Between major affective episodes some people with bipolar disorder experience persistent low mood or mood instability. Here we report an initial evaluation of the STABILISE programme (ISRCTN19416314; registration date 01.02.23), an adaptation of individual behavioural therapy that includes concepts and techniques addressing emotion regulation designed to support people experiencing these inter-episode symptoms. This study aimed to evaluate the safety, feasibility and acceptability of the intervention and to explore whether the pattern of clinical change had potential for the intervention to be of benefit. Twelve individuals with inter-episode bipolar symptoms received the STABILISE therapy in a randomised, multiple baseline case series. Participants were randomly assigned to wait 3, 4 or 5 weeks before commencing treatment, which comprised up to 22 sessions up to 7 months. Measures of symptoms, mood lability, recovery and quality of life were completed at intake, pre-therapy, and post therapy. Participants completed weekly measures of affective symptoms over the baseline and therapy periods, and for three weeks after. All 12 participants completed the therapy programme and reported high levels of satisfaction overall. No adverse events were judged to be therapy related. There was one instance of reliable deterioration on one outcome measure. Across all parameters of clinical change 9 of the 12 participants showed an overall pattern of improvement and none showed a pattern of deterioration overall. This study provides preliminary support for the feasibility, acceptability, safety, and clinical potential of the STABILISE therapy. Further investigation of these aspects in a larger sample and within a randomised controlled trial design is required.

Impaired sustained attention, the ability to selectively attend to information and resist interference, has been associated with reduced response to cognitive therapies for posttraumatic stress disorder (PTSD; e.g., Crocker et al., 2018, Worse baseline executive functioning is associated with dropout and poorer response to trauma-focused treatment for veterans with PTSD and comorbid traumatic brain injury. Behaviour Research and Therapy, 108, 68-77). However, little is known about how attentional capacity impacts exposure-focused treatment. Further, as serotonin deficits relate to impaired sustained attention and SSRIs may enhance cognitive functioning, serotonergic antidepressants may moderate this impact. In 142 treatment-seeking individuals with PTSD, sustained attention was assessed using the flanker task prior to receiving prolonged exposure (PE) or PE plus sertraline. At pre-treatment, sustained attention was not strongly associated with PTSD or depression severity. Higher pre-treatment sustained attention was associated with greater pre-posttreatment reductions in PTSD symptom severity with a small to moderate effect (γ11 = -3.95, d = .46) and most predictive of lower avoidance symptoms (γ11 = -0.61, d = .43). This effect did not achieve significance for depression severity. Treatment modality did not moderate this relationship. Impaired sustained attention may be one moderator to consider towards treatment optimization. Research should examine specific in-session attentional mechanisms impacting outcomes such as reduced engagement with trauma-related stimuli during exposure.

Obsessive-compulsive disorder (OCD) affects approximately 1.3% of adults and is characterized by intrusive thoughts (obsessions) and repetitive behaviors (compulsions) aimed at alleviating distress. Despite its impact on daily functioning, OCD remains underdiagnosed. Models suggest that OCD arises from maladaptive learning processes and/or biological factors, such as genetic predispositions and dysfunctional abnormalities in the cortico-striato-thalamo-cortical loops. First line treatment for OCD in Sweden is exposure and response prevention (ERP), a form of cognitive behavioral therapy (CBT). Selective serotonin reuptake inhibitors (SSRI) are first line pharmacological treatment. If treatment response is inadequate, low-dose antipsychotics can be added, followed by a switch to clomipramine. Deep transcranial magnetic stimulation (dTMS) and deep brain stimulation (DBS) may be considered for severe, treatment-resistant OCD.

