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Diagnostic Discrimination of BOKE STARS, a Bimodal Continuous Performance Test, for Attention-Deficit/Hyperactivity Disorder Assessment in Chinese Children: Single-Center Case-Control Study

Background: Attention-deficit/hyperactivity disorder (ADHD) affects 6.3% of Chinese children, but only 10% are diagnosed, as diagnosis is hindered by low awareness and lack of culturally adapted, objective tools. Existing continuous performance tests are unimodal and lack validity. Objective: This study aimed to conduct an initial evaluation of the diagnostic discrimination of BOKE STARS (Sustained Task and Attention Response Screening), a culturally adapted bimodal continuous performance test, for distinguishing children with ADHD from typically developing children in a Chinese clinical setting. Methods: In this prospective, single-center diagnostic accuracy study with a case-control design, 100 children aged 6 to 12 years (n=50 with ADHD and n=50 controls) were recruited at Xinhua Hospital between January and May 2024. Parents completed the Swanson, Nolan, and Pelham Rating Scale–fourth version (SNAP-IV), and children completed the BOKE STARS assessment on a tablet device under standardized conditions. Group comparisons were conducted using independent-sample 2-tailed tests or Mann-Whitney tests, as appropriate. Receiver operating characteristic (ROC) curve analysis was performed in the full case-control sample to assess diagnostic discrimination. Sensitivity and specificity were reported descriptively across ROC-derived cutoffs; these cutoffs were not interpreted as clinically validated diagnostic thresholds. Secondary exploratory analyses included comparisons among ADHD subtypes and correlations between BOKE STARS indices and parent-reported SNAP-IV symptom severity scores. Results: Compared with controls, children with ADHD performed significantly worse on all major BOKE STARS indices, including errors of omission, errors of commission, reaction time, reaction time variability (RTV), discrimination prime, and total score. In the full case-control sample, the total score showed the strongest diagnostic discrimination (area under the ROC curve [AUC] 0.962, 95% CI 0.931-0.992), followed by RTV (AUC 0.919, 95% CI 0.867-0.971), errors of omission (AUC 0.884, 95% CI 0.818-0.950), and discrimination prime (AUC 0.819, 95% CI 0.737-0.900). Errors of commission (AUC 0.689, 95% CI 0.585-0.792) and reaction time (AUC 0.634, 95% CI 0.524-0.743) showed comparatively weaker discrimination. No significant differences were observed among ADHD subtypes. Several BOKE STARS indices were modestly correlated with SNAP-IV inattention and hyperactivity or impulsivity scores. Conclusions: BOKE STARS showed promising preliminary diagnostic discrimination for identifying Chinese children with ADHD in this case-control sample, with the total score and RTV showing the strongest discriminatory performance. However, because the case-control design artificially fixed the ratio of ADHD cases to controls, diagnostic performance estimates and exploratory cutoffs should be interpreted cautiously and should not be considered representative of real-world clinical diagnostic performance. BOKE STARS may serve as an adjunctive assessment tool to complement clinical interviews and caregiver-reported rating scales, but further external validation in larger and clinically heterogeneous populations is required before broader clinical implementation.
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Deprexis for Veteran Depression: Open-Label Pilot Trial Examining Feasibility, Acceptability, and Preliminary Efficacy

