BackgroundExtended-release injectable naltrexone (XR-NTX), a long-acting opioid antagonist, is an effective relapse prevention strategy in the treatment of opioid use disorder (OUD). However, standard XR-NTX initiation requires completion of opioid withdrawal management and a 1–2 week opioid-free period. This interval is associated with heightened vulnerability to lapse and relapse, and many patients fail to initiate XR-NTX treatment successfully. Therefore, alternative strategies that enable rapid XR-NTX initiation are needed. This study aimed to compare the effectiveness and safety of naltrexone-accelerated (NA) versus sublingual buprenorphine (SB) withdrawal management in facilitating XR-NTX initiation among patients with OUD.MethodsThis single-center, open-label, randomized controlled trial uses a parallel-group design. Eligible patients aged 18–60 years with moderate to severe OUD who are actively using opioids and are not receiving regular maintenance treatment with methadone or buprenorphine are randomly assigned to one of two groups: (1) NA withdrawal management, comprising one day of adjunctive non-opioid medications, one day of buprenorphine administration, one day of washout, and four days of gradual oral naltrexone titration (1, 3, 12, and 25 mg/day); or (2) SB withdrawal management, comprising one day of adjunctive non-opioid medications, six days of buprenorphine tapering (up to 8 mg on Day 2, 6 mg on Day 3, 4 mg on Days 4–5, 2 mg on Day 6, and 1 mg on Day 7), and a seven-day washout period. Adjunctive non-opioid medications in both groups comprised clonidine, clonazepam, gabapentin, and trazodone. The primary outcomes are the proportions of participants who (1) achieve a negative urine drug test for the assessed opioids and (2) receive XR-NTX at the end of the withdrawal management period. Secondary outcomes include severity of withdrawal symptoms, opioid craving intensity, and adverse effects. All analyses are conducted according to the intention-to-treat principle.DiscussionThe findings of this trial may provide clinically relevant evidence to support rapid initiation of XR-NTX treatment in patients with OUD and inform clinical practice.Clinical trial registrationhttps://en.irct.ir/trial/81525, Iranian Registry of Clinical Trials IRCT20250123064499N1.
The dynamic features of long-term habituation of negative emotions: evidence from eye-tracking and hypothalamic-pituitary-adrenal axis research
ObjectivesNegative emotional habituation (NEH) plays a crucial role in individuals’ survival and adaptation. However, systematic research on long-term negative emotional habituation remains limited. This study aimed to explore the dynamics of the habituation process during prolonged repeated exposure to negative stimuli, from the perspectives of eye-tracking and hypothalamic–pituitary–adrenal (HPA) axis responses.MethodsEmploying a 2 × 7 mixed factorial design, we enrolled 50 healthy male undergraduates and randomly assigned them to moderate- or high-intensity negative-image groups. Negative stimulus intensity served as the between-subject factor, and repeated exposure across seven consecutive daily testing sessions served as the within-subject factor. A single-blind procedure was adopted. Baseline trait anxiety and resilience were assessed. On each testing day, we concurrently obtained subjective ratings (valence, arousal), eye-tracking indices [mean fixation duration (MFD), pupil size], and salivary cortisol samples.ResultsOver the seven-day repetition, valence increased over time while arousal decreased. MFD increased significantly while pupil size decreased significantly, with both indices differing by stimulus intensity. Daily changes in salivary cortisol exhibited a significant downward trend, with a steeper decline under high-intensity negative stimulation. Cross-system coupling varied by intensity: under moderate intensity, valence and cortisol habituation were positively correlated, whereas under high intensity, this association was not significant. Additionally, trait anxiety was significantly negatively correlated with pupil habituation, and resilience moderated the relationship between trait anxiety and valence habituation at a marginally significant level.ConclusionThese findings indicate that NEH is not a unitary pathway but a dynamic process jointly realized by multiple systems with distinct sensitivities and convergence rhythms. The results reveal nonlinear cross-level coupling in NEH and may inform methodological bases for timing, dose optimization, and process evaluation in exposure-based therapies.
