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Online Social Support for Intimate Partner Violence Victims in China: Quantitative and Automatic Content Analysis
Violence Against Women
Abstract
To examine the nature and content of messages presented in a popular Chinese online community about intimate partner violence (IPV), this study utilized a two-step analytic approach that combined quantitative content analysis and automatic content analysis. We collected 90,040 messages from the online community’s IPV group. Study 1 analyzed 8,343 randomly selected messages. The findings suggest that social support is commonly presented, while only a few messages expressed blame toward the victims. Study 2 analyzed the whole sample via machine learning technique and further showed that this online community was a space for the victims to obtain informational resources and emotional encouragement.
... Six of the seven qualitative papers were published within the last five years. Both Cao's (2023) study on domestic violence victims' experience and Chu et al. (2021) utilized data posted on public online platforms to study levels of social support for DV victims, while Wu et al. (2021Wu et al. ( , 2022 and Wong (2011) contacted domestic violence victims directly. Cao et al. (2023) described five themes of women's experience of violence by examining the posts of 42 women shared on an online social media forum. ...
... Wong's (2011) study of 26 victims of domestic violence highlighted the use of self-harm as a method for expressing painful emotions or as a last resort to escape DV. Except for the role of blame and self-blame examined by Chu et al. (2021), the literature reviewed did not investigate the perceived causality of DV, nor the impact of DV on women and their children, nor the changes in DV over time, for which we may question the wisdom of the literature that encourages women to forgive their violent partner (Wu et al., 2021) and/or to remain in their home and work to bring harmony to the situation (Xie et al., 2018). The present research problematizes such recommendations by identifying both the physical and psychological danger that women and their children face by remaining with the DV partner, and the causes of DV that are unlikely to change. ...
... The present research problematizes such recommendations by identifying both the physical and psychological danger that women and their children face by remaining with the DV partner, and the causes of DV that are unlikely to change. Chu et al. (2021) identified that online communities served as a source of social support for victims of violence by analyzing over 90,000 messages posted on social media. Whereas, Xie et al. (2018) examined how the staff of the Women's Federation employed a discourse of gender and social harmony to persuade victims of domestic violence to remain in their marriages. ...
Purpose
There has been an increasing awareness of Domestic Violence (DV) in China following the announcement of the First Anti-Domestic Violence Law, in 2015 yet, there has been limited in-depth research concerning DV in China -with most focused on prevalence and risk factors. This study aims to capture female DV victims’ experience of violence in China, and identify the perceived causes and impacts of DV.
Methods
This qualitative research, conducted from June to September 2019 in Hangzhou, China, consisted of in-depth semi-structured interviews with 30 women who had experience of DV. Social cognitive theory served as the theoretical framework and Interpretive Phenomenological Analysis to analyze the data.
Results
The most common types of physical violence reported included hitting, throwing objects at women, choking, kicking, and slapping. Psychological violence consisted of insults and denigration, physical threats, and enforcement of social isolation. Sexual violence consisted of forced sexual behaviors against women’s willingness. All informants suffered physical or psychological impacts from the violence experienced. Perceived causes of DV included the perpetrator’s personality and childhood experience of violence; victims’ self-blame; conflict between couples that include those concerning raising children and household finances; family conflicts, especially with parents-in-law; social factors including rural-to-urban migration for work, social norms and constraints, and legal constraints to separation. 80% of informants reported that they still cohabit with their abusive partner.
Conclusion
Our findings provide insights into potential preventative measures for DV from individual, family, and social perspectives, and the need to de-stigmatize and support victims of DV in China.
... The prevalence of informational support in online support groups on IPV was also established in another study [19] in which the authors also found that women spent little time actively online and their contribution to the online discussions was small. On the other hand, a study in China showed that female victims of IPV mostly receive emotional support (e.g., offering encouragement and empathy), only then followed by informational support (providing explanations and giving information about immediate and long-term actions) [20]. Another study [21] revealed that victims of sexual violence primarily visited an online group to find a supportive community, seek advice, and share their own stories. ...
... Other types of social support have rarely been identified in research studies analyzing the content of online discussions. Some women in a Chinese study sought instrumental support, like free temporary lodging, albeit such posts were rare [20]. ...
... Going one step further, the multiple multinomial logistic regression revealed that such support was sought significantly more often by authors describing sexual violence than those writing about other types of violence. Similar results were found in a study of rape survivors visiting a public forum on Reddit [21] and in a study of Twitter messages posted by female IPV victims, where sexual abuse is common [20]. ...
Women, as victims of violence, among which intimate partner violence prevails, venture online to seek a supportive community. Members of online support groups differ in the experiences and needs they have and support they seek. The objective of this research was to explore the difference in types of support sought and support received between women who self-report having been a witness/victim of violence and others who directly ask for help without explaining their circumstances. For this purpose, content analysis of 600 randomly selected starting posts from an online support community was performed. The results reveal an association between the needs expressed and the experience of violence described. Although users most frequently sought informational support, those recounting sexual violence more often asked for emotional support or were looking for an emotional release. Posts describing a different kind of violence were more likely to bring more support than short posts directly asking for help. The findings are important since women in a violent relationship tend to become more isolated or controlled by their partners, pointing to the crucial role of online support in helping and encouraging those women to take the first step in seeking help from formal institutions.
... Indeed, a small number of studies have applied similar approaches to the study of IPV. Publications examined online support-seeking behaviours of victim-survivors (Chu et al., 2021), studied reasons given for staying and leaving abusive relationships in microblog posts (Homan et al., 2020), and identified crisis posts on social media platforms such as Facebook (S. Subramani et al., 2018aSubramani et al., , 2018b. ...
... Organisations that interact with victimsurvivors -such as police forces or health services -collect large quantities of IPV data which they are unable to analyse manually (Botelle et al., 2022;. Additionally, victim-survivors of IPV increasingly make use of online venues such as blogs and bulletin boards to express their experiences of abuse and to receive and offer support (Chu et al., 2021;S. Subramani et al., 2019). ...
... Matlab, R and Python were mentioned most often as technologies used in the studies, reflecting their popularity for data science applications. At least seven studies mentioned using Python (Chu et al., 2021;Garrett & Hassan, 2019;Homan et al., 2020;More & Francis, 2021;Schrading et al., 2015;Xu et al., 2022;Xue et al., 2019), although many studies did not report any specific technology or programming language used. ...
Purpose
Computational text mining methods are proposed as a useful methodological innovation in Intimate Partner Violence (IPV) research. Text mining can offer researchers access to existing or new datasets, sourced from social media or from IPV-related organisations, that would be too large to analyse manually. This article aims to give an overview of current work applying text mining methodologies in the study of IPV, as a starting point for researchers wanting to use such methods in their own work.
Methods
This article reports the results of a systematic review of academic research using computational text mining to research IPV. A review protocol was developed according to PRISMA guidelines, and a literature search of 8 databases was conducted, identifying 22 unique studies that were included in the review.
Results
The included studies cover a wide range of methodologies and outcomes. Supervised and unsupervised approaches are represented, including rule-based classification (n = 3), traditional Machine Learning (n = 8), Deep Learning (n = 6) and topic modelling (n = 4) methods. Datasets are mostly sourced from social media (n = 15), with other data being sourced from police forces (n = 3), health or social care providers (n = 3), or litigation texts (n = 1). Evaluation methods mostly used a held-out, labelled test set, or k-fold Cross Validation, with Accuracy and F1 metrics reported. Only a few studies commented on the ethics of computational IPV research.
Conclusions
Text mining methodologies offer promising data collection and analysis techniques for IPV research. Future work in this space must consider ethical implications of computational approaches.
... Social media data contain many daily conversations, which generate much noise. For example, Chu et al. (2020) [29] reported that frequent use of words such as "mother" and "abuse" can confuse researchers, making it hard for them to differentiate between topics, while Homan et al. (2020) [32] also mentioned that noise from spam bots, along with jokes or mistruths from users, are not easily filtered by the text-mining method. ...
... Social media data contain many daily conversations, which generate much noise. For example, Chu et al. (2020) [29] reported that frequent use of words such as "mother" and "abuse" can confuse researchers, making it hard for them to differentiate between topics, while Homan et al. (2020) [32] also mentioned that noise from spam bots, along with jokes or mistruths from users, are not easily filtered by the text-mining method. ...
... In addition to the challenges of psychological prediction, leveraging ML techniques in DV research also suffers from limitations. Only two studies found that ML techniques were useful and practical when applied to real-world settings [29,32]. While a model may appear successful in classifying the correct groups and needs, deployment in real-world settings throws up different challenges. ...
Unlabelled:
Domestic violence (DV) is a public health crisis that threatens both the mental and physical health of people. With the unprecedented surge in data available on the internet and electronic health record systems, leveraging machine learning (ML) to detect obscure changes and predict the likelihood of DV from digital text data is a promising area health science research. However, there is a paucity of research discussing and reviewing ML applications in DV research.
Methods:
We extracted 3588 articles from four databases. Twenty-two articles met the inclusion criteria.
Results:
Twelve articles used the supervised ML method, seven articles used the unsupervised ML method, and three articles applied both. Most studies were published in Australia (n = 6) and the United States (n = 4). Data sources included social media, professional notes, national databases, surveys, and newspapers. Random forest (n = 9), support vector machine (n = 8), and naïve Bayes (n = 7) were the top three algorithms, while the most used automatic algorithm for unsupervised ML in DV research was latent Dirichlet allocation (LDA) for topic modeling (n = 2). Eight types of outcomes were identified, while three purposes of ML and challenges were delineated and are discussed.
Conclusions:
Leveraging the ML method to tackle DV holds unprecedented potential, especially in classification, prediction, and exploration tasks, and particularly when using social media data. However, adoption challenges, data source issues, and lengthy data preparation times are the main bottlenecks in this context. To overcome those challenges, early ML algorithms have been developed and evaluated on DV clinical data.
