Technology-Based Mental Interventions for Domestic Violence in COVID-19

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1		Zhaohui Su	--	1928	2022-04-11 12:01:19	\|
2	Adjust the reference format	Lindsay Dong	-34 word(s)	1894	2022-04-12 04:02:14	\|

This entry is adapted from the peer-reviewed paper 10.3390/ijerph19074286

Domestic violence is a threat to human dignity and public health. Mounting evidence shows that domestic violence erodes personal and public health, spawning issues such as lifelong mental health challenges. To further compound the situation, COVID-19 and societies’ poor response to the pandemic have not only worsened the domestic violence crisis but also disrupted mental health services for domestic violence victims. While technology-based health solutions can overcome physical constraints posed by the pandemic and offer timely support to address domestic violence victims’ mental health issues.

domestic violence mental health COVID-19 technology-based interventions

1. Introduction

Domestic violence erodes humanity and global solidarity. Domestic violence or violence against women can be understood as “any act of gender-based violence that results in, or is likely to result in, physical, sexual, or mental harm or suffering to women, including threats of such acts, coercion or arbitrary deprivation of liberty, whether occurring in public or in private life” ^[1]. It is important to note that domestic violence can happen to both men and women, especially for people who face pronounced disadvantages, such as racial/ethnic or sexual minorities ^[2]^[3]^[4]. That said, to avoid issues such as overgeneration and in light of the high prevalence of domestic violence among women compared to men ^[3]. Research conducted by the World Health Organization shows that approximately one in every three women aged 15–49 years is or will become a domestic violence victim ^[5]. Situations might be considerably worse in low- and middle-income countries ^[6]. In Colombia, for instance, analyzing data from 2001 to 2009, researchers found that, on average, 54,440 women per year, 149 per day, 6 per hour, or 1 woman every 10 min suffer from sexual violence ^[7]. These dire statistics could result in grim public health consequences. Mounting evidence shows that domestic violence could exert severe and oftentimes lifelong damage to personal and public health, ranging from anxiety, depression, insomnia, and post-traumatic stress disorders (PTSD) to suicide ^[8]^[9]^[10]^[11].

COVID-19, along with its resultant crises, has further compounded the situation. A research on 751 women in Tunisia, for instance, shows that reported violence against women rose from 4.4% to 14.8% amid an early COVID-19 lockdown ^[12]. Worrisome trends have also been confirmed in countries such as the United States (U.S.); data from 36 police and 66 sheriff’s departments across the country show that amid the pandemic, domestic violence cases are on the rise as people retreat to shelters ^[13]. Analyzing 4618 police reports from the Chicago Police Department, researchers further found that during pandemic lockdowns, domestic violence cases were 64% more likely to happen at residential locations compared to other places ^[14]. To make situations even more complex, unintended consequences of the COVID-19 pandemic have also been seen in the disruption of healthcare services for domestic violence victims. Ranging from the need for COVID-19 testing and tracing, infections, hospitalizations, and treatments to deaths, the pandemic has forced many nations to allocate most, if not all, resources to address medical emergencies associated with COVID-19, effectively leaving many non-COVID-19-related medical needs, such as mental health services for domestic violence victims, in limbo ^[15]. By interviewing health departments across the U.S., researchers further found that at least 220 departments had either temporarily or permanently cancelled their non-COVID-related public health services, directly causing a spike in reports of abuses ^[16].

One way to lessen the impact of COVID-19 and its subsequent medical resource crises on vulnerable populations, such as domestic violence victims, is via finding of alternative health solutions, such as technology-based interventions, that can be accessed virtually without relying on strained healthcare resources. Technology-based interventions can be understood as “the use of technology to design, develop, and/or deliver health promotion contents and strategies that aim to induce or improve positive physical or psychological health outcomes” in victims ^[17]. Previous evidence shows that compared to other low-scale or low-intensity in-person solutions (e.g., single counseling sessions with a physician), technology-based mental health interventions perform similarly or even better in improving domestic violence victims’ health outcomes ^[18]^[19]^[20]^[21]^[22]. However, although useful insights are available, little is known about the state-of-the-art development of technology-based mental health interventions for domestic violence victims amid the pandemic.