Sex differences in sleep architecture among patients with severe mental disorders: a polysomnographic study
BackgroundSleep disturbances are common in severe mental illness, including schizophrenia, bipolar disorder, and major depressive disorder. Yet sex-specific sleep patterns across schizophrenia, bipolar disorder, and major depressive disorder remain poorly characterized.MethodsIn this cross-sectional study, we compared overnight polysomnography between 372 first-episode patients (aged 18-45) (93 schizophrenia, 181 major depressive disorder, 98 bipolar disorder). All participants underwent a single-night 10-channel polysomnography.ResultsAfter controlling for age, illness duration, BMI, and medications, women achieved significantly longer total sleep time (median 449.3 vs 420.3 min; p <0.001), time in bed (543.0 vs 525.5 min; p = 0.03), and higher sleep efficiency (83.3% vs 82.3%; p = 0.004) than men. Exploratory post-hoc analyses revealed potential sex-related differences in major depressive disorder and bipolar disorder (all p < 0.05, uncorrected for multiple comparisons). However, these findings did not survive correction for multiple comparisons, indicating that the observed differences should be interpreted with caution as preliminary.ConclusionsThis study found that biological sex modulated sleep macro-architecture in severe mental illness, with women exhibiting longer sleep duration and higher sleep efficiency relative to men. Although the cross-diagnosis comparison revealed only a marginally significant sex-by-diagnosis interaction that did not persist after multiple testing correction, these exploratory subgroup findings suggest potential nuanced variations in sleep architecture. Consequently, future studies with larger cohorts are warranted to evaluate whether sex-stratified approaches could refine clinical sleep interventions across psychiatric conditions.
A comparison of recovery benefits associated with participation in SMART Recovery, AA, both SMART and AA, or neither, following a new alcohol use disorder recovery attempt
BackgroundSelf-Management and Recovery Training (SMART Recovery or “SMART”) is an internationally known “second-wave” addiction recovery mutual-help organization that has grown over several decades. Despite this, little is known empirically about who uses SMART and how they fare on important alcohol-specific outcomes over time relative to individuals using more established options such as Alcoholics Anonymous (AA), or indeed those who utilize both SMART and AA, or neither. Greater knowledge could deepen understanding of the clinical and public utility of SMART in its own right and inform clinical referral options.MethodsA naturalistic, longitudinal cohort study (N = 361) of individuals recruited between February 2019 and February 2022 who were initiating a new alcohol use disorder (AUD) recovery attempt and self-selected into one of four groups at study entry: (1) SMART Recovery; (2) AA; (3) SMART + AA; and (4) neither SMART nor AA. Assessments were conducted at intake, 3 months, and 6 months and measured a variety of alcohol/drug-related and functioning outcomes.ResultsCompared to the AA and Both groups, SMART Recovery pathway participants exhibited a pattern of less severe clinical pathology and legal system involvement histories, along with higher psychosocial stability and recovery capital. In terms of meeting attendance frequency, the SMART group did not attend as many meetings as the AA or Both groups, but nevertheless was able to achieve levels of improvement in alcohol indicators (i.e., fewer drinking days, fewer heavy drinking days, and fewer alcohol-related consequences) and rates of early AUD remission similar to those of the AA and Both groups.ConclusionsSMART Recovery may provide a valuable alternative source of recovery-specific support that may be a good fit, particularly for certain individuals with AUD. As such, it serves as a valuable addition to the menu of available community-based recovery-support service options.