... In each of these studies, the researchers examined a unique intervention. Most involved some form of service delivery via technologies such as online apps, texts, social media, online discussion forums, and websites (e.g., Alvarez et al., 2018;Anderson et al., 2021b;Bacchus et al., 2016;Cameron, 2011;Chu et al., 2021;Doherty, 2017;Draucker et al., 2019;Fiorillo et al., 2017;Ford-Gilboe et al., 2017;Glass et al., 2017;Hatch et al., 2020;Khaki, 2016;Ross & Aitken, 2022). Other studies looked at individual psychotherapy and supports that were delivered via videoconferencing or by telephone (Burge et al., 2017;Chidanand, 2014;Gondolf, 1998;Steinmetz & Gray, 2017;Tschirch et al., 2006). ...
... Examples and country (if known) incident, provide services using various technologies (e.g., email, teleconference delivery of cognitive behavioral therapy) or video-mediated triage into appropriate services, Interventions involved safety planning for future incidents records voice and takes photographs and transfers information to police (Eisenhut et al., 2020) • iCanPlan4Safety (Canada) online support tool for women experiencing IPV, helps women think about their situation, weigh the risk, and learn about options (Rempel et al., 2019) • Videoconferencing/telehealth technology to provide evidence-based treatment to reach rural IPV survivors (USA) (Rempel et al., 2019) • Web-based danger assessment and safety planning interventions culturally adapted for women who are immigrants, refugees, or indigenous (USA) (Anderson et al., 2021a) • Motivational interviewing followed by telephone follow-up sessions (USA) (Goldstein et al., 2017) • Daily phone survey and weekly phone check ins with a professional after experiencing IPV (USA) (Burge et al., 2017) • Focusing-Oriented Arts Therapy adapted to an internet format (FOAT-IP) (USA) to promote emotional and spiritual healing in South Asian women living in the USA (Chidanand, 2014) • Baidu Tieba's IPV Group (Hong Kong) social network site for IPV survivors to share their experiences and to seek suggestions from community members (Chu et al., 2021) Supporting women after leaving an abusive partner: 9/238, 4% 5/218 systematic review interventions, 4/20 individual study interventions Technology-mediated support groups and individual psychotherapy; technology-mediated access to the legal and justice system; supports and resources to gain financial security; access to healthcare personal safety; establish future plans; alternate models of emergency shelters • E-mail mediated interaction for survivors of abuse after receiving a protection for abuse court order (USA) (Rempel et al., 2019) • Online application for domestic violence protection orders to provide (continued) ...
... The value and satisfaction with the interventions were assessed in several ways. General results of usefulness and applicability were found across several studies (Anderson et al., 2021b;Chidanand, 2014;Chu et al., 2021). Several studies reported improved awareness of services and knowledge about IPV (Abeid et al., 2015;Alvarez et al., 2018;Bacchus et al., 2016;Cameron, 2011). ...
Women have experienced increased rates of intimate partner violence (IPV) since the onset of the COVID-19 global pandemic, and at the same time requirements for physical distancing and/or remote delivery of services have created challenges in accessing services. We synthesized research evidence from 4 systematic reviews and 20 individual studies to address how IPV interventions can be adapted within the context of the pandemic. As many interventions have been delivered via various technologies, access to technology is of particular importance during the pandemic. Our results can inform the provision of services during the remainder of the COVID-19 pandemic including how to support women who have little access to in-person services.
... The sense of Accepted Manuscript PARTNER VIOLENCE EXPERIENCES OF CHINESE WOMEN community creates an environment that encourages women to break the silence. Lastly, the supportive environment within the online realm for women who experienced IPV (Chu et al., 2021) has also been found to reduce their anxiety about being blamed for disclosure and further motivates them to share their experiences. ...
... Researchers have successfully used different online platforms, including forums and other social media, to study sensitive topics or stigmatized experiences including IPV and sexual abuse (Bogen et al., 2019;Chu et al., 2021;Storer et al., 2021). This study aims to describe experiences of IPV against Chinese women using the conventional qualitative content analyses of posts shared on a public online forum on domestic violence from October 2017 to October 2018. ...
... This environment revealed that people replied mostly with supportive messages, with only a few messages blaming the victims when sharing IPV experiences (Chu et al., 2021) into one narrative in chronological order whenever applicable. Second, women's replies to other members' comments on the initial posts were also included if women further described their IPV experiences in detail when responding. ...
An understanding of intimate partner violence (IPV) experiences is a crucial first step toward shaping effective responses. However, relevant knowledge among Chinese women is scant. This study described Chinese women’s IPV experiences by analyzing 46 posts shared by 42 women on a public online forum. Five overarching themes were identified using conventional qualitative content analysis: being trapped in my roles, no power in the relationship, the struggles are real but I need to tolerate, I want to leave but have no help, and hope for the future. This study has important implications for future research, practice, and education.
... Some serious negative health consequences result from IPV victimization, including emotion dysregulation (ED), post-traumatic stress disorder (PTSD), depression, anxiety, and sexual risk behavior [2][3][4]. IPV victims have been utilizing different technologies to seek help and support and to escape from abusive relationships, especially during the pandemic [5]. However, lockdowns, social distancing, and voluntary self-isolation reduce the options for social support [5]. ...
... IPV victims have been utilizing different technologies to seek help and support and to escape from abusive relationships, especially during the pandemic [5]. However, lockdowns, social distancing, and voluntary self-isolation reduce the options for social support [5]. ...
... Social networking sites (SNS) have been integrated into young people's daily lives, extending to their help-seeking behavior [7]. Social media has many advantages in the process of help-seeking, such as aiding the identification of abusive behaviors within a partnership, promoting awareness of available IPV resources, encouraging disclosure of IPV, and encouraging seeking assistance to leave a violent relationship [5]. In China, people are reluctant to make private family affairs public due to strong cultural norms about saving face. ...
During the COVID-19 pandemic, lockdowns and isolation have limited the availability of face-to-face support services for victims of intimate partner violence (IPV). Despite the growing need for online help in supporting IPV victims, far less is known about the underlying mechanisms between IPV and online help-seeking. We studied the mediating role of emotion dysregulation (ED) and the moderating role of perceived anonymity (PA) on the internet to explain IPV victims’ willingness of online help-seeking (WOHS). Through a PROCESS analysis of the questionnaire data (n = 510, 318 female, 192 male, Mage = 22.41 years), the results demonstrate that: (1) ED has been linked with the experience of IPV, and IPV significantly induces ED. (2) When IPV victims realize the symptoms of ED, they have a strong willingness to seek external intervention to support themselves. ED mediates the relationship between IPV and online help-seeking. (3) For youth growing up in the era of social networking sites (SNS), personal privacy protection is an important factor when seeking online help. The anonymity of the internet has a positive effect on victims who experience IPV and ED, and it increases WOHS. This study introduces a new perspective on the psychological mechanism behind IPV victims’ help-seeking behaviors, and it suggests that the improvement of anonymity in online support can be an effective strategy for assisting IPV victims.
... Online help-seeking behaviors can be categorized based on the types of support, which include emotional and informational support (Rose et al., 2000). Emotional support involves offering empathy, care, and encouragement, and importantly avoiding victim blaming, which has been found to significantly hinder an individual's ability to reach a pivotal moment, such as deciding to leave an abusive relationship (e.g., Chu et al., 2020;Ogbe et al., 2020). In contrast, informational support encompasses providing advice, resources, and information to help individuals navigate their situations (e.g., Renner et al., 2024). ...
... To assess ChatGPT's capability in providing emotional and informational support for content containing IPV, ChatGPT's output was manually coded by types of support. The coding scheme, adapted from Shi and Chen (2014) and Chu et al. (2020), categorizes messages into emotional support provisions, informational support provisions, and instrumental support provisions. ChatGPT cannot provide physical or direct intervention support, so we removed the instrumental support category from the coding. ...
Objective
This study aims to examine the efficiency and consistency of ChatGPT in identifying intimate partner violence (IPV) and the frequency of emotional and informational support ChatGPT provided.
Background
The integration of artificial intelligence–based conversational large language models, such as ChatGPT, in understanding relationship dynamics has sparked both interest and debate within the scientific community. This tool could be valuable in offering immediate, personalized responses to questions about relationships, including those involving conflicts and violence.
Method
We extracted 500 posts involving IPV and 80 posts involving nonviolent family tension from online IPV help‐seeking forums as prompts for ChatGPT (Version 3.5). We coded ChatGPT's responses and examined their congruence and consistency in identifying IPV compared to human experts. We also examined incidents where ChatGPT misjudged. Lastly, we assessed the presence of informational and emotional support in ChatGPT's responses to prompts involving IPV.
Results
ChatGPT‐3.5 was able to identify cases involving IPV (physical violence, psychological violence, and controlling behavior) correctly in 91.2% of the cases. Misjudgment mostly occurred due to community policies or nuanced context information. ChatGPT consistently provided emotional support and informational support to users who presented IPV‐related inquiries.
Conclusion
ChatGPT‐3.5 could reach a relatively high accuracy and consistency in identifying IPV and can provide supportive responses.
Implications
ChatGPT can serve as an initial resource for individuals and family members seeking help with IPV, offering immediate, empathetic, and informational support. However, improvements are needed to address its limitations in handling nuanced cases and to ensure ethical use and user safety.
... A few relevant studies often narrow their focus to specific victim groups, such as men experiencing intimate partner violence (Simon and Wallace, 2018) or rural women facing domestic violence (Xie et al., 2018). Chu et al. (2021), utilizing machine learning and content analysis, have delved into online support communities associated with intimate partner violence, highlighting the simultaneous presence of support and condemnation within Chinese domestic violence communities. In line with the observations made by Gueta et al. (2023), the existing research on domestic violence disclosure predominantly reflects a Western-centric orientation, underscoring the imperative of exploring non-Western perspectives. ...
... Third, this study also attempts to explore the effects of disclosure. As previously mentioned, victims of domestic violence disclose their experiences in online support communities to seek support, fostering a supportive environment for discussion (Chu et al., 2021;McCauley et al., 2018). Through the interaction of posting disclosures and responding with support, users create a sustainable structure of supportive communication (Butler, 2001). ...
