IntroductionAnxiety disorders are among the most frequent reasons for psychiatric emergency consultations, yet their identification remains challenging. Joint hypermobility syndrome has consistently been associated with anxiety in both clinical and community samples, but its usefulness in psychiatric emergency settings has not been investigated.AimTo investigate whether joint hypermobility is associated with anxiety in psychiatric emergency care, to examine its relationship with illness severity and global functioning, and to evaluate its predictive value for an anxiety diagnosis at discharge.Material and methodsThis prospective study included 400 consecutive patients attending the psychiatric emergency department of a general hospital. Participants were assessed using the Severity of Psychiatric Illness (SPI) scale, the Anxiety Screening Questionnaire (ASQ-15), the Global Assessment of Functioning (GAF) scale, and a validated self-administered questionnaire developed by Hakim and Grahame for joint hypermobility. Associations between joint hypermobility and anxiety diagnoses were examined using bivariate analyses (ANOVA and chi-squared test) and multivariable logistic regression.ResultsAt discharge, 61.2% of patients diagnosed with an anxiety disorder met criteria for joint hypermobility (score ≥3), compared with only 17.4% of patients with other diagnoses (χ² = 39.34, p < 0.0001). In the multivariable logistic regression model, joint hypermobility was independently associated with an anxiety diagnosis at discharge (OR = 4.70, 95% CI 2.31–9.56), together with lower psychiatric illness severity, and younger age. The final model showed good discriminative ability (AUC = 0.863). Joint hypermobility screening demonstrated a sensitivity of 68.1% and a specificity of 80.6% for anxiety disorders at discharge.ConclusionJoint hypermobility is associated with anxiety disorders in psychiatric emergency care and may provide a simple, low-cost clinical marker to support the identification of anxiety disorders in this setting. Further studies are warranted to confirm its diagnostic utility and generalizability.
Preliminary diagnostic performance of the MOXO continuous performance test in young adults undergoing ADHD assessment
IntroductionAttention-deficit/hyperactivity disorder (ADHD) diagnosis in young adults is often challenging due to symptom overlap with affective disorders and the inherent subjectivity of clinical evaluations. While Continuous Performance Tests (CPTs) provide objective metrics, their preliminary diagnostic performance and concordance with clinical evaluations relative to self-report questionnaires require evaluation in clinical settings. This study explored the diagnostic performance of the MOXO-CPT and formally examined its incremental predictive value beyond commonly used self-report measures in young adults assessed for ADHD.Materials and methodsA total of 118 young adults (aged 18–25 years) consecutively referred with attention-related complaints completed the MOXO-CPT and self-report scales (ASRS, WURS-25, STAI, RRS-SF). ADHD diagnoses were established via comprehensive semi-structured clinical interviews based on DSM-5 criteria by an experienced psychiatrist blinded to test and questionnaire scores. Multivariable logistic regression and Receiver Operating Characteristic (ROC) analyses evaluated independent predictors and discriminative performance relative to this clinical reference standard.ResultsADHD was diagnosed in 58.5% (n=69) of the cohort, while the remaining 41.5% (n=49) comprised a clinical comparison group predominantly presenting with alternative psychiatric conditions (63.3%). Participants with ADHD showed poorer performance across all MOXO-CPT indices (attention, timing, impulsivity, and hyperactivity) compared to the non-ADHD clinical comparison group. In multivariable modeling, average or above-average performance on the attention and hyperactivity indices was independently associated with a lower likelihood of ADHD diagnosis. ROC analysis indicated that the MOXO-CPT attention index demonstrated favorable discriminative capacity relative to the clinical diagnosis (AUC = 0.87, sensitivity = 81.2%, specificity = 85.7%), whereas other indices showed acceptable-to-poor discriminative performance.DiscussionIn this help-seeking sample of young adults, the MOXO-CPT attention index demonstrated promising discriminative ability in differentiating ADHD from a non-ADHD clinical comparison group predominantly presenting with anxiety and depressive disorders. These preliminary findings suggest that distractor-embedded continuous performance testing may serve as a useful objective adjunct for distinguishing ADHD from common psychiatric mimics in outpatient settings, rather than a stand-alone tool or a general screening instrument for healthy populations.
