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Digital therapeutics (DTx) have attracted attention as the substitutes or add-ons to conventional pharmacotherapy. The number of clinical trials for DTx has increased recently, and one of the main targets for DTx is psychiatric disorders. Generalized anxiety disorder (GAD) is one of the most common and notable psychiatric disorders, and it's known that the magnitude of placebo effect in the pharmacotherapy is quite large. The randomized controlled trials (RCTs) with digital placebos are the most reliable clinical trials to evaluate the safety and efficacy of DTx. However, the magnitude of the digital placebo effect and its moderators on GAD have not been investigated, although they are critical to assess the true treatment effect of DTx. The objectives of this study were to identify RCTs with digital placebos as comparators that evaluated GAD assessment scores, to review the characteristics of the RCTs and of the digital placebos in the systematic review, and to investigate the magnitude and its moderators in the meta-analysis. The RCTs evaluating the GAD assessment scores by setting digital placebos as comparators were identified by searching the database of PubMed, Web of Science, and Scopus in July 2024. The characteristics of the RCTs and of the digital placebos were reviewed systematically. The meta-analysis, including subgroup analyses and meta-regressions, was conducted to investigate the magnitude and its moderators of the digital placebos. A total of 54 RCTs were included in the systematic review and 32 RCTs with 3 GAD assessment scores were included in the meta-analysis with a total of 5311 participants. The magnitude of digital placebos for all the included studies was small to moderate (Hedges g=0.28, 95% CI 0.18-0.38). The subgroup analyses showed the significant difference in the magnitude among target population (P=.03), placebo approach (P=.02), and baseline values (P=.02). The meta-regressions also indicated that the primary psychiatric patients in the target population (P=.01), \"Removed\" type in placebo approach (P=.04) and high baseline values (P =.02) were moderators for the magnitude of digital placebos. This study showed the small-to-moderate and statistically significant digital placebo effect on GAD assessment scores. Target population, placebo approach, and baseline values were also identified as the moderators of the placebo effect. It would be effective to create the study protocols for the DTx trials with digital placebos by considering the moderators identified in this study.

Cognitive behavioral therapy for insomnia (CBT-I) has proven to be an effective treatment; however, its accessibility is limited. To address this issue, digital therapeutics for insomnia (DTx-Is), which are software-driven interventions designed to treat insomnia based on CBT-I, have emerged as a potential solution to enhance access. This study aimed to verify the efficacy and safety of WELT-I, a DTx-I. Due to the impact of the global pandemic during the study period, we thought that a decentralized clinical trial (DCT) design that does not require visits to institutions would be appropriate for a clinical study of a digital therapeutic for patients with insomnia. Thus, we also examined the potential of the DCT design as an effective method for validating DTx-Is. A double-blind, sham-controlled randomized DCT was conducted with participants who met the diagnostic criteria for insomnia. Participants were recruited through advertisements posted on an open-access website. WELT-I is a DTx-I based on CBT-I. A sham app was engineered to mirror WELT-I's installation, login, user engagement, and content delivery processes while maintaining double-blind protocols. After randomization, participants were asked to use WELT-I or the sham app for 6 weeks. All treatment processes were fully automated. Sleep parameters were measured through an app-based sleep diary. Self-report questionnaires on sleep, depression, and anxiety were administered via the app at baseline and the end of the study. The primary outcome was sleep efficiency. To investigate the feasibility of the DCT design, compliance, retention rate, participant satisfaction, and time to reach the recruitment goal were evaluated. A total of 89 participants provided consent and underwent screening, and 68 participants were randomly assigned to the WELT-I group (n=33) or control group (n=35). Among them, 14 participants discontinued the trial, leaving 54 participants who completed the study and were included in the final analysis (28 in the WELT-I group and 26 in the control group). WELT-I significantly improved sleep efficiency (least-squares difference=8.28; P=.04) and dysfunctional beliefs about sleep (least-squares difference=-1.03; P=.008) compared with the sham app. The study completed recruitment in 73 days, and the compliance rate was 95% (186/196) in the WELT-I group and 91% (165/182) in the control group. Moreover, the retention rate was 82% (23/28), and the average satisfaction score was 7.2 out of 10. WELT-I showed significant therapeutic efficacy and safety in improving sleep efficiency and sleep-related dysfunctional attitudes in cases of insomnia. In addition, this study demonstrated the feasibility of DCTs, and the findings of rapid recruitment, high compliance and retention rates, and strong participant satisfaction suggest that DCTs have sufficient potential to be expanded to clinical studies verifying the efficacy of other DTx-Is in the future.

