable × ACASI control variable ACASI Factors affecting disclosure (z-scores) (1a) (1b) (2a) (2b) Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 Logistical factors discouraging disclosure 0.038 −0.016 −0.041 −0.003 (0.012)∗∗∗ (0.016) (0.018)∗∗ (0.021) Partner is cohabiting 0.052 −0.023 −0.081 0.004 (0.012)∗∗∗ (0.016) (0.015)∗∗∗ (0.020) Crowding index 0.006 −0.017 −0.018 0.014 (0.012) (0.014) (0.015) (0.019) Interruptions during violence module 0.012 0.012 0.028 −0.014 (0.013) (0.018) (0.015)∗ (0.019) Attitudes and norms (z-scores) Attitudes and norms justifying VAWG 0.077 0.014 0.096 −0.032 (0.016)∗∗∗ (0.017) (0.018)∗∗∗ (0.021) Attitudes justifying VAWG 0.041 0.017 0.049 −0.021 (0.016)∗∗∗ (0.017) (0.018)∗∗∗ (0.019) Norms justifying VAWG 0.084 0.006 0.101 −0.029 (0.015)∗∗∗ (0.016) (0.018)∗∗∗ (0.020) N 2,891 3,398 Source: Authors’ calculations based on primary data collection in Senegal. Note: ACASI = Audio computer−assisted self-interviews; VAWG = Violence against women and girls; ∗ = p < 0.10, ∗ ∗ = p < 0.05, ∗∗∗ = p < 0.01; Coefficients are from separate estimates regressing violence outcomes on each control variable (group) and its interaction with ACASI. Standard errors are clustered at the village level. See table S1.3 for full descriptions of indicators. generally more likely to disclose violence—they are equally likely to disclose regardless of mode of survey administration. Results are replicated for continuous measures of violent acts, as well as for attitude and norm measures aggregated to the village level; however, very similar results are found (thus the study does not report them). The analysis may lack sufficient power to detect heterogenous effects reported in table 3; however, note that in most cases coefficients are very small and thus are unlikely to contribute substantially to overall differences in disclosure. 5. Discussion and Conclusions This study reports on a survey experiment in rural Senegal randomly varying whether women and ado- lescent girls complete a violence module administered by enumerators face-to-face or through ACASI. Respondents randomized to ACASI report higher lifetime IPV (ranging from 3.7 to 7.2 pps), as well as lifetime nonpartner VAWG (ranging from 6.1 to 11.7 pps). These same patterns are observed for auxiliary measures of IPV, including willingness to intervene and help seeking, as well as for scales of violent acts and 12-month measures of violence experience. These results add to existing evidence from the Africa region that find divergent results, with some studies showing higher prevalence among ACASI groups as compared to face-to-face measures, but not for all IPV measures or contexts (Cullen 2023; Park et al. 2022). In this study’s population, patterns suggest higher prevalence in ACASI groups across outcomes, including nonpartner VAWG. Approximately a third of the sample are adolescent girls (aged 15–19 years), who are a key target group for both IPV prevention, as well as multi-faceted VAWG intervention program- ming. Historically, adolescent girls have been overlooked by violence sectors focusing on either children or adult women (Engel et al. 2022). However, adolescents are increasingly the target of primary prevention interventions, as a group facing high risk of violence and their unique situation in formative years, when The World Bank Economic Review 627 norms and relationship trajectories are determined (Yount, Krause, and Miedema 2017). Understanding how to best collect accurate measures of VAWG within the adolescent population is critical for future evaluation and prevention research. Results show few significant correlates of higher disclosure via ACASI, adding to the limited and vari- able results from studies experimenting with modalities of survey administration. For example, in Rwanda women in communities with more unequal gender norms, higher vulnerability, and poorer relationship Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 quality were more likely to report IPV in a list experiment, as compared to a face-to-face survey (Cullen 2023). However, these and other factors did not differ significantly between women who participated in ACASI versus face-to-face surveys in the same study. In addition, no differences in disclosure of forced sex among adolescents were found by background characteristics in a face-to-face versus sealed-envelope survey method, including by age and sex (Barr et al. 2017). The lack of identified correlates may indicate that the current study did not identify and test meaningful background characteristics for this setting, and that other unobservable or other unmeasured operational factors might be driving increased disclosure, or that the analysis is underpowered. For example, participants may be influenced by how fearful they are of adverse reactions by partners, how comfortable they feel with enumerators (including whether they feel enumerators are empathetic or open to their responses) or if they have previously discussed or disclosed violence to family members or friends. Overall, this analysis suggests that similar surveys in Senegal that collect face-to-face measures may be at risk of low VAWG disclosure. For example, this study finds rates of lifetime physical and/or sexual IPV that are double the prevalence as compared to the most recent nationally representative data (23 percent versus 13 percent) (table S1.8) (ANSD and ICF 2020). Rates are consistently larger in this study when the comparison is a DHS sample of adolescent girls and women in rural areas, in the same regions as the current study and of the same age range.7 If national data on VAWG is a lower bound of true prevalence, these statistics may lead to underinvestment in VAWG prevention. Moreover, they may lead to incorrect conclusions from impact evaluations if low disclosure weakens the power of studies to detect impacts or if disclosure is nonrandom. In cases where surveys aim to measure impacts of evaluations that might increase disclosure in the first instance (as is the case for social norms interventions), the cost of low disclosure may be high. In these cases, interventions may increase disclosure rates in treatment groups, leading to the inability to conclude if the intervention increased violent behavior—or just increased disclosure of violence more generally. This study shows the process through which ACASI is developed and how the manner in which survey logistics are handled will have implications for accuracy of data and success of self-interviewing tech- niques. For example, acknowledging that the current sample was rural and that a meaningful proportion of women and girls had never been to school, the practice (test) questions were built into the survey pro- tocol and participants were allowed to “opt-out” of ACASI