Background: Depression carries the highest burden of mental health–related disability in the United States. Approximately 13% of military veterans report elevated rates of depression. Despite the availability of evidence-based treatments for depression, nearly 50% of veterans in need of mental health care remain untreated. Internet-based interventions show promise in reducing this gap; however, there are currently no standard self-guided internet-based interventions for depressive symptoms in veterans. Deprexis is one such intervention that leverages cognitive behavioral therapy to target depressive symptoms. Objective: This pilot study evaluated the feasibility, acceptability, and preliminary effectiveness of Deprexis, a fully self-guided internet-based intervention for depression, in US military veterans with mild to severe depressive symptoms. Methods: This open-label pilot trial recruited 19 veterans with mild to severe depression (mean age 55.5, SD 8.2 y; baseline Quick Inventory of Depressive Symptomatology—Self-Report [QIDS-SR]: mean 16.2, SD 4.1) for an 8-week course of Deprexis, with self-report assessments at baseline, posttreatment (8 wk), and follow-up (16 wk). Primary outcomes included depressive symptoms (QIDS-SR), functional disability (World Health Organization Disability Assessment Schedule 2.0), and symptom-related disability (Sheehan Disability Scale). Feasibility was assessed through recruitment and retention rates, and acceptability was measured using validated questionnaires (Credibility and Expectancy Questionnaire and Client Satisfaction Questionnaire). Multilevel models examined change over time, with effect sizes calculated using pooled SDs from unconditional models. Results: Recruitment and retention targets were met, with 15 out of 19 (79%) participants meeting the adherence criteria (ie, ≥60 min of active program use). Of these, 14 participants completed posttreatment questionnaires and were included in the completer analyses. The program received a positive acceptability rating: of the 18 participants who completed follow-up assessments, 78% (n=14) rated services as good or excellent and 72% (n=13) were satisfied with the amount of help received. No safety concerns were reported. Among completers (n=14), QIDS-SR scores decreased from baseline to posttreatment (estimate −2.22, SE 1.44; =.14; =−0.54, 95% CI −1.07 to 0.13) and follow-up (estimate −2.85, SE 1.19; =.02; =−0.70, 95% CI −1.21 to −0.08) with moderate-to-large effect sizes. Effect sizes were similar in the total sample. Functioning (World Health Organization Disability Assessment Schedule 2.0) improved among completers at follow-up (estimate −8.09, SE 3.80; =.045; =−0.41, 95% CI −0.96 to −0.05). Disability (Sheehan Disability Scale) did not significantly improve from baseline to posttreatment or follow-up. Conclusions: This pilot trial demonstrates that Deprexis is feasible and acceptable for veterans with mild to severe depression, with preliminary evidence of effectiveness for depressive symptoms. The delayed emergence of functional improvements and sustained gains at follow-up support the potential of this scalable intervention. The results provide a strong foundation for the ongoing randomized controlled trial. Trial Registration: ClinicalTrials.gov NCT06217198; https://clinicaltrials.gov/study/NCT06217198 International Registered Report Identifier (IRRID): RR2-10.2196/59119
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Developing a Text Messaging Intervention to Increase Uptake of the Screening and Treatment for Anxiety and Depression Program Among Community College Students: Formative Study Using a Human-Centered Design Approach

Background: Community college (CC) students face significant mental health concerns but are unlikely to receive treatment. Barriers to mental health service uptake among CC students have been delineated, but few studies have identified strategies to improve uptake. Text messaging has been used to address engagement barriers to mental health services among adolescents and adults, but little research has explored this strategy for CC students. Objective: The goal of this study was to partner with CC students to co-design and conduct pilot usability testing of a text messaging intervention to address barriers and increase uptake of a mental health screening and treatment program, called Screening and Treatment for Anxiety and Depression (STAND), offered to CC students. Methods: We conducted 2 parallel sets of 4 co-design focus groups with CC students who had varying levels of engagement with STAND. We used rapid qualitative analysis to extract key themes, create text message prototypes and refine them, and present updated prototypes to gather feedback across workshops. We also assessed six usability factors on a 5-point Likert scale: satisfaction, helpfulness, attractiveness, readability, comprehension, and likelihood of getting started with STAND after receiving texts. Results: Key themes emerged about perceptions of texting, barriers to STAND, a basic framework for the text message intervention, feedback about the format of messages, and feedback about the content of messages. Students expressed positive regard for text messaging and general agreement on key barriers to STAND. Students codeveloped a framework for the intervention, including (1) delivering introductory texts to engage students in the text messages, (2) providing a personalized approach for students to select barriers most salient for them, and (3) delivering tailored content designed by students to address each barrier. Across workshops, several themes emerged with regard to how messages should be formatted and delivered, including the following: use short messages; use not too many messages; use relevant language; use images, memes, and short videos; and make messages “human-like.” Themes related to the content of messages included the following: reminders that you are not alone, knowledge that STAND has worked for other students, expressing understanding of student context and stressors, and providing an option to speak to a team member. Mean ratings on usability factors ranged from 3.88 (SD 0.64) to 4.25 (SD 0.46). Conclusions: This study describes a process for co-designing a text messaging mental health engagement intervention with CC students that is grounded in a human-centered design approach. Further research is needed to rigorously test this intervention and make iterative refinements to improve response and effectiveness.
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Optimizing Treatment Strategies in the Bipolar Disorder Spectrum With Classical AI Approaches: Systematic Review of Performance, Bias, and Clinical Applicability