Domestic violence is a global issue with devastating consequences, which can be mitigated through disclosure in supportive communications. Proxy disclosure, a special form of disclosure, involves individuals disclosing experiences of victims who are supportively connected with them. This study explores proxy disclosure within the context of domestic violence in Chinese online support groups. Using data from three support groups, the study employs content analysis, structural topic modeling, and propensity score matching to examine the disclosers, content, and supportive effects. Findings reveal proxy disclosers in China are predominantly male and often advocate for mothers and siblings. Six themes emerged, with childhood trauma memories and judicial intervention significantly affecting supportive communication. In addition, self-disclosure generally receives more replies than proxy disclosure. This study introduces and conceptualizes proxy disclosure, providing insights into disclosure for silent victims, and extending the understanding of online anti-domestic-violence support systems in non-Western settings. It enhances the theoretical framework of online disclosure and offers practical implications for social work and domestic violence interventions.
... Considerable research has examined social media as safe spaces for self-disclosing sensitive, distressing experiences such as intimate partner violence, sexual abuse, self-harm, and bullying that people tend to keep secret (Andalibi, 2019;Chu et al., 2021;Yeo, 2021). Much of this work focuses on more "private" disclosures within topic-based online communities (subreddits, Facebook groups, question-and-answer websites, story-sharing blogs, etc.) (Danielson & Emmers-Sommer, 2017;Yeo & Chu, 2017). ...
... Another substantive contribution of this study is in illustrating the utility and robustness of various computational techniques for studying social media self-disclosures of sexual victimization, which can be readily extended to examine other forms of distressing experiences. Hitherto, only a handful of studies on online interpersonal violence discussions have utilized similar techniques such as machine learning to infer disclosure of sexual victimization in online messages and topic modeling to identify salient topics in support messages for intimate partner violence survivors (Chu et al., 2021;Gorissen et al., 2023). Most previous studies involve qualitative analysis and small data samples, which were neither representative nor generalizable. ...
Hashtag campaigns calling out sexual violence and rape myths offer a unique context for disclosing sexual victimization on social media. This study investigates the applicability of adaptive self-reflection as a potential self-effect from such public disclosures of unreported sexual victimization experiences by analyzing 92,583 tweets that invoked #WhyIDidntReport. A supervised machine learning classifier determined that 61.8% of the tweets were self-disclosures of sexual victimization. Linguistic Inquiry and Word Count (LIWC) analysis showed statistically significant differences in four psycholinguistic dimensions (greater use of past focus, cognitive processes, insight, and causation words) connected with reflective processing in tweets with self-disclosed sexual victimization compared to those without. Additionally, topic modeling and thematic analysis identified nine salient topics within the self-disclosing tweets, comprising three self-distanced representations (i.e., relatively abstract and insightful construals) of the unwanted experiences: (a) acknowledging one's previously unacknowledged victimization, (b) reaffirming one's rationale for not reporting, and (c) decrying invalidating response to one's disclosure. Moving beyond reception effects and social support in extant research about social media as a coping tool, this study provides new empirical insights into the potential of social media to promote expressive meaning-making of upsetting and traumatic experiences in ways that support recovery and resilience.
... Looking for a supportive community was also one of the main motives for rape survivors when visiting a public rape survivor forum on Reddit [19]. They were, however, more often looking for emotional rather than informational support, which was also the case in a Chinese study analyzing the Twitter messages of victims of IPV [17]. In our study, only 4% of the 600 randomly chosen starting posts included emotional support seeking. ...
... Online interventions definitely have a lot of potential to help victims of IPV [16] and could be an effective channel for promoting anti-IPV campaigns [17]. However, they can only offer a certain level of help and support, as the process of leaving an abusive relationship is complex and includes many individual and subjective factors. ...
Some women, especially victims of violence, seek support in online groups. The objective of this research was to investigate the nature of the social support women receive in such online communities. For this purpose, all the posts from a large online support community group for women in Slovenia, Women in Need, from 2002 to the end of 2020 were retrieved and analyzed manually as well as by using a text-mining approach. The results show that women in the investigated community mostly seek informational support, spend little time actively contributing to online discussions, and rarely become engaged members of supportive groups within the focal online space. Some recommendations on how to improve the functionality of online social support sites are provided.
... The study's data was collected from Baidu Tieba's Binge Eating Group (暴食吧; https://wefan.baidu.com/f?kw=暴食 &ie=utf-8), one of the largest online support groups for people suffering from binging-related issues or disorders (including BED and BN). Baidu Tieba is the largest online communication platform in China and is particularly popular among Chinese young people (Chu et al., 2021;Dragon Social, 2019). Similar to Reddit, Baidu Tieba permits users who share similar interests or issues to create virtual groups. ...
... Consistent with previous studies on discussions of sensitive issues and stigmatized illnesses in anonymous sites in the Chinese context (e.g., Chu et al., 2021;Yeo, 2021), our findings provide further evidence of the utility of such anonymous sites in facilitating the disclosure and online peer communication regarding eating disorders. As one of the first studies to examine online ED discussions in China, our findings demonstrate how Chinese internet users utilized an anonymous online community to share their eating problems and the struggles that they faced with their peers. ...
Despite the distress and disruption associated with eating disorder (ED), people struggling with EDs are often ambivalent about their eating issues and unmotivated for recovery. Rather than seek professional help, these people tend to turn to online ED groups for information and support. Using the stages of change model, this study investigates the characteristics of online peer communication around binging vis-à-vis participants' motivation and readiness for behavioral change. Our results illustrate how individuals with binging issues in different motivational stages discuss their problematic eating online and provides insights into their ambivalence toward treatment and relapses into binging. This study further clarifies how people with binging issues feel trapped in a cycle of dieting-binging, which is observed to be undergirded by unresolved weight-related issues, and how they cope with the stressful relationship between eating and body weight through their postings on social media. These findings suggest that healthcare providers should promote healthier methods of addressing the weight gain from binge eating and provide support tailored to individuals' motivational stage in breaking the dieting-binging cycle.
... Six studies did not indicate where the support groups, and so informal support, was being provided. The EGM also included support groups operating via online forums/platforms (Berg 2015;Chu et al. 2020). ...
Background
Domestic Violence and Abuse (DVA) is a significant global problem that warrants a robust, multi‐sectoral response. The Covid‐19 pandemic highlighted that informal and social networks play a critical role in responding to victim‐survivors, alongside formal agencies and specialist services. Friends, relatives, neighbours and colleagues are uniquely placed to recognise abuse, respond and refer to wider services, where appropriate. Seeking to harness this potential, interventions tailored towards such informal supporters are being developed and implemented around the world. Yet little is known about such interventions. By pulling together the research on such programmes, this evidence and gap map begins to advance the understanding of informal support interventions, pinpointing the range and type of interventions implemented around the world, and the extent of the available evidence. This provides valuable insights for policy makers and practitioners seeking to commission or develop interventions and research in this area, with a view to facilitating a holistic, societal‐wide response to domestic abuse. The evidence and gap map was a collaboration of academics and specialists, as well as domestic abuse researchers, with input and guidance from an Advisory Group.
Objectives
This evidence and gap map aims to establish the nature and extent of the empirical primary research on interventions aiming to create or enhance informal support for victim‐survivors of domestic abuse, identifying clusters of evidence potentially suitable for synthesis, and gaps in the research base.
Search Methods
The following bibliographic databases were searched for published studies from inception to 31st October 2022: APA PsycINFO, Social Policy and Practice, ASSIA, PubMed, and Social Science Citation Index. Identifying grey literature was an important pillar of the search strategy and so websites of domestic abuse organisations, predominantly in the United Kingdom, were also searched. Similarly, a targeted search of specialist systematic review, policy and domestic abuse databases was undertaken from inception to 10th July 2023.
Selection Criteria
The evidence and gap map focused on any interventions that explicitly aimed to create or enhance informal social support for victim‐survivors of domestic abuse. Eligible interventions targeted the providers of the support (i.e., friends, relatives, neighbours or colleagues), the victim‐survivor, the relationship between them, and/or the wider community within which the informal support was provided. All study designs were included, reporting qualitative or quantitative data for samples or victim‐survivors (adults who were/had been experiencing abuse in an intimate relationship) or informal supporters. Outcomes were not used as part of the eligibility criteria. Eligible studies needed to be published in English.
Data Collection and Analysis
All studies included in the evidence and gap map were coded by two independent reviewers, using specialist systematic review software EPPI Reviewer. Details were collected about the study sample, study design, intervention and outcomes. Quality appraisal was not undertaken.
Main Results
The EGM identified 47 primary studies of interventions that aimed to create, enhance or facilitate informal support for victim‐survivors of domestic violence and abuse. The overwhelming majority of evidence is drawn from the Global North, and there is dissonance between the small evidence base and the relatively larger number of informal support interventions implemented around the world. The EGM highlights the importance of diverse study designs and grey literature in this field. The body of research is unevenly distributed, with the greatest concentration of studies around interventions directed towards victim‐survivors, such as support groups or mentoring, and those tailored towards informal supporters, such as education and training. Most research reported on female, adult victim‐survivors with a particular emphasis on their mental health and wellbeing, and their help‐seeking behaviours. The reporting of such outcomes aligns with wider service user/provider priorities and highlights the imperative of DVA research to improve the lives of victim‐survivors. The EGM found little research focused on interventions targeting structural factors that shape informal support, such as social relationships or community norms, and a lack of data on specific population groups including victim‐survivors in the longer term, ethnic minority groups and men. There are major gaps in the research for informal supporters with limited data or outcomes for this group, and specific types of informal supporters (namely friends and family members) are notably absent from samples. The EGM also highlights a gap in the research on community‐level outcomes.
