Implementation of Cognitive Behavioral Therapy in e-Mental Health Apps: Literature Review

mHealth Applications for Childhood Anxiety Disorders: Current Landscape, Challenges, and Future Directions

Purpose of Review

We review the literature on mHealth applications for childhood anxiety disorders, highlighting current use, limitations, and future directions.

Recent Findings

Although mHealth apps targeting childhood anxiety disorders have recently increased, most have not been evaluated for clinical effectiveness, data security, or quality standards. Many apps do not contain scientifically based content and do not adequately incorporate the principles of exposure-based cognitive behavioral therapy. In addition, many apps have significant deficiencies in age-appropriateness, data security, privacy, cultural sensitivity, and accessibility. Limitations remain in terms of the standards for evaluating apps in pediatric populations.

Summary

While interest in mHealth applications for childhood anxiety disorders is increasing, more research is needed to develop effective, safe, and age-appropriate digital interventions. Priorities include scientific grounding, privacy, equitable access, gamification, and parental involvement. Studies in this direction will increase the quality of applications and strengthen equality in access to mental health services.

mHealth Applications for Childhood Anxiety Disorders: Current Landscape, Challenges, and Future Directions

PURPOSE OF REVIEW

We review the literature on mHealth applications for childhood anxiety disorders, highlighting current use, limitations, and future directions.

RECENT FINDINGS

Although mHealth apps targeting childhood anxiety disorders have recently increased, most have not been evaluated for clinical effectiveness, data security, or quality standards. Many apps do not contain scientifically based content and do not adequately incorporate the principles of exposure-based cognitive behavioral therapy. In addition, many apps have significant deficiencies in age-appropriateness, data security, privacy, cultural sensitivity, and accessibility. Limitations remain in terms of the standards for evaluating apps in pediatric populations. While interest in mHealth applications for childhood anxiety disorders is increasing, more research is needed to develop effective, safe, and age-appropriate digital interventions. Priorities include scientific grounding, privacy, equitable access, gamification, and parental involvement. Studies in this direction will increase the quality of applications and strengthen equality in access to mental health services.

Could the use of web-based applications assist in neuropsychiatric treatment? An umbrella review

BACKGROUND

The aim of this study was to evaluate the use of applications accessed through internet browsers as tools for neuropsychiatric treatment, as well as to verify the benefits and efficacy of virtual support as a therapeutic approach.

METHODS

A broad review of the MEDLINE (PubMed), SciELE and Cochrane databases for review articles was conducted. Articles involving the use of browser-based applications as a support for neurological and psychiatric treatment, with available texts on the selected platforms with no language or year restrictions, were included.

RESULTS

A total of 83 reviews were included in this study. Due to the homogeneity of the information between some articles, the research was grouped according to the following revised themes: mindfulness, tinnitus, electronic health (eHealth), youth and students' mental health, mobile health applications (mHealth), depression, anxiety and stress, psychoactive substances, sleep quality, chronic diseases and mental disorders.

CONCLUSION

The findings suggest that the use of virtual support through applications helps neuropsychiatric treatment, improving the well-being and quality of life of these patients.

The Effects of Online Cognitive Behavioral Therapy on Postpartum Depression: A Systematic Review and Meta-Analysis

BACKGROUND/OBJECTIVES

Postpartum depression seriously affects the safety and health of mothers and children. Online cognitive behavioral therapy is considered to be a promising treatment; however, whether it is effective at improving postpartum depression is inconsistent and the specific intervention measures are not the same. The objectives of this study were to comprehensively review the effects of online cognitive behavioral therapy on postpartum depression and further explore the specific intervention measures.

METHODS

A literature search was conducted using thirteen electronic databases and two clinical trial registries from the establishment of the databases to 31 December 2023. The study selection and data extraction were independently performed by two researchers. The latest Cochrane Risk of Bias tool was selected to evaluate the quality of the included studies. Data were analyzed using Review Manager 5.4, and the certainty of the evidence was evaluated using the online GRADEpro tool. Eighteen studies involving 3689 women were included.

RESULTS

The results showed that online cognitive behavioral therapy was effective at improving postpartum depression. A subgroup analysis showed that the duration of online cognitive behavioral therapy with total intervention was 9 weeks and above, the total intervention number was 12 times or fewer, and using a website or Zoom online conference room as the intervention platform could more significantly improve postpartum depression. In particular, providing professional guidance could be more effective.

CONCLUSIONS

In summary, online cognitive behavioral therapy was effective for postpartum depression. Furthermore, this study found out how specific intervention measures of online cognitive behavioral therapy could be more effective. Finally, nurses can participate in the therapy to improve access to evidence-based treatment.

Mining User Reviews for Key Design Features in Cognitive Behavioral Therapy-Based Mobile Mental Health Apps

Background: Cognitive behavioral therapy (CBT)-based mobile apps have been shown to improve CBT-based interventions effectiveness. Despite the proliferation of these apps, user-centered guidelines pertaining to their design remain limited. The study aims to identify design features of CBT-based apps using online app reviews. Methods: We used 4- and 5-star reviews, preprocessed the reviews, and represented the reviews using word-level bigrams. Then, we leveraged latent Dirichlet allocation (LDA) and visualization techniques using python library for interactive topic model visualization to analyze the review and identify design features that contribute to the success and effectiveness of the app. Results: A total of 24,902 reviews were analyzed. LDA optimization resulted in 86 topics that were labeled by two independent researchers, with an interrater Cohen's kappa value of 0.86. The labeling and grouping process resulted in a total of six main design features for effective CBT-based mobile apps, namely, mental health management and support, credibility support, self-understanding and personality insights, therapeutic approaches and tools, beneficial rescue sessions, and personal growth and development. Conclusions: The high-level design features identified in this study could evidently serve as the backbone of successful CBT-based mobile apps for mental health.