Effects of Transcranial Direct Current Stimulation for Enhancing Cognitive Function in Individuals With Autism Spectrum Disorder – A Pilot fMRI Study
Conditions: Transcranial Direct Current Stimulation; Autistic Spectrum Disorder; Functional Magnetic Resonance Imaging
Interventions: Device: Active-tDCS with computerized cognitive training; Device: Sham-tDCS with computerized cognitive training
Sponsors: The Hong Kong Polytechnic University
Recruiting
Interventions: Device: Active-tDCS with computerized cognitive training; Device: Sham-tDCS with computerized cognitive training
Sponsors: The Hong Kong Polytechnic University
Recruiting
IMPACT-Ready Study
Conditions: Autism Spectrum Disorder; Neurodevelopmental Disorders
Sponsors: Coalition for Aligning Science
Not yet recruiting
Sponsors: Coalition for Aligning Science
Not yet recruiting
Study of Anxiety Free Experiences at the Dentist
Conditions: Dental Phobia; Dental Anxiety in Children; Dental Fear; Dental Fear and Anxiety
Interventions: Behavioral: One-Session Treatment for Dental Phobia (OSTD); Behavioral: Psychoeducation and Relaxation Training (RELAX)
Sponsors: University of Texas Rio Grande Valley; National Institute of Dental and Craniofacial Research (NIDCR)
Recruiting
Interventions: Behavioral: One-Session Treatment for Dental Phobia (OSTD); Behavioral: Psychoeducation and Relaxation Training (RELAX)
Sponsors: University of Texas Rio Grande Valley; National Institute of Dental and Craniofacial Research (NIDCR)
Recruiting
A Co-Designed and Bilingual WhatsApp-Based Chatbot Intervention (PflegeBot) for Informal Caregivers in Germany: Single-Arm Nonrandomized Feasibility Study
Background: Informal caregivers play a central role in long-term care but experience elevated risks of stress, depressive symptoms, and caregiver burden, alongside barriers to accessing preventive support. Low-threshold digital public health interventions may offer scalable support; however, evidence on their feasibility, usability, and contextual fit remains limited, particularly for heterogeneous caregiver populations. Objective: This study describes the development and implementation of PflegeBot, an intersectionality-informed WhatsApp-based chatbot intervention, and evaluates its feasibility, usability, and acceptability among informal caregivers in Germany. Methods: A single-arm, nonrandomized feasibility study with pre-post assessments was conducted between December 2023 and March 2024. Informal caregivers aged 18 years and older were recruited via community-based, institutional, and online channels. PflegeBot was a co-designed, bilingual (German and Turkish) WhatsApp-based chatbot that delivered 84 scheduled messages over 12 weeks. Content included caregiving information, self-care, and cognitive behavioral therapy–informed self-help, plus optional frequently asked questions and question functions. Baseline and full follow-up assessments were administered online. Feasibility was assessed using indicators of recruitment, chatbot initiation and message delivery, opt-out, and provision of follow-up measures. Usability was assessed using the System Usability Scale (SUS), and acceptability was assessed using study-specific items. Exploratory outcomes included perceived stress (4-item Perceived Stress Scale [PSS-4]), caregiver burden (4-item Zarit Burden Interview [ZBI-4]), depressive symptoms (Center for Epidemiologic Studies Depression Scale [CES-D]), and loneliness (6-item De Jong Gierveld Loneliness Scale [DJGLS-6]). Analyses were descriptive; no hypothesis tests were conducted. Open-ended follow-up feedback was examined using a systematic inductive descriptive approach. Results: Of 102 participants included in the baseline analysis sample, 84 (82%) were women. According to chatbot log data, message delivery was initiated for 67 participants. Forty-nine participants provided at least one follow-up measure, and complete SUS data were available for 46 participants. The mean SUS score was 82.45 (SD 14.86, 95% CI 78.03‐86.86; range 47.5‐100), and 35 out of 46 (76%) participants scored at or above the benchmark of 68. Overall satisfaction with PflegeBot had a mean rating of 4.02 out of 5 (SD 0.98; n=46). Among participants responding to the relevant item, 1 out of 45 (2%) reported using the optional FAQ function. Mean changes were −0.57 (95% CI −1.24 to 0.10; n=35) for perceived stress, 0.81 (95% CI −0.02 to 1.63; n=36) for caregiver burden, −2.38 (95% CI −5.42 to 0.66; n=34) for depressive symptoms, and −0.39 (95% CI −0.90 to 0.12; n=36) for loneliness. Open-ended feedback highlighted needs for more flexible delivery, greater tailoring, and easier navigation. Conclusions: PflegeBot could be delivered through WhatsApp, and participants providing follow-up data reported high usability and generally favorable satisfaction. Controlled evaluations with objective engagement data and assessment of differential reach and outcomes are warranted.