Authors' Conclusions
To our knowledge, this EGM is the first to provide a comprehensive and rigorous overview of the evidence on informal support interventions in domestic abuse. The EGM provides a valuable tool for policymakers, practitioners and researchers seeking to navigate the evidence around such interventions. Whilst the EGM provides a partial picture of interventions around the world, the studies offer insight into informal support for victim‐survivors of DVA and the potential effects of intervening. The suite of interventions covered by the EGM can inspire policymakers to broaden the response to domestic abuse beyond frontline services, identify stakeholders and commission pilot studies to further understanding of informal support interventions. The evidence base can be strengthened with additional studies examining interventions that target relationships and communities, as well as individuals, and assessing a wider range of population groups. At the same time, the EGM offers pockets of rich data, such as outcomes on victim‐survivor mental health or interventions in faith‐based organisations, which can be utilised to inform current and future service provision.
... As compared to previous research on Persian content [22], the performance metrics in the model constructed in this study have increased by 10 units, so that accuracy has almost reached 96 % from 86 %. Although the model's performance is lower than the model developed by Liu et al. (ACC = 97 %) [44], it has a higher performance than the model developed by Garrett et al. on the English language (F = 0.78 %) [45], a higher performance than the model developed by Chu et al. on the Chinese language (ACC = 0.94 %) [46], and a higher performance than the model developed by Subramani et al. on the English language (ACC = 0.91 %) [47]. ...
Objective
Due to the importance of monitoring social networks to categorize domestic violence content and extract practical knowledge for conducting preventive interventions, as well as analyzing the extensive Persian textual content related to domestic violence generated in social networks following the COVID-19 pandemic, primarily, this research aims to create the best domestic violence Persian textual content classification model using topic modeling content at first and then combining algorithms using ensemble learning to achieve the best model performance.
Method
By collecting Persian textual data using hashtags related to domestic violence equally and randomly from Telegram, Twitter, and Instagram networks between April 2020 and April 2023, the content were considered for topic modeling using the LDA algorithm. By extracting the probabilities of each topic for each document in our dataset, we considered the topic that had the highest probability to be a label for that document. Following feature extraction from labeled datasets, the Stacking and Voting ensemble learning methods were applied.
Result
The analysis of 337,287 textual data revealed five topics: family crime news, war violence, women's rights, and violent reactions. Also, compared to the voting method, the stacking method performed better with 96.4577 precision, 96.4499 accuracy, 96.4499 recall, and 96.4475 F-score.
Conclusion
According to the study findings, practical knowledge of the extracted topics can assist mental health centers in making preventive decisions. Moreover, the built model has the most efficient performance among the built models for the multi-class classification of DV texts in the Persian language for social media monitoring.
... Dukungan sosial menjadi langkah perlindungan untuk mengatasi IPV dan mengurangi dampak negatif yang dapat terjadi di kemudian hari. Chu et al. (2020) memberikan dukungan sosial online melalui dua pendekatan, yaitu analisis konten kuantitatif dan analisis konten otomatis. Analisis konten kuantitatif digunakan untuk menganalisis jenis dukungan sosial yang dibutuhkan oleh korban IPV. ...
Research related to the use of Artificial Intelligence (AI) in the world of health has been
widely discussed and published. However, discussion regarding the comprehensive role of AI in
reducing the incidence of stunting is still very limited. This study discusses the use of AI in reducing
the incidence of stunting in the first 1000 days of life (HPK) based on stunting risk factors. The
method used in this study is a literature review. The articles reviewed are publications from 2014
to 2023. A search for articles on risk factors for stunting was carried out using the Google Scholar
and Sciencedirect search engines. The results showed that in general the risk factors for stunting
came from the mother factors, child factors, and socio-demographic factors. Based on this, the
utilization of AI in a comprehensive manner is divided into 4 main areas, namely (1) maternal
health; (2) child health; (3) environmental health; and (4) behavior change. The author is
responsible for the originality of the research results. It is hoped that this research can become a
framework for implementers across sectors, from government agencies, organizations, to health
cadres, to innovate and utilize all resources, such as the use of AI, so that stunting prevention can
be more optimal.
... Similar approaches were applied to build cohorts of patients for whom comprehensive data may not be available from EHRs or populations excluded from traditional studies such as clinical trials. Such studies have focused on topics including but not limited to drug safety during pregnancy, 7,8 substance use, 9,10 intimate partner violence [11][12][13] , and chronic stress. 14,15 Since social media data are constantly generated, once the cohort-building methods are developed, they can be deployed to continuously grow the cohort, increase the volume of collected data, and conduct long-term studies. ...
Migraine is a highly prevalent and disabling neurological disorder. However, information about migraine management in real-world settings is limited to traditional health information sources. In this paper, we (i) verify that there is substantial migraine-related chatter available on social media (Twitter and Reddit), self-reported by those with migraine; (ii) develop a platform-independent text classification system for automatically detecting self-reported migraine-related posts, and (iii) conduct analyses of the self-reported posts to assess the utility of social media for studying this problem. We manually annotated 5750 Twitter posts and 302 Reddit posts, and used them for training and evaluating supervised machine learning methods. Our best system achieved an F1 score of 0.90 on Twitter and 0.93 on Reddit. Analysis of information posted by our 'migraine cohort' revealed the presence of a plethora of relevant information about migraine therapies and sentiments associated with them. Our study forms the foundation for conducting an in-depth analysis of migraine-related information using social media data.
... Also, as mentioned above, although IPV victims with the perpetrators at home face more challenges to seek help, traditional support systems remain reactive rather than proactive, losing their utility to many IPV victims who cannot reach out. Perhaps as a consequence of this, many IPV victims discuss their situations with their peers on social media, and often seek information and support [6][7][8][9][10] . There is thus the potential of utilizing social media for proactively detecting potential IPV victims, identifying their needs, and reaching out to them for support or intervention safely, unobtrusively, and at scale. ...
Social media platforms are increasingly being used by intimate partner violence (IPV) victims to share experiences and seek support. If such information is automatically curated, it may be possible to conduct social media based surveillance and even design interventions over such platforms. In this paper, we describe the development of a supervised classification system that automatically characterizes IPV-related posts on the social network Reddit. We collected data from four IPV-related subreddits and manually annotated the data to indicate whether a post is a self-report of IPV or not. Using the annotated data (N=289), we trained, evaluated, and compared supervised machine learning systems. A transformer-based classifier, RoBERTa, obtained the best classification performance with overall accuracy of 78% and IPV-self-report class 𝐹1 -score of 0.67. Post-classification error analyses revealed that misclassifications often occur for posts that are very long or are non-first-person reports of IPV. Despite the relatively small annotated data, our classification methods obtained promising results, indicating that it may be possible to detect and, hence, provide support to IPV victims over Reddit.
... These studies were conducted to investigate the ability of machine learning algorithms to classify various languages. According to Table 2, the performance of the machine learning approach on texts related to DV in the Persian language, such as Chinese [45], Spanish [19], and English [7,46], was proficient, with an accuracy of at least 80%. Also, the findings of this study are consistent with previous studies that utilized the same foreign sample. ...
Domestic violence (DV) against women in Iran is a hidden societal issue. In addition to its chronic physical, mental, industrial, and economic effects on women, children, and families, DV prevents victims from receiving mental health care. On the other hand, DV campaigns on social media have encouraged victims and society to share their stories of abuse. As a result, massive amount of data has been generated about this violence, which can be used for analysis and early detection. Therefore, this study aimed to analyze and classify Persian textual content pertinent to DV against women in social media. It also aimed to use machine learning to predict the risk of this content. After collecting 53,105 tweets and captions in the Persian language from Twitter and Instagram, between April 2020 and April 2021, 1611 tweets and captions were chosen at random and categorized using criteria compiled and approved by an expert in the field of DV. Then, using machine learning algorithms, modeling and evaluation processes were performed on the tagged data. The Naïve Base model, with an accuracy of 86.77% was the most accurate model among all machine learning models for predicting critical Persian content pertinent to domestic violence on social media. The obtained findings indicate that using a machine learning approach, the risk of Persian content related to DV in social media against women can be predicted.
... Similar approaches were applied to build cohorts of patients for whom comprehensive data may not be available from EHRs or populations excluded from traditional studies such as clinical trials. Such studies have focused on topics including but not limited to drug safety during pregnancy, 7,8 substance use, 9,10 intimate partner violence, [11][12][13] , and chronic stress. 14,15 Since social media data is constantly generated, once the cohort-building methods are developed, they can be deployed to continuously grow the cohort, increase the volume of collected data, and conduct long-term studies. ...
Migraine is a high-prevalence and disabling neurological disorder. However, information migraine management in real-world settings could be limited to traditional health information sources. In this paper, we (i) verify that there is substantial migraine-related chatter available on social media (Twitter and Reddit), self-reported by migraine sufferers; (ii) develop a platform-independent text classification system for automatically detecting self-reported migraine-related posts, and (iii) conduct analyses of the self-reported posts to assess the utility of social media for studying this problem. We manually annotated 5750 Twitter posts and 302 Reddit posts. Our system achieved an F1 score of 0.90 on Twitter and 0.93 on Reddit. Analysis of information posted by our 'migraine cohort' revealed the presence of a plethora of relevant information about migraine therapies and patient sentiments associated with them. Our study forms the foundation for conducting an in-depth analysis of migraine-related information using social media data.
... Automatic content analysis gauges digital traces and measures online users' behavior unobtrusively. Several studies have been employing this method to study online health communication by discovering communication trends and patterns from a large amount of unstructured text corpus (e.g., [5,48]). DivoMiner, a text-mining and automatic content analysis platform supported by machine learning algorithms, was then employed in this study specifically for identifying Chinese language texts. ...
The COVID-19 outbreak has caused significant stress in our lives, which potentially increases frustration, fear, and resentful emotions. Managing stress is complex, but helps to alleviate negative psychological effects. In order to understand how the public coped with stress during the COVID-19 pandemic, we used Macao as a case study and collected 104,827 COVID-19 related posts from Facebook through data mining, from 1 January to 31 December 2020. Divominer, a big-data analysis tool supported by computational algorithm, was employed to identify themes and facilitate machine coding and analysis. A total of 60,875 positive messages were identified, with 24,790 covering positive psychological themes, such as “anti-epidemic”, “solidarity”, “hope”, “gratitude”, “optimism”, and “grit”. Messages that mentioned “anti-epidemic”, “solidarity”, and “hope” were the most prevalent, while different crisis stages, key themes and media elements had various impacts on public involvement. To the best of our knowledge, this is the first-ever study in the Chinese context that uses social media to clarify the awareness of solidarity. Positive messages are needed to empower social media users to shoulder their shared responsibility to tackle the crisis. The findings provide insights into users’ needs for improving their subjective well-being to mitigate the negative psychological impact of the pandemic.
