Background: Virtual reality (VR) is increasingly used for adjunctive relaxation training in psychiatric care. However, evidence remains limited among hospitalized patients with depressive disorders, particularly in routine inpatient settings in China, and little is known about whether improvement varies by session frequency. Objective: This retrospective study examined whether adjunctive VR-based relaxation training was associated with changes in depressive and anxiety symptoms among inpatients with depressive disorders and whether improvement differed by session frequency. Methods: We conducted a retrospective, nonrandomized natural-group comparison using complete anonymized medical records from patients hospitalized in Lishui Second People’s Hospital between January 1 and December 31, 2022. Patients met () diagnostic criteria for depressive episodes or recurrent depressive disorders and were screened using predefined criteria. The analytic sample included 133 inpatients: 63 (47.4%) received adjunctive VR-based relaxation training plus usual care and 70 (52.6%) received usual care only. Usual care included pharmacotherapy and physiotherapy. The VR intervention consisted of 25-minute immersive relaxation sessions delivered approximately 3 times per week. Symptoms were assessed at admission and discharge using the 17-item Hamilton Depression Scale and Hamilton Anxiety Rating Scale. Response was defined as a reduction of 50% or more from baseline, and remission was defined as a total score of 7 or less. Baseline characteristics, outcome scores, response and remission rates, and exploratory session-frequency subgroups were compared. All analyzed variables were checked against complete medical records; no missing values were identified, and no imputation was performed. Results: The VR and control groups did not differ significantly in baseline depressive or anxiety scores. At discharge, adjunctive VR-based relaxation training was associated with lower depressive and anxiety symptom scores than usual care alone. The VR group also showed higher response rates for both depressive and anxiety symptoms and a higher anxiety remission rate, whereas depression remission was similar. Exploratory session-frequency analyses suggested that anxiety improvement may be more consistently associated with VR exposure than depression remission; however, the pattern was not strictly linear and should be interpreted cautiously because treatment frequency was linked to hospitalization duration and routine care factors. Conclusions: This study is innovative in evaluating structured VR-based relaxation training as an adjunct to routine inpatient depression care and in providing preliminary observations on session-frequency patterns in a real-world Chinese psychiatric setting. Unlike many previous VR studies conducted in noninpatient, nonclinical, or short-term experimental contexts, this study reflects everyday clinical practice among hospitalized patients with depressive disorders. The findings contribute practical evidence for integrating immersive relaxation into comprehensive inpatient care, particularly when additional anxiety relief is desired. Because the study was retrospective and nonrandomized, the findings indicate associations rather than causal effects and should be confirmed in prospective randomized controlled trials.
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Digital Cognitive Behavioral Therapy for Older Adults With Symptoms of Depression: Feasibility Cohort Study
Background: Depressive symptoms are common among older adults and can significantly impact their quality of life. However, many older adults face barriers to accessing psychological treatment. Internet-based cognitive behavioral therapy (iCBT) is a promising alternative to face-to-face treatments, but its feasibility among older adults has been less extensively studied than in adult populations. Objective: This study evaluated the feasibility of guided iCBT for adults aged 55 years and older with mild to moderate depressive symptoms recruited from the general population. Methods: This study is a feasibility study with a single-group, pretest-posttest design (n=21), in which all participants received guided iCBT for 8 weeks. Assessments were conducted at baseline (T0) and after the intervention (T1). The primary outcome was feasibility, conceptualized as satisfaction, usability, engagement, and uptake of iCBT. Secondary outcome measures included depression severity, working alliance, and technical alliance. Results: Participants were mostly highly educated (13/21, 61.9%), female (18/21, 85.7%), had an average age of 59.85 (SD 4.19; range 55-68) years, and reported moderate digital literacy. Feasibility outcomes indicated high satisfaction and engagement and moderate usability. Working alliance was rated as good by both participants and coaches, and technical alliance was rated as moderate by the participants. There was a nonsignificant modest decrease in depressive symptoms (Cohen <i>d</i>=0.47). Of the 20 participants who started the intervention, all completed the first 2 modules, but completion declined across the remaining 6 modules, with only 1 (5%) participant completing all modules. Conclusions: This study found that guided iCBT has the potential to be a feasible option for older adults experiencing depressive symptoms, with participants reporting generally positive satisfaction, moderate engagement, and a moderate therapeutic bond with their coaches. However, below-average usability ratings and a moderate technical alliance suggest that some aspects of the platform require improvement. Future research should focus on improving usability and adherence, as well as testing the intervention in a larger and more diverse population.