if they did not feel comfortable. These results are not fully reconcilable with concerns of mechanical misreporting due to lack of comprehension of the ACASI found in Malawi and Liberia; however, the allowance to opt out of ACASI in the current study partially mitigates this concern (Park et al. 2022). In practice, approximately 16 percent of the sample originally randomized to ACASI was redirected to face-to-face interviews, either because they were not able to complete test questions correctly, or because they preferred not to continue. Table S1.9 shows the women and girls who switch to face-to-face interviews are on average older, more likely to be partnered, have lower education levels, and vary on a number of other background characteristics. This indicates that planning and flexibility may be needed to accommodate cases in which respondents may not be 7 Senegalese DHS rates are consistently closer to this study’s face-to-face prevalence as compared to ACASI prevalence, with the subsample corresponding to Kaolack and Kolda regions approaching comparability in any physical and/or sexual IPV (both at approximately 18–19 percent). Note that the DHS is not meant to be representative at these lower levels and there are small differences in the questions used in the DHS versus the current experiment. Thus, comparisons are illustrative only. 628 Peterman et al. willing or able to accurately complete ACASI on their own. A process evaluation in Ethiopia and the Democratic Republic of Congo find similar results that indicate high acceptability and understanding of ACASI, yet still include a minority sample that had comprehension challenges (90 percent of girls in DRC and 75 percent of girls in Ethiopia stated ACASI was “easy to understand”) (Falb et al. 2017). ACASI implementation also requires substantial up-front investment in terms of coding and additional supplies (headphones, cleaning agents for tablets if interviewing during COVID-19 etc.) (Falb et al. 2017). Finally, Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 ACASI comes with a time cost—participants who completed the ACASI module (1 of 16 modules in the survey) spent on average 4 minutes longer than face-to-face interviews, an increase of 8 percent in the total survey time. These factors indicate that ACASI requires advanced planning and careful attention to survey implementation to ensure that modules are well suited for the target population. There are also trade-offs between ACASI and face-to-face methods in terms of data completeness and detail of information that is collected. The current survey did not ask follow-up questions about the frequency of experiencing different acts (as is common in the DHS) or ask about type of perpetrator for nonpartner VAWG, as these were assessed to include too many complex response options to ensure accuracy. These limitations were weighed against the benefits of simpler measures in ACASI that could increase disclosure. The mode of data collection may also affect the occurrence of “don’t know or refuse” responses. In the current study, overall rates were low (4 percent for VAWG measures); however, ACASI more than doubled these rates (significant at the p < 0.01 level). While suggestive, this could be because women and girls could more easily opt out of answers without pressure from enumerators. This option might be welcome for participants; however, it should be weighed against concerns around data com- pleteness. Although the majority of research examining the role of survey administration indicates that there is higher disclosure of violence via private methods, there is still little research validating accuracy of either method to understand trade-offs across methods, target groups, and locations. Additional analysis is warranted on what aspects of face-to-face interviews might reduce disclosure in the first instance— whether it is fear that responses will be overheard by others, concern that responses may have broader repercussions for women or perpetrators, or interview fatigue, among others.8 Qualitative methods or survey experiments may be well suited to answer these questions. Finally, additional guidance around ethical protocols appropriate for ACASI survey administration is needed (Peterman et al. 2023). In this study, similar ethical protocols were followed for both face-to-face and ACASI, as survey work required preparation for both modalities. However, it is not clear if the mode of interviewing has implications for future uptake of services or negative (positive) emotional reactions that might be associated with surveys, or if studies would seek to streamline some aspects of ethics if no direct interaction with participants required asking about violence via interviewers. While measurement of some types of violence, including IPV, has been established for decades—there is need for additional ethical experimentation to improve the accuracy of measurement. In addition to a tendency to under-report due to stigma and shame, survivors of severe violence may block out or fail to re- member traumatic events, or the specific time period when such events occurred. Further, no standardized scales exist for some forms of violence, including economic coercion or sexual harassment and warrant further testing and validation (Ranganathan et al. 2021; Yount et al. 2022). Moreover, outcome measures still tend to be one-dimensional (binary prevalence measures), obscuring the understanding of changes in frequency, severity, and dynamism over time (Boyer et al. 2022). While indirect methods to solicit expe- rience of violence have become more popular in recent years, including list randomization, there are still outstanding questions as to the accuracy and utility of these types of measures (Cullen 2023; Gilligan 8 Violence modules are often placed at the end of the survey, in order to increase rapport between interviewer and participant over the course of the interview and maximize potential for privacy. However, this may also lead to under-reporting if participants understand the interview time will shorten with fewer “yes” answers that lead to follow-up questions. The World Bank Economic Review 629 et al. 2024; Peterman 2021; Peterman et al. 2018). Ethical and survivor-centered experimentation can spur progress towards more accurate data collection of measures, and more effective policy and program action to reduce VAWG. Data Availability Statement Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 The data underlying this article and analysis replication files are provided as online supplementary mate- rials. References ANSD, & ICF. 2020. Senegal: Enquête Démographique et de SantéContinue (EDS- Continue) 2019. ICF: Rockville, Maryland, United States. Accessed May 15, 2023. https://dhsprogram.com/publications/publication- FR368- DHS- Final-Reports.cfm. Assefa, T., A. Kadam, N. Magnan, E. McCullough, and T. McGavock. 