Table 3 eHealth for GBV (All Age Groups) [59,60,61,62]

Huang, et al. (2016) [61]

Aim: Review studies on sex-related apps and dating apps

Methods

• Free apps in the Apple iTunes store and Android Google Play store with English language interface were reviewed

• P for Sex apps: user reach between 1000 and 5000 (based on download records). Android apps that contained sexual health info were downloaded less frequently than other sex apps or entertainment apps

• P for Dating apps: 73% apps (k = 44) target heterosexual users, 15% target men who have sex with men (MSM), 5% target lesbian women, and 7% for group dating

• Of the 137 sex-related apps, 15 (11.0%) had sexual health content, and 15 (11.0%) contained messages about sexual assault or violence. 78% of the apps did not contain any sexual health content

• Of the 60 dating apps: Only 9 apps contained sexual health content, of which 7 targeted MSM

• Of the 15 apps that contained sexual health content, 33% had both contraception and STI info, 27% contained contraception info, and 40% contained STI and preventing STI info. Most apps were from the sex education and information category (73%)

• Of the 15 apps offering information about sexual assault, 33% had info regarding management after sexual assault, 33% had general info about sexual assault, 7% (1) focused on identifying sexual assault victims, and the other 27% had information about sexual assault prevention. None mentioned the potential adverse sexual health outcomes faced by sexual assault victims

• Not studied

Anderson et al. (2021) [59]

Aim: A systematic review of Web-Based and mHealth TX for IPV

Methods

• 31 studies (23 unique TXs) published between 1998–2019 (61% published in or after 2015)

• 67% RCTs or RCT protocols

• P: Adults or adolescents IPV victims (most ~ age 30)

• 84% of studies included females; 85% IPV victims, 9% both victims & perpetrators, 9% pregnant victims; all victim-oriented TXs targeted only women

• Countries: US (k = 23) & Cambodia (k = 1)

• Settings: outpatient medical (26%), psychological/ therapy (10%), academic research (52%), community organization (13%) settings

• mHealth TXs: 29% web-based (WB) educational, 29% prevention outcomes depended on use of a computer, 19% WB interactive/responsive to participants; 13% WB communication w/TX provider

• Length of TX: ranged from < 1 h to 14 weeks/6 month

• 26% of studies were computer-based screening with or without integrated education; 23% include safety decision aids. Most were secondary (n = 18) and tertiary (n = 10), and less were primary prevention (n = 3). Some IPV TXs were included as the secondary focus in the sexual health/violence-focused TX (n = 6)

• Among RCTs, control arms included waitlist control, usual care, paper-based screening, face-to-face screening or TX delivery, health information materials related or not related to IPV

• Feasibility/acceptability are high

• Insufficient evidence to support mHealth screening would increase IPV disclosure and better SRH outcomes (inconsistently defined)

• IPV prevention with access to telehealth services (iCBT, online support groups for victims, changing behavior expectation through education) showed more promising in reducing IPV risk

• Attrition is lower when using a WB method of participant-provider communication than the WB method without communication

El Morr et al. (2020) [60]

Aim: A systematic review of IPV, domestic violence TX that used ICT

Methods

• 25 studies addressing were identified

• 64% (16/25) RCTs, 4/25 pre-post design

• P: Most are women (pregnant, postpartum, with a history of IPV, high HIV risk), except 1 includes both genders

• Countries: 92% in North America, 12% Canada, 1 in Australia, and 1 New Zealand

• mHealth provided in a medical setting (56%), community (24%), social service (16%), and legal service settings

• IPV ICT TXs: for screening, prevention, mental health TX, and support/empowerment

• ICT strategies: 68% solely desktop or laptop-based, 8% tablet-based, 4% use tablet and telephone, 4% study implemented a kiosk system, 12% were not reported and supposed any type of ICT

• 52% studies were IPV screening and disclosure, 20% IPV prevention, 16% mental health TXs (e.g., video conference for IPV trauma); 8% support/ empowerment TX (e.g., enhance decision making & self-efficacy)

• Control arms included usual care, face-to-face paper-based screening, wait-list control, non-tailored version of ICT, health information, interventions not related to IPV

• IPV screening/disclosure: equally effective or more effective as using the usual paper/face-to-face methods

• IPV prevention: reduction on physical IPV, IPV injury, severe sexual IPV, physical aggression

• Women’s mental health (TX): TXs that addressed mental health (MH) & substance use showed improvement on MH, PTSD & user satisfaction

• Support/empowerment TXs: increase women's rate of leaving abusive partners, safety behaviors, improve decision-making skills, lower decisional conflicts

• Usability of ICT software: generally are high

Linde, et al., (2020) [62]

Aim: Systematic review & meta-analysis of IPV eHealth TXs

Methods

• 14 RCTs in comparison to standard care, articles publish up till April 2019 were included (8 published between 2002–2019; 7 RCTs included in the meta-analysis; follow up from 1.5–12 months)

• P: Women exposed to IPV, and age ranged from 27 to 40 years

• Countries: 6 US, 1 Australia, and 1 New Zealand

• eHealth IPV TX: IPV education, prevention, safety, support, skill-building

• mHealth strategies: use of information and communication technologies for health, including mHealth, online WB platform, and telehealth

3 trials focused on Online safety decision aid (vs. control website or standard safety planning), 1 trial focused on online IPV education (vs online popular TV shows), 2 trials assessed telephone support (vs standard care), 1 trial focused on email modules with relationship communication skills & problem-solving training (vs. placebo email module), 1 3-armed trial focus on email module with IPV support(vs. face-to-face modules with IPV support, vs Standard Care)

• Meta-analysis of RCTs found no evidence that eHealth TXs reduce IPV (overall IPV, physical violence, psychological violence, sexual violence, depression, and PTSD)

• Subgroup analysis that compared low risk with high risk of bias trials showed similar results

• Similarly, when data were stratified according to the type of scale or type of eHealth TX, subgroup analyses showed no effect of eHealth on the reduction of IPV