Comparing Message-Based Psychotherapy to Once-Weekly, Video-Based Psychotherapy for Moderate Depression: Randomized Controlled Trial.

BACKGROUND: Despite the high prevalence of major depressive disorder and the related societal burden, access to effective traditional face-to-face or video-based psychotherapy is a challenge. An alternative that offers mental health care in a flexible setting is asynchronous messaging therapy. To date, no study has evaluated its efficacy and acceptability in a randomized controlled trial for depression. OBJECTIVE: The aim of this study was to compare the efficacy and acceptability of message-based psychotherapy for depression to once-weekly video-based psychotherapy. METHODS: In this 2-armed randomized controlled trial, individuals (N=83) with depressive symptomatology (Patient Health Questionnaire-9 ≥10) were recruited on the internet and randomly assigned to either a message-based intervention group (n=46) or a once-weekly video-based intervention group (n=37). Patients in the message-based treatment condition exchanged asynchronous messages with their therapist following an agreed-upon schedule. Patients in the video-based treatment condition met with their therapist once each week for a 45-minute video teletherapy session. Self-report data for depression, anxiety, and functional impairment were collected at pretreatment, weekly during treatment, at posttreatment, and at a 6-month follow-up. Self-reported treatment expectancy and credibility for the assigned intervention were assessed at pretreatment and therapeutic alliance at posttreatment. RESULTS: Findings from multilevel modeling indicated significant, medium-to-large improvements in depression (d=1.04; 95% CI 0.60-1.46), anxiety (d=0.61; 95% CI 0.22-0.99), and functional impairment (d=0.66; 95% CI 0.27-1.05) for patients in the message-based treatment condition. Changes in depression (d=0.11; 95% CI -0.43 to 0.66), anxiety (d=-0.01; 95% CI -0.56 to 0.53), and functional impairment (d=0.25; 95% CI -0.30 to 0.80) in the message-based treatment condition were noninferior to those in the video-based treatment condition. There were no significant differences in treatment credibility (d=-0.09; 95% CI -0.64 to 0.45), therapeutic alliance (d=-0.15; 95% CI -0.75 to 0.44), or engagement (d=0.24; 95% CI -0.20 to 0.67) between the 2 treatment conditions. CONCLUSIONS: Message-based psychotherapy could present an effective and accessible alternative treatment modality for patients who might not be able to engage in traditional scheduled services such as face-to-face or video-based psychotherapy. TRIAL REGISTRATION: ClinicalTrials.gov NCT05467787; https://www.clinicaltrials.gov/ct2/show/NCT05467787.

An Integrative Engagement Model of Digital Psychotherapy: Exploratory Focus Group Findings.

BACKGROUND: Digital mental health interventions, such as 2-way and asynchronous messaging therapy, are a growing part of the mental health care treatment ecosystem, yet little is known about how users engage with these interventions over the course of their treatment journeys. User engagement, or client behaviors and therapeutic relationships that facilitate positive treatment outcomes, is a necessary condition for the effectiveness of any digital treatment. Developing a better understanding of the factors that impact user engagement can impact the overall effectiveness of digital psychotherapy. Mapping the user experience in digital therapy may be facilitated by integrating theories from several fields. Specifically, health science's Health Action Process Approach and human-computer interaction's Lived Informatics Model may be usefully synthesized with relational constructs from psychotherapy process-outcome research to identify the determinants of engagement in digital messaging therapy. OBJECTIVE: This study aims to capture insights into digital therapy users' engagement patterns through a qualitative analysis of focus group sessions. We aimed to synthesize emergent intrapersonal and relational determinants of engagement into an integrative framework of engagement in digital therapy. METHODS: A total of 24 focus group participants were recruited to participate in 1 of 5 synchronous focus group sessions held between October and November 2021. Participant responses were coded by 2 researchers using thematic analysis. RESULTS: Coders identified 10 relevant constructs and 24 subconstructs that can collectively account for users' engagement and experience trajectories in the context of digital therapy. Although users' engagement trajectories in digital therapy varied widely, they were principally informed by intrapsychic factors (eg, self-efficacy and outcome expectancy), interpersonal factors (eg, the therapeutic alliance and its rupture), and external factors (eg, treatment costs and social support). These constructs were organized into a proposed Integrative Engagement Model of Digital Psychotherapy. Notably, every participant in the focus groups indicated that their ability to connect with their therapist was among the most important factors that were considered in continuing or terminating treatment. CONCLUSIONS: Engagement in messaging therapy may be usefully approached through an interdisciplinary lens, linking constructs from health science, human-computer interaction studies, and clinical science in an integrative engagement framework. Taken together, our results suggest that users may not view the digital psychotherapy platform itself as a treatment so much as a means of gaining access to a helping provider, that is, users did not see themselves as engaging with a platform but instead viewed their experience as a healing relationship. The findings of this study suggest that a better understanding of user engagement is crucial for enhancing the effectiveness of digital mental health interventions, and future research should continue to explore the underlying factors that contribute to engagement in digital mental health interventions. TRIAL REGISTRATION: ClinicalTrials.gov NCT04507360; https://clinicaltrials.gov/ct2/show/NCT04507360.