2022. “Measuring the Effects of Survey Methods on Women’s Life Experience (WLE).” Research in Agricultural & Applied Economics. Barr, A.L., L. Knight, I. França-Junior, E. Allen, D. Naker, and K.M. Devries. 2017. “Methods to Increase Reporting of Childhood Sexual Abuse in Surveys: The Sensitivity and Specificity of Face-to-Face Interviews versus a Sealed Envelope Method in Ugandan Primary School Children.” BMC International Health and Human Rights 17(1): 4. https://doi.org/10.1186/s12914- 016- 0110- 2. Borker, G. 2021. “Publication: Safety First: Perceived Risk of Street Harassment and Educational Choices of Women.” Policy Research Working Paper #9731, https://openknowledge.worldbank.org/entities/publication/3867d5d3-4f2c - 5b2a- 8d7a- 9204fc9dcae6. Accessed May 15, 2023. World Bank: Washington D.C., United States. Boyer, C., S. Chatterji, J. Cooper, and L. Heise. 2022. “Outcome Coding Choice in Randomized Trials of Programs to Reduce Violence.” (arXiv:2204.12385). Accessed May 15, 2023. http://arxiv.org/abs/2204.12385. Ithaca, N.Y., United States. Cullen, C. 2023. “Method Matters: The Underreporting of Intimate Partner Violence.” World Bank Economic Review 37(1): 49–73. https://doi.org/10.1093/wber/lhac022. Dione, M., J. Heckert, M. Hidrobo, A. Le Port, A. Peterman, and M. Seye. 2023. “C’est la Vie!: Mixed Impacts of an Edutainment Television Series in West Africa.” International Food Policy Research Institute: Washington D.C., United States. https://doi.org/10.2499/p15738coll2.137017. Engel, D., S. Vyas, S. Chalasani, J.R. Luna, and A. Robinson. 2022. “Violence against Adolescents: Prevention Must Cross the Divide between Children and Women.” BMJ 379: e067682. https://doi.org/10.1136/bmj- 2021- 067682. Falb, K., S. Tanner, K. Asghar, S. Souidi, S. Mierzwa, A. Assazenew, T. Bakomere, P. Mallinga, K. Robinette, W. Tibebu, and L. Stark. 2017. “Implementation of Audio-Computer Assisted Self-Interview (ACASI) among Adolescent Girls in Humanitarian Settings: Feasibility, Acceptability, and Lessons Learned.” Conflict and Health 10(1): 32. https: //doi.org/10.1186/s13031- 016- 0098- 1. Folke, O., and J. Rickne. 2022. “Sexual Harassment and Gender Inequality in the Labor Market.” Quarterly Journal of Economics 137(4): 2163–212. https://doi.org/10.1093/qje/qjac018. Garcia-Moreno, C., H.A. Jansen, M. Ellsberg, L. Heise, and C.H Watts. 2006. “Prevalence of Intimate Partner Violence: Findings from the WHO Multi-Country Study on Women’s Health and Domestic Violence.” Lancet 368(9543): 1260–9. https://doi.org/10.1016/S0140- 6736(06)69523- 8. Gilligan, D.O., M. Hidrobo, J. Leight, and H. Tambet. 2024. “Using a List Experiment to Measure Intimate Partner Violence: Cautionary Evidence from Ethiopia.” Applied Economics Letters. 1–7. https://doi.org/10.1080/135048 51.2024.2308579. Humbert, A.L., S. Strid, J. Hearn, and D. Balkmar. 2021. “Undoing the ‘Nordic Paradox’: Factors Affecting Rates of Disclosed Violence against Women across the EU.” PLoS ONE 16(5): e0249693. https://doi.org/10.1371/journal. pone.0249693. Lépine, A., C. Treibich, and B. D’Exelle. 2020. “Nothing but the Truth: Consistency and Efficiency of the List Ex- periment Method for the Measurement of Sensitive Health Behaviours.” Social Science & Medicine 266: 113326. https://doi.org/10.1016/j.socscimed.2020.113326. 630 Peterman et al. Le Port, A., M., Seye, J., Heckert, A., Peterman, A.N., Tchamwa, M., Dione, A.S., Fall, and M. Hidrobo, 2022) A community edutainment intervention for gender-based violence, sexual and reproductive health, and maternal and child health in rural Senegal: a process evaluation BMC Public Health 22(1165): 1471–2458. https://doi.org/10.1 186/s12889- 022- 13570- 6. OECD. 2014. “Social Institutions and Gender Index (SIGI): Senegal.” OECD Development Center: Paris, France. Accessed May 15, 2023. https://www.genderindex.org/wp-content/uploads/files/datasheets/SN.pdf. Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 Palermo, T., J. Bleck, and A. Peterman. 2014. “Tip of the Iceberg: Reporting and Gender-Based Violence in Developing Countries.” American Journal of Epidemiology 179(5): 602–12. https://doi.org/10.1093/aje/kwt295. Park, D.S., S. Aggarwal, J. Robinson, D. Jeong, A. Spearot, and N. Kumar. 2022. “Private but Misunderstood? Evidence on Measuring Intimate Partner Violence via Self-Interviewing in Rural Liberia and Malawi.” World Bank Research Working Paper #10124. World Bank: Washington, D.C., United States. Accessed March 1, 2023. https://hdl.hand le.net/10986/37732. Pereira, A., A. Peterman, A.N. Neijhoft, R. Buluma, R.A. Daban, A. Islam, E.T.V. Kainja, I.F. Kaloga, T. Kheam, A.K. Johnson, M.C. Maternowska, A. Potts, C. Rottanak, C. Samnang, M. Shawa, M. Yoshikawa, and T. Palermo. 2020. “Disclosure, Reporting and Help Seeking among Child Survivors of Violence: A Cross-Country Analysis.” BMC Public Health [Electronic Resource] 20(1): 1051. https://doi.org/10.1186/s12889- 020- 09069- 7. Perrin, N., M. Marsh, A. Clough, A. Desgroppes, C.Y. Phanuel, A. Abdi, F. Kaburu, S. Heitmann, M. Yamashina, B. Ross, S. Read-Hamilton, R. Turner, L. Heise, and N. Glass 2019. Social norms and beliefs about gender based violence scale: a measure for use with gender based violence prevention programs in low-resource and humanitarian settings Conflict and Health 13(6): 1752–1505 . https://doi.org/10.1186/s13031- 019- 0189- x. Peterman, A. 2021. “The Art of Indirect Measures: Asking about Violence Against Women and Children in Remote Surveys.” Accessed May 1, 2023. https://www.cgdev.org/blog/art- indirect- measures- asking- about- violence- against - women- and- children- remote- surveys. Center for Global Development: Washington, D.C., United States. Peterman, A., J. Bleck, and T. Palermo. 2015. “Age and Intimate Partner Violence: An Analysis of Global Trends Among Women Experiencing Victimization in 30 Developing Countries.” Journal of Adolescent Health 57(6): 624–30. https://doi.org/10.1016/j.jadohealth.2015.08.008. Peterman, A., K. Devries, A. Guedes, J.S. Chandan, S. Minhas, R.Q.H. Lim, F. Gennari, and A Bhatia. 2023. “Ethical Reporting of Research on Violence against Women and Children: A Review of Current Practice and Recommen- dations for Future Guidelines.” BMJ Global Health 8(5): e011882. https://doi.org/10.1136/bmjgh- 2023- 011882. Peterman, A., T.M. Palermo, S. Handa, and D. Seidenfeld. 2018. “List Randomization for Soliciting Experience of 10:30 AM: Application to the Evaluation of Zambia’s Unconditional Child Grant Program.” Health Economics 27(3): 622–28. https://doi.org/10.1002/hec.3588. Peterman, A., E. Valli, and T. Palermo 2022. “Government Antipoverty Programming and Intimate Partner Violence in Ghana.” Economic Development and Cultural Change 70(2):529–66. https://doi.org/10.1086/713767. Punjabi, M., J. Norman, L. Edwards, and P. Muyingo. 