Mobile health for mental health

There is some evidence that mobile health (mHealth) interventions improve mental health in the short-term, particularly anxiety and depression (Goldberg 2022, Wang 2018d, Rathbone 2017a, Rathbone 2017b, Versluis 2016, Cochrane-Lavender 2013, Donker 2013). However, additional evidence is needed to confirm effects over the long-term, as well as among different populations, for various mental health concerns, and how mHealth interventions compare to in-person treatment (Firth 2017a, Rathbone 2017a, Rathbone 2017b).

Overall, mental health mobile apps reduce anxiety, depression, and stress more than no intervention; however, effect sizes vary (Rathbone 2017a). Apps may also reduce symptom severity and disability for adults with bipolar disorder, schizophrenia, or major depressive disorder (Ben-Zeev 2021). Mental health mobile apps that are based on elements of cognitive behavioral therapy (CBT) or that provide self-management and monitoring can improve mental health (Rathbone 2017b, Rathbone 2017a, Versluis 2016, Donker 2013), particularly anxiety (Firth 2017, Lui 2017), and may also improve depression self-management (Firth 2017a). CBT features a wide range of components, all of which may not be included in an individual app; many apps based on CBT may also include aspects of other therapies (Stawarz 2018).

mHealth has been shown to have greater effects on mental health when combined with support from a mental health professional (Versluis 2016). Apps combined with psychotherapy and other behavioral interventions can improve treatment outcomes (Lindhiem 2015), including reduced anxiety (Lui 2017). For example, combining face-to-face therapy and DBT Coach, an app which provides dialectical behavioral therapy (DBT), appears to reduce substance use for adults with borderline personality disorder (Rizvi 2011).

mHealth interventions can reduce the use of methamphetamines and opioids by adults (Tofighi 2017), tobacco and alcohol use by young adults (Mason 2015a), and may reduce alcohol and drug use in high risk populations (Kazemi 2017). For example, a study of young adults identified as hazardous drinkers during emergency department visits suggests that text message drinking assessments with real-time feedback may reduce binge drinking in the short-term (Suffoletto 2012). Contact through voice calls or texts appears to increase medication adherence for adults dependent on alcohol or illicit drugs (Tofighi 2017), and for individuals living with severe mental illness following hospital discharge (Bright 2018).

Mood monitoring apps may identify mental health and substance use problems among youth (Dubad 2018), yet additional research is needed to determine the effectiveness of mHealth apps at treating mental health problems in children and adolescents (Goldberg 2022, Grist 2017), including anxiety (Bry 2018). Additional evidence is also needed to determine the effectiveness of apps for self-management of post-traumatic stress disorder (PTSD) among adults generally (Rodriguez-Paras 2017), although one study among military service members and their families suggests apps may reduce the severity of PTSD (Roy 2017). More evidence is also needed to determine the effectiveness of mHealth apps for suicide prevention (De la Torre 2017) and how they may support treatment of borderline personality disorder (Xie 2022).

Text messaging and app-based interventions are largely acceptable to patients, including those with severe mental health problems (Firth 2016, Berry 2016, Berrouiguet 2016, Ben-Zeev 2021), youth with substance abuse issues (Dubad 2018), pregnant and postpartum women (Varma 2023), and veterans (Betthauser 2020).

Experts suggest consumers use caution when purchasing apps, as most have not been clinically validated (Melcher 2020a, Wang 2018d, Bry 2018, Rodriguez-Paras 2017, Frank 2018) even though hundreds of studies on feasibility, acceptability, effectiveness, and engagement are conducted every year (Goldberg 2022); high app turnover rates make it difficult for providers to recommend quality apps (Larsen 2016). For example, a survey of apps recommended by mental health providers at various college campuses discovered that nearly 30% were no longer available and others had not been updated within the last 6 months, suggesting apps may be outdated, no longer maintained, or unsupported by current cell phone software (Melcher 2020a). Given that many apps do not yet have sufficient evidence of impact, some experts have concerns about the use of apps without provider support (Philippe 2022). Additionally, privacy concerns are often noted by both current patients and potential users (Varma 2023, Melcher 2020, Torous 2018a). Some apps include Health Insurance Portability and Accountability Act (HIPAA) compliant messaging systems for secure patient contact with providers (Lindhiem 2015); however, many apps are not regulated by HIPAA (Rosenfeld 2017) and may collect data for internal purposes or share it externally with third parties (Melcher 2020a, Rosenfeld 2017).

Experts suggest app designs protect users’ privacy and secure information (Torous 2018) and that apps include methods to respond to emergency situations (Torous 2018). Researchers, patients, and providers should all play a role in app development to maximize usability and likelihood of effectiveness (McCarthy 2024, Lattie 2022, Rathbone 2017b, Kassianos 2017). App features which may support user engagement include goal setting, educational information, data visualizations, personalized content and feedback, reminders, and self-monitoring functions (Oakley-Girvan 2022).

It is unclear what impact mobile health (mHealth) interventions have on disparities in mental health care access and outcomes among individuals who experience barriers to mental health care. More research is needed to confirm which types of mHealth are most effective and appropriate for those who experience marginalization or other barriers to accessing digital health interventions (Philippe 2022, Hensel 2019).