Background: Bipolar disorder (BD) is a complex and heterogeneous psychiatric condition, characterized by fluctuating clinical courses that affect approximately 1%‐2% of the global population in their lifetime. Despite pharmacological advances, treatment response varies significantly among patients, making the identification of individualized treatment strategies a major challenge. Artificial Intelligence (AI), through its classical approaches, has emerged as a powerful tool in precision psychiatry to identify subtle patterns in complex data and inform personalized clinical decisions. Objective: The present systematic review aimed to examine the current evidence on classical AI-supported treatment optimization in the BD spectrum. Methods: The review was conducted in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines. Four databases (PubMed, Web of Science, Scopus, and Embase) were searched for original studies published after 2015 on the application of classical AI in the treatment of BD in adult patients. Publication bias was evaluated by visual inspection of a funnel plot. The methodological quality, risk of bias, and clinical applicability of the predictive models were assessed using the Prediction Model Risk Of Bias Assessment Tool for prediction models using regression or AI methods (PROBAST+AI; PROBAST+AI Working Group) tool. Results: A total of 35 studies were included and classified into 5 outcome-based categories, including acute symptomatic response, long-term maintenance response, relapse and readmission risk, safety and dose optimization, and brain aging and phenotyping. Acute symptomatic response models performed modestly (pooled area under the curve [AUC] 0.68), while imaging improved accuracy (74%‐77%). Long-term maintenance response models showed moderate-to-high performance (pooled AUC 0.80), with biomarker- and cellular-based models reaching 96%‐99% accuracy. Relapse and readmission prediction achieved a pooled AUC of 0.71, with digital phenotyping and rule-based methods performing best (AUC 0.85‐0.88). Safety and dose optimization models achieved 85%‐97% accuracy. Brain aging and phenotyping studies highlighted accelerated brain aging in BD, partially mitigated by lithium, and revealed novel data-driven subgroups. However, 3 studies were considered at high risk of bias due to small sample sizes associated with disproportionately high-performance estimates. An additional study was identified as potentially biased because it lay markedly distant from the funnel plot’s confidence line. Finally, the PROBAST+AI assessment revealed a high risk of bias in most studies, primarily due to data analysis limitations, small sample sizes, and lack of external validation. Conclusions: The adoption of classical AI tools in BD serves as a driver for therapeutic optimization, although current AI tools in BD should still be considered exploratory rather than ready for clinical use. Effective implementation in real-world clinical scenarios requires more robust, transparent, and externally validated models to ensure reliability and generalizability.
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Digital Reassurance Seeking in OCD

– by Jordan Karr, PhD

We all need reassurance once in a while. Receiving reassurance from a friend, loved one, or expert can reduce short-term distress, foster a sense of connection, and help us move forward in a productive way. On the other hand, excessive reassurance seeking can lead to a painful cycle of stress and doubt. For individuals with obsessive-compulsive disorder (OCD), reassurance is fleeting and is quickly followed by a resurgence of perceived threat and a compelling drive to seek additional reassurance.

As an OCD and anxiety specialist, I am no stranger to reassurance traps. I see them in the patient who repeatedly consults doctors but never fully trusts their answers; the partner who keeps asking, “Do you still love me?” while scrutinizing every response; and the teenager who needs her homework checked repeatedly but does not learn to tolerate uncertainty. While the content of excessive reassurance seeking may vary, its function remains the same, relieving anxiety momentarily while allowing obsessions to rebound more strongly in the long run. In each example, we see an individual desperately trying to protect something they hold dear while being misled by one of OCD’s most convincing lines: “What if this time the reassurance sticks?”