Depression and anxiety have become increasingly prevalent across the globe. The rising need for treatment and the lack of clinicians has resulted in prolonged waiting times for patients to receive their first session. Responding to this gap, digital mental health interventions (DMHIs) have been found effective in treating depression and anxiety and are potentially promising pretreatments for patients who are awaiting face-to-face psychotherapy. Nevertheless, whether digital interventions effectively alleviate symptoms for patients on waiting lists for face-to-face psychotherapy remains unclear. This review aimed to synthesize the effectiveness of DMHIs for relieving depression and anxiety symptoms of patients on waiting lists for face-to-face therapy. This review also investigated the features, perceived credibility, and usability of DMHIs during waiting times. In this systematic review, we searched PubMed, PsycINFO, Cochrane, and Web of Science for research studies investigating the effectiveness of DMHIs in reducing either depression or anxiety symptoms among individuals waiting for face-to-face psychotherapy. The search was conducted in June 2024, and we have included the studies that met the inclusion criteria and were published before June 6, 2024. Of the 9267 unique records identified, 8 studies met the eligibility criteria and were included in the systematic review. Five studies were randomized controlled trials (RCTs), and 3 studies were not. Among the RCTs, we found that digital interventions reduced depression and anxiety symptoms, but the majority of interventions were not more effective compared to the control groups where participants simply waited or received a self-help book. For the non-RCTs, the interventions also reduced symptoms, but without control groups, the interpretation of the findings is limited. Finally, participants in the included studies perceived the digital interventions to be credible and useful, but high dropout rates raised concerns about treatment adherence. Due to the lack of effective interventions among the reviewed studies, especially among the RCTs, our results suggest that waiting list DMHIs are not more effective compared to simply waiting or using a self-help book. However, more high-quality RCTs with larger sample sizes are warranted in order to draw a more robust conclusion. Additionally, as this review revealed concerns regarding the high dropout rate in digital interventions, future studies could perhaps adopt more personalized and human-centered functions in interventions to increase user engagement, with the potential to increase treatment adherence and effectiveness.

Research typically shows a higher preference for professionally led face-to-face mental health interventions over digital ones. It remains unclear in which circumstances digital self-help tools are preferred. To address this gap, it is important to examine user characteristics that may help predict when digital interventions are more desirable, ultimately guiding their design to enhance engagement and appeal. This study aims to examine how distress severity and capacity to invest effort relate to intervention preferences, using an ecological assessment of individuals seeking to receive feedback on their mental health. A comprehensive digital mental health screening tool with automated feedback was developed and advertised on social media. The sample comprised 684 adult participants aged 18 to 82 years who opted to complete the screening to receive feedback on their mental health state. Participants completed questionnaires measuring general psychological distress, depression, generalized anxiety, and demographics. The Kessler Psychological Distress Scale-6 was used as the primary measure for distress. Participants were also presented with questions measuring capacity to invest effort and preferences for a professional therapist versus digital self-help tools and for psychotherapy versus a mobile app. The effectiveness of distress, capacity to invest effort, and background characteristics in predicting preferences (a professional vs digital self-help tools; psychotherapy vs a mobile app) was examined using hierarchical linear regressions. The distributions of dichotomized preferences were plotted against distress and capacity to invest effort for transparent visualization. A hierarchical linear regression found that distress, capacity to invest, and currently being in psychotherapy significantly predicted preference for a professional versus digital self-help tools. Distress (β=.25, 95% CI .18-.32; P<.001) and capacity to invest effort (β=.23, 95% CI .16-.30; P<.001) were the strongest predictors, with similar effect size. The model explained 20% of the variance in preference, with the capacity to invest effort uniquely contributing 5%. Most participants experiencing distress with low capacity (158/239, 66.1%) preferred digital self-help tools, whereas most participants experiencing distress with high capacity (147/243, 60.5%) favored a professional. Similar results were obtained when using the Patient Health Questionnaire-4 as an alternative distress measure. Capacity to invest effort remained significant (β=.18, 95% CI .10-.26; P<.001) when predicting a preference for psychotherapy versus a mobile app, while distress was not significant (β=-.03, 95% CI -.10 to .05; P=.51). This study highlights that the preference for digital interventions is driven by a reduced capacity to invest effort in an intervention. Attempts to reduce the mental health treatment gap through digital interventions should focus on optimizing the effort elicited by users to improve desirability and engagement.