Digital Cognitive Behavioral Therapy for Insomnia (dCBT-I) is an effective alternative to therapist-delivered CBT-I. However, there is a lack of meta-analyses assessing its effects on other sleep-related outcomes. We aimed to conduct a meta-analysis of randomized controlled trials (RCTs) evaluating dCBT-I in adults with insomnia through polysomnography (PSG) and sleep diary. Systematic searches were performed in PubMed and Web of Science. The outcomes considered were total sleep time (TST), sleep onset latency (SOL), sleep efficiency (SE), wake after sleep onset (WASO), and number of awakenings (NWAK). Meta-analyses were performed using random-effects models to compare dCBT-I with active (in-person or telehealth CBT-I) or inactive (waiting list, no treatment, or minimal intervention) control groups. Of the fourteen RCTs included, only three employed an active control. As no trials used PSG, the analyses relied solely on sleep diary data. DCBT-I showed no statistically significant differences from active controls, indicating comparable effects with therapist-delivered CBT-I. In contrast, it demonstrated statistically significant effects against inactive controls; TST increased by 0.20 h, SOL decreased by 15.53 min, SE improved by 7.91%, WASO reduced by 15.61 min, and NWAK decreased by 0.53. Future research should prioritize comparisons with therapist-delivered CBT-I and incorporate PSG for measuring these parameters.

Background: Insomnia is the most prevalent sleep disorder, associated with impaired daytime functioning, increased risk of mental and physical illness, as well as social and economic burden. Aim: This review summarizes the current state of knowledge on insomnia disorder and assesses the clinical value of scientifically proven treatment strategies, including both pharmacological and non-pharmacological methods. Methods: A narrative literature review was conducted using PubMed/MEDLINE (January 2015- November 2025). Peer-reviewed human studies, clinical guidelines, systematic reviews, meta-analyses, and high-quality narrative reviews addressing definition and classification, epidemiology, mechanisms, consequences, diagnostic tools, or treatment outcomes were included. Results: Insomnia affects approximately 10% of the adult population and is more common in women, elderly people, individuals with chronic stress, and those with comorbid medical or psychiatric conditions. Evidence supports a multidimensional hyperarousal model as the core mechanism of insomnia pathophysiology. Insomnia is linked to a higher risk of anxiety, depression, cardiometabolic disease, cognitive impairment, accidents, and reduced quality of life. Diagnosis relies on clinical assessment supported by sleep diaries and validated questionnaires. Cognitive Behavioral Therapy for Insomnia (CBT-I) is the first-line treatment, with chronotherapy, mindfulness-based interventions, exercise, and complementary approaches as useful adjuncts. Pharmacological options, including benzodiazepines, "Z-drugs", and other medications, may be considered, but with careful monitoring of safety and potential dependence. Conclusions: Insomnia requires personalized care that prioritizes non-pharmacological strategies. Medications should be used with caution, for selected patients, and for short durations only. Early recognition, patient education, and wider access to CBT-I are essential to reduce the burden of insomnia.

Many individuals who experience binge eating face significant challenges in accessing timely and adequate treatment, often due to limited healthcare resources. To address this, the digital, programme-led (self-help) version of Enhanced Cognitive Behaviour Therapy (CBT-E) has been developed. This service improvement project piloted the digital programme with adults on a specialist eating disorder service waiting list in the UK's National Health Service (NHS). Its aim was to assess the feasibility, acceptability, and preliminary clinical effects of a digital programme for adults on a waiting list for an eating disorder characterised by binge eating. The digital programme was offered to patients with eating problems characterised by binge eating (binge eating disorder or bulimia nervosa or atypical or subclinical threshold cases), for whom a programme-led treatment was appropriate and who were on a waiting list for a specialist outpatient service. Patients used the programme independently, without any additional support. They completed self-report measures assessing eating disorder features, secondary impairment, and features of depression before and after the programme. Patients provided feedback through semi-structured interviews, and staff completed a survey. Fifty patients started the programme, and 19 completed all active programme sessions. Those who completed the full programme and the post-programme assessments (n = 14) reported significant reductions in binge eating frequency, eating disorder psychopathology, secondary impairment, and features of depression. Qualitative feedback from patients and staff highlighted the programme's value as a waiting list offer and its role in supporting patients' progress towards recovery. Some patients expressed a desire for human interaction to help them better engage with the programme. These findings suggest that the digital, programme-led version of CBT-E is feasible, acceptable, and shows promise in reducing binge eating and related impairments in adults on a waiting list for a specialist outpatient eating disorder services. Offering this evidence-informed programme could help address the challenge of long delays in accessing care. Future research should focus on strategies to enhance patient engagement and adherence, improve human interaction within the programme, and explore ways to scale the intervention to benefit broader populations, including its use as an early intervention.