“Mirror, mirror, on the wall, without you, I will fall”: investigation into body dysmorphic disorder from an attachment perspective
ObjectiveBody dysmorphic disorder (BDD) is a prevalent concern among young adults. However, the underlying mechanisms of BDD development remain elusive. This study aims to investigate the intricate relationship between attachment styles and BDD symptoms, with appearance-based rejection sensitivity (ARS) as a mediating factor and gender as a moderator.MethodsA total of 815 young adults participated, completing a battery of questionnaires including the Revised Adult Attachment Scale (RAAS), Appearance-Based Rejection Sensitivity Scale (ARSS), and Scale of Body Image (SBI).ResultsData indicated a positive association between attachment anxiety and BDD symptoms, with ARS found to mediate this link. Furthermore, gender differences were observed to moderate the relationship between ARS and BDD symptoms.ConclusionThis study sheds light on the foundational mechanisms of BDD, tracing its origins to early caregiver-infant bonds and highlighting the enduring impact of ambivalent care on body image perceptions. Additionally, the identification of ARS as a specific contributing factor to BDD onset underscores its significance in understanding and addressing this disorder. By considering the influence of social norms and cultural context, gender differences in the association between ARS and BDD symptoms are elucidated.
Intranasal esketamine plus oral antidepressant for treatment-resistant depression: acute induction and maintenance relapse-prevention outcomes in a systematic review and meta-analysis
Treatment-resistant depression (TRD) remains a major clinical challenge. Intranasal esketamine, used adjunctively with an oral antidepressant, has been evaluated in randomized trials, but uncertainty persists regarding the magnitude and consistency of benefit, durability, and key harms. This systematic review and meta-analysis included randomized controlled trials comparing intranasal esketamine plus an oral antidepressant versus placebo nasal spray plus the same oral antidepressant in TRD. Acute induction (≈4 weeks) and maintenance randomized-withdrawal phases were analyzed separately. Depression outcomes were assessed primarily using the Montgomery–Åsberg Depression Rating Scale (MADRS), and functional outcomes using the Sheehan Disability Scale (SDS). Two reviewers independently screened studies, extracted data, and assessed risk of bias using RoB 2.0. Random-effects models pooled mean differences (MD) for continuous outcomes, risk ratios (RR) for binary outcomes, and hazard ratios (HR) for relapse prevention. Certainty of evidence was rated using GRADE. From 1,518 records, nine reports representing six unique RCTs (1,836 participants) were included. Four acute induction RCTs (n=937) showed greater symptom reduction at day 28 with esketamine (MADRS MD −2.99, 95% CI −5.10 to −0.89; I²=48.5%). Rapid improvement was evident by day 2 (MD −3.25, 95% CI −4.65 to −1.85). Esketamine increased day-28 response (RR 1.44, 95% CI 1.20–1.74) and remission (RR 1.52, 95% CI 1.20–1.92), corresponding to approximately +154 responders and +106 remitters per 1,000 patients, respectively, based on pooled control risks. Functioning improved (SDS MD −1.70, 95% CI −2.61 to −0.79). Two maintenance randomized-withdrawal RCTs (n=899) demonstrated reduced relapse risk with continued esketamine (HR 0.51, 95% CI 0.42–0.62; I²=0%). In acute induction, esketamine increased any treatment-emergent adverse event (TEAE) (RR 1.37, 95% CI 1.25–1.50) and discontinuation due to adverse events (RR 2.68, 95% CI 1.35–5.29), with notable increases in dissociation (RR 7.33, 95% CI 4.49–11.98) and blood pressure increased events (RR 3.96, 95% CI 2.24–7.01). Maintenance TEAE rates were similar between groups (RR 1.07, 95% CI 0.99–1.17). Intranasal esketamine plus an oral antidepressant provides rapid, modest acute improvement and reduces relapse risk during maintenance among stabilized responders/remitters, but increases acute adverse events, supporting use within supervised care and individualized benefit–risk assessment.