Compulsive sexual behavior disorder and paraphilic disorders in a large Brazilian community sample: an online investigation
BackgroundThe International Classification of Diseases 11th Revision (ICD-11) includes Compulsive Sexual Behavior Disorder (CSBD) among impulse control disorders, aiming to standardize diagnostic criteria and improve the understanding of problematic sexual behaviors across cultures. However, few large-scale studies have investigated CSBD and its association with Paraphilic Disorders (PD) in Latin American populations.ObjectiveTo investigate the occurrence of high-risk CSBD in a large Brazilian community sample, examine its association with paraphilic interests and disorders, and evaluate associated sociodemographic and clinical factors.MethodsThis cross-sectional online study included 5,227 Brazilian adults recruited through convenience sampling between September 2022 and April 2023. Participants completed sociodemographic questionnaires, a Brazilian Portuguese version of the CSBD-19, and a translated inventory assessing paraphilic interests and disorders based on DSM-5-TR criteria. Descriptive statistics, chi-squared tests, linear discriminant analysis, and multivariate backward stepwise logistic regression were performed.ResultsThe prevalence of high-risk CSBD (CSBD-19 > 50) was 5.4% (n = 282). The mean CSBD-19 score was 30.4 (SD = 9.7), increasing to 56.4 (SD = 6.1) among individuals classified as high risk. Male sex was strongly associated with high-risk CSBD (OR = 3.32, 95%CI: 2.45–4.50, p < 0.001). Significant associations were also identified for sexual sadism disorder (OR = 2.69, 95%CI: 1.79–4.07), paraphilic disorder involving specific body characteristics (OR = 2.46, 95%CI: 1.49–4.04), zoophilic interest (OR = 2.39, 95%CI: 1.70–3.37), partialism disorder (OR = 2.00, 95%CI: 1.17–3.42), and paraphilia-related distress (OR = 1.94, 95%CI: 1.44–2.61). Linear discriminant analysis demonstrated that the Negative Consequences domain showed the strongest discriminative contribution for high-risk CSBD classification (ω = 1.23).ConclusionsThis study contributes to more inclusive research on compulsive sexual behavior disorder (CSBD) by investigating a large Brazilian sample, including individuals with diverse sexual orientations and gender identities. Using the ICD-11 framework, the estimated prevalence of high-risk CSBD was 5.4%, a rate comparable to those reported for other common mental health conditions. The study also supports the psychometric applicability of the Brazilian Portuguese version of the CSBD-19 for future epidemiological and cross-cultural research in Latin American populations. Further longitudinal and nationally representative studies are needed to clarify causal pathways, psychiatric comorbidities, minority stress influences, and the neurobiological and psychosocial mechanisms underlying the relationship between CSBD and paraphilic disorders.
Mindfulness-Based Intervention for Parents of Autistic Children in Pakistan
Conditions: Autism Spectrum Disorder; Parental Stress
Interventions: Behavioral: Stronger Together Mindfulness-Based Intervention; Behavioral: Psychoeducation Program
Sponsors: Northeast Normal University
Completed
Interventions: Behavioral: Stronger Together Mindfulness-Based Intervention; Behavioral: Psychoeducation Program
Sponsors: Northeast Normal University
Completed
Reliability of Childhood Autism Rating Scale, Second Edition, Assessments Using Telepsychiatry for Children With Neurodevelopmental Disorders and Their Caregivers: Randomized Feasibility Study
Background: The COVID-19 pandemic has increased the demand for telepsychiatry in neurodevelopmental assessment; however, few studies have examined the interrater reliability of clinician-rated autism scales, such as the Childhood Autism Rating Scale, Second Edition (CARS2), when used remotely. Although the feasibility and validity of telehealth assessments have been explored previously, the consistency between remote and in person CARS2 ratings by different clinicians remains underinvestigated. Objective: The objective of this study was to evaluate agreement between CARS2 total scores obtained by different evaluators using telepsychiatry and face-to-face assessments in children with autism spectrum disorder (ASD) and/or attention-deficit/hyperactivity disorder (ADHD). Methods: In this randomized feasibility study, 75 children aged 6 to 17 