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Background: Blended care therapy models are intended to increase the efficiency and effectiveness of evidence-based psychotherapy by combining synchronous and asynchronous components of care., Objective: This retrospective cohort study evaluated the clinical effects of synchronous video therapy sessions and asynchronous guided practice session elements on anxiety and depression in a blended care therapy program, with a novel focus on asynchronous provider feedback messages., Methods: Participants were adults (N=33,492) with clinical symptoms of anxiety (Generalized Anxiety Disorder 7-item scale [GAD-7] score of ≥8) and depression (Patient Health Questionnaire 9-item scale [PHQ-9] score of ≥10) at intake. Symptom trajectories were evaluated via individual growth curve models. Time-varying covariates evaluated effects of synchronous video session attendance and the presence or absence of each asynchronous guided practice session element occurring within 7 days and 8-14 days prior to each clinical outcome assessment. Guided practice session elements included client digital lesson completion, client digital exercise completion, and feedback messages sent by providers., Results: Approximately 86.6% (29,012/33,492) of clients met criteria for clinical improvement by end of care (median 6, IQR 4-8 synchronous sessions). Synchronous video session attendance and client digital lesson completion in the past 7 days and in the past 8-14 days were each uniquely and significantly associated with lower GAD-7 scores (video session effects: b session7 =-0.82, b session8-14 =-0.58, P values<.001; digital lesson effects: b lesson7 =-0.18, b lesson8-14 =-0.26, P values <.001) and PHQ-9 scores (video session effects: b session7 =-0.89, b session8-14 =-0.67, P values <.001; digital lesson effects: b lesson7 =-0.12, b lesson8-14 =-0.30, P values <.001). Client digital exercise completion in the past 8-14 days was significantly associated with lower GAD-7 scores (b exercise8-14 =-0.10; P<.001) but exercise completion in the 7 days prior to clinical outcome assessment was not (b exercise7 =0.00; P=.89). Exercise completion in the past 7 days was significantly associated with lower PHQ-9 scores (b exercise7 =-0.16; P<.001) but exercise completion in the past 8-14 days was not (b exercise8-14 =-0.05; P=.09). Provider feedback messaging in the past 7 days and in the past 8-14 days was significantly associated with lower GAD-7 and PHQ-9 scores, respectively (GAD-7: b feedback7 =-0.12, P<.001; b feedback8-14 =-0.07, P=.004; PHQ-9: b feedback7 =-0.15, P<.001; b feedback8-14 =-0.08, P=.01)., Conclusions: Provider feedback between synchronous therapy sessions provided significant benefit for symptom reduction, beyond the effects of client digital engagement and synchronous video sessions. When guided practice sessions are well integrated into care, blended care therapy provides meaningful improvements upon the traditional, synchronous session-only therapy model. Provider guidance and feedback for clients between synchronous sessions support more efficient and effective mental health care overall., (©Hallie M Espel-Huynh, Lu Wang, Emily G Lattie, Robert E Wickham, Alethea Varra, Connie E Chen, Anita Lungu, Jennifer L Lee. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 18.10.2024.)

Background: College students are increasingly reporting common mental health problems, such as depression and anxiety, and they frequently encounter barriers to seeking traditional mental health treatments. Digital mental health interventions, such as those delivered via the Web and apps, offer the potential to improve access to mental health treatment., Objective: This study aimed to review the literature on digital mental health interventions focused on depression, anxiety, and enhancement of psychological well-being among samples of college students to identify the effectiveness, usability, acceptability, uptake, and adoption of such programs., Methods: We conducted a systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines (registration number CRD42018092800), and the search strategy was conducted by a medical research librarian in the following databases: MEDLINE (Ovid), EMBASE (Elsevier), PsycINFO (EbscoHost), the Cochrane Library (Wiley), and Web of Science (Thomson Reuters) from the date of inception to April 2019. Data were synthesized using a systematic narrative synthesis framework, and formal quality assessments were conducted to address the risk of bias., Results: A total of 89 studies met the inclusion criteria. The majority of interventions (71/89, 80%) were delivered via a website, and the most common intervention was internet-based cognitive behavioral therapy (28, 31%). Many programs (33, 37%) featured human support in the form of coaching. The majority of programs were either effective (42, 47%) or partially effective (30, 34%) in producing beneficial changes in the main psychological outcome variables. Approximately half of the studies (45, 51%) did not present any usability or acceptability outcomes, and few studies (4, 4%) examined a broad implementation of digital mental health interventions on college campuses. Quality assessments revealed a moderate-to-severe risk of bias in many of the studies., Conclusions: Results suggest that digital mental health interventions can be effective for improving depression, anxiety, and psychological well-being among college students, but more rigorous studies are needed to ascertain the effective elements of these interventions. Continued research on improving the user experience of, and thus user engagement with, these programs appears vital for the sustainable implementation of digital mental health interventions on college campuses., (©Emily G Lattie, Elizabeth C Adkins, Nathan Winquist, Colleen Stiles-Shields, Q Eileen Wafford, Andrea K Graham. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.07.2019.)