Exercise interventions are most consistently supported for depressive disorders: an umbrella review of diagnosed depressive and anxiety disorders
BackgroundExercise is increasingly discussed as part of lifestyle-based and multimodal care for mood and anxiety disorders, but review-level evidence often mixes formally diagnosed clinical populations with symptom-defined or medically mixed samples.MethodsWe conducted an umbrella review of systematic reviews, meta-analyses, and network meta-analyses of structured exercise interventions for adults with depressive or anxiety disorders. Six databases were searched from inception to 1 March 2026. Primary outcomes were depressive and anxiety symptom severity, remission, and response; secondary outcomes were acceptability and tolerability. Review quality was appraised with AMSTAR 2, and primary-study overlap was quantified with corrected covered area (CCA), including overall and symptom-cluster analyses. The synthesis was designed to summarize review-level credibility and clinical interpretability rather than to generate a second-order pooled efficacy estimate.ResultsNine reviews met eligibility criteria; four supplied directly extractable primary overall review-level estimates for core psychiatric symptom outcomes. AMSTAR 2 appraisal rated one review as high, three as low, and five as critically low. Recalculated overall overlap was slight (112 primary-study occurrences, 89 unique primary studies; CCA = 3.23%), although cluster-level analyses identified localized redundancy, particularly within anxiety-disorder-specific reviews. In major depressive disorder, one clinically focused review reported a large reduction in depressive symptoms for aerobic exercise versus non-exercise comparators (Hedges’ g = -0.79, 95% CI -1.00 to -0.57; I² = 21%). Across diagnosed depressive and/or anxiety disorders, broader review-level estimates also favored exercise for depressive symptoms (SMD = -0.97, 95% CI -1.28 to -0.66) and anxiety symptoms (SMD = -0.66, 95% CI -1.09 to -0.23), but heterogeneity was high. Anxiety-disorder-specific evidence was less secure: the primary DSM-IV anxiety-disorder pooled estimate showed no clear benefit over selected controls (SMD = 0.02, 95% CI -0.20 to 0.24). Acceptability estimates were close to null, and adverse-event reporting was too sparse to support confident safety conclusions.ConclusionExercise is best supported as an adjunctive, patient-centered component of care for depressive disorders. Anxiety-disorder-specific efficacy remains uncertain when comparator rigor, diagnostic heterogeneity, and localized overlap are considered, and safety reporting needs substantial improvement.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier CRD420261364264.