Available evidence suggests individuals with less money or education and individuals with complex life circumstances, such as those experiencing homelessness or emergency situations, may experience fewer benefits from digital health interventions than those with greater advantages (Philippe 2022). Additionally, communities that are rural or economically disadvantaged may face increased barriers to accessing mHealth interventions, such as limited internet access, the high costs of smartphones (McCarthy 2024, Connolly 2018), and cultural barriers presented by programs not adapted to user needs (McCarthy 2024). However, mHealth interventions have the potential for customization to meet the needs of diverse populations (McCarthy 2024, Gonzalez 2021), and can be tailored to local resources, culture, and language (McCarthy 2024). Also, access to smartphones continues to grow in some rural communities (McCarthy 2024).

Disparities in mental health outcomes exist in the U.S. within racially, ethnically (Sharifian 2024), gender (Mongelli 2020), and geographically (McCarthy 2024) diverse civilian populations, as well as among service members and veterans, compared with those at less risk because of their identity, military service status (Sharifian 2024), or community type (McCarthy 2024).

Experts recommend creating mHealth interventions that are culturally tailored for individuals from a specific minoritized background (McCarthy 2024, Gonzalez 2021).

People with mental health concerns, including those with serious mental illness, appear to use smartphones and mobile technologies at rates similar to the general population (Ben-Zeev 2021).

Barriers in access to care for mental illness are a problem worldwide, and estimates for the U.S. suggest that less than half of individuals with mental illness receive treatment (Sugarman 2023).

As early as 2011, smartphones and mobile apps were being evaluated for possible integration into behavioral health care services (Luxton 2011). As of 2022, thousands of mHealth apps are available for immediate download (Goldberg 2022).

The Federal Communications Commission Lifeline Program, originally created to increase access to landlines for people with low incomes was extended to mobile phones in 2005 and broadband services in 2016 (Jayakar 2019), which could broaden access to mHealth programs (Ben-Zeev 2021). As of 2022, the majority of people in the U.S. without broadband access are rural residents (Mack 2023); a strong digital divide also exists between urban and suburban areas with high incomes and rural and urban areas with low incomes, suggesting household income may affect access more than geography (CRS-Rachfal 2020, CRS-Kruger 2019, UW Ext-Conroy 2021).

As of January 2024, 97% of Americans own a mobile phone; 90% have smartphones (Pew-Mobile fact sheet); mobile phone and data use by Hispanic consumers, previously less likely to be mobile users, has largely caught up to other consumers (Gonzalez 2021).

• Who has access to mental health services in your community and who does not? How could mobile health (mHealth) for mental health interventions help remove barriers (e.g., health insurance coverage, transportation) so more people can access services?
• Who is choosing which forms of mHealth interventions to offer and how are those decisions being reached? Which mental health needs are the focus? Which patient groups? Is there guidance available to teach patients to use smartphones for services?
• How are health care providers, community members, and policymakers engaged in efforts to expand broadband services? What partnerships are possible and which local resources may support access to smartphones for mHealth use?

As of 2023, there are more than 10,000 mental health apps available (King 2023). The American Psychiatric Association (APA) provides guidelines for psychiatrists and other mental health providers to select useful, safe, and effective apps (APA-MH app). The Anxiety and Depression Association of America collaborated with MindApps.org to provide interactive searching of mental health apps which have been examined according to the APA’s App Evaluation Model for ease of use, effectiveness, personalization, availability of feedback, and strength of research evidence (ADAA-MH app, Mindapps.org).

The U.S. Department of Veterans Affairs (VA) provides several mental health mobile apps designed for treatment and self-care for veterans, military service members, and their families, such as PTSD Coach, PTSD Family Coach, Mindfulness Coach, CBT-I Coach, and Insomnia Coach (US VA-Mobile apps).

ADAA-MH app - Anxiety and Depression Association of America (ADAA). Find help: ADAA reviewed mental health apps.

APA-MH app - American Psychiatric Association (APA). Mental health apps: Why rate mental health apps?

Mindapps.org - M-Health Index & Navigation Database (Mindapps.org). App library.

* Journal subscription may be required for access.

ADAA-MH app - Anxiety and Depression Association of America (ADAA). Find help: ADAA reviewed mental health apps.

APA-MH app - American Psychiatric Association (APA). Mental health apps: Why rate mental health apps?

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McCarthy 2024* - McCarthy MJ, Wicker A, Roddy J, et al. Feasibility and utility of mobile health interventions for depression and anxiety in rural populations: A scoping review. Internet Interventions. 2024;35(January):100724.

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Stawarz 2018 - Stawarz K, Preist C, Tallon D, et al. User experience of cognitive behavioral therapy apps for depression: An analysis of app functionality and user reviews. Journal of Medical Internet Research. 2018;20(6):e10120.

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Torous 2018* - Torous J, Nicholas J, Larsen ME, et al. Clinical review of user engagement with mental health smartphone apps: Evidence, theory and improvement. Evidence-Based Mental Health. 2018;21:116-119.

Torous 2018a - Torous J, Wisniewski H, Liu G, Keshavan M. Mental health mobile phone app usage, concerns, and benefits among psychiatric outpatients: Comparative survey study. JMIR Mental Health. 2018;5(4):1-11.

US VA-Mobile apps - U.S. Department of Veterans Affairs (U.S. VA). PTSD: National Center for PTSD. Mobile applications.

UW Ext-Conroy 2021 - Conroy T, Deller S, Kures M, et al. Broadband and the Wisconsin economy. University of Wisconsin-Madison Extension. Study Series No. 7. 2021.

Varma 2023 - Varma DS, Mualem M, Goodin A, et al. Acceptability of an mHealth App for monitoring perinatal and postpartum mental health: Qualitative study with women and providers. JMIR Formative Research. 2023;7:1-11.

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