2021. Using ACASI to Measure Gender-Based Violence in Ugandan Primary Schools. RTI Press: Research Triangle Park, N.C., United States. https://doi.org/10.3768/rtipre ss.2021.rb.0025.2104. Ranganathan, M., J. Wamoyi, I. Pearson, and H. Stöckl. 2021. “Measurement and Prevalence of Sexual Harassment in Low- and Middle-Income Countries: A Systematic Review and Meta-Analysis.” BMJ Open 11(6): e047473. https://doi.org/10.1136/bmjopen- 2020- 047473. Rathod, S.D., A.M. Minnis, K. Subbiah, and S. Krishnan. 2011. “ACASI and Face-to-Face Interviews Yield Inconsis- tent Estimates of Domestic Violence Among Women in India: The Samata Health Study 2005–2009”. Journal of Interpersonal Violence 26(12): 2437–56. https://doi.org/10.1177/0886260510385125. Sandberg, J.F., V. Delaunay, Y. Boujija, L. Douillot, S. Bignami, S. Rytina, and C Sokhna. 2021. “Individual, Commu- nity, and Social Network Influences on Beliefs Concerning the Acceptability of Intimate Partner Violence in Rural Senegal.” Journal of Interpersonal Violence 36(11–12): 5610−5642. https://doi.org/10.1177/0886260518805778. Sardinha, L., M. Maheu-Giroux, H. Stöckl, S.R. Meyer, and C. García-Moreno. 2022. “Global, Regional, and National Prevalence Estimates of Physical or Sexual, or Both, Intimate Partner Violence Against Women in 2018.” Lancet 399(10327): 803–13. https://doi.org/10.1016/S0140- 6736(21)02664- 7. Stark, L., M. Sommer, K. Davis, K. Asghar, A. Assazenew Baysa, G. Abdela, S. Tanner, and K. Falb 2017. Disclosure bias for group versus individual reporting of violence amongst conflict-affected adolescent girls in DRC and Ethiopia. PLoS One 12, e0174741. https://doi.org/10.1371/journal.pone.0174741. The World Bank Economic Review 631 United Nations Development Program. 2021. “Gender Development Index.” Human Development Reports. UNDP: New York, N.Y., United States. Accessed March 1, 2023. https://hdr.undp.org/gender- development- index. van der Elst, E.M., H.S. Okuku, P. Nakamya, A. Muhaari, A. Davies, R.S. McClelland, M.A. Price, A.D. Smith, S.M. Graham, and E.J. Sanders. 2009. “Is Audio Computer-Assisted Self-Interview (ACASI) Useful in Risk Behaviour Assessment of Female and Male Sex Workers, Mombasa, Kenya?” PLoS ONE 4(5): e5340. https://doi.org/10.137 1/journal.pone.0005340. Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 World Health Organization. 2001. “Putting Women First: Ethical and Safety Recommendations for Research on Domestic Violence against Women (WHO/FCH/GWH/01.1).” Global Programme for Evidence for Health Policy. World Health Organization: Geneva, Switzerland. Accessed May 1, 2022. https://apps.who.int/iris/handle/10665 /65893. Yount, K.M., Y.F. Cheong, S. Miedema, and R.T. Naved. 2022. “Development and Validation of the Economic Coercion Scale 36 (ECS-36) in Rural Bangladesh.” Journal of Interpersonal Violence 37(13–14): NP10726–57. https://doi.org/10.1177/0886260520987812. Yount, K.M., K.H. Krause, and S.S Miedema. 2017. “Preventing Gender-Based Violence Victimization in Adolescent Girls in Lower-Income Countries: Systematic Review of Reviews.” Social Science & Medicine 192: 1–13. https: //doi.org/10.1016/j.socscimed.2017.08.038. Zegeye, B., G. Shibre, B.O. Ahinkorah, M. Keetile, and S. Yaya. 2021. “Urban-Rural Disparities in Wife-Beating Attitude Among Married Women: A Decomposition Analysis from the 2017 Senegal Continuous Demographic and Health Survey.” Archives of Public Health 79(1): 1−14. https://doi.org/10.1186/s13690- 021- 00612- 5. Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 Supplementary Online Appendix Disclosure of Violence against Women and Girls in Senegal Amber Peterman , Malick Dione, Agnes Le Port , Justine Briaux, Fatma Lamesse, and Melissa Hidrobo S1: Additional Figures and Tables Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 Figure S1.1. Map of study Regions and Survey Administration Randomization (top: Kaolack, bottom: Kolda) Source: Authors’ calculations based on primary data collection in Senegal. Figure S1.2. ACASI Tablet Screen Examples Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 Source: Authors’ screenshots based on Survey CTO tablet application for primary data collection in Senegal. Figure S1.3. Cumulative Distribution Plots of Violence Acts (Continuous Indicators) by Survey Administration Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 Source: Authors’ calculations based on primary data collection in Senegal. Note: ACASI = Audio computer-assisted self-interviews; IPV = intimate partner violence; VAWG = Violence against women and girls; lines show the cumulative distribution of violence acts for IPV and VAWG by randomization to either ACASI or face-to-face interviews for each outcome. See table S1.3 for full descriptions of indicators. Table S1.1. Evidence on the Role of Survey Administration on Measures of Violence against Women and Adolescent Girls Survey Authors (year) Setting Sample VAWG measure(s) administration Main finding(s) Assefa et al. Ethiopia 637 women (age Controlling behaviors (index of 10 Face-to-face • Women are equally likely to indicate they have freedom of (2022)† range NR) items related to mobility) (male movement with male and female enumerators (conditional on enumerator) a phone interview) vs. phone • Women are 0.23 SDs less likely to state they have freedom (male of movement over the phone (conditional on a male enumerator) enumerator) vs. phone (female enumerator)1 Barr et al. Uganda 3,842 adolescents Forced sex (1 item) Sealed • Sealed envelope method resulted in significantly higher (2017)∗ aged ∼13–14 years envelope vs. disclosure (7.1%) as compared to face-to-face methods face-to-face (1.1%) Cullen (2023)∗ Rwanda 1,855 women Nonpartner sexual violence (1 item); Face-to-face vs. • ACASI associated with 3 pp higher disclosure of sexual aged ≥ 18 years physical IPV (1 item) ACASI violence; no significant difference for physical IPV 1,851 men Emotional IPV perpetration (2 items) • ACASI associated with 20 pp higher disclosure of limiting aged ≥ 18 years family contact; no significant difference for threating to hurt wife or someone close to her Park et al. Liberia 1,261 women (age Controlling behaviors, emotional, Face-to-face vs. • ACASI associated with 7 pp higher values for index of (2022)† range NR) physical, sexual, and combined IPV ACASI controlling behaviors and 8 pp higher values on index of (20 items) sexual IPV; no significant difference on emotional, physical, or combined IPV Malawi 1,737 women (age • ACASI associated with higher values on all indices: range NR) controlling behaviors (18 pp), emotional IPV (10 pp), physical IPV (5 pp), sexual IPV (6 pp), any IPV (13 pp) Punjabi et al. Uganda 