Psychologists have long argued that excessive reassurance seeking helps maintain OCD, anxiety, and depression (Abramowitz et al., 2002; Burns et al., 2006). What is new is the landscape. Today, reassurance is available instantly and endlessly through search engines, medical websites, social media, and artificial intelligence tools. Emerging research suggests that online reassurance seeking may be as prevalent as interpersonal reassurance seeking (Parsons & Alden, 2022). These digital reassurance traps present in a variety of forms, including:

  • Excessive symptom-checking on WebMD
  • Checking a loved one’s location on Find My Friends to make sure they are still alive or where they promised they would be
  • Asking Google Gemini whether an intrusive thought makes you a monster, a pedophile, or a bad Christian, Muslim, or Jew
  • Analyzing the contents of a partner’s Instagram to see whether their feelings have changed
  • Endlessly searching Reddit for answers to existential questions
  • Obsessively checking likes and read receipts to monitor the durability of a relationship
  • Finding creative ways to ask ChatGPT whether you might be responsible for spreading a virus or causing someone harm
  • Compulsively checking the news to confirm whether a feared event has taken place

Why do some individuals seek reassurance primarily from others in face-to-face contexts while others turn to the internet? Findings from one study suggest that individuals may be more likely to seek interpersonal reassurance when they desire emotional support, whereas online reassurance seeking is more likely when individuals feel ashamed or fear judgment from others (Parsons et al., 2025). In the same study, shame was reported more frequently among individuals with OCD. The perceived anonymity of the internet creates a compelling environment for seeking reassurance about our most distressing fears and the fears we feel ashamed to have.

Wait, hold on… shouldn’t having access to all the information on the internet be empowering? After all, there’s that famous saying, “Knowledge is Power.” Well I’m not sure what Francis Bacon would say if he could scroll on TikTok, but in the age of the internet, more information does not always mean more power or knowledge. In fact, information overload seems to trigger excessive reassurance seeking online (Yang & Luo, 2024). Once digital algorithms detect health-related concerns, users may be exposed to increasingly frequent and targeted content, further amplifying health anxiety and driving additional reassurance seeking online (Zhang et al., 2024).

Despite these challenges, evidence-based treatments offer hope. Exposure and response prevention (ERP), the gold-standard treatment for OCD, helps individuals tolerate uncertainty and break free from compulsive behaviors. ERP therapists are prepared to respond to clients who compulsively seek reassurance while taking care to avoid reinforcing a client’s anxiety and setting boundaries when appropriate. On the other hand, AI chatbots are available 24/7 and will continue to reassure users when it would be clear to a skilled therapist that more reassurance is harmful. Some helpful activities I have encouraged clients to try include:

  • Going for a walk and leaving your phone behind
  • When you have the urge to seek reassurance, use a timer to delay. Start with 5 minutes and gradually increase the time as you go.
  • Imaginal exposure: Writing out OCD’s worst case scenario while refraining from seeking reassurance.
  • Embracing the uncertainty: When you have the urge to seek reassurance, lean into the uncertainty by responding “maybe that will happen, maybe not.”
  • Watch a movie that triggers obsessions but leave your phone in the other room
  • Try a fast from social media. Start with a short fast and increase the length of each fast as you gain confidence.
  • Agreeing with the obsessions: Whatever your OCD throws at you, respond by saying “Sure, that is true!”

Clinicians working with youth should also attend to parental accommodations that inadvertently facilitate online reassurance seeking. Supportive Parenting for Anxious Childhood Emotions (SPACE) is an evidence-based, parent-focused intervention that emphasizes increasing supportive statements while reducing unhelpful accommodations. Setting reasonable limits on smartphone use while responding with empathy and confidence can help youth build resilience and independence (i.e. “I know it’s tough to be away from your phone and I know you got this!”).