Young adults' adoption and use of mental health apps: efficient, effective, but no replacement for in-person care

Objective: Millions of people use mobile phone or computer-based applications-apps-to maintain their mental health and connect with treatment providers through text- and video-based chat functions. The present study sought to understand young adults' motivations for adopting this technology using the unified theory of acceptance and use of technology (UTAUT), how they use mental health apps, and the gratifications they receive from using mental health apps. Participants: One hundred-eighteen mental health app users responded to an online survey. Methods: A survey was conducted with students at a Midwestern university. The survey included questions regarding current mental health services, mental health apps used, UTAUT and gratifications survey items. Results: A regression analysis suggested users' performance expectancies, effort expectancies, and facilitating conditions predicted the adoption of mental health apps. Young adults most often use mental health apps for stress relief. While they preferred in-person treatment, users described mental health apps as efficient and helpful. Conclusion: Overall, the results reinforce the sense of optimism for the future of mental health apps, suggesting the potential for apps to supplement-but not necessarily replace-in-person care.

Attitudes and barriers to mobile mental health interventions among first-year college students: a mixed-methods study

OBJECTIVE

This mixed-methods study examined attitudes, barriers, and preferences for mobile mental health interventions among first-year college students.

PARTICIPANTS

351 students (64% women; 51% non-Hispanic White; 66% Heterosexual) from two campuses completed self-report assessments and 10 completed individual semi-structured interviews.

METHODS

Paired t-tests compared attitudes for various mHealth applications and logistic regressions examined sociodemographic and clinical characteristics of mental health app users. Themes, topics, and quotes from interviews were derived through rapid qualitative analysis.

RESULTS

Mental health applications were less used and perceived to be less helpful than other mHealth applications. Past mental health app use was best predicted by past use of formal mental health care.

CONCLUSIONS

Mobile health interventions have significant potential to diversify mental health services for students. Despite limited engagement with these resources, openness to digital interventions among students is quite high. Improving intervention features and increasing problem-recognition to facilitate help-seeking may result in greater uptake.

RegulEm, a smartphone app based on the unified protocol for the transdiagnostic treatment of emotional disorders: description of its application in blended format in a clinical case

Objective

The Spanish national health system (SNHS) faces significant barriers to psychological care, such as long waiting lists and a lack of human resources. In addition, with emotional disorders being the most prevalent disorders worldwide, and less than half of those affected receiving proper treatment, there is an urgent need for new treatment alternatives for this group of disorders. The Unified Protocol (UP) is presented as a possible solution that has amply demonstrated its efficacy in different formats and contexts. Another promising alternative involves the use of blended formats, combining face-to-face UP sessions with a UP-based application. This manuscript focuses on the description of RegulEm, a UP-based application developed following a participatory design approach. In addition, a case example of receiving UP in a blended format in a specialized mental health unit of the SNHS is presented.

Methods

The following components of RegulEm are described: content and exercises of the modules; aesthetics and multimedia-based content; intervention delivery; testimonials section; emotional and motivation assessment; exposure hierarchy for guided in vivo and imaginal exposure; emergency button and Gamification. A case example of a 26-year-old male patient with anxiety and depressive symptoms receiving UP in a blended format in a specialized mental health unit of the SNHS is presented.

Results

The user showed improvements in emotional regulation skills, anxiety, and depressive symptoms over time, though stressors remained. RegulEm allowed independent progress between face-to-face UP sessions, but low internalization of some content emphasized the importance of therapist guidance in face-to-face sessions. User feedback highlighted satisfaction with the intervention but improvement proposals for RegulEm were identified, such as simplifying emotional exposure exercises.

Conclusion

This manuscript describes in detail the first UP-based smartphone application's components and illustrates important implications, such as enabling users to progress at their own pace between sessions and advancing more quickly in the intervention.

Usability of a mobile app for suicide risk awareness in South Korea

Background

Suicide rates have significantly increased in South Korea, yet many individuals lack adequate support. Barriers such as reluctance to seek mental health help and fear of social stigma contribute to this gap. A mobile app focused on suicide risk awareness could provide accessible support, though none are currently available for public use in South Korea. This study conducted a usability test on a newly developed suicide risk awareness app using a mixed methods approach.

Methods

Thirty-eight students from a large university in South Korea participated in the study, with 19 in a high-risk suicide group and 19 in a nonrisk suicide group. After using the app for 2 weeks, all participants completed an online usability survey, and 19 students took part in individual interviews.

Results

Independent samples t-tests showed that participants, regardless of risk group, rated the app positively for ease of use, accessibility, design, perceived learning, and satisfaction. Regression analysis identified perceived learning as the strongest predictor of satisfaction, followed by ease of use. The qualitative analysis highlighted areas for improvement, including providing direct and guided feedback on suicide risk.

Conclusion

The study demonstrated the potential of a mobile app to enhance suicide risk awareness among young adults in South Korea. Moreover, user engagement with the app can be improved by ensuring confidentiality and fostering perceived learning.