Background: Digital mental health tools have tended to use psychoeducational strategies based on treatment orientations developed and validated outside of digital health. These features do not map well to the brief but frequent ways that people use mobile phones and mobile phone apps today. To address these challenges, we developed a suite of apps for depression and anxiety called IntelliCare, each developed with a focused goal and interactional style. IntelliCare apps prioritize interactive skills training over education and are designed for frequent but short interactions., Objective: The overall objective of this study was to pilot a coach-assisted version of IntelliCare and evaluate its use and efficacy at reducing symptoms of depression and anxiety., Methods: Participants, recruited through a health care system, Web-based and community advertising, and clinical research registries, were included in this single-arm trial if they had elevated symptoms of depression or anxiety. Participants had access to the 14 IntelliCare apps from Google Play and received 8 weeks of coaching on the use of IntelliCare. Coaching included an initial phone call plus 2 or more texts per week over the 8 weeks, with some participants receiving an additional brief phone call. Primary outcomes included the Patient Health Questionnaire-9 (PHQ-9) for depression and the Generalized Anxiety Disorder-7 (GAD-7) for anxiety. Participants were compensated up to US $90 for completing all assessments; compensation was not for app use or treatment engagement., Results: Of the 99 participants who initiated treatment, 90.1% (90/99) completed 8 weeks. Participants showed substantial reductions in the PHQ-9 and GAD-7 (P<.001). Participants used the apps an average of 195.4 (SD 141) times over the 8 weeks. The average length of use was 1.1 (SD 2.1) minutes, and 95% of participants downloaded 5 or more of the IntelliCare apps., Conclusions: This study supports the IntelliCare framework of providing a suite of skills-focused apps that can be used frequently and briefly to reduce symptoms of depression and anxiety. The IntelliCare system is elemental, allowing individual apps to be used or not used based on their effectiveness and utility, and it is eclectic, viewing treatment strategies as elements that can be applied as needed rather than adhering to a singular, overarching, theoretical model., Trial Registration: Clinicaltrials.gov NCT02176226; http://clinicaltrials.gov/ct2/show/NCT02176226 (Archived by WebCite at http://www.webcitation/6mQZuBGk1)., Competing Interests: Conflicts of Interest: None declared., (©David C Mohr, Kathryn Noth Tomasino, Emily G. Lattie, Hannah L Palac, Mary J Kwasny, Kenneth Weingardt, Chris J Karr, Susan M Kaiser, Rebecca C Rossom, Leland R Bardsley, Lauren Caccamo, Colleen Stiles-Shields, Stephen M Schueller. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 05.01.2017.)

BackgroundTreatments for depression and anxiety have several behavioral and psychological targets and rely on varied strategies. Digital mental health treatments often employ feature-rich approaches addressing several targets and strategies. These treatments, often optimized for desktop computer use, are at odds with the ways people use smartphone applications. Smartphone use tends to focus on singular functions with easy navigation to desired tools. The IntelliCare suite of apps was developed to address the discrepancy between need for diverse behavioral strategies and constraints imposed by typical app use. Each app focuses on one strategy for a limited subset of clinical aims all pertinent to depression and anxiety. This study presents the uptake and usage of apps from the IntelliCare suite following an open deployment on a large app marketplace.MethodsThirteen lightweight apps, including 12 interactive apps and one Hub app that coordinates use across those interactive apps, were developed and made free to download on the Google Play store. De-identified app usage data from the first year of IntelliCare suite deployment were analyzed for this study.ResultsIn the first year of public availability, 5,210 individuals downloaded one or more of the IntelliCare apps, for a total of 10,131 downloads. Nearly a third of these individuals (31.8%) downloaded more than one of these apps. The modal number of launches for each of the apps was 1, however the mean number of app launches per app ranged from 3.10 to 16.98, reflecting considerable variability in the use of each app.ConclusionsThe use rate of the IntelliCare suite of apps is higher than public deployments of other comparable digital resources. Our findings suggest that people will use multiple apps and provides support for the concept of app suites as a useful strategy for providing diverse behavioral strategies.

