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Background While existing psychological treatments for depression are effective for many, a significant proportion of depressed individuals do not respond to current approaches and few remain well over the long-term. Anhedonia (a loss of interest or pleasure) is a core symptom of depression which predicts a poor prognosis but has been neglected by existing treatments. Augmented Depression Therapy (ADepT) has been co-designed with service users to better target anhedonia alongside other features of depression. This mixed methods pilot trial aims to establish proof of concept for ADepT and to examine the feasibility and acceptability of a future definitive trial evaluating the clinical and cost-effectiveness of ADepT, compared to an evidence-based mainstream therapy (Cognitive Behavioural Therapy; CBT) in the acute treatment of depression, the prevention of subsequent depressive relapse, and the enhancement of wellbeing. Methods We aim to recruit 80 depressed participants and randomise them 1:1 to receive ADepT (15 weekly acute and 5 booster sessions in following year) or CBT (20 weekly acute sessions). Clinical and health economic assessments will take place at intake and at 6-, 12-, and 18-month follow-up. Reductions in PHQ-9 depression severity and increases in WEMWBS wellbeing at 6-month assessment (when acute treatment should be completed) are the co-primary outcomes. Quantitative and qualitative process evaluation will assess mechanism of action, implementation issues, and contextual moderating factors. To evaluate proof of concept, intake-post effect sizes and the proportion of individuals showing reliable and clinically significant change on outcome measures in each arm at each follow-up will be reported. To evaluate feasibility and acceptability, we will examine recruitment, retention, treatment completion, and data completeness rates and feedback from patients and therapists about their experience of study participation and therapy. Additionally, we will establish the cost of delivery of ADepT. Discussion We will proceed to definitive trial if any concerns about the safety, acceptability, feasibility, and proof of concept of ADepT and trial procedures can be rectified, and we recruit, retain, and collect follow-up data on at least 60% of the target sample. Trial registration ISCRTN85278228 , registered 27/03/2017

•This overview addresses the evidence supporting the efficacy of VR interventions in psychiatric disorders.•In anxiety/phobias, virtual reality can be used as supportive therapy, not a replacement for traditional treatments.•In pain management, it is emphasized using virtual reality instead of traditional medication therapy.•There is a lack of standardization of the hardware and the software used in virtual reality therapy. Virtual reality (VR) is being used more and more often as a therapeutic tool in psychology or psychiatry. In recent years, VR interventions appear more extensively also in disorders such as depression, anxiety and phobia. However, there has yet to be a comprehensive synthesis and critical review of the literature to identify future directions to advance the field in this area. To broadly characterize the literature to date on the application of VR in psychiatric disorders by conducting a systematic review of reviews, describe the limitations of existing research, suggest avenues for future research to address gaps in the current literature and provide practical recommendations for incorporating VR into various treatments for psychiatric disorders. PubMed and Web of Science databases were searched for reviews on VR use in psychiatric disorders (e.g. various pain perceptions, post-traumatic stress disorder, phobias, attention deficit hyperactivity disorder, psychosis, depression). The methodological quality of each literature review was assessed using AMSTAR. The original search identified 848 reviews, of which 70 were included in the systematic review of reviews. Broadly, the literature indicates that various VR interventions could be useful in different psychiatric disorders. This study provides evidence supporting the positive impact of VR therapy in psychiatric disorders. However, the impact is defined differently according to the studied area. Nevertheless, due to the continuous development of VR hardware and software, it is essential to conduct further research in the area of psychiatric disorders, especially as no review has concluded that VR does not work.

Depression significantly impacts quality of life, affecting approximately 280 million people worldwide. However, only 16.5% of those affected receive treatment, indicating a substantial treatment gap. Immersive technologies (IMTs) such as virtual reality (VR) and augmented reality offer new avenues for treating depression by creating immersive environments for therapeutic interventions. Despite their potential, significant gaps exist in the current evidence regarding the design, implementation, and use of IMTs for depression care. We aim to map the available evidence on IMT interventions targeting depression treatment. This scoping review followed a methodological framework, and we systematically searched databases for studies on IMTs and depression. The focus was on randomized clinical trials involving adults and using IMTs. The selection and charting process involved multiple reviewers to minimize bias. The search identified 16 peer-reviewed articles, predominantly from Europe (n=10, 63%), with a notable emphasis on Poland (n=9, 56%), which contributed to more than half of the articles. Most of the studies (9/16, 56%) were conducted between 2020 and 2021. Regarding participant demographics, of the 16 articles, 5 (31%) exclusively involved female participants, and 7 (44%) featured participants whose mean or median age was >60 years. Regarding technical aspects, all studies focused on VR, with most using stand-alone VR headsets (14/16, 88%), and interventions typically ranging from 2 to 8 weeks, predominantly in hospital settings (11/16, 69%). Only 2 (13%) of the 16 studies mentioned using a specific VR design framework in planning their interventions. The most frequently used therapeutic approach was Ericksonian psychotherapy, used in 56% (9/16) of the studies. Notably, none of the articles reported using an implementation framework or identified barriers and enablers to implementation. This scoping review highlights the growing interest in using IMTs, particularly VR, for depression treatment but emphasizes the need for more inclusive and comprehensive research. Future studies should explore varied therapeutic approaches and cost-effectiveness as well as the inclusion of augmented reality to fully realize the potential of IMTs in mental health care.