Psychotherapy 2.0 - Application context and effectiveness of sensor technology in psychotherapy with children and adolescents: A systematic review

Background

E-mental health applications have been increasingly used in the psychotherapeutic care of patients for several years. State-of-the-art sensor technology could be used to determine digital biomarkers for the diagnosis of mental disorders. Furthermore, by integrating sensors into treatment, relevant contextual information (e.g. field of gaze, stress levels) could be made transparent and improve the treatment of people with mental disorders. An overview of studies on this approach would be useful to provide information about the current status quo.

Methods

A systematic review of the use of sensor technology in psychotherapy for children and adolescents was conducted with the aim of investigating the use and effectiveness of sensory technology in psychotherapy treatment. Five databases were searched for studies ranging from 2000 to 2023. The study was registered by PROSPERO (CRD42023374219), conducted according to Cochrane recommendations and used the PRISMA reporting guideline.

Results

Of the 38.560 hits in the search, only 10 publications met the inclusion criteria, including 3 RCTs and 7 pilot studies with a total of 257 subjects. The study population consisted of children and adolescents aged 6 to 19 years with mental disorders such as OCD, anxiety disorders, PTSD, anorexia nervosa and autistic behavior. The psychotherapy methods investigated were mostly cognitive behavioral therapy (face-to-face contact) with the treatment method of exposure for various disorders. In most cases, ECG, EDA, eye-tracking and movement sensors were used to measure vital parameters. The heterogeneous studies illustrate a variety of potential useful applications of sensor technology in psychotherapy for adolescents. In some studies, the sensors are implemented in a feasible approach to treatment.

Conclusion

Sensors might enrich psychotherapy in different application contexts.However, so far there is still a lack of further randomized controlled clinical studies that provide reliable findings on the effectiveness of sensory therapy in psychotherapy for children and adolescents. This could stimulate the embedding of such technologies into psychotherapeutic process.https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023374219, identifier [CRD42023374219].

Exploring the Role of Mobile Apps for Insomnia in Depression: Systematic Review

BACKGROUND

The COVID-19 pandemic has profoundly affected mental health, leading to an increased prevalence of depression and insomnia. Currently, artificial intelligence (AI) and deep learning have thoroughly transformed health care-related mobile apps, offered more effective mental health support, and alleviated the psychological stress that may have emerged during the pandemic. Early reviews outlined the use of mobile apps for dealing with depression and insomnia separately. However, there is now an urgent need for a systematic evaluation of mobile apps that address both depression and insomnia to reveal new applications and research gaps.

OBJECTIVE

This study aims to systematically review and evaluate mobile apps targeting depression and insomnia, highlighting their features, effectiveness, and gaps in the current research.

METHODS

We systematically searched PubMed, Scopus, and Web of Science for peer-reviewed journal articles published between 2017 and 2023. The inclusion criteria were studies that (1) focused on mobile apps addressing both depression and insomnia, (2) involved young people or adult participants, and (3) provided data on treatment efficacy. Data extraction was independently conducted by 2 reviewers. Title and abstract screening, as well as full-text screening, were completed in duplicate. Data were extracted by a single reviewer and verified by a second reviewer, and risk of bias assessments were completed accordingly.

RESULTS

Of the initial 383 studies we found, 365 were excluded after title, abstract screening, and removal of duplicates. Eventually, 18 full-text articles met our criteria and underwent full-text screening. The analysis revealed that mobile apps related to depression and insomnia were primarily utilized for early detection, assessment, and screening (n=5 studies); counseling and psychological support (n=3 studies); and cognitive behavioral therapy (CBT; n=10 studies). Among the 10 studies related to depression, our findings showed that chatbots demonstrated significant advantages in improving depression symptoms, a promising development in the field. Additionally, 2 studies evaluated the effectiveness of mobile apps as alternative interventions for depression and sleep, further expanding the potential applications of this technology.

CONCLUSIONS

The integration of AI and deep learning into mobile apps, particularly chatbots, is a promising avenue for personalized mental health support. Through innovative features, such as early detection, assessment, counseling, and CBT, these apps significantly contribute toward improving sleep quality and addressing depression. The reviewed chatbots leveraged advanced technologies, including natural language processing, machine learning, and generative dialog, to provide intelligent and autonomous interactions. Compared with traditional face-to-face therapies, their feasibility, acceptability, and potential efficacy highlight their user-friendly, cost-effective, and accessible nature with the aim of enhancing sleep and mental health outcomes.

Examining the Effects of Cognitive Behavioral Therapy With a Virtual Agent on User Motivation and Improvement in Psychological Distress and Anxiety: Two-Session Experimental Study

BACKGROUND

Cognitive behavioral therapy (CBT) is a valuable treatment for mood disorders and anxiety. CBT methods, such as cognitive restructuring, are employed to change automatic negative thoughts to more realistic ones.

OBJECTIVE

This study extends on previous research conducted by the authors, focused on the process of correcting automatic negative thoughts to realistic ones and reducing distress and anxiety via CBT with a virtual agent. It was aimed to investigate whether the previously applied virtual agent would achieve changes in automatic negative thoughts when modifications to the previous experimental paradigm are applied and when user motivation is taken into consideration. Furthermore, the potential effects of existing participant knowledge concerning CBT or automatic thoughts were explored.