Background: IntelliCare is a modular platform that includes 12 simple apps targeting specific psychological strategies for common mental health problems.Objective: This study aimed to examine the effect of 2 methods of maintaining engagement with the IntelliCare platform, coaching, and receipt of weekly recommendations to try different apps on depression, anxiety, and app use.Methods: A total of 301 participants with depression or anxiety were randomized to 1 of 4 treatments lasting 8 weeks and were followed for 6 months posttreatment. The trial used a 2X2 factorial design (coached vs self-guided treatment and weekly app recommendations vs no recommendations) to compare engagement metrics.Results: The median time to last use of any app during treatment was 56 days (interquartile range 54-57), with 253 participants (84.0%, 253/301) continuing to use the apps over a median of 92 days posttreatment. Receipt of weekly recommendations resulted in a significantly higher number of app use sessions during treatment (overall median=216; P=.04) but only marginal effects for time to last use (P=.06) and number of app downloads (P=.08). Coaching resulted in significantly more app downloads (P<.001), but there were no significant effects for time to last download or number of app sessions (P=.36) or time to last download (P=.08). Participants showed significant reductions in the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) across all treatment arms (P s<.001). Coached treatment led to larger GAD-7 reductions than those observed for self-guided treatment (P=.03), but the effects for the PHQ-9 did not reach significance (P=.06). Significant interaction was observed between receiving recommendations and time for the PHQ-9 (P=.04), but there were no significant effects for GAD-7 (P=.58).Conclusions: IntelliCare produced strong engagement with apps across all treatment arms. Coaching was associated with stronger anxiety outcomes, and receipt of recommendations enhanced depression outcomes.Trial Registration: ClinicalTrials.gov NCT02801877; https://clinicaltrials.gov/ct2/show/NCT02801877. [ABSTRACT FROM AUTHOR]

Digital interventions offer great promise for supporting health-related behavior change. However, there is much that we have yet to learn about how people respond to them. In this study, we present a novel mixed-methods approach to analysis of the complex and rich data that digital interventions collect. We perform secondary analysis of IntelliCare, an intervention in which participants are able to try 14 different mental health apps over the course of eight weeks. The goal of our analysis is to characterize users' app use behavior and experiences, and is rooted in theoretical conceptualizations of engagement as both usage and user experience. In the first aim, we employ cluster analysis to identify subgroups of participants that share similarities in terms of the frequency of their usage of particular apps, and then employ other engagement measures to compare the clusters. We identified four clusters with different app usage patterns: Low Usage, High Usage, Daily Feats Users, and Day to Day users. Each cluster was distinguished by its overall frequency of app use, or the main app that participants used. In the second aim, we developed a computer-assisted text analysis and visualization method - message highlighting - to facilitate comparison of the clusters. Last, we performed a qualitative analysis using participant messages to better understand the mechanisms of change and usability of salient apps from the cluster analysis. Our novel approach, integrating text and visual analytics with more traditional qualitative analysis techniques, can be used to generate insights concerning the behavior and experience of users in digital health contexts, for subsequent personalization and to identify areas for improvement of intervention technologies. [ABSTRACT FROM AUTHOR]

A large number of trials have consistently shown that guided digital mental health treatments (DMHTs) are effective for depression and anxiety. As DMHTs are adopted by healthcare organizations, payers, and employers, they are often considered most appropriate for people with mild-to-moderate levels of symptom severity. Thus, the aim of this study was to examine the effects of symptom severity on depression and anxiety outcomes and app use across three trials of a guided DMHT, IntelliCare. Participants were categorized into mild, moderate, moderately severe, and severe symptom severity groups on depression and anxiety. All symptom severity groups showed significant reductions in depression and anxiety in a clear ordinal pattern, with the mild symptom severity group showing the smallest changes and the severe symptom group showing the largest improvements. Those with the lowest levels of educational attainment showed the largest symptom improvement. Baseline symptom severity was not significantly related to app use. App use was significantly related to depression and anxiety outcomes. These findings suggest that depression and anxiety symptom severity is not useful in determining who should be referred to a guided DMHT. • IntelliCare, a guided digital mental health treatment for depression and anxiety, was effective across three trials at all levels of baseline symptom severity. • There was no evidence that baseline symptom severity, or comorbidity of depression and anxiety affected app use. • Symptom severity alone is not useful in determining who should be referred to a guided digital mental health treatment for depression or anxiety. [ABSTRACT FROM AUTHOR]