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Depression Screening Positivity, Treatment-Seeking Intention, and Willingness to Take Antidepressants in a Self-Selected Online Sample of Korean Adults: Cross-Sectional Questionnaire Study
Background: Depression is a prevalent psychiatric condition with functional and socioeconomic consequences. Understanding the barriers to professional help-seeking and treatment acceptance among individuals with depressive symptoms is important. Objective: This study aimed to quantify depression screening positivity and examine treatment-seeking intention, willingness to use antidepressants, and perceived barriers among Korean adults, with attention to prior depression-related health care experiences. Methods: A cross-sectional online survey was conducted in South Korea (March 16-April 5, 2024) via paid social media advertising and messaging app invitations. A total of 1053 adults aged 20 years and older participated in this study. Depression screening was conducted using 2 Primary Care Evaluation of Mental Disorders–derived items, with the endorsement of either item defining a positive screen. History of depression diagnosis or treatment, intentions toward professional treatment, antidepressant use, and perceived barriers were assessed. Results: Overall, 65% (684/1053) of the participants had a positive depression screen. A positive depression screen was not associated with the intention to seek professional treatment for depression (adjusted odds ratio [aOR] 1.04, 95% CI 0.77‐1.41). Participants with a positive depression screen had lower odds of being willing to take antidepressants than those with a negative screen (aOR 0.73, 95% CI 0.54‐0.99). A within-participant analysis showed that the association of depression screening status differed between treatment-seeking intention and willingness to take antidepressants (ratio of odds ratios 0.70, 95% CI 0.53‐0.94; interaction =.02). The joint response of intending to seek treatment while being unwilling to take antidepressants was more common among participants with a positive than a negative depression screen (75/384, 11% vs 23/369, 6.2%; aOR 1.70, 95% CI 1.04‐2.77). A history of depression diagnosis or treatment was positively associated with treatment-seeking intention and willingness to use antidepressants. Among screen-positive adults, those without such a history more often reported that they would not seek treatment if diagnosed with depression (129/505, 25.5% vs 26/179, 14.5%; =.002) or would be unwilling to take antidepressants if recommended (154/505, 30.5% vs 29/179, 16.2%; <.001). Barrier profiles to treatment seeking differed by history of depression diagnosis or treatment (interaction <.001), whereas the patterns of reasons for unwillingness to take antidepressants did not differ according to history (interaction =.08). Conclusions: In this online survey sample, a positive depression screen was associated with a lower willingness to use antidepressants but not with treatment-seeking intention. Among screen-positive participants, those without prior depression-related health care experience had lower help-seeking intention and willingness to take antidepressants than those with prior contact, suggesting the need to reduce barriers to care and support earlier treatment initiation.