... 220 Greater coordination would also enable big-data analyses. Data mining of electronic health records, for example, will allow for finer analysis of the associations between IPV and mental health problems (if information about IPV is recorded), 221 temporal identification of mental health sequelae, and identification of high-risk women, men, and gender minorities for targeted preventive interventions, 222 thereby supporting improvements in the clinical response to IPV. 223,224 Similarly, the application of machine-learning models to administrative data records of IPV samples could help to identify highrisk women, men, and gender minorities for targeted preventive interventions, based on risk models' predictions of sexual violence victimisation in other highrisk non-IPV samples. 222 ...
... 220 Greater coordination would also enable big-data analyses. Data mining of electronic health records, for example, will allow for finer analysis of the associations between IPV and mental health problems (if information about IPV is recorded), 221 temporal identification of mental health sequelae, and identification of high-risk women, men, and gender minorities for targeted preventive interventions, 222 thereby supporting improvements in the clinical response to IPV. 223,224 Similarly, the application of machine-learning models to administrative data records of IPV samples could help to identify highrisk women, men, and gender minorities for targeted preventive interventions, based on risk models' predictions of sexual violence victimisation in other highrisk non-IPV samples. 222 ...
Domestic violence (DV) is a major public health problem worldwide, impacting the physical and mental health, wellbeing and safety of women and families. DV during pregnancy is associated with additional health consequences, including obstetric risks, mental health problems, suicide and femicide. This chapter outlines the prevalence of DV globally and during pregnancy, its impact on perinatal physical and mental health and the evidence for interventions addressing the mental health of pregnant women experiencing DV. The perinatal period is an important opportunity for health services to identify women experiencing DV, initiate first-line support and connect them to appropriate agencies. Mental health professionals in contact with pregnant and postpartum women are well-placed to identify and support women experiencing DV. Addressing DV alongside perinatal mental health enables holistic care plans to be tailored to the bio-psycho-social factors precipitating and perpetuating women’s symptoms.KeywordsDomestic violenceIntimate partner violenceFamily violenceAbusePerinatal mental healthPregnancyInterventionsCommon mental disordersSocial determinants of health
... While prior research has long examined the important role of social support for individuals experiencing IPV, more research is needed to understand benefits and risks of seeking support online during COVID-19. For example, social media could be a platform for receiving emotional and informational support for IPV survivors (Chu et al., 2020). However, social media could also induce nonsupportive and victim-blaming messages (Whiting et al., 2019) and more research is needed to further understand the risks and benefits of social media in IPV communication ecologies. ...
COVID-19 is a pandemic event not seen in a century. The purpose of this research is to identify important predictors related to the ongoing COVID-19 pandemic to intimate partner violence (IPV) and to provide insight into communication ecologies that can address IPV in disaster contexts. This study uses a cross-sectional design, with purposive snowball sampling, for primary survey data collected over 10 weeks starting the first week in April 2020. Participants completed a self-administered questionnaire on demographics and behavioral factors. 374 adults participated in the study. Logistic binary regression was used to identify key predictors among socio-demographics, stress related to COVID-19, and perceived stress of group membership for those who reported IPV experiences. A t-test was used to statistically differentiate between IPV-reporters and non-IPV reporters based on perceived stress measured by the Perceived Stress Scale. Results indicated that respondents who reported renting, lost income due to COVID-19, and increased nutritional stress were all more likely to belong to the IPV-reporters group. IPV-reporters were also more likely than non-reporters to have higher levels of perceived stress. These findings suggest the importance of communication ecologies to leverage strategies that communicate the additional stressors related to the ongoing pandemic, such as stress due to income loss, nutritional stress, and stress due to renting, and their likelihood of increasing IPV victimization. Decision-makers should also take into consideration the importance of rent relief and subsidized income measures to reduce the likelihood of additional IPV.
... A study carried out in China also highlighted the importance of social support for women in situations of violence based on messages posted in an online community, revealed as a means of support, information and encouragement for victims. Half of the shared messages (58.9%) had social support content; of these, 22.27% involved seeking help or support from others (24) . ...
Objective:
to know the strategies to cope with domestic violence against women disseminated by digital media at the beginning of the COVID-19 pandemic.
Methods:
a documentary study with a qualitative approach. The search took place from March 11 to April 30, 2020, from four sources: newspapers and online portals, social network, official government pages and third sector portals. Thematic content analysis of the findings was performed.
Results:
seventy-seven strategies were identified in the journalistic press, 93 in the social network, 45 in government portals and 40 in third sector organizations. From analysis, three empirical categories emerged: Strategies for communication with women; Strategies adopted by customer service; Strategies to inform the population.
Final considerations:
most of strategies were adaptations of existing services, centered on the reporting of violence by women
... 220 Greater coordination would also enable big-data analyses. Data mining of electronic health records, for example, will allow for finer analysis of the associations between IPV and mental health problems (if information about IPV is recorded), 221 temporal identification of mental health sequelae, and identification of high-risk women, men, and gender minorities for targeted preventive interventions, 222 thereby supporting improvements in the clinical response to IPV. 223,224 Similarly, the application of machine-learning models to administrative data records of IPV samples could help to identify highrisk women, men, and gender minorities for targeted preventive interventions, based on risk models' predictions of sexual violence victimisation in other highrisk non-IPV samples. 222 ...
Domestic violence and abuse (DVA) is a global public health problem, accounting for up to 7% of the overall burden of disease among women, mostly due to its impact on mental ill health. It includes partner violence and violence perpetrated by other family members on adults, and may involve mutual violence or can involve coercive and controlling behaviours. Women are at greatest risk of serious physical and sexual assaults, including being victims of domestic homicide. There is growing evidence that men and women with mental disorders, particularly severe disorders, are at increased risk of being both victims and perpetrators of DVA. Despite barriers to disclosure, psychiatric services are well placed to identify and reduce the risk of future DVA and treat the mental health consequences.
Objective
This study investigated help‐seeking behaviors among Korean immigrant women facing intimate partner violence (IPV) and examined how their social networks influence the help‐seeking process.
Background
Although existing research highlights the role of social networks in supporting IPV survivors, limited studies explore how these networks specifically impact Korean immigrant women's help‐seeking experiences.
Method
We conducted in‐depth interviews with 16 Korean immigrant women who self‐identified as IPV survivors. Interviews occurred either in person at our New York office or via online or phone interviews. Thematic analysis was employed for data analysis.
Results
Two primary themes emerged regarding Korean immigrants' help‐seeking behavior in IPV situations: (a) passive help‐seeking within interpersonal networks and (b) active help‐seeking through ethnic‐based online networks. Korean women tended to avoid disclosing IPV and seeking help from family or local church members. Instead, they often preferred to seek anonymous support through ethnic‐based online platforms.
Conclusions
Existing interpersonal networks were rarely used as a route for seeking help, primarily due to cultural norms and stigma. However, online Korean communities emerged as a meaningful resource, facilitating connections with others facing similar challenges and providing anonymous support.
Implications
To facilitate IPV disclosure and better support abused Korean immigrants, we should promote and enhance online platforms that offer confidential emotional support, information, and resources.
Understanding the experiences of intimate partner violence (IPV) is a critical first step in developing effective responses. However, the majority of research has focused on male perpetration against women, with male victimization being relatively marginalized. This study aims to explore the experiences of men with IPV in the context of Chinese society, where adherence to masculinity and the societal pursuit of face and harmony contribute to tolerance of IPV and hinder the understanding of male victim experiences. This study analyzes the IPV experiences shared by 57 men on public internet forums and invited 11 of them to participate in semi-structured interviews through private messages. Finally, thematic analysis was employed to qualitatively analyze the collected textual data. This study revealed seven key themes in the narratives of men. This study has significant implications for future research on IPV in China, as well as for policy formulation and service provision.
As the number of people using and participating in social media grows, academics become interest in studying this new media, specifically comment analysis, in order to comprehend public opinion and user behavior. However, there are no studies that map the development of comment analysis domain, which would be valuable for future research. To address the issue, we examine prior publications using PRISMA approach, and offer suggestions for further research. An investigation was conducted to locate pertinent publications published in databases between 2010 and 2022. On the basis of our examination of 115 relevant articles, we found that, within the scope of methodology, prior researches employ two methods (sentiment and content analysis) and three tools (human, software, and mixed coders), and the majority of them concentrate on gathering data from western countries, covering numerous platforms and topics. Based on these findings, we recommend that future research in comment analysis should synthesize methods and instruments. In addition, examine areas that have not been fully explore in terms of platforms (e.g., Instagram and Tiktok), topic (e.g., local government), and regions (e.g., eastern countries) that would be valuable in order to enhance the body of knowledge in this domain.
Purpose: This article reports on a scoping review that maps the empirical research on virtual intimate partner violence (IPV) interventions.
Method: Following the Joanna Briggs Institute’s nine-step scoping review methodology, 25 studies were selected.
Results: The majority of the studies (72%) were published in the United States, and included quantitative (56%), mixed methods (24%), and qualitative study designs (20%). The most frequent focus of the virtual interventions to support survivors of IPV included safety (52%), with other interventions focusing mainly on treatment (36%), and education and prevention (12%). Forms of interventions included interactive, internet-based (72%), smartphone apps (16%), live videoconferencing (8%), and an asynchronous chatroom (4%). Barriers and strengths of virtual IPV interventions are identified.
Discussion: From this analysis, emerging models in virtual IPV intervention are identified, as well as next steps necessary in virtual IPV practice and research. The article concludes with implications for social work practice and research.