Depression and chronic pain are commonly comorbid, mutually reinforcing, and debilitating. Emerging approaches to mobile behavioral health care (mHealth) promise to improve outcomes for patients with comorbid depression and chronic pain by integrating with existing care models to bolster support and continuity between clinical visits; however, the evidence base supporting the use of mHealth to augment care for this patient population is limited. To develop an evidence base that sets the stage for future research, we aimed to explore the associations between changes in depression severity and various integrated care models, with and without mHealth augmentation, among patients with comorbid depression and nonmalignant chronic pain. Our team leveraged retrospective, real-world data from 3837 patients with comorbid depression and nonmalignant chronic pain who received integrated behavioral health care (IBH) at a subspecialty pain clinic. We analyzed one IBH-only, non-mHealth cohort (n=2765), an mHealth-augmented cohort (n=844), and a collaborative care (CoCM)+mHealth cohort (n=136), which were supported by the NeuroFlow mHealth platform, and a pre-CoCM mHealth cohort (n=92), which was supported by the mHealth platform for 3 months prior to beginning the chronic pain treatment. We evaluated changes in depression severity between treatment cohorts via longitudinal analyses of both clinician- and mHealth-administered Patient Health Questionnaire-9 (PHQ-9) assessments. mHealth-augmented integrated care led to significantly greater proportions of patients reaching clinical benchmarks for reduction (725/844, 86% vs 2112/2765, 76%), response (689/844, 82% vs 2027/2765, 73%), and remission (629/844, 75% vs 1919/2765, 69%) compared with integrated care alone. Furthermore, hierarchical regression modeling revealed that patients who received mHealth-augmented psychiatric CoCM experienced the greatest sustained reductions in on-average depression severity compared with other cohorts, irrespective of clinical benchmarks. In addition, patients who engaged with an mHealth platform before entering CoCM experienced a 7.2% reduction in average depression severity before starting CoCM treatment. Our findings suggest that mHealth platforms have the potential to improve treatment outcomes for patients with comorbid chronic pain and depression by providing remote measurement-based care, tailored interventions, and improved continuity between appointments. Moreover, our study set the stage for further research, including randomized controlled trials to evaluate causal relationships between mHealth engagement and treatment outcomes in integrated care settings.

Background: Exercise has been shown to improve quality of life (QoL) and even treatment outcomes in cancer patients. However, the evidence to support the benefits of exercise in patients with high-grade glioma (HGG) is limited. Therefore, we performed a randomized clinical trial (RCT) to examine the effect of augmented-reality-based rehabilitation exercises on physical and functional fitness, cognitive function, fatigue, mood, QoL, selected blood parameters, brain derived neurotrophic factor (BDNF), and S100 protein in patients with HGG. Methods: Adult patients with HGG scheduled to undergo radiotherapy after tumor resection were randomized to participate in an exercise program (experimental group, n = 25) or to receive usual care (controls, n = 22). Physical and mental fitness was measured at baseline, after the completion of radiotherapy, and at 3 months. The following tests were administered: Handgrip Strength Test; 6-Minute Walk Test; Time Up and Go test; Functional Independent Measure scale; Addenbrooke’s Cognitive Examination III (ACE III); Hospital Anxiety and Depression Scale; Functional Cancer Therapy Assessment—Brain; and Functional Assessment of Chronic Illness Therapy—Fatigue. We also measured blood parameters, BDNF, and S100 protein levels. Results: No significant changes were observed in the exercise group. However, the controls experienced a significant decrease in HGS and in the ACE III attention domain. No significant changes were observed in QoL, fatigue, BDNF, or S100 levels in either group. Conclusions: Augmented-reality-based exercise during radiation therapy may prevent loss of muscle strength and attention in patients with HGG.

Depressive disorders are characterized by persistent negative affect, rumination, and impaired emotion regulation, contributing substantially to global disease burden. As recurrent rumination and negative attentional biases are central cognitive mechanisms of depression, interventions targeting these processes have gained increasing attention. Mindfulness-based interventions (MBIs) effectively treat depressive disorders but face adherence challenges, which immersive technology may resolve through multi-sensory stimulation and real-time feedback. This systematic review assesses the therapeutic potential of mindfulness-based immersive interventions (MBIIs, which combine immersive technologies with MBIs) for depressive disorders. Following PRISMA guidelines, we identified 37 eligible studies from 670 screened records. Across the included studies, a proportion of studies (69%) reported greater improvements in depressive and anxiety-related symptoms in MBII conditions compared with conventional therapies, while 78% of the trials reported improvements in psychological processes. A subset of trials reported greater feasibility and acceptance for immersive implementations compared with non-immersive approaches (67%), and 89% reported improvements in physiological outcomes. However, significant gaps remain, including substantial variability in sessions and VR configurations, insufficient active controls, and limited long-term validation. Future research is recommended to prioritize mechanistic studies to clarify neurocognitive pathways, standardize sessions, and evaluate cost-effectiveness.