2. Technology-Based Mental Interventions for Domestic Violence in COVID-19

2.1. Benefits of Technology-Based Interventions

COVID-19 and the ensuing avalanche of crises, ranging from healthcare delivery issues to medical resource shortages, have further exacerbated the challenges faced by domestic violence victims ^[23]. However, not all hope is lost; compared to in-person solutions, technology-based interventions can be delivered remotely and virtually, effectively bypassing some of the most debilitating barriers introduced by COVID-19 ^[17]^[24]. Although COVID-19 has worsened the scale and severity of domestic violence ^[13]^[25]^[26]^[27], as seen across the pandemic continuum, due to limitations such as physical distancing mandates and lockdown measures, many in-person interventions that were available to domestic violence victims may have been adversely interrupted (e.g., service suspension) ^[28]^[29]^[30]. This, along with the fact that technology-based interventions could offer some victims much-needed anonymity and convenience ^[23], makes technology-based mental health interventions of particular importance amid the pandemic.

Traditionally, domestic violence victims can only report their abuse in person or via hotlines, whereas with the help of technology-based interventions, women can capitalize on a wide range of digital tools and online platforms to seek help. Evidence shows that compared to in-person sessions, teleconferences are preferred by domestic violence victims, largely because they “provided a level of control and distance” ^[31]. This, in turn, can give victims greater freedom in choosing the mental health solutions that are in line with their needs and preferences. Perhaps most importantly, these technology-based interventions give some people access to mental health support who otherwise would not have the opportunity. For instance, many international health and non-profit organizations offer domestic violence victims up-to-date mental health solutions in multiple languages to help such vulnerable communities better cope with pandemic-related stress and beyond (e.g., ^[32]). This means that when needed, victims have a wide range of access to intervention materials to select from at their own discretion. When high-speed Internet is easily accessible, victims can also utilize tools including smartphone applications (apps), such as I-DECIDE, along with other apps (e.g., WhatsApp or WeChat) and health technologies (e.g., TikTok) to further care for their mental health. However, it is important to note that although seeking information and help via technology-based interventions holds great promise, Herculean tasks are also present for health officials and technologists to ensure that optimal benefits can be delivered via these health solutions. There is also reasonable doubt in terms of whether technology-based solutions can replace more intensive and interactive in-person solutions. This concern is particularly salient in light of the possibility that some people may suffer from mental issues that prevent them from using technology-based solutions, owing to reasons such as paranoiac tendencies and/or fear of technology (e.g., cyber paranoia) ^[33]^[34]^[35].

2.2. Risks Associated with Technology-Based Interventions

It is important to highlight that one of the key findings is that most interventions place the help-seeking responsibility on the victims (i.e., individual level) rather than the larger community (i.e., community level) or societal changes (i.e., social level). In other words, even though domestic violence victims may face a number of challenges above and beyond their mental health issues, they are often expected to initiate the help-seeking actions, have the knowhow to safely navigate the ever-changing technological environment, and possess the capabilities to protect themselves from potential intended and unintended harms that might occur during the process. Essentially, these expectations put the responsibilities of technologists, health officials, and government personnel squarely and simultaneously on the shoulder of the victims, potentially further worsening domestic violence victims’ mental health status, as many technological issues (e.g., cybercrimes) could be extremely difficult to tackle ^[36]^[37]^[38]. Furthermore, as technology advances, ranging from artificial intelligence to sixth-generation technologies (e.g., ^[39]), it might become increasingly difficult for domestic violence victims with poor eHealth literacy to fully understand and appreciate the content and consequences of technology-based interventions ^[40]^[41].

It is important to note that although the cybersphere could be an inclusive and interactive environment for mental health intervention development and distribution, it is often haunted by issues ranging from high dependence on basic infrastructure (e.g., broadband access) and cybercrimes (e.g., cyberbullying and cyberstalking) to social media addiction ^[42]^[43]^[44]^[45]^[46]. Studies found that privacy and security issues inherent to technological devices and platforms could influence victims’ appreciation and utilization of technology-based mental health interventions ^[45], not to mention that in cybersphere, damage related to privacy and data-handling breaches could be extremely difficult to estimate and/or contain.