Anxiety is one of the most common mental health problems experienced by children worldwide. In the United Kingdom, many children experiencing anxiety do not receive adequate or timely help. Children living in economically disadvantaged areas experience more mental health problems than those living in high-income areas and are less able to engage in activities that can have a positive or protective impact on their mental health. The need for providing low-cost, accessible, and engaging mental health interventions for children living in these areas is high. The study aimed to explore how a digital mental health therapeutic, \"Lumi Nova: Tales of Courage\" (BfB Labs Ltd), could be used to support children living with anxiety in economically disadvantaged areas. A mixed method study design was used to explore the implementation of Lumi Nova using a supported delivery model with mental health teams based in the North of England. Quantitative data collection on recruitment and engagement patterns were collected and analyzed. Qualitative research explored children's, parents', and practitioners' views and experiences with the Lumi Nova app. 113 children consented to use Lumi Nova and 98 (87%) accessed the intervention at least once. Qualitative semistructured interviews found that children, their parents, and practitioners viewed the Lumi Nova app positively. Quantitative analysis of the recruitment data suggested the feasibility of a future larger roll-out. Analysis of usage data demonstrated varied patterns of engagement with the intervention. The frequency and duration of usage varied across children, as did the activities completed within the game: almost half (49%) completed 3 in-game challenges, indicating progression through the treatment pathway. The study demonstrated that a digital mental health intervention could be successfully deployed within economically disadvantaged areas in the United Kingdom to support children experiencing anxiety. Expected barriers to the deployment of digital mental health interventions in economically disadvantaged areas (eg, lack of access to smartphones, data plans, and lack of technical skills) were not reported. Digital mental health interventions have the potential to address current gaps in mental health provision for disadvantaged individuals and communities.

Digital mental health technologies (DMHTs) are playing an increasing role in mental health services. The quality of evidence for DMHTs is variable, and there are concerns that evidence is not sufficient to support decision-making. This study used a cross-sectional analysis of evidence supporting DMHTs included in National Institute for Health and Care Excellence (NICE) evaluations to examine the strength of evidence available for decision-making. We identified all NICE evaluations relating to DMHTs by reviewing details of published NICE evaluations on the NICE website. From each of these evaluations, we identified included DMHTs and reviewed committee documentation to identify studies that provided supporting evidence for each of these technologies. We extracted information on a series of items relating to study quality and summarized the characteristics of evidence both at the level of individual studies and across the package of evidence from multiple studies supporting DMHTs. We also identified key evidence gaps in available evidence. We included nine NICE evaluations relating to anxiety, depression, psychosis, insomnia, attention deficit hyperactivity disorder (ADHD), and tic disorders. These evaluations included 30 DMHTs and referenced 78 supporting studies. We identified common evidence gaps relating to effectiveness compared to relevant comparators, use of appropriate outcomes, including health-related quality of life, cost of delivery, and impact on resource use, and reporting of adverse events. Our study highlights that some DMHTs have been supported by high-quality studies and that evidence to support DMHTs is likely to be developed across a series of studies. However, there are often key evidence gaps that need to be addressed to provide a stronger case for adoption. Developers should ensure that they consider these gaps while planning evidence generation, and where possible, address them earlier in the product lifecycle.