An Online Cross-Sectional Research Domain Criteria (RDoC) Positive Valence Assessment Study With Patients With a Severe Mental Illness: Methodological Evaluation
Background: Abnormal reward processing is considered a core feature of severe mental illness (SMI). Deficits in this domain can have severe implications for daily functioning. The Online Positive Valence Study aimed to assess reward processing in bipolar disorder and schizophrenia using the National Institute of Mental Health (NIMH) Research Domain Criteria (RDoC) Positive Valence Systems (PVS) framework in an online task-based study. Recruitment and study adherence fell short of expectations. Objective: This paper critically evaluates the methodology used and shares the lessons learned from conducting an online task-based study of reward processing in a sample of patients with SMI. Methods: Using a cross-sectional design, the Online Positive Valence Study measured reward processing using 3 reward tasks, the monetary incentive delay task (MID), effort expenditure of rewards task (EEfRT), and a social and coin version of the Bandit task. Participants were eligible if they were 18 years or older. They were recruited mainly via email from 2 completed prospective cohorts. From 2023, the initial recruitment goal was no longer followed. Recruitment strategies and task performance are evaluated. Results: The sample consisted of 319 participants: 186 patients (58.3%), 81 first-degree relatives (25.4%), and 52 controls (16.3%). Multinomial logistic regression analyses revealed participants who were additionally called were more than 4 times more likely to respond “no” (odds ratio [OR] 4.57, 95% CI 3.12 to 6.70, <.001) and more than twice as likely to respond “yes” (OR 2.75, 95% CI 1.93 to 3.92, <.001) versus no response compared with those who received only emails. Personal salutations in invitation mails reduced the likelihood of participation compared to nonpersonal salutations (OR 0.31, 95% CI 0.20 to 0.47, <.001). Analyses of covariance (ANCOVAs) and linear mixed effects models (LLMs) revealed task performance was comparable between in-lab and online groups. Online participants showed longer reaction times on the MID task (=20.43, SE=2.55, =8.02, <.001) and lower win-stay rates on both Bandits (Bandit Coin: =–0.55, 95% CI –0.68 to –0.42, SE=0.06, =–8.73, <.001, η² =.14; Bandit Social: =–0.65, 95% CI –0.80 to –0.49, SE=0.08, =–8.54, <.001, η² =.14). Conclusions: For the first time, we performed a remote online task-based assessment of the PVS domain in patients with SMI, and we learned important lessons along the way. Future studies should carefully consider recruiting from existing cohorts; hire full-time dedicated personnel; and use personal approaches to recruitment, like phone calls, adjusting recruitment to the target population(s), and making participation technically as simple as possible. Attrition may be reduced by shortening the duration of participation and/or adding gamification. This study offers guidance for future research in online cognitive assessment in patients with SMI.
Examining the Feasibility, Acceptability, and Preliminary Efficacy of a Health App for Postacute Pandemic Years in Managing Physical and Psychological Distress Symptoms: Pilot Quasi-Experimental Study
<strong>Background:</strong> Physical and psychological distress symptoms can adversely affect daily functioning and quality of life, highlighting the need for accessible self-management support. Although mobile health (mHealth) interventions show promise in supporting physical symptom management, evidence regarding their feasibility and potential effects on psychological distress remains limited. <strong>Objective:</strong> This pilot study aimed to evaluate the feasibility, acceptability, and preliminary efficacy of the health app for postacute pandemic years (HAPPY) for managing physical and psychological distress symptoms. <strong>Methods:</strong> A 2-arm, single-blind, quasi-experimental trial was conducted from July 2023 to January 2024. Thirty-eight participants experiencing distress symptoms related to COVID-19 were assigned to the experimental group or a waitlist control group. The experimental group received a 24-week mHealth intervention through the HAPPY app, which included an 8-week supervised phase with weekly face-to-face sessions and a 16-week self-management phase. The control group received no active treatment. Feasibility was assessed through recruitment, adherence, and adverse event monitoring, whereas preliminary efficacy was evaluated at 8 weeks (T1) and 24 weeks (T2) and compared with baseline (T0) using quantitative