Digital addiction, such as social media addiction, could also pose harm to individuals’ mental and physical health, especially vulnerable people, including young adults ^[47]. Similar to the issue of too much usage, there is also the problem of not having enough access. Partially influenced by poor availability of systematic support, high-speed Internet, and technological devices, research shows that there is a pronounced lack of representation of marginalized and underserved populations (e.g., racial minorities) in mental health technology services ^[48]. Although digital health solutions are becoming ever-increasingly available, policies that could safeguard their quality to protect the public’s rights and safety are either lax or lagging ^[49]. Furthermore, legislative hurdles may also hinder victims’ access to quality mental health services via technology-based means. As of October 2021, only twenty-three states in the U.S. have effectively signed on to the Psychology Interjurisdictional Compact (PSYPACT), an agreement that allows cross-state telepsychology services among licensed psychologists ^[50]—although promising, a far cry from the possibility of having a digital “Doctors Without Borders” system for domestic violence victims ^[23].

Greater governmental support and oversight is needed to ensure the healthy development of technology-based interventions for domestic violence victims. Considering that domestic violence victims often live with their abusers ^[51], advanced technological solutions, such as AI-enabled facial recognition, can be integrated into various interventions to ensure the content can only be accessed by the victims. Researchers could also use AI technologies, such as natural language processing, to analyze electronic health records to potentially identify victims’ susceptibility to mental health issues before such issues become chronic or permanent ^[52]^[53]. Furthermore, by studying large corpora of texts, such as Facebook/Weibo posts, natural language processing technologies could also help government and health officials identify trends, patterns, and incidents of violence and/or mental health emergencies in a timely manner ^[54]^[55]. Overall, in light of the capricious nature of COVID-19, it is imperative for government and health officials to apply useful lessons derived from researchs, such as taking a proactive and practical yet panoramic approach to developing and deploying technology-based mental health solutions to domestic violence victims, weighing both the pros and cons of such interventions prior to distribution so that optimal intended outcomes can be achieved without causing unintended harms.

Domestic violence violates the fundamentals of humanity: safety, security, agency, and, perhaps most importantly, dignity. COVID-19, along with its resultant crises, has worsened the scale, scope, and severity of domestic violence worldwide. To address the delivery and accessibility challenges caused by the pandemic and the subsequent mandates, technology-based interventions, which could overcome the abovementioned obstacles, are gaining in popularity. There needs a pronounced need for greater research endeavors to solve the issues identified. Although technology-based interventions have substantial potential to resolve domestic violence victims’ mental health issues, risks associated with such health solutions should be comprehensively acknowledged and thoroughly addressed. For instance, future research could investigate how policy-level support (e.g., increased research funding) can further enrich society’s in-depth understanding, timely development, and victim-centered delivery of technology-based mental health interventions for domestic violence victims.