Health outcomes across socioeconomic strata B, C, and DE among Brazilian adults living in moderate social vulnerability
ObjectivesThis study examined whether socioeconomic status was associated with anxiety symptoms, depressive symptoms, BMI, waist-to-hip ratio, and quality of life among Brazilian adults living in areas of moderate social vulnerability. In addition, we described anxiety and depressive symptoms, BMI and waist-to-hip ratio, and quality of life in individuals living in moderate social vulnerability.MethodsThis is a cross-sectional study. In a socially vulnerable cohort, interviews captured demographics, comorbidities, medications, anxiety and depressive symptoms, and quality of life, followed by measurement of anthropometric characteristics.ResultsAmong 299 socially vulnerable adults, 8% had moderate–severe depressive symptoms and 7% had moderate–severe anxiety symptoms; ~50% showed increased risk of cardiometabolic diseases (i.e., waist-to-hip ratio greater or equal to 0.90 for men and 0.85 for women, respectively). Poor quality of life affected 4–12% across domains. Mental health, anthropometrics (waist-to-hip ratio, BMI), increased risk of cardiometabolic diseases and quality of life in physical, social and environmental domains did not differ by socioeconomic status (B, C, DE; all P>0.05). Poor psychological quality of life was more frequent among participants in higher socioeconomic status (B: 8%; C: 6%; DE: 4%, P = 0.0157). Linear regression analyses showed no statistically significant differences across socioeconomic status in depressive symptoms, anxiety symptoms, BMI, waist-to-hip ratio, or quality of life scores in any domain (all P>0.05).ConclusionsOur findings suggest that, among Brazilian adults living in moderate social vulnerability and classified within socioeconomic status B, C, and DE, mental health, BMI, waist-to-hip ratio, and quality-of-life indicators were similar across socioeconomic strata. However, these results should be interpreted as reflecting intra-group socioeconomic differences within a moderately vulnerable population and should not be generalized to individuals from the highest socioeconomic status.
<![CDATA[Expert explores fast-acting depression treatments, psilocybin trial pitfalls, and why stigma still limits buprenorphine access for opioid use disorder.]]>
Effects of Virtual Reality on Postoperative Pain Management Following Minimally Invasive Gynecologic Surgery: Randomized Controlled Trial
<strong>Background:</strong> Postoperative pain and anxiety remain common concerns after minimally invasive gynecologic surgery despite advances in surgical techniques and analgesic strategies. Virtual reality (VR) has been investigated as a potential nonpharmacological intervention for pain management; however, evidence in gynecologic postoperative settings is limited. <strong>Objective:</strong> This study aims to evaluate the efficacy and safety of VR technology compared with standard postoperative analgesia for pain and anxiety management in patients undergoing minimally invasive gynecologic surgery. <strong>Methods:</strong> This randomized controlled trial was conducted at Sun Yat-sen Memorial Hospital of Sun Yat-sen University in China. A total of 131 patients undergoing laparoscopy or combined hysteroscopy for benign gynecologic diseases were randomly assigned in a 1:1 ratio to either a VR group (n=68) or a control group (n=63). All patients received a standardized general anesthesia protocol intraoperatively. The control group received conventional analgesic therapy after surgery, and the VR group received a 20-minute VR intervention 6 hours postoperatively. The pain and anxiety levels were evaluated using a visual analog scale at 6 and 7 hours postoperatively. The primary outcome was the change in pain scores between 6 and 7 hours. Secondary outcomes included maximum pain score, anxiety score changes, length of hospital stay, hospitalization costs, and occurrence of adverse events. Analyses were performed according to the intention-to-treat principle. <strong>Results:</strong> There was no statistically significant difference in the primary outcome between the VR and control groups (mean difference 0.169, 95% CI −0.271 to 0.608; <i>P</i>=.45). Similarly, no significant differences were observed in the maximum pain score (mean difference 0.839, 95% CI −0.101 to 1.779; <i>P</i>=.08), and no improvement was observed in the anxiety score (mean difference 0.042, 95% CI −0.365 to 0.449; <i>P</i>=.84). No significant differences were found in length of hospital stay, hospitalization costs, or incidence of adverse events, including dizziness, nausea, and vomiting (all <i>P</i>>.05). <strong>Conclusions:</strong> A single 20-minute VR intervention did not provide additional analgesic or anxiolytic benefit compared with standard postoperative care after minimally invasive gynecologic surgery. VR was well tolerated, and its role in postoperative recovery requires further investigation. <strong>Trial Registration:</strong> Chinese Clinical Trial Registry ChiCTR2400091244; https://tinyurl.com/4b92a9td
From Alliance to Nexus: Rethinking Digital Therapeutic Relationships
In traditional human psychotherapy, the therapeutic alliance (TA) is regarded as a fundamental factor that describes the client-therapist relationship, mainly due to strong evidence demonstrating its impact on treatment outcomes regardless of theoretical orientation. More recently, advances in artificial intelligence (AI) and other technologies have led to the emergence of the concept of digital TA, used to characterize the relationship between clients and AI-based therapeutic systems. This approach replicates human dynamics but overlooks key differences between human therapists and digital agents. Prematurely translating the concept of TA into the digital context fails to address issues such as the sycophantic tendencies of current systems and the inherent limitations of algorithmic interaction. We propose the digital therapeutic nexus, a framework that recognizes these differences and provides a set of structured criteria for categorizing digital interactions into 3 progressive levels. This Viewpoint argues that only at the highest level can parallels be drawn to the human TA and stratifies the main risks associated with each nexus level. Transitioning from the concept of alliance to that of a nexus offers a more precise conceptual basis for describing and evaluating digital therapeutic relationships, with implications for research, design, and the ethical development of AI-based mental health interventions.