Artificial intelligence (AI)-powered cognitive behavioral therapy (CBT) tools show promise for anxiety and stress management, but patient perspectives remain poorly understood. To synthesize qualitative evidence on patient experiences, attitudes, and preferences regarding AI-powered CBT tools for anxiety and stress management. Systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, searching eight databases through March 2025. Qualitative studies exploring patient perspectives on AI-powered CBT interventions were included. Thematic synthesis was employed with GRADE-CERQual confidence assessment. Nine studies (n = 600+ participants) from nine countries were included. Six major themes emerged: (1) Perceived benefits and therapeutic value, including enhanced self-awareness and 24/7 accessibility; (2) Technical limitations and personalization challenges; (3) Trust, privacy, and acceptability concerns; (4) User preferences for conversational interfaces and human-AI integration; (5) Facilitators and barriers to engagement; and (6) Cultural and demographic influences on user experiences. Users consistently viewed AI tools as supplements to human therapy. AI-powered CBT tools provide accessible, non-judgmental support and practical coping strategies. However, technical limitations and personalization gaps remain significant challenges. Future development should enhance conversational capabilities, cultural adaptation, and integration with traditional care. Limitations of this study include English-language restriction, heterogeneity of AI interventions, and limited evidence for specific populations such as older adults.

Stopping smoking can improve mental health, with effect sizes similar to antidepressant treatment. Internet-based cognitive behavioral therapy (iCBT) provides evidence-based treatment for depression and anxiety, and digital interventions can support smoking cessation. However, combined digital smoking and mental health support is not currently available in UK health services. This feasibility trial aimed to investigate the acceptability and feasibility of a digital tailored smoking cessation intervention delivered alongside usual iCBT, and test trial procedures. The study design was a 2-armed, parallel groups, pragmatic, feasibility randomized controlled trial. Eligible participants were adult (18 years and older), regular smokers referred to iCBT from National Health Service Talking Therapies services in England. Participants were screened, consented, and randomized via a web-based platform and allocated to intervention (integrated smoking cessation support) or control (usual care) arms. Fully automated processes ensured allocation concealment. It was not possible to blind participants or clinicians to the behavioral intervention. Follow-ups via web-based questionnaires were completed at 3- and 6-months. Prespecified progression criteria, to determine the feasibility of the integrated intervention and trial procedures for a definitive trial, were enrolment of eligible clients (≥20%); recruitment to the target (≥80%); outcome data completeness (≥70%); and self-reported quit attempts in the intervention arm (≥8%). A total of 309 participants were randomized: 154 to the intervention arm and 155 to the control arm. The proportion of eligible clients enrolled (309/1484, 21%) met the criteria for progression; however, the number randomized was below target (309/500, 62%). In the intervention arm, 18% (27/154) self-reported at least one quit attempt, which exceeded the progression criteria but was comparable to the control arm (32/155, 21%). High loss to follow-up meant data completeness was low (<30% across 6 key pilot clinical outcomes). Integrating smoking cessation within digital mental health treatment and using automated procedures to enroll and randomize participants appears feasible. Adjustments to site recruitment could improve participant recruitment; however, a large loss to follow-up undermines the feasibility of progression. ISRCTN Registry ISRCTN10612149; https://www.isrctn.com/ISRCTN10612149. RR2-10.1016/j.cct.2024.107541.