eHealth literacy is an essential skill for pursuing electronic health information, particularly for older people whose health needs increase with age. South Korea is now at the intersection of a rapidly digitalizing society and an increasingly aged population. eHealth literacy enables older people to maximize the effective use of emerging digital technology for their health and quality of life. Understanding the eHealth literacy of Korean older adults is critical to eliminating the gray digital divide and inequity in health information access. This study aims to investigate factors influencing eHealth literacy in older Korean adults and its impact on health outcomes and eHealth use. This was a cross-sectional survey. Community-dwelling older adults 65 years and older in 2 urban cities in South Korea were included. eHealth literacy was measured by the eHealth Literacy Scale. Ordinal logistic regression was used to analyze factors associated with eHealth literacy and multivariate ANOVA for the impact of eHealth literacy on health outcomes and eHealth use. In total, 434 participants were analyzed. A total of 22.3% (97/434) of participants had high eHealth literacy skills. Increasing age, higher monthly income, and time spent on the internet were significantly associated with eHealth literacy (P<.001), and social media users were 3.97 times (adjusted odds ratio 3.97, 95% CI 1.02-15.43; P=.04) more likely to have higher skill. Higher eHealth literacy was associated with better self-perceived health and frequent use of digital technologies for accessing health and care services (P<.001). Disparity in socioeconomic status and engagement on the internet and social media can result in different levels of eHealth literacy skills, which can have consequential impacts on health outcomes and eHealth use. Tailored eHealth interventions, grounded on the social and digital determinants of eHealth literacy, could facilitate eHealth information access among older adults and foster a digitally inclusive healthy aging community.

Internet-based interventions for depression are increasingly integrated into health care due to their effectiveness, availability, and cost-effectiveness. However, negative effects have largely been ignored. This study aimed to evaluate both positive and negative effects of an unguided intervention. In total, 303 participants were analyzed using mixed models for repeated measures to assess changes in depressive symptoms via Beck Depression Inventory-II (primary outcome) after 12 weeks compared to waitlist controls with care as usual. Secondary endpoints included depressive symptoms (Patient Health Questionnaire-9 [PHQ-9]), self-esteem, and quality of life. Negative effects were evaluated using the positive and negative effects of psychotherapy scale for internet-based interventions (PANEPS-I). Moderation analyses were conducted to explore influential effects on treatment outcomes. The intervention group showed greater reduction in depressive symptoms compared to controls, with small to medium effect sizes (g=0.30-0.42) with averaged 14 logins. Although improvements in self-esteem and quality of life were not observed in intention-to-treat analyses, the completer sample indicated higher self-esteem in the intervention group. Negative effects were reported by 22% (22/100) to 68% (66/97), with the highest rates for program-related effects (eg, not addressing personal problems). No moderation effects were identified. The intervention effectively reduces depressive symptoms. Although negative effects were present, they did not impact treatment outcome, tentatively suggesting that overall benefits may outweigh the negative effects for users.