measures of distress, fatigue, sleep quality, pain, emotional regulation, and posttraumatic stress disorder (PTSD). <strong>Results:</strong> The study demonstrated the feasibility of the HAPPY app, with a recruitment rate of 88.37% (38/43), a dropout rate of 10.5% (4/38), and an adherence rate of 93.33% (14/15) for the supervised sessions. No adverse events were reported. Significant within-group improvements were observed for distress (Kessler Psychological Distress Scale [K10]; <i>P</i><.001), fatigue (Brief Fatigue Inventory–Chinese [BFI-C]; <i>P</i><.001), sleep quality (Chinese Pittsburgh Sleep Quality Index [CPSQI]; <i>P</i>=.009), and PTSD symptoms (Chinese Impact of Event Scale–Revised [CIES-R]; <i>P</i>=.02). However, between-group differences were limited. <strong>Conclusions:</strong> The study demonstrated the HAPPY app’s feasibility, acceptability, and potential efficacy for managing physical and psychological distress symptoms. High recruitment, retention, and adherence rates, along with measurable improvements in distress, fatigue, sleep quality, and pain, suggest the app’s promise as a scalable intervention. <strong>Trial Registration:</strong> ClinicalTrials.gov NCT05459896; https://clinicaltrials.gov/study/NCT05459896
Psychosocial Correlates of AI Chatbot Use for Emotional Support Among Young Adults: Cross-Sectional Study
<strong>Background:</strong> Generative AI chatbots are increasingly used for mental health–related purposes, yet little is known about the factors associated with such use or AI chatbot dependence. <strong>Objective:</strong> This study examined factors associated with young adults’ use of AI chatbots for emotional self-disclosure and mental health–related support, as well as the associations between AI chatbot use and dependence. <strong>Methods:</strong> A cross-sectional online survey of individuals aged 18 to 29 years was conducted in Japan. Self-report measures assessed psychosocial factors (self-esteem and loneliness), mental health symptoms (anxiety and depression), AI chatbot use (emotional self-disclosure and mental health–related support), and AI chatbot dependence (emotional dependence and social anxiety–related dependence). <strong>Results:</strong> Of 820 participants, 381 (46.5%) reported using AI chatbots for emotional self-disclosure at least once in the past month, including 65 (7.9%) who reported doing so every day or almost every day. In addition, 336 (41%) reported using AI chatbots for mental health–related support, including 53 (6.5%) who reported doing so every day or almost every day. Anxiety and depressive symptoms were combined into a composite measure of mental health symptoms because they are highly correlated. Multivariable logistic regression showed that greater mental health symptom severity, but not self-esteem or loneliness, was associated with both emotional self-disclosure (odds ratio [OR] 2.23, 95% CI 1.85-2.69; <i>P</i><.001) and mental health–related support (OR 2.42, 95% CI 2.01-2.94; <i>P</i><.001). Among emotional self-disclosure users (n=381), the frequency of emotional self-disclosure was positively associated with emotional dependence (β=0.334; <i>P</i><.001) and social anxiety–related dependence (β=0.307; <i>P</i><.001). Path analyses indicated that a model specifying psychosocial factors and mental health symptoms as antecedent variables to AI chatbot use and dependence fit the data better than an alternative model specifying AI chatbot use and dependence as the antecedent variables (comparative fit index [CFI]=0.994 vs 0.583; root mean square error of approximation [RMSEA]=0.033 vs 0.293). In this model, lower self-esteem and greater loneliness were associated with more severe mental health symptoms, which, in turn, were associated with greater AI chatbot dependence, primarily through direct pathways and, to a lesser extent, through more frequent emotional self-disclosure. Among emotional self-disclosure users, loneliness was the only significant psychosocial correlate of emotional dependence (<i>F</i><sub>1,369</sub>=7.78; <i>P</i>=.006). <strong>Conclusions:</strong> Emotional engagement with AI chatbots was common in this sample of young adults in Japan. Findings suggest that young adults experiencing mental health symptoms may be more likely to use AI chatbots for emotional self-disclosure and mental health–related support, while loneliness may be particularly relevant to emotional dependence among users. These findings highlight the need to understand AI chatbot use not only as a technological behavior but also as part of young adults’ broader emotional and help-seeking landscape.