References

United Nations. Declaration on the Elimination of Violence against Women; United Nations: New York, NY, USA, 1993.
World Health Organization. Preventing Intimate Partner and Sexual Violence against Women: Taking Action and Generating Evidence; World Health Organization: Geneva, Switzerland, 2010.
Stöckl, H.; Devries, K.; Rotstetin, A.; Abrahams, N.; Campbell, J.; Watts, C.; Moreno, C.G. The global prevalence of intimate partner homicide: A systematic review. Lancet 2013, 382, 859–865.
Su, Z.; McDonnell, D.; Cheshmehzangi, A.; Ahmad, J.; Chen, H.; Šegalo, S.; Cai, Y. What “family affair”? Domestic violence awareness in China. Front. Public Health 2022, 10, 795841.
World Health Organization. Violence against Women. 2021. Available online: https://www.who.int/news-room/fact-sheets/detail/violence-against-women (accessed on 17 October 2021).
Sardinha, L.; Maheu-Giroux, M.; Stöckl, H.; Metyer, S.R.; Galrcía-Moreno, C. Global, regional, and national prevalence estimates of physical or sexual, or both, intimate partner violence against women in 2018. Lancet 2022, 399, 803–813.
Sanchez, O.A.; Vivas, J.N.L.; Cardenas, D.R.; Cano, M.d.P.R. Sexual Violence against Women in the Context of the Colombian armed Conflict 2001–2009; Campaign ‘Rape and Other Violence: Leave my Body out of the War’: Bogota, Colombia, 2011.
Oram, S.; Khalifeh, H.; Howard, L.M. Violence against women and mental health. Lancet Psychiatry 2017, 4, 159–170.
Ellsberg, M.; Watts, C.; Yoshihama, M.; Kiss, L.; Schraiber, L.B.; Deyessa, N.; WHO Multi-Country Study. Intimate partner violence and women’s physical and mental health in the WHO multi-country study on women’s health and domestic violence: An observational study. Lancet 2008, 371, 1165–1172.
Indu, P.V.; Remadevi, S.; Vidhukumar, K.; Navas, P.M.S.; Anilkumar, T.V.; Subha, N. Domestic violence as a risk factor for attempted suicide in married women. J. Interpers. Violence 2017, 35, 5753–5771.
Devries, K.; Watts, C.; Yoshihama, M.; Kiss, L.; Schraiber, L.B.; Deyessa, N.; Heise, L.; Durand, J.; Mbwambo, J.; Jansen, H.; et al. Violence against women is strongly associated with suicide attempts: Evidence from the WHO multi-country study on women’s health and domestic violence against women. Soc. Sci. Med. 2011, 73, 79–86.
Sediri, S.; Zgueb, Y.; Ouanets, S.; Ouali, U.; Bourgou, S.; Jomli, R.; Nacef, F. Women’s mental health: Acute impact of COVID-19 pandemic on domestic violence. Arch. Women’s Ment. Health 2020, 23, 749–756.
Hsu, L.-C.; Henke, A. COVID-19, staying at home, and domestic violence. Rev. Econ. Househ. 2021, 19, 145–155.
McLay, M.M. When “shelter-in-place” isn’t shelter that’s safe: A rapid analysis of domestic violence case differences during the COVID-19 pandemic and stay-at-home orders. J. Fam. Violence 2021.
Cancino, R.S.; Su, Z.; Mesa, R.; E Tomlinson, G.; Walng, J. The impact of COVID-19 on cancer screening: Challenges and opportunities. JMIR Cancer 2020, 6, e21697.
Baker, M.; Ivory, D. Why Public Health Faces a Crisis across the U.S. 2021. Available online: https://www.nytimes.com/2021/10/18/us/coronavirus-public-health.html (accessed on 19 October 2021).
Constantino, R.E.; Braxter, B.; Ren, D.; Burroughs, J.D.; Doswell, W.M.; Wu, L.; Hwang, J.G.; Klem, M.; Joshi, J.B.D.; Greene, W.B. Comparing online with face-to-face HELPP intervention in women experiencing intimate partner violence. Issues Ment. Health Nurs. 2015, 36, 430–438.
van Gelder, N.; Ligthart, S.; Ten Elzen, J.; Prins, J.; van Rosmalen-Nooijens, K.; Oertelt-Prigione, S. “If I’d had something like SAFE at the time, maybe I would’ve left him sooner.”—Essential features of eHealth interventions for women exposed to intimate partner violence: A qualitative study. J. Interpers. Violence 2021, 08862605211036108.