METHODS

A single-group, 2-session experiment was conducted using a within-group design. The study recruited 35 participants from May 15, 2023, to June 2, 2023, via Inter Group Corporation, with data collection following from June 5 to June 20, 2023, at Nara Institute of Science and Technology, Japan. There were 19 male and 16 female participants (age range: 18-50 years; mean 33.66, SD 10.77 years). Participants answered multiple questionnaires covering depressive symptomatology and other cognitive variables before and after a CBT session. CBT was carried out using a virtual agent, who participants conversed with using a CBT dialogue scenario on the topic of automatic negative thoughts. Session 2 of the experiment took place 1 week after session 1. Changes in distress and state anxiety were analyzed using a Wilcoxon signed-rank test and t-test for paired samples. The relationships of motivation with cognitive changes and distress or anxiety changes were investigated via correlation analysis. Multiple linear regression was used to analyze the potential predictive qualities of previous knowledge of CBT and automatic negative thoughts regarding outcome measures.

RESULTS

Significant reductions in distress (all P<.001) and state anxiety (all P<.003) emerged throughout the first and second experimental sessions. The CBT intervention increased participants' recognition of their negative thinking and their intention to change it, namely their motivation to change it. However, no clear correlations of motivation with changes in distress or anxiety were found (all P>.04). Participants reported moderate subjective changes in their cognition, which were in part positively correlated with their motivation (all P<.007). Lastly, existing knowledge of CBT did not predict reductions in distress during the first session of the experiment (P=.02).

CONCLUSIONS

CBT using a virtual agent and a CBT dialogue scenario was successful in reducing distress and anxiety when talking about automatic negative thoughts. The promotion of client motivation needs to be critically considered when designing interventions using CBT with a virtual agent, and further experimental investigations on the causal influences between motivation and outcome measures need to be conducted.

Design, Implementation and Evaluation of a Health Promotion Program for Family Caregivers of Chronic Mental Disorders: A Mixed Methods Study

Family caregivers of patients with chronic mental disorders who are responsible for taking care of the patient face many problems that can endanger the psychosocial health of these people. This study was conducted to develop, implement, and evaluate a psychosocial health promotion program for family caregivers of patients with chronic mental disorders. This research is an exploratory sequential mixed-method study conducted using a qualitative-quantitative design. A qualitative study was conducted to explain the needs and psychosocial problems and the solution to improve the psychosocial health of family caregivers of patients with chronic mental disorders in two psychiatric care centers in Isfahan were conducted. Then the program was written based on Kern's programming development approach. In the quantitative stage, a part of the developed program was implemented as virtual group psychoeducation for 67 caregivers, and its impact on caregivers' burden of care was evaluated. The findings from the qualitative phase of the study led to the emergence of 3 main categories and the findings from the quantitative phase of the study indicated that the implementation of the compiled program causes a significant reduction in the burden of care in family caregivers of chronically mentally ill patients (p<0.05). The current program was prepared and developed using an evidence-based approach. Policymakers and members of the mental health team can take a valuable step toward reducing the care burden of family caregivers of chronic mental patients by using the content of the developed mental health promotion program.

Current state and practical recommendations on reproductive mental health: a narrative review

Emotional disorders (EDs) are highly prevalent during the reproductive period, including pregnancy, postpartum, and women undergoing fertility treatments. International guidelines are increasingly suggesting the need to evaluate, prevent, and treat EDs in those women. The main aim of this narrative review is to summarize current practice in the field of EDs management during fertility treatments, pregnancy, and the postpartum and to propose a new technology-based model of care that helps to provide psychological care to all women who are in these periods. Four different databases (Pubmed, Scopus, Science Direct, Web of Science) were consulted. Selected keywords were related with infertility, pregnancy, postpartum, EDs, assessment, prevention, treatment, and technologies. We identified 1603 studies and 43 were included in this review. According to these studies, different face-to-face protocols already exist to manage EDs in women undergoing fertility treatments, pregnant or at the postpartum. We noticed an increased interest in developing technology-based solutions to overcome the limitations of traditional mental healthcare services. However, we also detected some issues in the use of technologies (i.e. increased attention to the postpartum or the lack of transdiagnostic approaches). Our results evidenced that there is still a need to develop modern, well-designed, and conceptually-relevant ICT-based programs to be used in women undergoing fertility treatments, pregnant or at the postpartum.

The effectiveness of e-mental health interventions on stress, anxiety, and depression among healthcare professionals: a systematic review and meta-analysis

BACKGROUND

Many healthcare professionals are experiencing psychological distress. Electronic mental health (e-mental health) interventions are convenient and multifunctional. This review aimed to examine the effectiveness of e-mental health interventions in enhancing the well-being of healthcare professionals and to identify moderating factors.

METHODS

A comprehensive and systematic retrieval of randomized controlled trial (RCT) studies was conducted across eight databases. Population, intervention, comparison, and outcome (PICO) were used to define eligibility criteria. Stress, anxiety, and depression were included as the main outcomes. The overall effect was calculated based on the random effect model, and the effect size was presented using the standardized mean difference. The characteristics of the research design, intervention object, and intervention design were further selected as potential moderating factors for subgroup analysis. Meta-regression analyses were finally performed, incorporating intervention duration and sample size as independent variables.

RESULTS

A total of 20 studies were included in the systematic review, and 17 were included in the meta-analysis. A large effect on relieving stress and anxiety and a small-to-medium effect on reducing depression were observed. Subgroup analyses showed that features including mindfulness approaches, online courses, computer use, group interventions, and professional guidance were more favorable in the design of services. Meta-regression revealed that intervention duration only affected anxiety symptoms. Caution should be exercised, as some subgroups had fewer studies and higher heterogeneity. For the secondary outcomes, a large effect on emotional exhaustion and a small-to-medium effect on well-being were observed.

CONCLUSION

In general, e-mental health interventions significantly improve the psychological health of healthcare staff. Future high-quality, large-scale studies targeting healthcare professionals and specific intervention scenarios are warranted.