Finally, because shame plays a central role in digital reassurance traps, incorporating self-compassion practices may be beneficial. Compassion-focused exercises help individuals respond to their struggles with kindness rather than self-criticism, complementing ERP by fostering emotional resilience. I sometimes ask clients to imagine that a close friend or loved one is feeling ashamed because they are experiencing obsessions and are stuck in an OCD loop. Then, I invite them to write down how they would support this friend while paying special attention to how compassion feels in their body. By practicing compassion for others, we strengthen the same muscles in our brains that help us turn compassion inward.

If you are getting stuck in digital reassurance traps, you are not alone! Many of these technologies are brand new and we are learning how to integrate them into our lives in a healthy way. If you need help managing compulsive online habits, finding a therapist trained in ERP could be a useful step!

References

Abramowitz, J. S., Schwartz, S. A., & Whiteside, S. P. (2002). A contemporary conceptual model of hypochondriasis. Mayo Clinic Proceedings, 77(12), 1323–1330. https://doi.org/10.4065/77.12.1323

Burns, A. B., Brown, J. S., Plant, E. A., Sachs-Ericsson, N., & Joiner, T. E., Jr. (2006). On the specific depressotypic nature of excessive reassurance-seeking. Personality and Individual Differences, 40(1), 135–145. https://doi.org/10.1016/j.paid.2005.05.019

Parsons, C. A., & Alden, L. E. (2022). Online reassurance-seeking and relationships with obsessive-compulsive symptoms, shame, and fear of self. Journal of Obsessive-Compulsive and Related Disorders, 33, 100714. https://doi.org/10.1016/j.jocrd.2022.100714

Parsons, C. A., Kim, H. J., Singh, S., Lkhagva, T., Wang, J., & Alden, L. E. (2025). Covert or connected: Motivations for online and interpersonal reassurance-seeking in OCD. Journal of Anxiety Disorders, 115, 103057. https://doi.org/10.1016/j.janxdis.2025.103057

Yang, X., & Luo, X. (2024). Unpacking cyberchondria: The roles of online health information seeking, health information overload, and health misperceptions. Telematics and Informatics, 97, 102225.

Zhang, X., Zheng, H., Zeng, Y., Zou, J., & Zhao, L. (2024). Exploring how health-related advertising interference contributes to the development of cyberchondria: A stressor–strain–outcome approach. BMC Public Health, 24, 534.

Jordan Karr, PhD, is the owner of River Falls Therapy in Portland, OR. He is a licensed psychologist in Oregon and Virginia, and specializes in evidence-based therapies for OCD and anxiety disorders. Dr. Karr has experience working in outpatient, community-based, and school-based settings.

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Curcumin attenuates α-synuclein pathology in Parkinson’s disease model mice through modulation of UBC9-associated SUMOylation signaling

BackgroundPost-translational modifications, particularly SUMOylation, plays a crucial role in α-synuclein (α-syn) aggregation, a key pathological feature of Parkinson’s disease (PD). Curcumin, a natural polyphenol, has shown neuroprotective potential, but its effects on SUMOylation-related signaling in PD remain unclear.ObjectiveThis study aimed to investigate whether curcumin modulates α-syn SUMOylation and to elucidate the underlying molecular mechanisms in PD model mice.MethodsA PD model was established in male C57BL/6 mice via unilateral intrastriatal injection of α-syn preformed fibrils (PFFs). Six months after α-syn PFFs injection, mice were treated intravenously with curcumin (25 mg/kg/day) or vehicle for 1 month. Behavioral tests (open field, rotarod) assessed motor function. Neuropathology was evaluated by immunohistochemistry and western blotting for tyrosine hydroxylase (TH), phosphorylated α-syn (p-syn), SUMOylation pathway components (SUMO1, SAE2, UBC9, PIAS1/2), and ubiquitin. Striatal dopamine levels were measured by HPLC.ResultsCurcumin treatment ameliorated motor deficits and anxiety-like behaviors in PD mice. It partially preserved dopaminergic neurons and reduced p-syn aggregation in the substantia nigra, accompanied by increased striatal dopamine levels. Mechanistically, curcumin was associated with reduced SUMO1 and increased ubiquitin levels, suggesting modulation of SUMOylation-related signaling. Among SUMOylation enzymes, UBC9 expression was decreased, whereas E1 (SAE2) and E3 (PIAS1/2) components were not substantially affected.ConclusionOur findings demonstrated that curcumin exerted neuroprotective effects in a PD model by attenuating α-syn pathology. The protective mechanism involves the inhibition of α-syn SUMOylation, primarily through the downregulation of the UBC9 enzyme. This study identifies UBC9-mediated SUMOylation as a potential target for curcumin and highlight a promising strategy for modifying α-syn-associated pathology in PD.
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Subcortical gray matter atrophy and iron deposition in patients with vascular dementia: a multimodal MRI study