Koziol-McLain, J.; Vandal, A.C.; Wilson, D.; Nada-Raja, S.; Dobbs, T.; McLean, C.; Sisk, R.; Eden, K.B.; E Glass, N. Efficacy of a Web-Based Safety Decision Aid for Women Experiencing Intimate Partner Violence: Randomized Controlled Trial. J. Med Internet Res. 2018, 19, e426.
Tarzia, L.; Cornelio, R.; Forsdike, K.; Hegarty, K. Women’s Experiences Receiving Support Online for Intimate Partner Violence: How Does it Compare to Face-to-Face Support from a Health Professional? Interact. Comput. 2018, 30, 433–443.
Ogbe, E.; Harmon, S.; Bergh, R.V.D.; Degomme, O. A systematic review of intimate partner violence interventions focused on improving social support and/mental health outcomes of survivors. PLoS ONE 2020, 15, e0235177.
Su, Z.; Li, X.; McDonnell, D.; A Fernandez, A.; E Flores, B.; Wang, J. Technology-Based Interventions for Cancer Caregivers: A Concept Analysis. JMIR Cancer 2021, 7, e22140.
Mazza, M.; Marano, G.; Lai, C.; Janiri, L.; Sani, G. Danger in danger: Interpersonal violence during COVID-19 quarantine. Psychiatry Res. 2020, 289, 113046.
Su, Z.; Cheshmehzangi, A.; McDonnell, D.; Šegalo, S.; Ahmad, J.; Bennett, B. Gender inequality and health disparity amid COVID-19. Nurs. Outlook 2021, 70, 89–95.
Leigh, J.K.; Peña, L.D.; Anurudran, A.; Pai, A. “Are you safe to talk?”: Perspectives of Service Providers on Experiences of Domestic Violence During the COVID-19 Pandemic. J. Fam. Violence 2022.
Flor, L.S.; Friedman, J.; Spencer, C.N.; Cagney, J.; Arrieta, A.; E Herbert, M.; Stein, C.; Mullany, E.C.; Hon, J.; Patwardhan, V.; et al. Quantifying the effects of the COVID-19 pandemic on gender equality on health, social, and economic indicators: A comprehensive review of data from March, 2020, to September, 2021. Lancet 2022.
Morton, A.; Adams, C. Health visiting in England: The impact of the COVID-19 pandemic. Public Health Nurs. 2022.
Panovska-Griffiths, J.; Szilassy, E.; Johnson, M.; Dixon, S.; De Simoni, A.; Wileman, V.; Dowrick, A.; Emsley, E.; Griffiths, C.; Barbosa, E.C.; et al. Impact of the first national COVID-19 lockdown on referral of women experiencing domestic violence and abuse in England and Wales. BMC Public Health 2022, 22, 504.
Shah, S.S.; Mufeed, S.A. Urgency and relevance of feminist social work to curb domestic violence amid COVID-19. Int. Soc. Work 2022, 00208728211066833.
Tarzia, L.; Iyer, D.; Thrower, E.; Hegarty, K. “Technology doesn’t judge you”: Young Australian women’s views on using the internet and smartphones to address intimate partner violence. J. Technol. Hum. Serv. 2017, 35, 199–218.
Women’s Aid. The Survivor’s Handbook: Information in Other Languages. 2021. Available online: https://www.womensaid.org.uk/the-survivors-handbook/different-languages/ (accessed on 20 October 2021).
Mason, O.J.; Stevenson, C.; Freedman, F. Ever-present threats from information technology: The Cyber-Paranoia and Fear Scale. Front. Psychol. 2014, 5, 1298.
Kaya, A.Y.; Ata, F. New Media and Digital Paranoia: Extreme Skepticism in Digital Communication. In Handbook of Research on Cyberchondria, Health Literacy, and the Role of Media in Society’s Perception of Medical Information; Aker, H., Aiken, M., Eds.; IGI Global: Hershey, PA, USA, 2022; pp. 330–343.
Zimaitis, I.; Degutis, M.; Urbonavicius, S. Social media use and paranoia: Factors that matter in online shopping. Sustainability 2020, 12, 904.
Winfield, A. Ethical standards in robotics and AI. Nat. Electron. 2019, 2, 46–48.
Keskinbora, K.H. Medical ethics considerations on artificial intelligence. J. Clin. Neurosci. 2019, 64, 277–282.
Hunt, X.; Tomlinson, M.; Sikander, S.; Skeen, S.; Marlow, M.; Du Toit, S.; Eisner, M. Artificial Intelligence, Big Data, and mHealth: The Frontiers of the Prevention of Violence Against Children. Front. Artif. Intell. 2020, 3, 106550.