Neurofibromatosis Type 1 (NF1) is an autosomal dominant genetic disorder that presents with severe chronic pain (CP) in adults. A limited number of NF1 research studies have evaluated behaviorally based interventions to address CP. The current study evaluated the efficacy of cognitive behavior therapy delivered via mobile application. The three-arm (treatment as usual [control], iCanCope only [iCC-NF], iCanCope + contingency management [iCC-NF + CM]) randomized clinical trial of 108 adults with NF1 and CP was completed during a 2-month intervention period. Significant improvements in pain interference (p = 0.005, d = 0.815) occurred in the iCC-NF + CM group when compared to the control group. Outcomes for pain self-efficacy (p = 0.009, d = 0.718), pain inflexibility (p = 0.026, d = 0.629), and chronic pain acceptance (p = 0.036, d = 0.653) significantly improved among the iCC-NF + CM group when compared to the control group. No significant differences were noted between iCC-NF + CM and iCC-NF. The current findings offer preliminary evidence of the added benefit of contingency management to mobile pain applications and provide an auxiliary treatment option for individuals with NF1. Trial Registration: ClinicalTrials.gov identifier: 2000029045.

Background: Major Depressive Disorder (MDD) is a heterogeneous condition with a wide range of treatment options, yet achieving remission remains a challenge due to the trial-and-error nature of treatment selection. While machine learning (ML) promises to personalize this process, "black-box" models often lack clinical trust and actionable insights, limiting their adoption. Objective: This study aims to develop and validate an interpretable ML pipeline for predicting optimal first-line treatment selection between Selective Serotonin Reuptake Inhibitors (SSRIs) and Cognitive Behavioral Therapy (CBT) for patients with MDD. Methods: We utilized a dataset of 1,250 patients from the [Anonymized] Neuropsychiatric Dataset, featuring comprehensive clinical, demographic, and digital phenotyping data. We trained and compared several ML models, including a black-box Gradient Boosting Machine (GBM) and an interpretable Explainable Boosting Machine (EBM). Model performance was assessed using accuracy, F1-score, and Area Under the Receiver Operating Characteristic Curve (AUC). Interpretability was achieved through global feature importance and local explanations for individual predictions. Results: The GBM model achieved the highest performance (AUC = 0.87), with the EBM model performing comparably (AUC = 0.85). Crucially, the EBM provided transparent insights, identifying key predictors of treatment success, such as baseline anxiety severity, sleep disturbance patterns, cognitive performance scores, and actigraphy-derived physical activity levels. A novel, clinically-actionable visualization, the "Treatment Suitability Scorecard," is presented for individual patient guidance. Conclusion: Interpretable ML models can achieve performance comparable to black-box models while providing crucial transparency for treatment selection in MDD. The proposed pipeline and visualization tools facilitate the transition of ML from a research tool to a clinically-deployable decision-support system, fostering trust and enabling personalized, evidence-based care in digital neuropsychiatry.

Supplemental Material for Acculturation of Dialectical Behavior Therapy (DBT) Skills Training for Family Caregivers of Suicidal Patients in Taiwan: Initial Feasibility and Outcomes