Introduction to Large Language Models (LLMs) for dementia care and research

Introduction

Dementia is a progressive neurodegenerative disorder that affects cognitive abilities including memory, reasoning, and communication skills, leading to gradual decline in daily activities and social engagement. In light of the recent advent of Large Language Models (LLMs) such as ChatGPT, this paper aims to thoroughly analyse their potential applications and usefulness in dementia care and research.

Method

To this end, we offer an introduction into LLMs, outlining the key features, capabilities, limitations, potential risks, and practical considerations for deployment as easy-to-use software (e.g., smartphone apps). We then explore various domains related to dementia, identifying opportunities for LLMs to enhance understanding, diagnostics, and treatment, with a broader emphasis on improving patient care. For each domain, the specific contributions of LLMs are examined, such as their ability to engage users in meaningful conversations, deliver personalized support, and offer cognitive enrichment. Potential benefits encompass improved social interaction, enhanced cognitive functioning, increased emotional well-being, and reduced caregiver burden. The deployment of LLMs in caregiving frameworks also raises a number of concerns and considerations. These include privacy and safety concerns, the need for empirical validation, user-centered design, adaptation to the user's unique needs, and the integration of multimodal inputs to create more immersive and personalized experiences. Additionally, ethical guidelines and privacy protocols must be established to ensure responsible and ethical deployment of LLMs.

Results

We report the results on a questionnaire filled in by people with dementia (PwD) and their supporters wherein we surveyed the usefulness of different application scenarios of LLMs as well as the features that LLM-powered apps should have. Both PwD and supporters were largely positive regarding the prospect of LLMs in care, although concerns were raised regarding bias, data privacy and transparency.

Discussion

Overall, this review corroborates the promising utilization of LLMs to positively impact dementia care by boosting cognitive abilities, enriching social interaction, and supporting caregivers. The findings underscore the importance of further research and development in this field to fully harness the benefits of LLMs and maximize their potential for improving the lives of individuals living with dementia.

Diversity, equity and inclusion considerations in mental health apps for young people: protocol for a scoping review

INTRODUCTION

After COVID-19, a global mental health crisis affects young people, with one in five youth experiencing mental health problems worldwide. Delivering mental health interventions via mobile devices is a promising strategy to address the treatment gap. Mental health apps are effective for adolescent and young adult samples, but face challenges such as low real-world reach and under-representation of minoritised youth. To increase digital health uptake, including among minoritised youth, there is a need for diversity, equity and inclusion (DEI) considerations in the development and evaluation of mental health apps. How well DEI is integrated into youth mental health apps has not been comprehensively assessed. This scoping review aims to examine to what extent DEI considerations are integrated into the design and evaluation of youth mental health apps and report on youth, caregiver and other stakeholder involvement.

METHODS AND ANALYSIS

We will identify studies published in English from 2009 to 29 September 2023 on apps for mental health in youth. We will use PubMed, Global Health, APA PsycINFO, SCOPUS, CINAHL PLUS and the Cochrane Database and will report according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Scoping Review Extension guidelines. Papers eligible for inclusion must be peer-reviewed publications in English involving smartphone applications used by adolescents or young adults aged 10-25, with a focus on depression, anxiety or suicidal ideation. Two independent reviewers will review and extract articles using a template developed by the authors. We will analyse the data using narrative synthesis and descriptive statistics. This study will identify gaps in the literature and provide a roadmap for equitable and inclusive mental health apps for youth.

ETHICS AND DISSEMINATION

Ethics approval is not required. Findings will be disseminated through academic, industry, community networks and scientific publications.

Adapting the Number of Questions Based on Detected Psychological Distress for Cognitive Behavioral Therapy With an Embodied Conversational Agent: Comparative Study

BACKGROUND

The high prevalence of mental illness is a critical social problem. The limited availability of mental health services is a major factor that exacerbates this problem. One solution is to deliver cognitive behavioral therapy (CBT) using an embodied conversational agent (ECA). ECAs make it possible to provide health care without location or time constraints. One of the techniques used in CBT is Socratic questioning, which guides users to correct negative thoughts. The effectiveness of this approach depends on a therapist's skill to adapt to the user's mood or distress level. However, current ECAs do not possess this skill. Therefore, it is essential to implement this adaptation ability to the ECAs.

OBJECTIVE

This study aims to develop and evaluate a method that automatically adapts the number of Socratic questions based on the level of detected psychological distress during a CBT session with an ECA. We hypothesize that this adaptive approach to selecting the number of questions will lower psychological distress, reduce negative emotional states, and produce more substantial cognitive changes compared with a random number of questions.

METHODS

In this study, which envisions health care support in daily life, we recruited participants aged from 18 to 65 years for an experiment that involved 2 different conditions: an ECA that adapts a number of questions based on psychological distress detection or an ECA that only asked a random number of questions. The participants were assigned to 1 of the 2 conditions, experienced a single CBT session with an ECA, and completed questionnaires before and after the session.

RESULTS

The participants completed the experiment. There were slight differences in sex, age, and preexperimental psychological distress levels between the 2 conditions. The adapted number of questions condition showed significantly lower psychological distress than the random number of questions condition after the session. We also found a significant difference in the cognitive change when the number of questions was adapted based on the detected distress level, compared with when the number of questions was fewer than what was appropriate for the level of distress detected.