Intimate Partner Violence (IPV) is undoubtedly one of the most worrying concerns in today's global societies. Due to the many intertwined factors that explain the persistence of this reality among people from all sorts of backgrounds, finding a uniform strategy to cope with this social issue is far from unproblematic. In this study, I contribute to a growing field of research that examines the discourse of female survivors of IPV in online contexts. The main objective is to identify relevant linguistic patterns used by women to represent themselves and their perpetrators in a publicly-available online forum. More specifically, I seek to ascertain the discursive traits that characterise women in an initial stage in contrast to a final stage within an abusive relationship. To this end, I adopt a Corpus-Assisted Discourse Studies approach in a digital corpus of around 136,000 words, which are analysed with the software tool Sketch Engine. Findings show the most salient discursive traits that characterise IPV online discourse. Additionally, and drawing on verb patterns ascertained in the corpus and their semantic categorisation, I also connect linguistic textual evidence to the power imbalances that sustain this social phenomenon.
Social media has become a ubiquitous form of interacting and sharing information. However, comments on social media sites are often aggressive and contemptuous, especially when topics are controversial or politically charged. For example, discussion of intimate partner violence (IPV) tends to provoke strong reactions from outsiders, who make angry or blaming remarks about those involved. Although IPV is common, it has not been widely discussed in popular media until recent years when high-profile cases of abuse have come to light. In 2016, a celebrity accusation of domestic violence led to thousands of comments on social media, with outsiders weighing in about who was at fault and what should be done. This study involved a content analysis of 400 of these comments, with the intent of better understanding typical types of social media reactions to domestic violence accusations. Key themes included judgment and blame, with around 37% of commenters blaming the supposed victim in this case, while only 9% blamed the alleged perpetrator. The findings show how people comment about domestic violence and illustrate the contentious and often distorted nature of social media interactions. Implications for professionals and researchers are discussed.
Objective: The present study sought to characterize social reactions to disclosures of sexual violence that occurred online through the Twitter hashtag #NotOkay. Method: A sample of 306 original content, English-language tweets containing the hashtag #NotOkay were collected via the NVivo software addition NCapture over a period of 5 nonconsecutive weekdays. Qualitative content analysis was conducted by a 3-person team. Results: Ullman’s (2000) Social Reactions Questionnaire served as a preliminary coding guide. Resulting themes included egocentric and distracting social reactions (which are commonly classified as negative responses), as well as a range of positive social reactions (providing emotional support, providing tangible or informational aid, and expressing validation and belief). Advocacy and taking responsibility for social change also emerged as positive responses within the online forum. It unclear whether tweets that distracted from survivors’ experience by commenting broadly on the prevalence of violence, or by placing responsibility on perpetrators, would be considered as helpful or hurtful by survivors. Conclusion: The resulting classification of online social reactions to disclosure of sexual victimization differs from existing classification systems of in-person social reactions to disclosure, suggesting that online forums may offer a unique context for disclosing violence and receiving support. Online forums may also provide an opportunity for support providers to engage in advocacy and voice a desire for social change, forms of social support that may not be provided in the context of an in-person disclosure. Future research may examine whether survivors who disclose on social media receive the support they desire.
A common response to intimate partner violence is to ask victims why they stay in the abusive relationship. Unfortunately this can have the effect of blaming or holding the victim responsible for the abuser’s actions. Recently, social media brought attention to this issue following the highly publicized case of intimate partner violence (IPV) with NFL player Ray Rice and his fiancé. Twitter users responded to the media’s perceived victim blaming by posting their own stories of why they stayed or left abusive relationships. The purpose of this study was to conduct a qualitative content analysis of these Twitter postings. The Twitter hashtags generated N = 676 responses (“whyIstayed” n = 409; “whyIleft” n = 267) and these were examined to answer the following research questions: (1) what factors influence victims of IPV to stay in an abusive relationship? (2) What factors influence victims of IPV to leave an abusive relationship? 12 themes and 8 subthemes emerged that highlight the numerous factors that influence decisions about abusive relationships. Clinical implications and future research recommendations are discussed.
Based on a recent survey and six focus groups, we use a mixed methods approach to examine the help-seeking behavior of Mexican female victims of partner violence in law-enforcement agencies and among family members. Support the family provides women is critically examined. The results of the study suggest that families are not always a source of support: 41 % of the women who turned to public authorities did not mention it to their families, and 11 % did not seek help because they feared their families would find out. Formal help-seeking at law-enforcement agencies is the only choice for many Mexican women since family support has a dual nature, positive and negative. Families may further victimize female victims since partner violence against women triggers the contradiction among core familistic values: individual expectations (family obligations and support) might go against family expectations.
The Internet has recently become an important source of social support. People living with HIV/AIDS (PLWHA) in China created an online support group (the HIV/AIDS Weibo Group) on Weibo, the Chinese equivalent of Twitter, in January 2011. To investigate social support in the HIV/AIDS Weibo Group, the content of all 7215 messages posted in this Weibo group since its launch on 18 January 2011, was analyzed. The analysis demonstrates that the majority of messages fell into the category of social support. Moreover, social support provisions were far more frequent than social support requests. The results also show that informational support, compared with emotional and instrumental support, was the most frequently requested and provided type of support in this Weibo group.
Massive datasets of communication are challenging traditional, human-driven approaches to content analysis. Computational methods present enticing solutions to these problems but in many cases are insufficient on their own. We argue that an approach blending computational and manual methods throughout the content analysis process may yield more fruitful results, and draw on a case study of news sourcing on Twitter to illustrate this hybrid approach in action. Careful combinations of computational and manual techniques can preserve the strengths of traditional content analysis, with its systematic rigor and contextual sensitivity, while also maximizing the large-scale capacity of Big Data and the algorithmic accuracy of computational methods.
Based on observations of court trials and extensive interviews with judges, this article explores how judicial mediation in China undermines the rights of the battered women in divorce cases. We find that even if the judges are able to establish that domestic violence is committed, it is often erased in the stage of judicial mediation. This is because judicial mediation inevitably focuses on settlement arrangements. Lingering reference to domestic abuse would simply invite new denials or refutations from the abuser. It thus risks ruining the mediation efforts made by the judge. Our findings raise important questions with regard to the compulsory practice of mediation in family cases in China. It also sheds light on hidden problems created by judicial mediation or conciliation in general.
Spouse abuse is an ignored, invisible, but significant problem in the Chinese community. This paper describes the experience of Chinese battered women in North America and provides suggestions for culturally sensitive and competent interventions for them. The discussion is based on an extensive review of the literature regarding Chinese battered women. In understanding the experience of Chinese battered women and their strategic responses to the abuse, helping professionals are urged to consider cultural, contextual, as well as individual factors including family dynamics. A three-tier model of intervention for treatment of spouse abuse in the Chinese community is proposed that targets the individual battered women, the family system, and the larger community.
This article presents a review of the published literature to date on rates, experiences, and correlates of victims' disclosure of or help seeking for intimate partner violence to informal social support network members (e.g., friends, family, classmates, and coworkers). Research indicates that the majority of individuals disclose to at least one informal support and that victims' disclosure is associated with a number of demographic (e.g., victims' sex, age, race), intrapersonal (e.g., victims' feelings of shame/embarrassment, perception of control over abuse), and situational (e.g., violence frequency and severity, if abuse is witnessed) factors. Following disclosure, victims experience a wide range of positive (e.g., believing the victim's reports, validating the victim's experiences) and negative (e.g. disbelieving, blaming the victim) social reactions, with positive reactions rated as the most common and most helpful forms of support by victims. Finally, a review of psychological correlates associated with reactions to disclosure indicates that positive social reactions are associated with more psychological health benefits and fewer negative health symptoms, whereas negative social reactions were associated with increased negative psychological health symptoms. Future research methodologies and implications for violence prevention, intervention, and policy are discussed.
With the increased sophistication and speed of computers, fewer text content analysis projects utilize traditional human coding. This methodological case study was designed to compare results of human versus computer-assisted coding using the same data set. The two processes yielded significantly different results in a content analysis of newspaper coverage of a political campaign. In computer-assisted coding, several subjective steps must be taken to adapt the content to the program. Those decisions can be arbitrary and fall outside the concept of traditional intercoder reliability.
Chinese people make up one fifth of the world's total population, yet little is known regarding the prevalence, risk factors, and health outcomes of intimate partner violence (IPV) among this population. There is a lack of public awareness as well as research about IPV in Chinese populations. Studies of IPV prevalence in the Chinese-American population are also limited. Thus, studies of IPV in Chinese populations are needed to increase the Chinese public's recognition of this social problem and its impact on women's rights and health. In order to help identify areas of needed focus for future research, this review centers on the strengths and weaknesses of existing literature on IPV in China and compares the findings with other populations. Also, knowledge about Chinese women's position in society and family, risk factors for IPV, social barriers preventing victims from receiving help, and mental and physical outcomes of IPV are reviewed.
How a support provider responds to disclosure of sexual victimization has important implications for the process of recovery. The present study examines the associations between various positive and negative social reactions to sexual assault disclosure and psychological distress, coping behavior, social support, and self-esteem in a sample of college women (N = 374). Social reactions to assault disclosure that attempted to control the survivor’s decisions were associated with increased symptoms of posttraumatic stress, depression, and anxiety and lower perceptions of reassurance of worth from others. Blaming social reactions were associated with less self-esteem and engagement in coping via problem solving. Social reactions that provided emotional support to the survivor were associated with increased coping by seeking emotional support. Contrary to expectations, social reactions that treated the survivor differently were associated with higher self-esteem. Implications are discussed.
This study examined university students' attitudes about attributing blame in incidents of domestic violence. The Domestic Violence Blame Scale (DVBS), which measures the attribution of blame for domestic violence to situational, perpetrator, societal, and victim factors, was used. The DVBS was administered to a voluntary sample of university students. Significant gender differences were found, with male students more likely to attribute blame to the victim for domestic violence than female students. Significant differences were also found between students with and without a prior history of violence in their family of origin. Students with prior experience of violence were more likely than their counterparts to ascribe blame for domestic violence to societal factors.