BackgroundIn blended care, digital mental health interventions (DMHIs) integrate with face-to-face psychotherapy provided in person or via telehealth. To incorporate DMHIs into routine care for depression and anxiety, it is important to understand the needs and expectations of mental health professionals for blended DMHIs.ObjectiveThe study objective was to partner with Australian mental health professionals in the design of a transdiagnostic, cognitive behavioral therapy–based blended model of care for adults experiencing depression and anxiety.MethodsParticipants were Australian health professionals who treat adults with depression and anxiety. The participatory design process included a web-based survey (N=258), one-on-one interviews (N=14), and a 2-part focus group (N=6). Quantitative and qualitative data were collected through the web-based survey. In-depth qualitative feedback from interviews and the 2-part focus group was subjected to reflexive thematic analysis.ResultsMental health professionals found blended care with face-to-face therapy more acceptable than telehealth and blended care with telehealth, with standalone DMHIs being the least preferred option. The most common ways in which mental health professionals thought a DMHI could integrate with face-to-face psychotherapy included homework completion (129/178, 72.5%), skills practice to support in-session therapy (128/178, 71.9%), and psychoeducation (127/178, 71.3%). Mental health professionals expect the blended DMHI to be easy to use, flexible, protective of client data, and to include evidence-based content from several therapeutic modalities (eg, cognitive behavioral therapy and mindfulness). Other preferences included mental health professionals being able to prescribe specific program modules to their clients, track the treatment progress of clients, and receive alerts if their clients’ symptoms worsened. In terms of implementation, mental health professionals were concerned about the time and effort needed to use blended care. They suggested that ongoing training and support would help mental health professionals implement blended care with their clients. Monitoring client risk and progress via a web-based dashboard and downloadable summaries was also important.ConclusionsDesigning DMHIs that support psychotherapy for adults with depression and anxiety has the potential to increase access to evidence-based treatment. Involving mental health professionals in DMHI design is expected to increase their acceptance of DMHIs and facilitate the integration of these digital products into routine care.

A systematic review and meta-analysis was conducted of different types of CBTs for ID in adults treated in routine clinical care. Ovid MEDLINE, Embase OVID, and PsycINFO were systematically searched for studies published until January 2025. The effectiveness of CBT, methodological quality, and moderators of treatment outcomes were examined and benchmarked by meta-analytically comparing them with efficacy studies for ID. Thirty-two studies were included, comprising 5231 participants. Very large within-group effect sizes (ES; Hedges' g) were obtained for ID-severity at post-treatment (1.87), and follow-up (1.68), on average 12 months post-treatment. Remission rates were 45% post-treatment and 51% at follow-up. Attrition rate was 13.9%. Risk of bias was considerable in the majority of studies. The benchmarking analysis showed that effectiveness studies (1.83) had almost exactly the same ES as efficacy studies (1.82) at post-treatment. Furthermore, there was no significant difference between effectiveness and efficacy studies on sleep diary measures, remission rates, and self-ratings of depression and anxiety. CBTs for ID are effective when delivered in routine clinical care, with ESs comparable to those found in efficacy studies. However, the evidence needs to be interpreted with caution because of the risk of bias in a high proportion of studies.Prospero registration id: CRD420251032141.

ABSTRACT Low sexual desire is a common sexual problem among women. When it is accompanied by significant personal distress, it may be diagnosed as hypoactive sexual desire dysfunction (HSDD). Both cognitive behavioral therapy (CBT) and mindfulness-based therapy (MBT) are effective treatments for HSDD when delivered in person or online. In this randomized controlled treatment study, CBT and MBT consisted of eight guided self-help modules delivered online, and participants completed measures at pretreatment and after 3, 6, and 12 months. Nine variables were examined as potential mediators of treatment outcomes (i.e., sexual desire and sexual distress), namely mindfulness, self-compassion, rumination, body connection, self-consciousness, relationship satisfaction, sexual communication, depression, and anxiety. In total, 212 women diagnosed with HSDD were randomized to either CBT or MBT (M age = 36.3, SD = 10.2). Improvements in self-compassion, rumination, body connection, and self-consciousness partially mediated treatment outcomes in at least one of the treatment groups. Mediation effects were mostly small, explaining up to 15% of the total effects. No systematic differences in mediation pathways between CBT and MBT were found. These findings emphasize the importance of emotion regulation, metacognitive processes, and embodiment for the effective treatment of HSDD. Future research should refine treatment components to enhance efficacy and ensure that psychological interventions adequately address common concerns among women with HSDD.