CONCLUSIONS

The results show that an ECA adapting the number of Socratic questions based on detected distress levels increases the effectiveness of CBT. Participants who received an adaptive number of questions experienced greater reductions in distress than those who received a random number of questions. In addition, the participants showed a greater amount of cognitive change when the number of questions matched the detected distress level. This suggests that adapting the question quantity based on distress level detection can improve the results of CBT delivered by an ECA. These results illustrate the advantages of ECAs, paving the way for mental health care that is more tailored and effective.

Software-based interventions for low back pain management: A systematic review and meta-analysis

INTRODUCTION

Using software for self-management interventions can improve health outcomes for individuals with low back pain, but there is a dearth of research to confirm its effectiveness. Additionally, no known research has evaluated the effective elements of software-based interventions for low back pain self-management components. This study aimed to synthesize the effectiveness of software-based interventions to promote self-management health outcomes among individuals with low back pain.

DESIGN

A systematic review and meta-analysis was conducted.

METHODS

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Statement, relevant studies up to July 2022 were searched via four electronic databases: PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature, and Web of Science.

RESULTS

4908 adults with low back pain who participated in 23 studies were included. Software-based interventions were effective in reducing fear avoidance (mean difference [MD] = -0.95, 95% CI: -1.45 to -0.44), pain catastrophizing (MD = -1.31, 95% CI: -1.84 to -0.78), disability (MD = -8.21, 95% CI: -13.02 to -3.39), and pain intensity (MD = -0.86, 95% CI: -1.17 to -0.55). Specifically, interventions that included an exercise component were more effective in reducing pain and disability. Additionally, cognitive behavioral therapy (CBT) intervention significantly reduced fear avoidance and pain catastrophizing but had no noticeable impact on disability and pain compared to standard treatment. The certainty of the evidence in this review varied from very low to high across outcomes. The heterogeneity of the study results was significant, suggesting that future studies in this area could optimize the design, time points, measures, and outcomes to strengthen the evidence.

CONCLUSIONS

Low back pain self-management interventions delivered through software-based programs effectively reduce pain intensity, disability, fear avoidance, and pain catastrophizing.

CLINICAL RELEVANCE

Low back pain is among the most common reasons for seeking healthcare visits. Combining exercise and counseling through soft-based programs may effectively address this issue and its associated suffering and disability.

A chatbot to improve adherence to internet-based cognitive-behavioural therapy among workers with subthreshold depression: a randomised controlled trial

BACKGROUND

Internet-based cognitive-behavioural therapy (iCBT) is effective for subthreshold depression. However, iCBT has problems with adherence, especially when unaccompanied by human guidance. Knowledge on how to enhance adherence to iCBT without human involvement can contribute to improving the effectiveness of iCBT.

OBJECTIVE

This is an implementation study to examine the effect of an automated chatbot to improve the adherence rate of iCBT.

METHODS

We developed a chatbot to increase adherence to an existing iCBT programme, and a randomised controlled trial was conducted with two groups: one group using iCBT plus chatbot (iCBT+chatbot group) and one group not using the chatbot (iCBT group). Participants were full-time employees with subthreshold depression working in Japan (n=149, age mean=41.4 (SD=11.1)). The primary endpoint was the completion rate of the iCBT programme at 8 weeks.

FINDINGS

We analysed data from 142 participants for the primary outcome. The completion rate of the iCBT+chatbot group was 34.8% (24/69, 95% CI 23.5 to 46.0), that of the iCBT group was 19.2% (14/73, 95% CI 10.2 to 28.2), and the risk ratio was 1.81 (95% CI 1.02 to 3.21).

CONCLUSIONS

Combining iCBT with a chatbot increased participants' iCBT completion rate.

CLINICAL IMPLICATIONS

Encouraging messages from the chatbot could improve participation in an iCBT programme. Further studies are needed to investigate whether chatbots can improve adherence to the programme in the long term and to assess their impact on depression, anxiety and well-being.

TRIAL REGISTRATION NUMBER

UMIN000047621.

Towards a self-applied, mobile-based geolocated exposure therapy software for anxiety disorders: SyMptOMS-ET app

Objective

While exposure therapy (ET) has the potential to help people tolerate intense situation-specific emotions and change avoidance behaviours, no smartphone solution exists to guide the process of in-vivo ET. A geolocation-based smartphone software component was designed and developed to instrumentalize patient guidance in in-vivo ET and its psychological validity was assessed by a group of independent psychology experts.

Methods

A team of computer scientists and psychologists developed the ET Component for in-vivo ET using geolocation-based technology, following the process-centred design methodology. The ET Component was integrated into the SyMptOMS-ET Android application, which was developed following the co-design methodology. Next, nine independent psychology experts tested and evaluated the ET Component and the SyMptOMS-ET app in the field, following the think-aloud methodology. Participants also completed the Mobile Application Rating Scale (MARS) instrument to quantitatively evaluate the solutions.

Results

We present the SyMptOMS-ET app's main features and the ET Component exposure workflow. Next, we discuss the feedback obtained and the results of the MARS instrument. Participants who tested the app were satisfied with the ET Component during exposure scenarios (score of μ 4.32 out of 5 [ σ 0.28] on MARS quality aspects), agreed on the soundness of the theoretical foundations of the solutions developed (score of μ 4.57 [ σ 0.48] on MARS treatment support aspects), and provided minor think-a-loud comments to improve them.

Conclusions

The results of the expert evaluation demonstrate the psychological validity of the ET Component and the SyMptOMS-ET app. However, further studies are needed to discern the acceptability and efficacy of the mHealth tool in the target population.