Researchers in this study examined the attitudes toward domestic violence, the victim, and her perpetrator. A total of 194 participants were randomly assigned to one of 4 hypothetical scenarios to evaluate how observers’ perceptions were influenced by their own sex and myths about domestic violence, by the victim’s decision to return to the abusive relationship, and by the relationship status of the victim (dating or married to the perpetrator). Results demonstrated significant main effects of participant’s sex, domestic violence myths, and of the victim’s relationship status and decision to return. That is, participants blamed the victim who reportedly returned to her abuser more than the victim about whom there is no such information. Further, participants with greater domestic violence myths tended to blame the victim more than those with less myths, and male participants blamed the victim and minimized the incident more than female participants. Implications, limitations of the study, and future research are discussed.
This research examined how contact with the legal, medical, and mental health systems affects rape survivors' psychological well-being. Although community services may be beneficial for some victims, there is increasing evidence that they can add trauma, rather than alleviate distress (termed secondary victimization). This study examined how secondary victimization affects rape survivors' posttraumatic stress (PTS) symptoms. Adaptive and snowball sampling were used to recruit a sample of 102 rape survivors. Victims of nonstranger rape who received minimal assistance from either the legal or medical system, and encountered victim-blaming behaviors from system personnel, had significantly elevated levels of PTS. This high-risk group of rape survivors had PTS levels significantly higher than all other victims in this study, including those who did not seek community assistance postrape. However, for these high-risk rape survivors, receiving sustained mental health services after these negative experiences was associated with a significant decrease in PTS.
Social support for abused women may reduce the impact of abuse on mental health, yet few studies have addressed this issue. We wish to determine associations between intimate partner violence (IPV) and mental health outcomes and to assess the protective role of abuse disclosure and support on mental health among abused women.
A cross-sectional survey was conducted of 1152 women, ages 18-65, recruited from family practice clinics from 1997 through 1999. They were screened for IPV during a brief in-clinic interview, and physical and mental health status was assessed in a follow-up interview.
IPV, defined as sexual, physical, or psychological abuse, was associated with poor perceived mental and physical health, substance abuse, symptoms of posttraumatic stress disorder (PTSD), current depression, anxiety, and suicide ideation/actions. Among women experiencing IPV and controlling for IPV frequency, higher social support scores were associated with a significantly reduced risk of poor perceived mental health (adjusted relative risk [aRR] 0.5, 95% confidence interval [CI] 0.3, 0.6) and physical health (aRR 0.6, 95% CI 0.5, 0.8), anxiety (aRR 0.3, 95% CI 0.2, 0.4), current depression (aRR 0.6, 95% CI 0.5, 0.8), PTSD symptoms (aRR 0.5, 95% CI 0.4, 0.8), and suicide attempts (aRR 0.6, 95% CI 0.4, 0.9).
Healthcare providers can be instrumental in identifying IPV and helping women develop skills, resources, and support networks to address IPV. Physicians, family, or friends may provide needed social support.
The research literature has demonstrated that battered women living in shelters experience impaired social support. This study examines this phenomenon among battered women living in the community. This study compared a group of pregnant battered women (n = 145) and a group of pregnant nonbattered women (n = 58) in terms of their structural [e.g., total number of supporters, network members in violent relationships with their partners (an index of homophily or nonhomophily) and functional (e.g., emotional)] social support. Four reasons for impaired support in battered women were proposed and examined, including social isolation, failure to disclose abuse, homophily, and low SES. Only homophily was related to impaired support among battered women. In addition, the relationship between structural and functional support and mental health outcomes (e.g., depression, self-esteem) was examined. Criticism, practical support, homophily, and disclosure were all significant predictors of mental health for battered women. Implications for community-based interventions are discussed in the context of current intervention strategies with battered women.
This study documented the types and extent of social support messages exchanged by persons with disabilities who participated in a computer-based support group. A modified version of Cutrona & Suhr's (1992) social support category system was used to code 1,472 support messages. The largest percentage of these messages offered emotional and informational support, whereas network support and tangible assistance were least frequently offered. It appeared that many of the support messages directly redressed limitations and challenges associated with disability-related mobility, socialization, and self-care. Results are discussed in terms of the generalizability of existing category systems for coding support to this mediated context, the relative importance of different types of support in the communication of support group members, and the unique features of social support in mediated environments. The implications of this study for social support researchers, persons with disabilities, and human services professionals are also discussed.
There is a growing need for novel approaches in supporting victims of intimate partner violence (IPV), particularly as the demand placed on formal services increases. Online interventions in this space have shown a great deal of theoretical promise. However, currently little is known about how women perceive this form of support, and how their experiences of receiving support online might differ from face-to-face approaches. This study aims to address this gap through qualitative interviews with n = 16 women who had experienced IPV. Eight of the women had received support via an interactive online intervention, and eight had received a counselling intervention delivered by their general practitioner (GP) (family doctor). The findings suggest that many elements of face-to-face support can also be delivered effectively online, leading to greater control over the help-seeking process. On the other hand, a trusting relationship with the GP can also be extremely helpful to women seeking to disclose, and is difficult to replicate online. Which method of delivery is preferred may depend on whether a woman values trust or control in her help-seeking journey. Both online and face-to-face interventions for IPV should focus on providing individualized support that raises awareness, lessens isolation and considers women’s own unique needs and circumstances.
E-petitions have become a popular vehicle for political activism, but studying them has been difficult because efficient methods for analyzing their content are currently lacking. Researchers have used topic modeling for content analysis, but current practices carry some serious limitations. While modeling may be more efficient than manually reading each petition, it generally relies on unsupervised machine learning and so requires a dependable training and validation process. And so this paper describes a framework to train and validate Latent Dirichlet Allocation (LDA), the simplest and most popular topic modeling algorithm, using e-petition data. With rigorous training and evaluation, 87% of LDA-generated topics made sense to human judges. Topics also aligned well with results from an independent content analysis by the Pew Research Center, and were strongly associated with corresponding social events. Computer-assisted content analysts can benefit from our guidelines to supervise every process of training and evaluation of LDA. Software developers can benefit from learning the demands of social scientists when using LDA for content analysis. These findings have significant implications for developing LDA tools and assuring validity and interpretability of LDA content analysis. In addition, LDA topics can have some advantages over subjects extracted by manual content analysis by reflecting multiple themes expressed in texts, by extracting new themes that are not highlighted by human coders, and by being less prone to human bias.
Background:
Public intimate partner violence (IPV) discourse emphasizes physical violence. In May 2016, the Twitter hashtag #MaybeHeDoesntHitYou generated a public conversation about abuse beyond physical IPV. Because of the often-disconnect between IPV research and what survivors struggle to name as abuse in their daily lives, we sought to understand how IPV discourse was unfolding as a result of the #MaybeHeDoesntHitYou hashtag.
Materials and methods:
NCapture was used to collect publically available Twitter data containing the hashtag "#MaybeHeDoesntHitYou" from May 10, 2016 to May 17, 2016. Using the Duluth Power and Control Wheel (a range of tactics used by abusers to control and harm their partners) and the Women's Experience with Battering (WEB) framework (emotional and behavioral responses to being abused), we analyzed 1,229 original content tweets using qualitative content analysis.
Results:
All dimensions of the Power and Control Wheel and five of six dimensions of the WEB framework were expressed via #MaybeHeDoesntHitYou; users did not express yearning for intimacy with their abusive partners. Users described one form of IPV not currently represented within the Power and Control Wheel-reproductive coercion (e.g., "#MaybeHeDoesntHitYou but he refuses to use condoms and forces you not to use contraception so you try to do it behind his back"). Two additional themes emerged; users challenged the gender pronoun of the hashtag, highlighting that abuse may happen with partners of all genders, and users provided social support for others (e.g., "#MaybeHeDoesntHitYou is real. Bruises and scars aren't the only measure of abuse! If this is you, help is there…").
Conclusions:
Results from our study underscore the potential for social media platforms to be powerful agents for engaging public dialogue about the realities of IPV, as well as a space for seeking and providing social support about this critical women's health issue.
Violence against women (VAW) is a global social issue affecting health, social, and legal systems. VAW contributes to the inequities with respect to the social determinants of health that many women face today. The onus on self-care in the face of violence remains almost singularly with the victims. Access to information and services in support of women’s health and safety is fundamental. However, research gaps exist regarding how women access health information across all stages of an abusive intimate relationship. Given the ubiquity of online access to information, the purpose of this scoping review was to provide an overview of online interventions available to women within the context of intimate partner violence (IPV). Research literature published between 2000 and 2016, inclusive, was reviewed: 11 interventions were identified. Findings suggest that online interventions focused on the act of leaving with less emphasis on the experiences that occur after a woman has left the relationship. In addition, the online interventions concentrated on the individual capacity of the survivor to leave an abusive relationship and demonstrated limited understanding of IPV in relation to the broader social-contextual factors. Findings from this research highlight information gaps for women who require significant support after leaving an abusive relationship.
This study examined strategies Hispanic and non-Hispanic White victims of domestic violence use to manage violence and leave their relationships. Participants (N = 76, 41% Hispanic) completed self-report questionnaires and a semistructured interview with a language-congruent research assistant. Hispanics reported child care needs and fears of social embarrassment as barriers to leaving, while non-Hispanic Whites reported fewer social supports as a barrier. Hispanics were more likely to use legal resources for help, while non-Hispanic Whites used more informal resources. Recognizing unique barriers to leaving abusive relationships and accessing help can guide service providers and others to target vulnerable populations more effectively.
Domestic violence (DV) affects over a third of Chinese women in a relationship. Focusing on ethnographic data from six staff members and six DV survivors at a rural, state-affiliated women’s center in China in 2010, this article relies on Henrietta Moore’s notion of the poststructuralist gendered subject to examine how the staff draw on discourses about gender and social harmony in persuading women to stay in their marriages, rather than on human rights discourses that emphasize survivor safety. It shows that DV survivors are frequently sent back to dangerous homes where their health is placed at risk.