Background/Objectives: Trauma-related distress poses significant mental health challenges, with psychotherapy serving as a primary intervention. The Walters Method is a promising new alternative that may help where traditional methods fall short (i.e., in complex or violent cases), but before it can be implemented widely, the existing evidence on the effectiveness of other psychotherapies for trauma-related distress must be mapped to see how and where it relates to other techniques. The aim of this scoping review was to provide an overview of existing evidence on the effectiveness of psychotherapy for trauma-related distress. Methods: A scoping review was conducted to better understand the effectiveness of psychotherapies for trauma-related distress (including PTSD, acute stress disorder, or other serious mental health issues). Results: Thirty-three articles were analysed. Included articles included adults with PTSD, incarcerated women, childbirth trauma survivors, female survivors of sexual abuse, hospitalised COVID-19 patients, adults with serious mental illness, veterans and active soldiers, firefighters, and refugees. Eye Movement Desensitisation and Reprocessing and Cognitive Behavioural Therapy were the most studied and effective treatments. Prolonged Exposure and Narrative Exposure Therapy were less common but noteworthy. Other therapies, including psychodynamic approaches, are seldom studied but have proven effective when explored, highlighting knowledge gaps and potential missed opportunities. Success with these alternative approaches—especially in complex trauma cases like intimate partner violence or child loss where EMDR and CBT may be less effective—suggests they have potential, but further research is needed for validation. Conclusions: This review offers novel contributions to the field by emphasising innovative therapeutic perspectives that extend beyond traditional, more studied, evidence-based approaches such as CBT and EMDR, thereby expanding treatment options for diverse clinical presentations. Alternative therapies show promise, particularly for complex trauma cases like intimate partner violence or child loss where established approaches may be less effective; however, further research is needed to validate their efficacy across diverse populations. Selection of psychotherapy should be based on clients’ goals and comfort, and the cultural and contextual compatibility between the person and intervention. Future research should prioritise underexplored therapies to address current knowledge gaps and improve treatment accessibility for varied clinical needs.

Digital health interventions (DHIs) offer scalable, accessible approaches to promote healthy sleep in adolescents and to prevent or treat poor sleep and insomnia. Given the high prevalence of sleep problems and their bidirectional links with mental health, this systematic review and meta-analysis examined the effectiveness and active components of DHIs for adolescent sleep. We searched six databases, which included 18 randomised controlled trials (RCTs). Eligible participants were aged 10–24 years. Eighteen RCTs (N = 13,296; mean age 19.0; 71% female) met inclusion criteria: ten evaluated digital cognitive behavioral therapy for insomnia (dCBT-I) and eight targeted sleep promotion (education, hygiene, or holistic programs). Most DHIs were unguided (55.5%) or provided minimal online support (33.3%). Pooled analyses showed that dCBT-I significantly reduced insomnia severity (SMD = −3.32, 95% CI − 5.09 to −1.56) and modestly improved sleep quality (SMD = −0.32, 95% CI − 0.53 to −0.11), with secondary benefits for mental health outcomes. Educational and lifestyle interventions yielded mixed effects. Active components included cognitive restructuring, mindfulness, stimulus control, and sleep restriction. dCBT-I appears most beneficial for adolescents with insomnia or poor sleep. Future research should refine digital delivery, ensure intervention fidelity, and clarify which active ingredients drive sustained improvements in sleep and mental health.