PurposeVascular dementia (VAD) is the second most common type of dementia worldwide. Therefore, early detection and diagnosis, along with a clear understanding of its pathogenesis are critical for mitigating disease progression. In the present study, we aimed to elucidate the associations of brain volume and iron deposition with VAD based on structural brain and iron content analyses.MethodsFifty-three patients with VAD and 43 control participants were recruited for this study. All participants underwent the Mini-Mental State Examination (MMSE) and brain MRI scans. This study primarily focused on the volume of specific brain regions (assessed using FreeSurfer) and iron deposition (evaluated using quantitative susceptibility mapping [QSM]). Linear regression analysis was also performed.ResultsPatients with VAD exhibited significant reductions in brain volume in the left putamen (β = −0.342, 95% CI: −0.581 to −0.104), left pallidum (β = −0.099, 95% CI: −0.187 to −0.001), left hippocampus (β = −0.138, 95% CI: −0.271 to −0.004), and right hippocampus (β = −0.235, 95% CI: −0.420 to −0.051). Additionally, significant increases in iron levels were identified in the left (β = 0.006, 95% CI: 0.002 to 0.010) and right (β = 0.005, 95% CI: 0.001 to 0.009) hippocampus.ConclusionsThese findings indicate that brain volume reduction and increased iron levels in specific regions may be associated with cognitive deficits in patients with VAD.
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Illness perception, family resilience, and emotional distress among hospitalized older adults with multimorbidity in Xinjiang, China: a latent profile and mediation analysis

BackgroundOlder adults with multimorbidity frequently encounter significant psychological challenges, with negative illness perception being a prevalent issue. Such perceptions can intensify emotional distress. Family resilience—the ability of a family system to adapt positively to adversity—plays a crucial role in alleviating negative emotions, including anxiety and depression. This study aimed to investigate the heterogeneity of illness perception among older patients with multimorbidity and to assess the mediating effect of family resilience on the relationship between illness perception and emotional distress.Materials and MethodsBetween October 2025 and January 2026, 420 multimorbid older patients were recruited in three tertiary hospitals of Xinjiang Province. The evaluation was done based on the Brief Illness Perception Questionnaire, the Chinese version of the Family Resilience Assessment Scale, and the Hospital Anxiety and Depression Scale. The two methods of analysis were the latent profile analysis used to determine the unique patterns of illness perception and the bootstrap-based mediation analysis to determine whether family resilience mediates.ResultsThree distinct illness perception profiles were identified: low (32.6%), moderate (47.6%), and high (19.8%) illness perceptions. Using the low illness perception group as the reference, family resilience showed a significant partial mediating effect between moderate illness perception and anxiety (indirect effect = 0.510, 95% CI: 0.325–0.724), moderate illness perception and depression (indirect effect = 0.450, 95% CI: 0.283–0.631), high illness perception and anxiety (indirect effect = 1.263, 95% CI: 0.819–1.739), and high illness perception and depression (indirect effect = 1.114, 95% CI: 0.707–1.555).DiscussionThe results demonstrated heterogeneity in the perception of illness among older multimorbid patients, as a substantial percentage of the sample had moderate-to-high levels. Family resilience played a major partial mediating role between illness perception and emotional distress. The findings suggest the significance of shifting the clinical emphasis to the family system and integrating family resilience improvement as one of the psychological support measures for chronic patients.