Background: Digital mental health interventions (DMHIs) have been increasingly deployed to bridge gaps in mental health care, particularly given their promising efficacy. Nevertheless, attrition among DMHI users remains high. In response, human support has been studied as a means of improving retention to and outcomes of DMHIs. Although a growing number of studies and meta-analyses have investigated the effects of human support for DMHIs on mental health outcomes, systematic empirical evidence of its effectiveness across mental health domains remains scant. Objective: We aimed to summarize the results of meta-analyses of human support versus no support for DMHI use across various outcome domains, participant samples, and support providers. Methods: We conducted a systematic meta-review of meta-analyses, comparing the effects of human support with those of no support for DMHI use, with the goal of qualitatively summarizing data across various outcome domains, participant samples, and support providers. We used MEDLINE, PubMed, and PsycINFO electronic databases. Articles were included if the study had a quantitative meta-analysis study design; the intervention targeted mental health symptoms and was delivered via a technology platform (excluding person-delivered interventions mediated through telehealth, text messages, or social media); the outcome variables included mental health symptoms such as anxiety, depression, stress, posttraumatic stress disorder symptoms, or a number of these symptoms together; and the study included quantitative comparisons of outcomes in which human support versus those when no or minimal human support was provided. Results: The results of 31 meta-analyses (505 unique primary studies) were analyzed. The meta-analyses reported 45 effect sizes; almost half (n=22, 48%) of them showed that human-supported DMHIs were significantly more effective than unsupported DMHIs. A total of 9% (4/45) of effect sizes showed that unsupported DMHIs were significantly more effective. No clear patterns of results emerged regarding the efficacy of human support for the outcomes assessed (including anxiety, depression, posttraumatic stress disorder, stress, and multiple outcomes). Human-supported DMHIs may be more effective than unsupported DMHIs for individuals with elevated mental health symptoms. There were no clear results regarding the type of training for those providing support. Conclusions: Our findings highlight the potential of human support in improving the effects of DMHIs. Specifically, evidence emerged for stronger effects of human support for individuals with greater symptom severity. There was considerable heterogeneity across meta-analyses in the level of detail regarding the nature of the interventions, population served, and support delivered, making it difficult to draw strong conclusions regarding the circumstances under which human support is most effective. Future research should emphasize reporting detailed descriptions of sample and intervention characteristics and describe the mechanism through which they believe the coach will be most useful for the DMHI.

Suicide and self-injury are difficult to predict because at-risk individuals are often unable or unwilling to report their intentions. Therefore, tools to reliably assess risk without reliance on self-report are critically needed. Prior research suggests that people who engage in suicidal and nonsuicidal self-injury (NSSI) often implicitly (i.e., outside conscious control) associate themselves with self-harm and death, indicating that self-harm-related implicit cognition may serve as a useful behavioral marker for suicide risk. However, earlier studies left several critical questions about the robustness, sensitivity, and specificity of self-harm-related implicit associations unaddressed. We recruited a large sample of participants (N = 7,015) via a public web-based platform called Project Implicit Mental Health (PIMH) to test several hypotheses about self-harm-related implicit associations using the Implicit Association Test (IAT). Participants were randomly assigned to complete 1 of 3 self-harm IATs (Self + Cutting using picture stimuli, Self + Suicide using word stimuli, Self + Death using word stimuli). Results replicated prior studies demonstrating that self-harm-related implicit associations were stronger among individuals with (vs. without) a history of suicide attempt and NSSI. Results also suggested that self-harm-related implicit associations are robust (based on internal replication), are sensitive to recency and severity of self-harm history (e.g., stronger associations for more recent and more lethal prior suicide attempts), and correlate with specific types of self-harm behaviors. These findings clarify the nature of self-harm-related implicit cognition and highlight the IAT's potential to track current risk for specific types of self-harm in ways that more fixed risk factors cannot. (PsycINFO Database Record

Historically, US federal policy has not supported harm reduction interventions, such as safe injection facilities (SIFs) and needle and syringe programs (NSPs), which can reduce the burden associated with injection drug use. Given recent increases in abuse of both legal and illegal opioids, there has been a renewed debate about effective ways to address this problem. The current study (1) assessed participants’ support for SIFs and NSPs, and (2) evaluated several demographic factors (e.g., age, gender, race, education, political ideology, and religiosity) and individual differences in stigmatizing beliefs about people who inject drugs (PWID) that might relate to support for these interventions. U.S. adults (N = 899) completed a web-based study that assessed self-reported support for NSPs and SIFs, and stigma about PWID. The majority of participants were at least somewhat supportive of both NSPs and SIFs. Regression analyses indicated greater support for NSPs and SIFs was predicted by more liberal political ideology, more agreement that PWID deserve help rather than punishment, older age, and male gender. Also, participants who endorsed lower stigma about PWID were more supportive of NSPs and SIFs. Race, religiosity, and education did not predict support for NSPs and SIFs. Most participants tended to report support for harm reduction strategies. Age, political ideology, and individual differences in stigmatizing beliefs about PWID were significantly associated with support. Given the potential malleability of stigmatizing beliefs, efforts that seek to shift stigma about PWID could have important implications for public policy towards harm reduction strategies for PWID.

Implicit cognitive processing is theorized to have a central role in many forms of psychopathology. In the current review, we focus on implicit associations, by which we mean evaluative representations in memory that are difficult to control and do not require conscious reflection to influence affect, cognition, or behavior. We consider definitional and measurement challenges before examining recent empirical evidence for these associations in anxiety, obsessive–compulsive, posttraumatic stress, depressive, and alcohol use disorders. This examination is framed by a brief review of the ways that prominent models of psychopathology represent biased implicit processing of disorder-relevant information. We consider to what extent models reflect more traditional automatic/implicit versus strategic/explicit dual-process perspectives or reflect more recent dynamical systems perspectives in which mental representations are iteratively reprocessed, evolving continuously. Finally, we consider the future research needed to better understand the interactive and temporal dynamics of implicit cognition in psychopathology.