This community service program aims to provide socialization and mentoring for Christian youth of the I.S. Kijne Congregation in Abepura, Papua, to address social media addiction through a community-based digital wellness intervention program. The program integrates evidence-based psychological approaches with Christian theological perspectives to enhance mental health and the quality of interpersonal relationships. The one-day intensive socialization activity was designed using a Community-Based Participatory Education approach combined with Experiential Learning Theory. The program incorporates Cognitive Behavioral Therapy techniques, digital detox strategies, and Christian stewardship principles. The effectiveness assessment utilized the Bergen Social Media Addiction Scale and mental health indicators among 45 participants aged 16–25 years. The preliminary survey revealed an alarming condition: 84.4% of respondents used social media for more than four hours per day, with 31.1% at high risk and 13.3% experiencing addiction. A strong correlation was found between problematic social media use and depression (r=0.567, p&lt;0.001) as well as anxiety (r=0.523, p&lt;0.001). The program results showed a significant increase in knowledge (≥40% pre–post improvement), a decrease in Fear of Missing Out (≥30%), and behavioral commitment (80% of participants pledged to reduce usage). The culturally adapted and faith-integrated program model proved effective for promoting digital wellness within religious communities. The program’s success demonstrates the importance of combining scientific evidence with theological frameworks to create sustainable behavioral change through peer support systems and community integration. This model offers a replicable solution for addressing digital addiction in faith-based contexts.

Cognitive behavioral therapy (CBT) is recommended as the first-line treatment for insomnia; however, few patients have access to it. A new class of Food and Drug Administration (FDA)-regulated digital CBT treatments has the potential to address this unmet need. These treatments are ordered or prescribed by health care providers and are fully automated, delivering CBT directly to patients without human coaches. This trial builds upon promising earlier digital cognitive behavioral therapy for insomnia (CBT-I) research by using a decentralized design to recruit a sample with greater representation of the US general population, including individuals from lower socioeconomic status groups who often face greater barriers to care. This decentralized trial evaluated the effectiveness of a fully automated digital CBT-I program (SleepioRx) for treating insomnia disorder compared with online sleep hygiene education (SHE) in a sample of participants recruited from across the United States. A decentralized, parallel-group randomized controlled trial was conducted between November 2022 and August 2023. Participants were recruited nationally from across the United States, and a total of 336 adults aged 22 and older, diagnosed with the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) insomnia disorder via structured clinical interview, were allocated 1:1 to either digital CBT-I (SleepioRx) or online SHE. The primary end points were insomnia severity, assessed using the Insomnia Severity Index (ISI), and sleep diary measures of sleep onset latency (SOL) and wake after sleep onset (WASO) at 10 weeks, with follow-up assessments at 16 and 24 weeks postrandomization. Compared with SHE, SleepioRx showed statistically and clinically significant improvements on the ISI at posttreatment (10 weeks; Cohen d=0.60, P<.001), with effects sustained at follow-up (16 weeks; d=0.65, P<.001; and 24 weeks, d=0.77, P<.001). SleepioRx led to significant reductions in WASO at all time points (10 weeks, P=.003; 16 and 24 weeks, P<.001); however, effects on SOL were not statistically significant at an adjusted α (10 weeks, P=.01; 16 weeks, P=.07; 24 weeks, P=.27). SleepioRx participants had 2.5 times (odds ratio 2.52; P<.001, 99% CI 1.33-4.75) and 5.8 times (odds ratio 5.78; P<.001, 99% CI 2.11-15.84) greater odds of response and remission at week 10, respectively, with statistically and clinically significant differences in rates sustained at follow-up assessments (P<.001). SleepioRx also demonstrated sustained improvements in secondary sleep and broader mental health outcomes. The results of this trial demonstrate the effectiveness of digital CBT-I (SleepioRx) for treating insomnia, with gains sustained at 6 months, and support the FDA authorization of SleepioRx for the treatment of insomnia disorder. These findings underscore the potential of a new class of FDA-authorized, fully automated digital treatments to provide first-line, guideline-recommended CBT at scale. Efforts should now focus on expanding access to these evidence-based treatments. ClinicalTrials.gov NCT05541055; https://clinicaltrials.gov/ct2/show/NCT05541055.