Major depressive disorder is a common diagnosis among adolescents. Cognitive behavioral therapy is recommended as the first line of treatment. Digital health interventions, such as apps, could contribute to treatment. Advantages could be easy accessibility and availability, reduced time for face-to-face therapy, and the ability to intensify therapy by incorporating it into the patients' everyday lives. Challenges such as low adherence rates are common in digital health interventions. Therefore, they need to undergo rigorous testing for feasibility and effectiveness. An evaluated, cognitive behavioral therapy-based face-to-face therapy program for depression in adolescents was transformed into an app called e-MICHI. This study examined its feasibility and efficacy for use in blended therapy in outpatient settings. Adolescents aged 12 to 18 years with major depressive disorder receiving outpatient care were recruited from 2 university hospitals (n=36 included in analysis). The e-MICHI intervention combined daily app engagement over 6 weeks with 3 face-to-face sessions with a therapist. Feasibility was measured using various variables, including an adherence score (0=no or little patient engagement to 3=excellent engagement) and engagement rates (number of modules completed, number of messages sent by participants via the in-app messenger), satisfaction ratings from both participants and therapists, as well as participants' ratings of the usefulness of the antidepressant strategies covered in the app and the transfer of these strategies to everyday practice. Trends of efficacy were evaluated from multiple perspectives (participant self-rating, independent rater, or therapist), using the Beck Depression Inventory-II, the Children's Depression Rating Scale-Revised, and the Clinical Global Impressions-Severity Scale. Feasibility metrics were assessed by analyzing their central tendency and dispersion, efficacy data were analyzed using a repeated measures ANOVA. e-MICHI was positively evaluated by both participants and therapists (participants: mean 7.3, SD 1.2 and therapists: mean 7.3, SD 1.1, on a scale from 0=bad to 10=excellent). Participants demonstrated high adherence rates (nearly 80%, n=25, received a \"good\" or \"excellent\" adherence score) and showed overall good engagement (app modules completed [maximum 6]: mean 5.03, SD 1.27 and messages sent via messenger: mean 23, SD 22.1). Participants rated the psychoeducational content of the app as particularly useful and reported consistent practice of the e-MICHI strategies in everyday life. Use of the app was associated with a significant reduction of depressive symptoms (before app use vs 3-month follow-up, Beck Depression Inventory-II: mean -6.76, SD 11.49, P=.01; Children's Depression Rating Scale-Revised: mean -16.45, SD 16.76, P<.001; Clinical Global Impressions-Severity Scale: mean -1.1, SD 1.24, P<.001). While acknowledging its limitations, such as the small number of participants and the limited validity concerning efficacy, this study confirms the feasibility of e-MICHI for treating adolescent depression in outpatient settings.

People with disabilities need rehabilitation interventions to improve their physical functioning, mental status, and quality of life. Many rehabilitation interventions can be delivered electronically (\"digitally\") via telehealth systems. For people with disabilities in underserved areas, electronically delivered rehabilitation interventions may be the only feasible service available for them. The objective of this study was to evaluate the current status of digital interventions for people with disabilities in remote and underserved areas. A systematic review was conducted on this topic. Keyword searches in multiple databases (PubMed, CINAHL, and Inspec) were performed to collect articles published in this field. The obtained articles were selected based on our selection criteria. Of the 198 identified articles, 16 duplicates were removed. After a review of the titles and abstracts of the remaining articles, 165 were determined to be irrelevant to this study and were therefore removed. The full texts of the remaining 17 articles were reviewed, and 6 of these articles were removed as being irrelevant to this study. The 11 articles remaining were discussed and summarized by 2 reviewers. These 11 studies cover a few types of disabilities, such as developmental disabilities and mobility impairments as well as several types of disability-causing disorders such as stroke, multiple sclerosis, traumatic brain injury, and facio-scapulo-humeral muscular dystrophy. Most of these studies were small-scale case studies and relatively larger-scale cohort studies; the project evaluation methods were mainly pre-post comparison, questionnaires, and interviews. A few studies also performed objective assessment of functional improvement. The intervention technology was mainly videoconferencing. Moreover, 10 of these studies were for people with disabilities in rural areas and 1 was for people in urban communities. A small number of small-scale studies have been conducted on digital interventions for people with disabilities in underserved areas. Although the results reported in these studies were mostly positive, they are not sufficient to prove the effectiveness of telehealth-based digital intervention in improving the situation among people with disabilities because of the small sample sizes and lack of randomized controlled trials.