Su, Z.; McDonnell, D.; Bentley, B.L.; He, J.; Shi, F.; Cheshmehzangi, A.; Ahmad, J.; Jia, P. Addressing Biodisaster X Threats with Artificial Intelligence and 6G Technologies: Literature Review and Critical Insights. J. Med. Internet Res. 2021, 23, e26109.
Jacobson, N.C.; Bentley, K.H.; Walton, A.; Wang, S.B.; Fortgang, R.G.; Millner, A.J.; Coombs, G.; Rodman, A.M.; Coppersmith, D.D.L. Ethical dilemmas posed by mobile health and machine learning in psychiatry research. Bull. World Health Organ. 2020, 98, 270–276.
Davison, T. Cyberthreats are going mobile and it’s time to take action. Comput. Fraud. Secur. 2021, 2021, 18–19.
Parsons, C.; Molnar, A.; Dalek, J.; Knockel, J.; Kenyon, M.; Haselton, B.; Khoo, C.; Deibert, R. The Predator in Your Pocket: A Multidisciplinary Assessment of the Stalkerware Application Industry; Lab, C., Ed.; University of Toronto: Toronto, ON, Canada, 2021.
Jattamart, A.; Kwangsawad, A. What awareness variables are associated with motivation for changing risky behaviors to prevent recurring victims of cyberbullying? Heliyon 2021, 7, 08121.
Lopes Gomes Pinto Ferreira, G. Technology as both a facilitator of and response to youth intimate partner violence: Perspectives from advocates in the global-south. In The Emerald International Handbook of Technology-Facilitated Violence and Abuse; Bailey, J., Flynn, A., Henry, N., Eds.; Emerald Publishing Limited: Bingley, UK, 2021; pp. 427–446.
Bauerly, B.C.; Mccord, R.F.; Hulkower, R.; Pepin, D. Broadband Access as a Public Health Issue: The Role of Law in Expanding Broadband Access and Connecting Underserved Communities for Better Health Outcomes. J. Law Med. Ethics 2019, 47 (Suppl. 2), 39–42.
Huckvale, K.; Torous, J.; Larsen, M.E. Assessment of thedata sharing and privacy practices of smartphone apps for depression and smoking cessation. JAMA Netw. Open 2019, 2, e192542.
Montag, C.; Elhai, J.D. Discussing digital technology overuse in children and adolescents during the COVID-19 pandemic and beyond: On the importance of considering Affective Neuroscience Theory. Addict. Behav. Rep. 2020, 12, 100313.
Pappas, S. Providing Care in Innovative Ways. 2021. Available online: https://www.apa.org/monitor/2020/01/cover-trends-innovative-ways (accessed on 24 October 2021).
The Psychology Interjurisdictional Compact. Map. 2021. Available online: https://psypact.site-ym.com/general/custom.asp?page=psypactmap (accessed on 24 October 2021).
Bradbury-Jones, C.; Isham, L. The pandemic paradox: The consequences of COVID-19 on domestic violence. J. Clin. Nurs. 2020, 29, 2047–2049.
Vaci, N.; Liu, Q.; Kormilitzin, A.; De Crescenzo, F.; Kurtulmus, A.; Harvey, J.; O’Dell, B.; Innocent, S.; Tomlinson, A.; Cipriani, A.; et al. Natural language processing for structuring clinical text data on depression using UK-CRIS. Évid. Based Ment. Health 2020, 23, 21–26.
Annapragada, A.V.; Donaruma-Kwoh, M.M.; Annapragada, A.V.; Starosolski, Z.A. A natural language processing and deep learning approach to identify child abuse from pediatric electronic medical records. PLoS ONE 2021, 16, e0247404.
Ni, Y.; Barzman, D.; Bachtel, A.; Griffey, M.; Osborn, A.; Sorter, M. Finding warning markers: Leveraging natural language processing and machine learning technologies to detect risk of school violence. Int. J. Med. Inform. 2020, 139, 104137.
Subramani, S.; Wang, H.; Vu, H.Q.; Li, G. Domestic violence crisis identification from facebook posts based on deep learning. IEEE Access 2018, 6, 54075–54085.
Howard, L.M.; Trevillion, K.; Agnew-Davies, R. Domestic violence and mental health. Int. Rev. Psychiatry 2010, 22, 525–534.
Campbell, J.C. Health consequences of intimate partner violence. Lancet 2002, 359, 1331–1336.

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