Takotsubo cardiomyopathy is an acute cardiac emergency presenting with severe left ventricular dysfunction. Physical exercise training or cognitive behavioral therapy may enhance myocardial recovery after takotsubo cardiomyopathy. In a prospective multicenter clinical trial conducted between February 2020 and August 2023, patients with acute takotsubo cardiomyopathy were randomized 1:1:1 to physical exercise training, cognitive behavioral therapy, or standard care for 12 weeks after index presentation. The primary end point was resting phosphocreatine/gamma-ATP ratio assessed by 31P-magnetic resonance spectroscopy. Secondary end points were the rate of oxygen consumption at peak exercise on cardiopulmonary exercise testing, 6-minute walk distance, left ventricular global longitudinal strain, and the Minnesota Living With Heart Failure Questionnaire. Twelve-week changes in outcome were compared between allocated trial interventions. Seventy-six participants were recruited: the median age was 66 years, and 91% were women. Compared with standard care, the primary end point of myocardial phosphocreatine/gamma-ATP ratio was improved by physical exercise training (0.4 [95% CI, 0.1-0.8]; P=0.016) and cognitive behavioral therapy (0.3 [0.01-0.7]; P=0.043). Both physical exercise training and cognitive behavioral therapy improved rate of oxygen consumption at peak exercise (4.7 [1.4-8.0] and 4.0 [1.5-6.4] mL/min per kg; P=0.001 and 0.004, respectively) and 6-minute walk distance (92.6 [24.7-160.6] and 73.3 [7.9-138.8] m; P=0.004 and 0.029, respectively) compared with standard care. There were no differences in global longitudinal strain or symptom burden. In patients with acute takotsubo cardiomyopathy, a 12-week intervention with exercise training or cognitive behavioral therapy improved left ventricular myocardial energetics and exercise performance without demonstrable effects on symptoms of heart failure. URL: https://www.clinicaltrials.gov; Unique identifier: NCT04425785.

Veterans with HIV/AIDS (VWH) frequently report alcohol misuse, which can impact antiretroviral therapy (ART) adherence and lead to poorer clinical outcomes. The TRAC (Tracking and Reducing Alcohol Consumption) intervention was developed to help VWH reduce alcohol use and its associated consequences. TRAC is delivered via mobile device, incorporates eight counseling sessions based in cognitive behavioral therapy and motivational interviewing, and utilizes mobile surveys and breathalyzers for daily monitoring of alcohol and ART use. We conducted a pilot randomized waitlist-controlled trial (N = 50). Participants were allocated to an immediate intervention group (N = 26), which received the TRAC intervention and completed twice-daily monitoring of alcohol and ART use for 8 weeks, or to a waitlist-control (n = 24), which started TRAC after 8 weeks. Participants provided ratings of intervention sessions and completed questionnaires assessing alcohol use, ART adherence, and treatment self-efficacy at baseline, 8, 16, and 24 weeks. Analyses included correlations and descriptive statistics for examining feasibility and acceptability, difference-in-differences analyses to compare changes between groups at the 8-week timepoint, matched pair tests to assess changes in alcohol use during the intervention, and general linear models to investigate long-term effects on outcomes with a pooled sample. Results indicated high feasibility and acceptability: 84% of participants were retained through the intervention and all follow-ups, average intervention session ratings were 9.6 (out of 10), and participants completed a median of 85% and 78% of mobile surveys and breathalyzer readings, respectively. While not statistically significant due to low power, there was a trend of decreased binge drinking episodes and fewer missed HIV medication doses in the intervention group compared to control. When pooling data among participants from both groups to examine long-term effects, TRAC was associated with reductions in several drinking-related outcomes. High acceptability and feasibility, as well as preliminary evidence that the intervention may reduce alcohol use relative to control, suggest that the TRAC intervention is promising for VWH and warrants further evaluation in a randomized controlled trial with adequate power to detect effects. If shown to be efficacious, TRAC has potential to be a highly scalable and acceptable intervention for delivery among VWH. This study was registered on ClinicalTrials.gov, #NCT03746600. Registration date: 09/24/2018.