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Prediction of Clinically Significant Depressive Symptoms at 2-Year Follow-Up in Older Adults: Machine Learning Study Using the English Longitudinal Study of Ageing
Background: Depression in older adults is often underdiagnosed due to atypical symptom presentation and generational stigma, leading to delayed intervention. Early identification of individuals at risk of developing elevated depressive symptoms is therefore critical, but traditional approaches show limited predictive accuracy. To date, no study has applied machine learning (ML) models to predict clinically significant depressive symptoms at 2-year follow-up in older adults in the United Kingdom using data from the English Longitudinal Study of Ageing (ELSA). Moreover, the impact of encoding strategies for categorical health care variables has not been examined. Objective: This study aimed to develop and evaluate ML models to predict the clinically significant depressive symptoms at 2-year follow-up in older adults using ELSA data. We further compared ordinal and one-hot encoding strategies across different ML architectures and identified key predictors of depressive symptoms at follow-up. Methods: Data were drawn from 4 consecutive waves of ELSA, including participants aged ≥50 years without significant depressive symptoms at the baseline wave (waves 6‐9). Clinically significant depressive symptoms were defined as 8-item Center for Epidemiologic Studies Depression Scale (CES-D 8) scores of ≥4 at the subsequent wave (waves 7‐10). Over 120 features spanning sociodemographic, psychological, and health-related domains were analyzed. Eight ML models were applied, including tree-based ensembles, deep learning architectures for tabular data, distance-based methods, probabilistic methods, and linear methods. Model performance was assessed using the area under the receiver operating characteristic curve (AUROC) and -score. Model interpretability was examined using Shapley additive explanations (SHAP). Sensitivity analyses assessed the robustness of results across alternative CES-D 8 thresholds (≥3, ≥4, and ≥5) and encoding strategies. Results: Across waves, the best-performing models achieved mean AUROC scores of 0.72‐0.73, with a peak of 0.75 in the highest-performing wave. Ordinal encoding consistently outperformed one-hot encoding across all ML models, yielding improvements in AUROCs and -scores, with the greatest increase in tree-based methods. SHAP consistently identified loneliness, sleep disturbances, and low social engagement as strong predictors of elevated depressive symptoms at follow-up. Sensitivity analyses across CES-D 8 thresholds demonstrated robust feature importance, with AUROCs ranging from 0.67 to 0.82. Traditional ML models (random forest, extreme gradient boosting, and support vector machines) generally achieved higher performance than the deep learning models for this task. Conclusions: Our findings demonstrate the feasibility of predicting clinically significant depressive symptoms at 2-year follow-up in UK older adults, with moderate accuracy. Ordinal encoding demonstrates superior performance for health care datasets with inherently ordered categorical features. The identification of consistent risk factors highlights opportunities for developing targeted clinical screening tools and preventive interventions. This study provides new evidence on depressive symptom prediction in the UK context, leveraging longitudinal data from ELSA, and contributes to advancing digital mental health research for aging populations.
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