Research on social support during the past two decades has been marked by a growth in scholarship examining supportive communication in computer-mediated contexts among individuals coping with illness. In an effort to summarize and advance this body of research, a meta-analytic review of content analyses was conducted. Across the 41 content analyses examining social support messages shared in health-related contexts online, informational and emotional support messages were most prevalent. Additionally, the prevalence of particular types of support messages varied based on several stressor dimensions relevant to illness. Nurturant forms of support were more common among content analyses examining health conditions likely to threaten personal relationships as well as among content analyses focusing on health conditions with a greater potential for loss in the form of death. Action-facilitating types of support were more common among content analyses examining more chronic conditions. The findings from this project offer insights about the nuanced ways in which computer-mediated communication is used as a resource for coping with illness.
Prior research shows that individual perceptions of victims play an integral role in the societal response to domestic violence, as well as victims' responses to their own victimization. However, little research has specifically examined individual perceptions of domestic violence victims who remain in abusive relationships. This study begins to fill the void in the literature by examining college students' attitudes toward battered women. Specifically, the study considers whether students adhere to common myths associated with battering and if myths lead college students to view domestic violence victims as “blameworthy.” The study relies on a sample of 370 university students attending a large Southern metropolitan university. Findings indicate that students moderately support domestic violence myths and that myth promotion is associated with support for increased criminal justice penalties such as prosecution of mothers and approval of delayed police response in cases of repeat victimization. Implications for policy, theory, and practice are provided.
While negative attributions are often made toward female victims of domestic violence, studies have not explored whether attributions shift contingent upon whether women stay with or leave abusive husbands. Further, no studies investigated whether negative attributions decrease if the participants receive information about the prevalence of domestic violence or the risks inherent in leaving an abuser. Therefore, two studies were designed that investigated attributions made by young adults when women either stay with or leave an abusive husband and whether educating the participants about prevalence of domestic violence and risks of leaving mitigate negative judgments. In both studies, young adults responded to surveys assessing attributions toward a female heterosexual victim of domestic violence. Results indicated that participants made more positive attributions about her personality characteristics and parenting ability if a woman left the relationship. Informing students beforehand about potential risks of leaving and personal experience with domestic violence did not erase this effect, but interactions mitigated some of the effects. Results suggest that educating young adults about risks of violence while useful, is not sufficient to change blaming attitudes. Educators may instead need to challenge the attribution process. Further research involving attributions toward gay and lesbian victims of domestic violence is suggested.
This article presents the first situation-rooted typology of intimate partner violence (IPV) postings in social question and answer (Q&A) sites. Survivors as well as abusers post high-risk health, legal, and financial questions to Q&A sites; answers come from individuals who self-identify as lawyers, experts, survivors, and abusers. Using grounded theory this study examines 1,241 individual posts, each within its own context, raising issues of agency and expectations. Informed by Savolainen's everyday life information seeking (ELIS) and Nahl's affective load theory (ALT), the resultant Q&A typology suggests implications for IPV service design, policy development, and research priorities.
This article presents the findings of a qualitative study of 15 Chinese women in Hong Kong who experienced marital conflict and family violence. Adopting a narrative approach, the authors found that the women had gradually developed a culture of concealment through a process of social construction. Individual, environmental, and cultural factors had combined to develop and reinforce their tendency to conceal their situation and to remain silent. This culture of concealment was highly oppressive and had a negative impact on the women’s personal, interpersonal, and social well-being. Social work strategies to break this pattern of behavior and to liberate the women from the culture of concealment are explored.
A total of 262 Chinese Americans were surveyed on the telephone about their definitions of domestic violence, attitudes toward the use of interpersonal violence, myths about domestic violence victims, and their attitudes toward the criminalization of domestic violence. Generally, Chinese Americans were more likely to define domestic violence in terms of physical and sexual aggression as opposed to psychological abuse. The majority did not approve of hitting spouses or using physical force as a means to solve problems but were ambivalent about using physical punishment to discipline children. A quarter stated that victims caused the abuse, and almost half reported that victims can easily leave an abusive relationship. Although many stated that domestic violence is a crime, many felt that family matters were private. Gender role beliefs impacted on various perceptions of domestic violence. Findings are discussed in their cultural context, and implications for practice and research are discussed for Chinese domestic violence victims.
Recognised as a global concern by the UN, and increasingly acknowledged as a gendered crime and welfare issue in such diverse settings as the UK and China, domestic violence provides an important window on the development of policy and action in a global context. Focusing specifically on England and China, and mainly on the latter, the article highlights the need for gender to be an integral aspect of global social policy analysis, examines the impact of international organisations (governmental and non-governmental) on domestic violence policy development, and demonstrates the importance of country context in constructing and implementing global policy frameworks.
The present study aimed to explore the extent and pattern of wife abuse in Hong Kong Chinese families. The sample included 1,132 married women aged 18 or older randomly selected from the community. Results showed that 67.2% of the surveyed women reported at least one incident of verbal abuse, and 10% experienced at least one incident of physical abuse by their husbands during the surveyed year. Husband-to-wife minor physical violence was almost seven times more than husband-to-wife severe physical violence (9.8% vs 1.4%). Couples' age and their age differences were related to physical wife abuse but not verbal wife abuse. Specifically, physical wife abuse in the form of minor violence occurred most frequently among married men and women aged 30 or below; and both minor and severe physical violence to wife was found most frequently among couples whose ages were more than 20 years apart. Couples' education level, differences in education, occupation, family income, and number of children were not related to various forms of wife abuse; whereas the length of marriage and marital satisfaction were significant correlates of wife abuse. Results were discussed with regard to relevant local and Western studies.
Efforts to understand and support the process of help seeking by victims of intimate partner violence are of considerable urgency if we are to design systems and responses that are capable of actively and appropriately meeting the needs of victims. Using data from the New Zealand Violence Against Women Study, which drew from a representative general population sample of women aged 18 to 64 years, the authors report on the help-seeking behaviors of the women who had ever in their lifetime experienced physical and/or sexual violence by an intimate partner (n = 956). More than 75% of respondents reported that they had told someone about the violence, indicating that it is not necessarily a "secret and private" problem. However, more than 40% of women indicated that no one had helped them. Informal sources of support (family and friends) were most frequently told about the violence but not all provided helpful responses. Fewer women told formal sources of help such as police, health care providers, and not all provided helpful responses. Women's reasons for seeking help and for leaving violent relationships were similar and included "could not endure more," being badly injured, fear or threat of death, and concern for children. Women's reasons for staying in or returning to violent relationships included perception of the violence as "normal/not serious," her emotional investment in the relationship, or staying for the sake of the children. The findings suggest that broader community outreach is required to ensure that family and friends are able to provide appropriate support for women in abusive relationships who are seeking help. Continued improvement in institutional responses is also required.
Social support is defined as information leading the subject to believe that he is cared for and loved, esteemed, and a member of a network of mutual obligations. The evidence that supportive interactions among people are protective against the health consequences of life stress is reviewed. It appears that social support can protect people in crisis from a wide variety of pathological states: from low birth weight to death, from arthritis through tuberculosis to depression, alcoholism, and the social breakdown syndrome. Furthermore, social support may reduce the amount of medication required, accelerate recovery, and facilitate compliance with prescribed medical regimens.
This study examined the role of social support in the partner violence-psychological distress relation in a sample of African American women seeking medical care at a large, urban hospital (n = 138). Results from bivariate correlational analyses revealed that partner violence was related to lower perceived social support and greater psychological distress, and lower social support was related to more distress. Furthermore, findings based on path analysis indicated that low levels of social support helped account for battered women's increased distress. Findings point to the need for service providers to screen for partner violence in nontraditional sites, such as hospital emergency rooms, and to address the role of social support resources in preventive interventions with African American battered women.
For women who are in abusive relationships, social support and close family relationships may be critical to the successful resolution of the abuse. Efforts to enhance battered women's support must be predicated on an understanding of women's perceptions of effective support and the constraints they experience to seeking support. In this paper we present findings from a qualitative analysis of semistructured interviews with 31 women who were in abusive relationships. The women were interviewed three times over two-and-a-half years. Results of the analysis included that women used female friends for support more often than family members, and that women were constrained from seeking support by (a) cultural and societal sanctions against leaving the relationship; (b) a pattern of caution in relating to others or forging new relationships; and (c) forced isolation/seeing self as isolative. Relationships with family members, especially parents, were not consistently seen as useful sources of support.
We sought to determine what women want from health care interventions for intimate partner violence (IPV) and understand why they found certain interventions useful or not useful.
We conducted interviews with 21 women who have a past or current history of intimate partner violence. Participants were given cards describing various IPV interventions and asked to perform a pile sort by placing cards into three categories ("definitely yes," "maybe," and "definitely no") indicating whether they would want that resource available. They were then asked to explain their categorizations.
The pile sort identified that the majority of participants supported informational interventions and individual counseling. Only 9 of 17, however, felt couple's counseling was a good idea with seven reporting it was definitely not useful. Half wanted help with substance use and treatment for depression. Interventions not well regarded included "Receiving a follow-up telephone call from the doctor's office/clinic" and "Go stay at shelter" with only 7 and 5 of the 21 women placing these cards in the "definitely yes" pile. "Health provider reporting to police" was the intervention most often placed in the "definitely no" pile, with 9 of 19 women doing so. The women described several elements that affected their likelihood of using particular IPV interventions. One theme related stages of "readiness" for change. Another theme dealt with the complexity of many women's lives. Interventions that could accommodate various stages of "readiness" and helped address concomitant issues were deemed more useful. Characteristics of such interventions included: 1) not requiring disclosure or identification as IPV victims, 2) presenting multiple options, and 3) preserving respect for autonomy.
Women who had experienced IPV described not only what they wanted from IPV interventions but how they wished to receive these services and why they would chose to use certain resources. They advised providing a variety of options to allow individualizing according to different needs and readiness to seek help. They emphasized interventions that protected safety, privacy, and autonomy.
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