854 students (half Sexual violence, corporal Face-to-face vs. • Sexual violence: Higher disclosure for ACASI (77.3% vs. (2021)† P5 level, mean age punishment, and bullying ACASI 43.3) 12 years & half P7 • Corporal punishment: Higher disclosure for ACASI (95.9% level, mean age 14) vs. 92.8%) • Bullying: No significant differences (97.1% vs. 96.0%) Rathod et al. India 464 women aged Physical IPV (1 item) Face-to-face vs. • ACASI associated with lower disclosure (RR = 0.61 and (2011)∗ 18 to 26 years ACASI 0.74 at wave 1 and wave 2) Stark et al. Ethiopia 165 adolescent girls Prevalence and perpetrators of ACASI vs. • Group-based qualitative narratives focused on disclosure of (2017)∗ aged 10 to 19 in physical, sexual, and emotional qualitative violence perpetrated by strangers or community members, refugee camps violence group while ACASI revealed violence disclosure predominantly by discussions intimate partners and family members Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 Table S1.1. Continued Survey Authors (year) Setting Sample VAWG measure(s) administration Main finding(s) van der Elst et Kenya 139 female sex Rape (1 item) Face-to-face vs. • No significant differences by survey administration al. (2009)∗ workers aged 22 to ACASI 35 years Source: Authors’ original compilation based on review of existing studies. Note: ∗ = journal publication; † = working paper, pre-print or research brief; ACASI = audio computer-assisted self-interview; IPV = intimate partner violence; NR = not reported; RR = risk ratio; SD = standard deviation; 1 In addition, some respondents were randomly assigned to have more frequent interaction with enumerators over the phone as part of a different treatment, thus authors are able to isolate the effects of increased rapport—however, there are no significant effects of this additional treatment either among the full sample or among female enumerators on freedom of movement. Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 Table S1.2. ACASI Screening Test Questions (n = 2,275) Response [%, n] Don’t know or Question Correct response Yes No refused 1 Are you at least 15 years old? Yes 0.95 [2,158] 0.04 [81] 0.02 [36] Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 2 Do you currently live in St. Louis? No 0.05 [115] 0.94 [2,143] 0.01 [17] 3 Is Macky Sall the president of Senegal? Yes 0.98 [2,221] 0.02 [48] 0.00 [6] Summary statistics [%, n] All questions correct (fully passed test) 0.89 [2,036] Source: Authors’ calculations based on primary data collection in Senegal. Note: ACASI = Audio computer-assisted self-interviews; Sample is among those originally randomized to ACASI; however, response percentages are nearly identical when including those who switched to ACASI due to inability to be interviewed in private. Table S1.3. Definitions and Indicator Construction of Key Outcome and Background Variables Outcome variables: Violence against women and girls indicators Indicator Description and construction of the variable Emotional IPV Binary and sum indicators created from a total of five questions following the WHO modified conflict tactics scale with all questions responding yes, no, or don’t know/refuse. Please tell me if these apply to your relationship (past relationship) with your husband or partner, did he ever: (1) He (does/did) things to scare or intimidate you on purpose, by the way he looked at you, by yelling or smashing things? (2) He (does/did) not trust you to spend money? (3) Said something to humiliate you in front of others? (4) He (threatens/threatened) to hurt or harm you or someone that you care about? (5) He (insults/insulted) you or made you feel bad about yourself? The binary aggregate is coded = 1 if any response is yes. If any item is missing (response is “don’t know/refuse”) and all other items are responded as no, the aggregate is coded as missing. This sum aggregate is coded as missing if any single item is missing. Physical IPV Binary and sum indicators created from a total of seven questions following the WHO modified conflict tactics scale with all questions responding yes, no, or don’t know/refuse. Please tell me if these apply to your relationship (past relationship) with your husband or partner, did he ever: (1) Push you, shake you, or throw something at you ?(2) Slap you ? (3) Twist your arm or pull your hair ? (4) Punch you with his fist or with something that could hurt you ? (5) Kick you, drag you, or beat you up? 6) Try to choke you or burn you on purpose ? (7) Threaten or attack you with a knife, gun, or sharp object or other weapon ? The binary aggregate is coded = 1 if any response is yes. If any item is missing (response is “don’t know/refuse”), and all other items are responded as no, the aggregate is coded as missing. This sum aggregate is coded as missing if any single item is missing. Sexual IPV Binary and sum indicators created from a total of three questions following the WHO modified conflict tactics scale, with all questions responding yes, no or don’t know/refuse. Please tell me if these apply to your relationship (past relationship) with your husband or partner, did he ever: (1) Physically force you to have sexual intercourse with him when you did not want to)? (2) Physically force you to perform any other sexual acts you did not want to? (3) Force you with threats or in any other way to perform sexual acts you did not want to? The binary aggregate is coded = 1 if any response is yes. If any item is missing (response is “don’t know/refuse”) and all other items are responded as no, the aggregate is coded as missing. This sum aggregate is coded as missing if any single item is missing. Physical and/or Combination of physical IPV and sexual IPV aggregates, coded as missing if either aggregate is missing. sexual IPV Table S1.3. Continued Outcome variables: Violence against women and girls indicators Indicator Description and construction of the variable Emotional Binary and sum indicators created from a total of six questions, with all questions responding yes, no, or VAWG don’t know/refuse. Has anyone ever (1) Screamed at you, either when you were alone or in front of others? Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 (2) Excessively criticized you or insulted you ether when you were alone or in front of others? (3) Threatened to hurt you or one of your children? (4) Spread false rumors about you or one of your children? (5) Ignored you and refused to talk to you, intentionally left you out or did not allow you to do things you wanted to? (6) Taken or stolen, broke or ruined your belongings? The binary aggregate is coded = 1 if any response is yes. If any item is missing (response is “don’t know/refuse”) and all other items are responded as no, the aggregate is coded as missing. This sum aggregate is coded as missing if any single item is missing. Physical Binary and sum indicators created from a total of four questions, with all questions responding yes, no, or VAWG don’t know/refuse. Has anyone ever (1) Forced you to work excessively against your will? (2) Withheld food from you, did not allow you to eat, starved you, or forced you to eat things that you did not want to? (3) Slapped you, pushed or punched you, shook you, or threw something at you, pushed you, grabbed your arm, pulled your hair, crushed your fingers or hands, punched or kicked you? (4) Beat you or attacked you with a weapon, cut you, dragged you, tried to strangle or suffocate you or burned you? The binary aggregate is coded = 1 if any response is yes. If any item is missing (response is “don’t know/refuse”) and all other items are responded as no, the aggregate is coded as missing. This sum aggregate is coded as missing if any single item is missing. Sexual Binary and sum indicators created from a total of eight questions, with all questions responding yes, no, or harassment don’t know/refuse. Has anyone ever (1) Whistled, called, or hooted at you in a sexual way? (2) Made gestures and VAWG or used body language of a sexual nature which embarrassed or offended you? (3) Made sexual comments or offensive remarks about your appearance, body, or sexual stories or jokes that were offensive? (4) Stared, leered, or ogled you in a way that made you feel uncomfortable? (5) Touched you in a way that made you feel uncomfortable or exposed themselves in front of you in a way that made you feel uncomfortable? (6) Made unwelcome attempts to establish a romantic or sexual relationship with you—despite your efforts to discourage it? (7) Tricked, threatened, or blackmailed you, or physically forced you to have sexual intercourse when you did not want to? (8) Tricked, threatenedii or blackmailed you, or physically forced you to perform any other sexual acts you did not want to, including forcing you to kiss them or touch yourself? The binary aggregate is coded = 1 if any response is yes. If any item is missing (response is “don’t know/refuse”) and all other items are responded as no, the aggregate is coded as missing. This sum aggregate is coded as missing if any single item is missing. Physical and/or Combination of physical VAWG and sexual harassment and VAWG aggregates, coded as missing if either sexual VAWG aggregate is missing. Factors affecting disclosure Indicator Description and construction of the variable Logistical Equally weighted z-score index comprised of the following individually standardized indicators with respect factors related to the face-to-face administered group: to disclosure (1) Indicator of if partner is currently co-habiting (=0 if the respondent is not partnered) (2) Crowding (household size divided by the number of sleeping rooms in the dwelling) (3) Index of interruptions during the violence module, defined as if enumerator recorded one interruption (coded = 1) or two or more interruptions (coded = 2) because of an adult trying to listen, come into the room, or interfere in the interview in any way. Indicators for husband/partner, and any other adult male are aggregated into a scale ranging from 0 to 4. Table S1.3. Continued Outcome variables: Violence against women and girls indicators Indicator Description and construction of the variable Attitudes and Equally weighted z-score index comprised of the following indices following Perrin et al. 2019’s “Social norms norms and beliefs about gender-based violence scale” (coded such that attitudes and norms justifying VAWG Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 justifying are higher)—all the scales’ alpha values from principal component analysis are > 0.80: VAWG (1) Sexual violence attitudes: Equally weighted index from five questions from the personal beliefs on response to sexual violence sub-scale—with response options: 1 (agree), 2 (not sure if I agree or disagree), 3 (disagree, but am not ready to tell others), and 4 (disagree and would be willing to tell others): (1) “Husbands should abandon/reject/divorce their wife if she reports that she has been raped”; (2) “A man should have the right to demand sex from a woman or girl even if he is not married to her”; (3) “A woman/girl would be stigmatized if she were to report sexual violence”; (4) A woman/girl should be blamed when she has been raped”; and (5) “Families should ignore/reject a daughter if she reports that she has been raped” 2) IPV attitudes: Equally weighted index created from four questions from the personal beliefs on husbands’ right to use violence subscale—with response options: 1 (agree), 2 (not sure if I agree or disagree), 3 (disagree, but am not ready to tell others), and 4 (disagree and would be willing to tell others): (1) “It is okay for a husband to beat his wife to discipline her”; (2) When a man beats his wife, he is showing his love for her"; (3) “A man has the right to beat/punish his wife”; and (4) “A husband should force his wife to have sex when she does not want to.” 3) Sexual violence norms: Equally weighted index from four questions concerning social norms on response to sexual violence subscale—with response options: 1 (none of them), 2 (a few of them), 3 (about half of them), 4 (most of them), and 5 (all of (them): (1) “How many of the people whose opinion matters most to you expect a husband to abandon his wife if she reports that she has been raped?”; (2) “How many of the people whose opinion matters most to you expect the family to ignore/reject a daughter if she reports that she has been raped?”; (3) “How many of the people whose opinion matters most to you accept sexual violence against women and girls as a normal part of life?” and (4) “How many of the people whose opinion matters most to you blame women/girls when they are raped?” 4) IPV norms: Equally weighted index from four questions from the personal beliefs on husbands’ right to use violence subscale of the—with response options: 1 (none of them), 2 (a few of them), 3 (about half of them), 4 (most of them), and 5 (all of them): (1) “How many of the people whose opinion matters most to you think that when a man beats his wife, he is showing his love for her?”; (2) “How many of the people whose opinion matters most to you think that a man has the right to beat/punish his wife?”; (3) “How many of the people whose opinion matters most to you think it is okay for a husband to beat his wife to discipline her?”; (4) “How many of the people whose opinion matters most to you expect a husband to force his wife to have sex when she does not want to?” Source: Authors’ notes on definitions used in primary data collection in Senegal. Note: IPV = intimate partner violence; VAWG = Violence against women and girls. Table S1.4. Differences in Disclosure of Lifetime IPV in ACASI and Face-to-Face Samples for Individual Physical and/or Sexual Indicators Sample means Regression analysis of differences (ACASI) Face-to- Coefficient Coefficient N All face ACASI [unadjusted] P-value [adjusted] p-value Intimate partner violence (ever partnered sample) (1) (2) (3) (4) (5a) (5b) (6a) (6b) (1) Does things to scare or intimidate you on purpose? 