years with diagnoses of ASD, ADHD, or both were enrolled at 5 medical institutions in Japan; 73 of 75 were included in the final analysis. Each participant underwent 2 independent CARS2 evaluations, one face-to-face and the other via telepsychiatry, conducted by different evaluators who were blinded to each other’s ratings. Remote assessments were conducted using a secure video platform with caregiver facilitation. Agreement was assessed using intraclass correlation coefficients (ICCs) for the overall sample and subgroups defined by primary diagnosis, sex, and age. Results: The overall ICC for CARS2 total scores between face-to-face and telepsychiatry assessments was 0.582 (95% CI 0.407‐0.717), indicating moderate agreement. The ICC was 0.546 among participants with ASD as the primary diagnosis and 0.495 among those with ADHD as the primary diagnosis. Point estimates were higher among girls than boys (0.666 vs 0.495) and among children aged 11 years or older than among those aged 10 years or younger (0.676 vs 0.419). In a sensitivity analysis including all participants with an ASD diagnosis, the ICC was 0.580. Conclusions: CARS2 total scores obtained through telepsychiatry showed moderate agreement with scores obtained through face-to-face assessment when the assessments were conducted by different evaluators in different settings. Higher point estimates were observed among older children and girls, although these subgroup findings should be interpreted cautiously. Telepsychiatry-based CARS2 assessment may be considered a complementary approach rather than a replacement for comprehensive face-to-face evaluation. Larger studies using more standardized assessment protocols are needed.
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Australian Digital Mental Health Services for Anxiety and Depression: Meta-Analysis and Comparison Study
Background: Mental Health Online, MindSpot, and THIS WAY UP are 3 Australian Government–funded digital mental health services (DMHSs). These services are free for consumers and deliver a range of (depression and anxiety disorder) psychological assessments and interventions using the internet, with or without clinician support. Objective: This study examines the uptake and effectiveness of these services. Methods: We used 3 data sources to examine the performance of the three DMHSs: (1) aggregated routinely collected service data to describe uptake of the services from January 2013 to December 2021, (2) peer-reviewed and gray literature reporting treatment outcomes, and (3) treatment outcome data from one evaluation conducted by Mental Health Online. The second and third data sources were used to analyze the effectiveness of the DMHSs compared to other mental health treatment programs (Australian primary, public, and low-intensity mental health care; UK stepped psychological care). We generated pooled mental health symptom (Cohen ) effect sizes for each service’s clinician-supported and self-directed treatments and compared those with effect sizes we calculated for the alternative treatment programs. Results: The 3 DMHSs offered care to more than 282,000 consumers and therefore contributed to improving overall access to mental health care in Australia. Clinician-supported online treatment significantly improved the mental health of consumers who use these services (Mental Health Online, Cohen =0.95; MindSpot, Cohen =1.42; and THIS WAY UP, Cohen =1.04), and self-directed treatment by Mental Health Online produced a moderate reduction (Cohen =0.59) in anxiety disorder severity ratings. Clinician-supported treatments produced improvements in mental health symptoms that are close or equivalent to most (face-to-face, phone, and stepped or symptom severity–matched mental health care) comparison treatments examined. Conclusions: Mental Health Online, MindSpot, and THIS WAY UP are producing clinically significant improvement for consumers experiencing psychological distress and anxiety and depression symptoms. The magnitude of improvement produced by clinician-supported treatment is comparable with more resource-intensive face-to-face treatment options. Heterogeneity in the magnitude of improvements produced by the 3 DMHSs (and comparator interventions across levels of clinical need) indicates that findings should be interpreted with caution, particularly in relation to the populations for whom DMHSs may be most appropriate.