Mental health disorders and substance use disorders (SUDs) frequently co-occur, yet digital interventions typically address them separately. This paper presents a novel graph-based chatbot framework that simultaneously addresses these co-occurring conditions through a unified system. Our framework employs a multi- agent architecture implemented with LangGraph, where specialized agents handle distinct conversation aspects while collaborating to provide comprehensive support. The system integrates validated screening tools directly into the conversation flow, uses Retrieval-Augmented Generation (RAG) to deliver evidence-based therapeutic content, and implements human-in-the-loop safety protocols that automatically alert therapists when crisis indicators are detected. Our comprehensive evaluation across 492 synthetic test cases demonstrates 96.88% screening accuracy, 93.33% crisis detection recall with 97.22% precision, significantly exceeding existing system performance. Our approach aims to overcome limitations of existing chatbots by combining systematic assessment, knowledge graph-based reasoning, therapeutic content retrieval, and explicit escalation protocols across both mental health and substance use domains.

Acceptability of digital mental health interventions is a significant predictor of treatment-seeking behavior and engagement. However, acceptability has been conceptualized and operationalized in various ways, which decreases measurement precision and leads to heterogeneous conclusions about acceptability. Standardized self-report measures of acceptability have been developed, which have the potential to ameliorate these problems, but none have demonstrated evidence for validation among Black communities, which limits our understanding of attitudes toward these interventions among racially minoritized groups with well-documented barriers to mental health treatment. This study aims to examine the psychometric validity and reliability of one of the first and most widely used measures of acceptability, the Attitudes Towards Psychological Online Interventions Questionnaire, among a Black American sample. Participants (N=254) were recruited from a large southeastern university and the surrounding metropolitan area and completed the self-report measure via a web-based survey. A confirmatory factor analysis using mean and variance adjusted weighted least squares estimation was conducted to examine the validity of the underlying hierarchical 4-factor structure proposed by the original authors of the scale. An alternative, hierarchical 2-factor structure model and bifactor model were examined for comparative fit. The findings indicated that the bifactor model demonstrated a superior fit (comparative fit index=0.96, Tucker-Lewis index=0.94, standardized root mean squared residual=0.03, and root mean square error of approximation=0.09) compared with both 2- and 4-factor hierarchical structure models. The findings suggest that, within a Black American sample, there may be greater utility in interpreting the Attitudes Towards Psychological Online Interventions Questionnaire subscales as attitudinal constructs that are distinct from the global acceptability factor. The theoretical and practical implications for culturally responsive measurements were explored.

The perinatal period is considered a window of vulnerability given the increased risk of psychiatric difficulties during this time, such as mood and anxiety disorders (ADs). Pre-pandemic rates of ADs in perinatal women were one in five but have since increased with the onset of the COVID-19 pandemic (COVID). In addition, recent research suggests that the focus of worry has shifted during the pandemic, with perinatal women reporting significantly more COVID-specific worries. The objective of this study was to augment our current evidence-based Cognitive Behavioural Group Therapy (CBGT) for perinatal anxiety protocol by targeting intolerance of uncertainty and tailoring existing strategies to address COVID-related worry and impact. Pregnant (n = 19) and postpartum (n = 49) women were recruited from regular clinic patient flow from a university-affiliated teaching hospital between September 2020 and March 2021. Improvements in generalized anxiety symptoms, worry, intolerance of uncertainty, and mood were observed at post-treatment, maintained at 3-months, and the intervention received high ratings of treatment satisfaction. This is the first study to examine an augmented CBGT for perinatal women with GAD during the pandemic and supports the inclusion of strategies that target intolerance of uncertainty as well as specific pandemic and perinatal worry content for effective outcomes.

The need for scalable solutions facilitating access to eating disorder (ED) treatment services that are efficient, effective, and inclusive is a major public health priority. Remote access to synchronous and asynchronous support delivered via health apps has shown promise, but results are so far mixed, and there are limited data on whether apps can enhance health care utilization. This study aims to examine the effects of app-augmented treatment on clinical outcomes and health care utilization for patients receiving treatment for an ED in outpatient and intensive outpatient levels of care. Recovery Record was implemented in outpatient and intensive outpatient services in a California-based health maintenance organization. We examined outcomes for eligible patients with ED by comparing clinical and service utilization medical record data over a 6-month period after implementation with analogous data for the control group in the year prior. We used a logistic regression model and inverse-weighted estimates of the probability of treatment to adjust for treatment selection bias. App-augmented treatment was associated with a significant decrease in emergency department visits (P<.001) and a significant increase in outpatient treatment utilization (P<.001). There was a significantly larger weight gain for patients in low-weight categories (ie, underweight, those with anorexia, or those with severe anorexia) with app-augmented treatment (treatment effect: 0.74, 0.25, and 0.35, respectively; P=.02), with a greater percentage of patients moving into a higher BMI class (P=.01). Integrating remote patient engagement apps into ED treatment plans can have beneficial effects on both clinical outcomes and service utilization. More research should be undertaken on long-term efficacy and cost-effectiveness to further explore the impact of digital health interventions in ED care.