Third-wave cognitive behavioral therapies for caregivers of cancer patients: a scoping review

BACKGROUND

Cancer caregivers extend comprehensive support covering all aspects of patients' daily lives. It has been reported that a significant proportion of cancer caregivers experience emotional distress. As one way to solve this problem, third-wave cognitive behavioral therapies (CBT), which involves integrating acceptance and mindfulness into cognitive‒behavioral therapy, has been applied to improve caregiver outcomes.

METHODS

A scoping review was conducted based on the scoping review guidelines proposed by the Jonna Briggs Institute (JBI). The population was caregivers of cancer patients, the concept was third-wave CBT, and the context remained open. English and Korean publications published from 2001 to June 2022 were identified from PubMed, Embase, CINAHL, PsycINFO, Cochrane, Korea Med, and RISS.

RESULTS

A total of 12 studies were included in this scoping review. Mindfulness-Based Stress Reduction (MBSR) and Acceptance and Commitment Therapy (ACT) was the most frequently applied intervention (n = 3, each). Among the components of third-wave CBT, 'mindfulness' was identified in all the studies reviewed (n = 12). Dyadic interventions comprised the majority (n = 9). Interventions using digital technologies such as mobile application/web page (n = 3), telephone (n = 3), and FaceTime (n = 2) have increased since 2017. Depression was the most frequently evaluated outcome (n = 8), followed by anxiety and mindfulness (n = 6, each).

CONCLUSIONS

The current review explored available third-wave CBT intervention studies for cancer caregivers and targeted outcomes. Most of the interventions were dyadic interventions and utilized mindfulness. Delivery methods were continuously updated with digital technologies. Further RCTs with robust research designs and a synthesis of the results of the trials would provide evidence about how to effectively apply third-wave CBTs for cancer caregivers.

Digital Cognitive Behavioral- and Mindfulness-Based Stress-Management Interventions for Survivors of Breast Cancer: Development Study

BACKGROUND

Psychosocial stress-management interventions can reduce stress and distress and improve the quality of life for survivors of cancer. As these in-person interventions are not always offered or accessible, evidence-informed digital stress-management interventions may have the potential to improve outreach of psychosocial support for survivors of cancer. Few such digital interventions exist so far, few if any have been developed specifically for survivors of breast cancer, and few if any have attempted to explore more than 1 distinct type of intervention framework.

OBJECTIVE

This study aimed to develop 2 digital psychosocial stress-management interventions for survivors of breast cancer; 1 cognitive behavioral therapy-based intervention (CBI), and 1 mindfulness-based intervention (MBI).

METHODS

The development of the CBI and MBI interventions originated from the existing StressProffen program, a digital stress-management intervention program for survivors of cancer, based on a primarily cognitive behavioral therapeutic concept. Development processes entailed a multidisciplinary design approach and were iteratively conducted in close collaboration between key stakeholders, including experts within psychosocial oncology, cancer epidemiology, stress-management, and eHealth as well as survivors of breast cancer and health care providers. Core psychosocial oncology stress-management and cancer epidemiology experts first conducted a series of workshops to identify cognitive behavioral and mindfulness specific StressProffen content, overlapping psychoeducational content, and areas where development and incorporation of new material were needed. Following the program content adaptation and development phase, phases related to user testing of new content and technical, privacy, security, and ethical aspects and adjustments ensued. Intervention content for the distinct CBI and MBI interventions was refined in iterative user-centered design processes and adjusted to electronic format through stakeholder-centered iterations.

RESULTS

For the CBI version, the mindfulness-based content of the original StressProffen was removed, and for the MBI version, cognitive behavioral content was removed. Varying degrees of new content were created for both versions, using a similar layout as for the original StressProffen program. New content and new exercises in particular were tested by survivors of breast cancer and a project-related editorial team, resulting in subsequent user centered adjustments, including ensuring auditory versions and adequate explanations before less intuitive sections. Other improvements included implementing a standard closing sentence to round off every exercise, and allowing participants to choose the length of some of the mindfulness exercises. A legal disclaimer and a description of data collection, user rights and study contact information were included to meet ethical, privacy, and security requirements.

CONCLUSIONS

This study shows how theory specific (ie, CBI and MBI) digital stress-management interventions for survivors of breast cancer can be developed through extensive collaborations between key stakeholders, including scientists, health care providers, and survivors of breast cancer. Offering a variety of evidence-informed stress-management approaches may potentially increase interest for outreach and impact of psychosocial interventions for survivors of cancer.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/47195.

Conceptualizing the digital therapeutic alliance in the context of fully automated mental health apps: A thematic analysis

Fully automated mental health apps provide a promising opportunity for increasing access to mental health care and resources. Given this opportunity, continued research into the utility and effectiveness of mental health apps is crucial. Therapeutic alliance (TA) refers to the relationship between a client and a healthcare professional, and has been shown to be an important predictor of clinical outcomes in face-to-face therapy. Given the significance of TA in traditional therapy, it is important to explore whether the notion of a digital therapeutic alliance (DTA) in the context of fully automated mental health apps also plays an important role in clinical outcomes. Current evidence shows that the conceptualization of DTA in the context of fully automated mental health apps can be potentially different to TA in face-to-face therapy. Thus, a new DTA conceptual model is necessary for comprehensively understanding the mechanisms underpinning DTA for fully automated mental health apps. To the best of our knowledge, this is the first study that qualitatively explored the dimensions of a DTA in the context of fully automated mental health apps. We conducted interviews with 20 users of mental health apps to explore the key dimensions comprising DTA in the context of fully automated mental health apps. We found that although conceptualizations of DTA and TA have shared dimensions, flexibility and emotional experiences are unique domains in DTA. On the other hand, although agreement on goals between a therapist and a client is important in face to face therapy, we found that users can have an alliance with an app without a goal. The importance of goal needs further investigations.