Participant retention in a fully remote trial of digital psychotherapy: Comparison of incentive types.

Numerous studies have found that long term retention is very low in remote clinical studies (>4 weeks) and to date there is limited information on the best methods to ensure retention. The ability to retain participants in the completion of key assessments periods is critical to all clinical research, and to date little is known as to what methods are best to encourage participant retention. To study incentive-based retention methods we randomized 215 US adults (18+ years) who agreed to participate in a sequential, multiple assignment randomized trial to either high monetary incentive (HMI, $125 USD) and combined low monetary incentive ($75 USD) plus alternative incentive (LMAI). Participants were asked to complete daily and weekly surveys for a total of 12 weeks, which included a tailoring assessment around week 5 to determine who should be stepped up and rerandomized to one of two augmentation conditions. Key assessment points were weeks 5 and 12. There was no difference in participant retention at week 5 (tailoring event), with approximately 75% of the sample completing the week-5 survey. By week 10, the HMI condition retained approximately 70% of the sample, compared to 60% of the LMAI group. By week 12, all differences were attenuated. Differences in completed measures were not significant between groups. At the end of the study, participants were asked the impressions of the incentive condition they were assigned and asked for suggestions for improving engagement. There were no significant differences between conditions on ratings of the fairness of compensation, study satisfaction, or study burden, but study burden, intrinsic motivation and incentive fairness did influence participation. Men were also more likely to drop out of the study than women. Qualitative analysis from both groups found the following engagement suggestions: desire for feedback on survey responses and an interest in automated sharing of individual survey responses with study therapists to assist in treatment. Participants in the LMAI arm indicated that the alternative incentives were engaging and motivating. In sum, while we were able to increase engagement above what is typical for such study, more research is needed to truly improve long term retention in remote trials.

Behavioral Activation, Depression, and Promotion of Health Behaviors: A Scoping Review.

Diverse approaches to the treatment of depressive disorders are necessary to improve evidence-based practice and maximize treatment outcomes. As a result, a range of behaviors and other factors associated with the onset and course of depressive disorders should be examined more comprehensively. Behavioral activation (BA) is a treatment approach to these disorders that can be tailored to address certain health behaviors within the context of depression in an attempt to promote health behaviors whose adoption and maintenance can prove complementary in the treatment of depression. We conducted a scoping review of published studies in which BA-based interventions were used to promote certain health behaviors in individuals with depression. Our search of Medline and the Web of Science identified 336 potential candidate studies. Following screening and with the application of inclusion and exclusion criteria to isolate potentially eligible full-text records, we ultimately identified and evaluated 20 papers that report the nature and efficacy of these modified interventions. Across various domains, including substance use, exercise, medication adherence, and occupational and social success, we found evidence that many-but not all-of the studies we reviewed demonstrated that BA-based interventions were efficacious in promoting the health behavior of interest as well as reducing depressive symptomatology in participants. Implications for more widespread dissemination of such interventions, especially via mobile and web-based platforms due to their accessibility and affordability, are discussed. More research on the feasibility and efficacy of BA-based interventions tailored toward various determinants of health behavior and comorbidities of depressive disorders is warranted.