2,895 0.144 0.130 0.151 0.021 0.117 0.014 0.299 (2) Does not trust you to spend money? 2,898 0.155 0.125 0.170 0.045 0.002 0.046 0.001 (3) Said something to humiliate you in front of others? 2,902 0.109 0.078 0.126 0.048 0.000 0.041 0.001 (4) Threatens to hurt or harm you or someone that you care about? 2,902 0.075 0.061 0.082 0.021 0.046 0.017 0.115 (5) Insults you or makes you feel bad about yourself? 2,899 0.111 0.097 0.118 0.021 0.071 0.017 0.151 (6) Push you, shake you, or throw something at you? 2,901 0.074 0.047 0.088 0.040 0.000 0.035 0.000 (7) Slap you? 2,899 0.161 0.129 0.178 0.049 0.001 0.035 0.010 (8) Twist your arm or pull your hair? 2,906 0.082 0.045 0.100 0.055 0.000 0.049 0.000 (9) Punch you with his fist or with something that could hurt you? 2,902 0.074 0.056 0.083 0.027 0.004 0.021 0.031 (10) Kick you, drag you, or beat you up? 2,902 0.069 0.040 0.084 0.044 0.000 0.040 0.000 (11) Try to choke you or burn you on purpose? 2,899 0.028 0.010 0.038 0.028 0.000 0.024 0.000 (12) Threaten or attack you with a knife, gun, or sharp object or other weapon? 2,900 0.023 0.007 0.032 0.025 0.000 0.022 0.000 (13) Physically forced you to have sexual intercourse with him when you did not want to? 2,902 0.068 0.054 0.074 0.020 0.049 0.013 0.189 (14) Physically force you to perform any other sexual acts you did not want to? 2,905 0.052 0.033 0.062 0.029 0.002 0.024 0.008 (15) Force you with threats or in any other way to perform sexual acts you did not want to? 2,901 0.043 0.023 0.054 0.031 0.000 0.027 0.000 Source: Authors’ calculations based on primary data collection in Senegal. Note: ACASI = Audio computer-assisted self-interviews; IPV = intimate partner violence; Coefficients and p-values are reported from separate regressions of violence outcomes on an indicator for being randomized to ACASI. Standard errors are clustered at the village level. Control variables used in columns (6a/6b) are: age splines, education levels, ethnicity indicators, an indicator of if the participant is ever partnered, household size, and enumerator fixed effects. See table S1.3 for full descriptions of indicators. Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 Table S1.5. Differences in Disclosure of Lifetime VAWG in ACASI and Face-to-Face Samples (Continuous Measures) Sample means (sum measure) Regression analysis of differences (ACASI, z-scores) Face-to- Coefficient Coefficient N All face ACASI [unadjusted] p-value [adjusted] p-value Intimate partner violence (1) (2) (3) (4) (5a) (5b) (6a) (6b) Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 (ever partnered sample) Emotional IPV 2,880 0.590 0.493 0.641 0.150 0.001 0.129 0.004 Physical IPV 2,886 0.508 0.336 0.598 0.275 0.000 0.233 0.000 Sexual IPV 2,895 0.163 0.111 0.190 0.167 0.001 0.133 0.007 Physical and/or sexual IPV 2,879 0.669 0.449 0.783 0.266 0.000 0.222 0.000 Nonpartner violence against women (full sample) Emotional VAWG 3,355 1.384 1.184 1.487 0.213 0.000 0.168 0.000 Physical VAWG 3,402 0.368 0.281 0.413 0.197 0.000 0.164 0.000 Sexual harassment or 3,381 1.156 0.922 1.276 0.229 0.000 0.192 0.000 VAWG Physical and/or sexual 3,371 1.523 1.205 1.687 0.250 0.000 0.209 0.000 VAWG Source: Authors’ calculations based on primary data collection in Senegal. Note: ACASI = Audio computer-assisted self-interviews; IPV = intimate partner violence; VAWG = Violence against women and girls; coefficients and p-values are reported from separate regressions of violence outcomes on an indicator for being randomized to ACASI. Standard errors are clustered at the village level. Control variables used in columns (6a/6b) are age splines, education levels, ethnicity indicators, an indicator of whether the participant is partnered, household size and enumerator fixed effects. See table S1.3 for full descriptions of indicators. Table S1.6. Differences in Disclosure of 12-Month VAWG in ACASI and Face-to-Face Samples Sample means Regression analysis of differences (ACASI) Coefficient Coefficient N All Face-to-face ACASI [unadjusted] p-value [adjusted] p-value Intimate partner violence (ever (1) (2) (3) (4) (5a) (5b) (6a) (6b) partnered sample) Emotional IPV 2,882 0.224 0.218 0.227 0.009 0.539 0.008 0.587 Physical IPV 2,887 0.122 0.084 0.141 0.057 0.000 0.051 0.000 Sexual IPV 2,892 0.059 0.043 0.068 0.024 0.008 0.018 0.043 Physical and/or sexual IPV 2,883 0.138 0.099 0.158 0.058 0.000 0.050 0.000 Nonpartner violence against women (full sample) Emotional VAWG 3,371 0.491 0.437 0.519 0.082 0.000 0.066 0.001 Physical VAWG 3,396 0.146 0.091 0.175 0.083 0.000 0.075 0.000 Sexual harassment or 3,384 0.340 0.268 0.377 0.108 0.000 0.099 0.000 VAWG Physical and/or sexual 3,382 0.370 0.292 0.410 0.118 0.000 0.106 0.000 VAWG Source: Authors’ calculations based on primary data collection in Senegal. Note: ACASI = Audio computer-assisted self-interviews; IPV = intimate partner violence; VAWG = Violence against women and girls; coefficients and p-values are reported from separate regressions of violence outcomes on an indicator for being randomized to ACASI. Standard errors are clustered at the village level. Control variables used in columns (6a/6b) are: age splines, education levels, ethnicity indicators, an indicator of if the participant is ever partnered, household size and enumerator fixed effects. See table S1.3 for full descriptions of indicators. Table S1.7. Differences in Disclosure of Lifetime VAWG in ACASI and Face-to-Face Samples from TOT Estimates Sample means Regression analysis of differences (ACASI) Coefficient Coefficient N All Face-to-face ACASI [unadjusted] p-value [adjusted] p-value Intimate partner violence (ever (1) (2) (3) (4) (5a) (5b) (6a) (6b) Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 partnered sample) Emotional IPV 2,892 0.312 0.291 0.328 0.060 0.003 0.052 0.013 Physical IPV 2,895 0.219 0.169 0.259 0.086 0.000 0.069 0.000 Sexual IPV 2,896 0.088 0.056 0.114 0.046 0.001 0.036 0.012 Physical and/or sexual IPV 2,891 0.237 0.184 0.280 0.089 0.000 0.071 0.001 Nonpartner violence against women (full sample) Emotional VAWG 3,393 0.594 0.501 0.666 0.130 0.000 0.107 0.000 Physical VAWG 3,405 0.229 0.171 0.274 0.074 0.000 0.062 0.001 Sexual harassment or 3,401 0.455 0.346 0.540 0.143 0.000 0.129 0.000 VAWG Physical and/or sexual 3,398 0.494 0.393 0.572 0.120 0.000 0.103 0.000 VAWG Auxiliary violence measures Would intervene in the case 3,430 0.720 