LAUSR

After nearly three decades of scientific research, digital mental health (DMH) is having its moment. Millions of dollars of venture capital funding are entering this space (Shah and Berry 2021; Wang and Zweing 2021) and a multitude of apps are available to consumers on commercial app marketplaces, leading to many optimistic conclusions such as that the “digital mental health genie is out of the bottle” (Ben-Zeev 2020). However, despite these signs of optimism, skepticism remains, a recent paper: “Is There an App for That?: Ethical Issues in the Digital Mental Health Response to COVID-19” (Skorburg and Yam, 2022), published in AJOB Neuroscience came to the pessimistic conclusion that resources for mental health support and services should not be allocated toward DMH. This conclusion was based on Skorburg and Yam’s (2022) synthesis and interpretation of four meta-analyses as suggesting that (1) DMH is ineffective, and (2) DMH will exacerbate inequities in mental health care. While we agree that DMH has the potential to increase, rather than reduce, inequities, clear evidence supports the effectiveness of certain DMH interventions. Rather than dismiss the whole field we argue that a more productive dialogue would focus on where DMH holds value, how to support those areas, and how to prioritize responsible innovation that leverages the affordances of technology to address mental health inequities. We address both these issues, DMH effectiveness and mental health inequities, in turn. An analysis of the effectiveness of DMH requires first a definition of what DMH is. In Skorburg and Yam’s definition, they use DMH as a “catchall term,” but it is worth noting that by catching all, one loses the distinction between specific products. DMH products have stark differences between their purposes (general wellness vs. disorder specific), interventions (mood trackers, meditation apps, digital cognitivebehavioral therapy platforms), and intersection with human support (self-guided, human-supported, virtual care platforms). We would not expect that a selfguided mood tracking app and a digital cognitivebehavioral therapy program with therapist guidance would have the same outcomes. Furthermore, the benefits that two people gain from any specific DMH product might differ. Along these lines in the case of digital cognitive-behavioral therapy platforms for depression, evidence suggests that those with more severe symptom severity might benefit only for those platforms with human support where those with low symptom severity show similar benefits from selfguided or support platforms (Karyotaki et al. 2021). Thus, any conclusion about DMH as a whole is likely to be inaccurate if only because such differences exist among different products and applications of DMH. Perhaps a better model is that of the National Institute for Health Care Excellence in their expert panel assessment of Space for Depression (SilverCloud) in the treatment of adults with depression. The panel reached the conclusion that the case for adoption is partially supported and that Space for Depression is suitable for use: (1) when monitoring can identify and help those who stop using the program, (2) when flexibility is provided in the communication between client and supporter, and (3) when clear plans are present to support service integration (National Institute for Health and Care Excellence 2020). We would also like to note, however, that the other side of our argument is that we need to identify areas where DMH is not effective and why it fails. For example, a recent large pragmatic clinical trial of lowintensity outreach programs among outpatients with frequent suicidal ideation found that a brief online dialectical behavioral therapy skills training program actually increased the risk of self-harm compared to care management or usual care (Simon et al. 2022). Engagement in the online program was quite poor, so