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Effectiveness of Chatbots in Mental Health Screening and Assessment: Systematic Review
Background: Mental health disorders affect 970 million people globally; yet, over 50% do not access timely evaluation due to structural barriers and professional shortages. Chatbots and AI-based conversational agents have emerged as promising tools for mental health screening and assessment. Objective: This study systematically evaluated the effectiveness, accuracy, reliability, and acceptability of chatbots and AI-based conversational agents for mental health screening and assessment in adults. Methods: Systematic search conducted in May 2025 across PubMed/MEDLINE, PsycINFO, Scopus, and Web of Science (2019‐2025), following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines. Eligible studies evaluated chatbots or AI for mental health screening/assessment in adults (≥18 y). Risk of bias was assessed using appropriate tools (Risk of Bias 2, Quality Assessment of Diagnostic Accuracy Studies-2, Joanna Briggs Institute checklists, and Mixed Methods Appraisal Tool). This systematic review was registered with PROSPERO (International Prospective Register of Systematic Reviews; CRD420251072392). Results: Eighteen studies (2021‐2025) were included, with samples ranging from 20 to 3902 participants. Rule-based chatbots demonstrated high reliability (Cronbach α >0.85) and good acceptability (Acceptability of Intervention Measure >19/25). Generative models (large language models) achieved sensitivities of 0.84 to 0.93 and specificities of 0.80 to 0.96 for depression and anxiety, with correlations up to =0.96 with expert clinicians in suicide risk assessment. Hybrid approaches combining large language models with machine learning achieved exceptional performance for cognitive impairment (-score of 92.1%, specificity of 99.6%). Most studies reported high user satisfaction (≥70%), although barriers existed among older populations. Methodological quality was heterogeneous with a moderate risk of bias in critical dimensions. Conclusions: Chatbots and AI conversational agents demonstrate clinically relevant performance in mental health screening and assessment. However, safe implementation requires clear clinical protocols, professional supervision, integration with electronic health records, and active mitigation of algorithmic bias. These technologies should complement rather than replace clinical judgment. Trial Registration: PROSPERO CRD420251072392; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251072392
Subject-independent classification of ADHD from pediatric EEG: a leakage-aware deep learning framework with interpretable neurophysiological mapping
BackgroundThe use of electroencephalography (EEG) in automated screening of Attention-Deficit/Hyperactivity Disorder (ADHD) has created a large body of literature that suggests promising outcomes, with reported classification accuracies often above 90%. A major methodological issue suggests that a substantial part of these results are actually due to data leakage, whereby EEG epochs pertaining to the same subject end up in both training and testing sets, allowing classifiers to capitalize on features specific to the individual rather than on genuine disorder-related biomarkers.MethodsWe assessed the performance of three classical machine learning algorithms, namely, Logistic Regression (LR), Random Forest (RF), and Support Vector Machine (SVM), as well as three deep learning models: Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and CNN-BiLSTM, on a standard pediatric EEG dataset containing 121 children and 4,173 epochs. The performance of each model was compared in terms of both segment-wise cross-validation (Protocol A) and subject-wise cross-validation (without any data leakage, Protocol B).To evaluate neurotopographic plausibility without making unsupported causal assertions, we applied Deep SHapley Additive exPlanations (SHAP) to the best-generalizing architecture.ResultsThe performance discrepancy was substantial. Under segment-wise evaluation, the SVM operating on power spectral density (PSD) features reached 90.0% accuracy (95% CI: [89.1%, 90.9%], AUC = 0.96). However, the same model dropped to 65.6% (95% CI: [62.1%, 69.1%], AUC = 0.72) under subject-wise evaluation—a statistically significant 24.4 percentage point collapse (p < 0.001, Wilcoxon signed-rank). In contrast, deep architectures learning directly from raw EEG were resilient: the stand-alone CNN lost only 2.5 percentage points, achieving 72.7% accuracy (95% CI: [66.0%, 79.4%], AUC = 0.72, recall = 88.0%) on completely unseen participants. Post-hoc SHAP attribution identified the highest relative contributions in frontal (F3, Fz, F4) and central (Cz) electrodes, aligning with established ADHD neurophysiology.ConclusionHand-engineered spectral features are highly vulnerable to identity leakage, whereas end-to-end convolutional models generalize across subjects with realistic, uninflated performance. Strict subject-wise validation is strongly recommended as standard practice for translational EEG research.