0.696 0.739 0.047 0.028 0.049 0.014 of neighbors’ physical IPV Told anyone about own IPV 2,915 0.190 0.115 0.251 0.135 0.000 0.134 0.000 (12 months) Tried to get help to stop 2,915 0.122 0.031 0.196 0.168 0.000 0.164 0.000 own IPV (12 months) Source: Authors’ calculations based on primary data collection in Senegal. Note: ACASI = Audio computer-assisted self-interviews; IPV = intimate partner violence; TOT = treatment-on-the-treated; VAWG = Violence against women and girls; reported coefficients and p-values are reported from separate regressions of violence outcomes on an indicator for being administered ACASI, instrumenting administration with an indicator of randomization to ACASI. Standard errors are clustered at the village level. Control variables used in columns (6a/6b) are age splines, education levels, ethnicity indicators, an indicator of if the participant is ever partnered, household size and enumerator fixed effects. See table S1.3 for full descriptions of indicators. Table S1.8. Comparison between Lifetime IPV Measures in Primary Data and the Senegalese Demographic and Health Survey (2019) Survey experiment: 15 to 35 years DHS: 15 to 49 years Rural Regions: Age group: 15 to 34 All ACASI Face-to-face Full sample sample Kaolack + Kolda years (1) (1a) (1b) (2a) (2b) (2c) (2d) Emotional IPV 0.312 0.328 0.279 0.099 0.103 0.149 0.091 Physical IPV 0.219 0.243 0.173 0.114 0.113 0.157 0.105 Sexual IPV 0.088 0.101 0.064 0.038 0.045 0.046 0.041 Physical and/or 0.237 0.262 0.189 0.131 0.129 0.184 0.124 sexual IPV Sample size 2,896 2,896 2,896 1,468 482 239 885 Source: Authors’ calculations based on primary data collection in Senegal and the Senegalese Demographic and Health Survey (2019). Note: ACASI = Audio computer-assisted self-interviews; DHS = Demographic and Health Survey; IPV = intimate partner violence; Means in the DHS use domestic violence sample weights and are constructed using the “subpop” command. Columns 2b, 2c, and 2d limit the DHS sample to the rural population only, the regional populations of Kaolack and Kolda and age range in the experiment, respectively. DHS estimates are not representative in subpopulations and thus are illustrative only. Small differences exist between the DHS and survey experiment questions for IPV; however, there is a high degree of comparability. See table S1.3 for full descriptions of indicators in the survey experiment data. Table S1.9. Analysis of Background Variables in “Switchers” from ACASI and Face-to-Face ACASI Switched to p-value from All [implemented] face-to-face difference Age splines (1) (2) (3) (2)–(3) Age 15–19 years 0.313 0.322 0.262 0.018 Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 Age 20–24 years 0.239 0.240 0.232 0.728 Age 25–29 years 0.205 0.203 0.216 0.554 Age 30–35 years 0.243 0.234 0.289 0.022 Education level Never attended school 0.444 0.424 0.549 0.000 Completed or some primary 0.281 0.280 0.284 0.897 Completed or some secondary 0.275 0.296 0.168 0.000 Ethnicity Wolof 0.301 0.305 0.278 0.466 Pular 0.450 0.440 0.500 0.129 Serer 0.154 0.165 0.100 0.002 Mandingue, Diola, Sonike, or other 0.095 0.090 0.122 0.338 Demographics Currently or previously partnered 0.847 0.840 0.884 0.027 Household size 11.175 11.269 10.695 0.070 Factors affecting disclosure Logistical factors discouraging disclosure (z-score) -0.047 -0.060 0.018 0.111 Partner is currently cohabiting 0.571 0.560 0.627 0.011 Crowding (household size/rooms) 2.771 2.769 2.784 0.843 Interruptions due to partner or other adult male (0–4) 0.092 0.093 0.089 0.904 Attitudes and norms justifying VAWG (z-score) 0.049 0.069 −0.054 0.178 Attitudes justifying VAWG 13.569 13.476 14.051 0.279 Norms justifying VAWG 14.738 15.049 13.138 0.002 Sample size 2,275 1,905 370 Source: Authors’ calculations based on primary data collection in Senegal. Note: ACASI = Audio computer-assisted self-interviews; VAWG = Violence against women and girls; p-values are reported from Wald tests on the equality of means of randomization to either ACASI or face-to-face interviews for each variable. Standard errors are clustered at the village level. See table S1.3 for full descriptions of indicators. References for the Supplementary Online Appendix Assefa, T., A. Kadam, N. Magnan, E. McCullough, and T. McGavock. 2022. “Measuring the Effects of Survey Methods on Women’s Life Experience (WLE).” Research in Agricultural & Applied Economics. Barr, A.L., L. Knight, I. França-Junior, E. Allen, D. Naker, and K.M. Devries. 2017. “Methods to Increase Reporting of Childhood Sexual Abuse in Surveys: The Sensitivity and Specificity of Face-to-Face Interviews versus a Sealed Envelope Method in Ugandan Primary School Children.” BMC International Health and Human Rights 17(1): 4. https://doi.org/10.1186/s12914- 016- 0110- 2. Cullen, C. 2023. “Method Matters: The Underreporting of Intimate Partner Violence.” World Bank Economic Review 37(1): 49–73. https://doi.org/10.1093/wber/lhac022. Park, D.S., S. Aggarwal, J. Robinson, D. Jeong, A. Spearot, and N. Kumar. 2022. “Private but Misunderstood? Evidence on Measuring Intimate Partner Violence via Self-Interviewing in Rural Liberia and Malawi.” World Bank Research Working Paper #10124. World Bank: Washington, D.C., United States. Accessed March 1, 2023. https://hdl.hand le.net/10986/37732. Punjabi, M., J. Norman, L. Edwards, and P. Muyingo. 2021. Using ACASI to Measure Gender-Based Violence in Ugandan Primary Schools. RTI Press: Research Triangle Park, N.C., United States. https://doi.org/10.3768/rtipre ss.2021.rb.0025.2104. Rathod, S.D., A.M. Minnis, K. Subbiah, and S. Krishnan. 2011. “ACASI and Face-to-Face Interviews Yield Inconsis- tent Estimates of Domestic Violence Among Women in India: The Samata Health Study 2005–2009”. Journal of Interpersonal Violence 26(12): 2437–56. https://doi.org/10.1177/0886260510385125. Stark, L., M. Sommer, K. Davis, K. Asghar, A. Assazenew Baysa, G. Abdela, S. Tanner, and K. Falb 2017. Disclosure bias for group versus individual reporting of violence amongst conflict-affected adolescent girls in DRC and Ethiopia. PLoS One 12, e0174741. https://doi.org/10.1371/journal.pone.0174741. van der Elst, E.M., H.S. Okuku, P. Nakamya, A. Muhaari, A. Davies, R.S. McClelland, M.A. Price, A.D. Smith, S.M. Graham, and E.J. Sanders. 2009. “Is Audio Computer-Assisted Self-Interview (ACASI) Useful in Risk Behaviour Assessment of Female and Male Sex Workers, Mombasa, Kenya?” PLoS ONE 4(5): e5340. https://doi.org/10.137 Downloaded from https://academic.oup.com/wber/article/39/3/614/7750303 by World Bank Publications user on 04 August 2025 1/journal.pone.0005340. C The Author(s) 2024. Published by Oxford University Press on behalf of the International Bank for Reconstruction and Development / THE WORLD BANK. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.