Meeting the Behavioral Health Needs of Health Care Workers During COVID-19 by Leveraging Chatbot Technology: Development and Usability Study

BACKGROUND

During the COVID-19 pandemic, health care systems were faced with the urgent need to implement strategies to address the behavioral health needs of health care workers. A primary concern of any large health care system is developing an easy-to-access, streamlined system of triage and support despite limited behavioral health resources.

OBJECTIVE

This study provides a detailed description of the design and implementation of a chatbot program designed to triage and facilitate access to behavioral health assessment and treatment for the workforce of a large academic medical center. The University of California, San Francisco (UCSF) Faculty, Staff, and Trainee Coping and Resiliency Program (UCSF Cope) aimed to provide timely access to a live telehealth navigator for triage and live telehealth assessment and treatment, curated web-based self-management tools, and nontreatment support groups for those experiencing stress related to their unique roles.

METHODS

In a public-private partnership, the UCSF Cope team built a chatbot to triage employees based on behavioral health needs. The chatbot is an algorithm-based, automated, and interactive artificial intelligence conversational tool that uses natural language understanding to engage users by presenting a series of questions with simple multiple-choice answers. The goal of each chatbot session was to guide users to services that were appropriate for their needs. Designers developed a chatbot data dashboard to identify and follow trends directly through the chatbot. Regarding other program elements, website user data were collected monthly and participant satisfaction was gathered for each nontreatment support group.

RESULTS

The UCSF Cope chatbot was rapidly developed and launched on April 20, 2020. As of May 31, 2022, a total of 10.88% (3785/34,790) of employees accessed the technology. Among those reporting any form of psychological distress, 39.7% (708/1783) of employees requested in-person services, including those who had an existing provider. UCSF employees responded positively to all program elements. As of May 31, 2022, the UCSF Cope website had 615,334 unique users, with 66,585 unique views of webinars and 601,471 unique views of video shorts. All units across UCSF were reached by UCSF Cope staff for special interventions, with >40 units requesting these services. Town halls were particularly well received, with >80% of attendees reporting the experience as helpful.

CONCLUSIONS

UCSF Cope used chatbot technology to incorporate individualized behavioral health triage, assessment, treatment, and general emotional support for an entire employee base (N=34,790). This level of triage for a population of this size would not have been possible without the use of chatbot technology. The UCSF Cope model has the potential to be scaled, adapted, and implemented across both academically and nonacademically affiliated medical settings.

Potential and Pitfalls of Mobile Mental Health Apps in Traditional Treatment: An Umbrella Review

While the rapid growth of mobile mental health applications has offered an avenue of support unbridled by physical distance, time, and cost, the digitalization of traditional interventions has also triggered doubts surrounding their effectiveness and safety. Given the need for a more comprehensive and up-to-date understanding of mobile mental health apps in traditional treatment, this umbrella review provides a holistic summary of their key potential and pitfalls. A total of 36 reviews published between 2014 and 2022—including systematic reviews, meta-analyses, scoping reviews, and literature reviews—were identified from the Cochrane library, Medline (via PubMed Central), and Scopus databases. The majority of results supported the key potential of apps in helping to (1) provide timely support, (2) ease the costs of mental healthcare, (3) combat stigma in help-seeking, and (4) enhance therapeutic outcomes. Our results also identified common themes of apps’ pitfalls (i.e., challenges faced by app users), including (1) user engagement issues, (2) safety issues in emergencies, (3) privacy and confidentiality breaches, and (4) the utilization of non-evidence-based approaches. We synthesize the potential and pitfalls of mental health apps provided by the reviews and outline critical avenues for future research.

Digital Marketing: A Unique Multidisciplinary Approach towards the Elimination of Viral Hepatitis

New technologies are supported by the global implementation of the internet. These improvements have deeply affected various disciplines of sciences and consequently changed services such as daily business, particularly health sectors. Innovative digital marketing strategies utilize the channels of social media and retrieved user data to analyze and improve relevant services. These multidisciplinary innovations can assist specialists, physicians and researchers in diagnostic, prophylaxis and treatment issues in the health sector. Accordingly, compared to recent decades, health decision makers are more accurate and trustful in defining new strategies. Interestingly, using social media and mobile health apps in current pandemics of SARS-CoV-2 could be an important instance of the key role of these platforms at the local and global level of health policies. These digital technologies provide platforms to connect public health sectors and health politicians for communicating and spreading relevant information. Adding influencers and campaigns to this toolbox strengthens the implementation of public health programs. In 2016, the WHO adopted a global program to eliminate viral hepatitis by 2030. Recent constructive measures that have been used in the battle against COVID-19 could be adopted for the elimination of viral hepatitis program. The presented evidence in our narrative review demonstrates that the application of digital marketing tools to create campaigns on social media, armed with professional influencers, can efficiently consolidate this program. The application of different strategies in using these popular tools will raise the public awareness about viral hepatitis. Subsequently, the availability of an effective vaccine for HBV and antiviral medication for HCV can motivate the audience to take steps towards prophylaxis and screening methods against these infectious illnesses. The encouragement of health policy makers to apply digital communication technologies and comprehensive roadmaps to implement this global program will certainly decrease the burden of viral hepatitis worldwide.