BackgroundNeuroimaging studies of internet gaming disorder (IGD) have primarily focused on reward-related and executive-control networks. However, sensory processing of addiction-related cues, particularly visual processing, may also contribute to IGD. Whether the intrinsic hierarchical organization of the visual system is altered remains unclear.MethodsThe study included 35 individuals with IGD and 30 healthy controls (HCs), with an overall age range of 9–33 years. The sample was predominantly composed of adolescents. An a priori three-level visual hierarchy model comprising the primary visual cortex (V1), lingual gyrus, and lateral occipital cortex (LOC) was constructed. Functional connectivity (FC) was calculated for the V1–Lingual, Lingual–LOC, and V1–LOC pathways. A hierarchical integration index (HII), derived from V1–LOC and V1–Lingual connectivity, was calculated to assess long-range relative to local visual coupling. Group differences were assessed using MANCOVA with follow-up univariate analyses and FDR correction. Within the IGD group, associations between IAT scores and all visual hierarchical measures were examined using Pearson and covariate-adjusted partial correlations with FDR correction.ResultsV1–LOC connectivity was significantly reduced in the IGD group compared with HCs (HC: 0.364 ± 0.132; IGD: 0.130 ± 0.189; F(1,59) = 30.809; FDR-corrected p < 0.001; partial η2 = 0.343). V1–Lingual and Lingual–LOC connectivity did not show significant group differences, although their effect sizes were small-to-moderate (Cohen’s d = 0.32 and 0.40, respectively). The HII was numerically lower in IGD but did not reach statistical significance (t = 1.90, p = 0.062; Cohen’s d = 0.46). Within the IGD group, lower V1–LOC connectivity was associated with higher IAT scores (r = −0.479, FDR-corrected p = 0.016), and this association remained significant after controlling for age, sex, education, and mean FD (partial r = −0.447, FDR-corrected p = 0.048).ConclusionsIGD is associated with altered long-range hierarchical connectivity within the visual system, particularly between early visual cortex and higher-order LOC. These findings provide a sensory-level perspective complementing reward- and control-centered accounts of IGD.
Association of Herpes Simplex Virus Type-1 With Dementia Outcomes: Longitudinal Retrospective Cohort Study Using Real-World Electronic Health Record Data
Background: Global dementia cases, currently exceeding 55 million, are projected to triple by 2050. In the absence of disease-modifying therapies, identifying modifiable risk factors is critical. Preclinical studies show that herpes simplex virus type-1 (HSV-1) is neurotropic and can drive amyloid-beta accumulation and tau hyperphosphorylation. Epidemiologic findings remain inconsistent, partly because many studies lack standardized designs for real-world data. Objective: To quantify the association between clinically coded HSV-1 diagnosis and incident cognitive impairment or dementia among patients receiving care in a health-system electronic health record (EHR) network. Methods: We assembled a retrospective cohort within an Observational Medical Outcomes Partnership (OMOP)–mapped EHR data lake (2010‐2024), comparing patients with a first HSV-1 diagnosis (n=6274) to those without HSV-1 codes but with parallel baseline criteria (n=379,975). Eligibility required at least 365 days of prior observation and absence of baseline cognitive, HIV, selected neurotropic viral, or recent transplant codes. The outcome combined mild cognitive impairment and Alzheimer disease and related dementias (ADRD). A high-dimensional propensity score (PS) incorporating approximately 17,000 baseline covariates was estimated with regularized logistic regression; 4 strata weights were applied in a Cox model. Sensitivity analyses examined equipoise trimming, doubly adjusted models, fixed 1-, 5-, and 10-year censoring horizons, and a dementia-only outcome subset. Negative-control outcomes (n=271) were prespecified to assess empirical calibration. Results: The HSV-1 cohort contributed 23,186 person-years (PY) and 469 events; the non-HSV-1 cohort contributed 1,519,827 PY and 24,764 events. Crude incidence was 20.23 (95% CI 18.44‐22.14) per 1000 PY in the HSV-1 cohort and 16.29 (95% CI 16.09‐16.50) in the non-HSV-1 cohort, an absolute difference of 3.94 events per 1000 PY. PS-stratified analysis yielded a hazard ratio (HR) of 1.14 (95% CI 1.03‐1.25; =.007). Estimates were comparable after equipoise trimming (HR 1.12, 95% CI 1.01‐1.25, =.04), doubly adjusted modeling (HR 1.13, 95% CI 1.02‐1.24, =.01), and fixed 5-year (=.008) and 10-year follow-up (=.004) (both HR 1.15). The 1-year censored model showed HR 1.00 (95% CI 0.84‐1.20; =.96). The dementia-only endpoint mirrored the primary analysis (HR 1.14, 95% CI 1.03‐1.25; =.008). No postindex events occurred for any negative-control outcome, so empirical calibration could not be performed and all estimates are uncalibrated. Conclusions: Within an OMOP-standardized EHR cohort, an HSV-1 diagnosis was associated with a small elevation in the hazard of subsequent cognitive impairment or dementia compared with individuals with no recorded HSV-1 diagnosis. Given the ubiquity of HSV-1, even a modest elevation in individual hazard could translate to a meaningful population-level increment if the association is causal. Confirmation in external data sets with laboratory viral typing, antiviral treatment records, and mortality linkage is warranted.
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Emerging Adults’ Experiences of Digital Measurement-Based Care in Routine Mental Health Care: Qualitative Study and Conceptual Synthesis
Background: Emerging adults (aged 18‐29 years) experience a high burden of mental health (MH) concerns during a developmental period marked by increasing autonomy and vulnerability to symptom onset. Many emerging adults face challenges in accessing and sustaining engagement with developmentally appropriate care. Digital measurement-based care (dMBC), which involves the routine use of patient-reported outcome measures (PROMs), has been introduced as an approach to support emerging adult engagement and improve responsiveness of care through ongoing monitoring and informed clinical decision-making. However, its integration into routine care remains variable, and there is limited understanding of how emerging adults experience and engage with dMBC in practice. Objective: This study aimed to examine how emerging adults experience dMBC within routine MH care and identify factors relevant to its use and integration in clinical practice. Methods: Using a descriptive qualitative design, semistructured interviews were conducted with 23 purposively sampled emerging adults who were either actively receiving care or had recently been discharged from 1 of 2 outpatient MH clinics in southern Alberta, Canada. dMBC was delivered through a web-based platform that enabled emerging adults to complete PROMs and view their results, which were also available to clinicians to inform care. All participants completed PROMs at baseline, with subsequent completion varying across participants and over the course of care. Interview data were analyzed using thematic analysis. Results: Four interconnected themes were identified and synthesized into a higher-level conceptual representation of emerging adults’ experiences with dMBC: technology, tracking, translation, and therapeutic guidance. Technology captured participants’ varied experiences with accessing and using the digital platform, including its usability and accessibility. Tracking reflected how monitoring PROM results over time supported reflection on changes in MH. Translation described how PROM data were interpreted and incorporated into therapeutic discussions, while therapeutic guidance reflected the role of clinician involvement in supporting the use of dMBC in care. Across the themes, participants described variation in the relevance and burden of measurement and in how consistently dMBC was integrated into clinical care. Conclusions: Emerging adults’ experiences of dMBC were shaped by both their interactions with digital measurement and the integration of PROMs into routine MH care. The findings highlight the importance of considering dMBC within the broader therapeutic context in which measurement occurs, rather than as a stand-alone digital activity. The conceptual synthesis provides a way of organizing these experiences and can inform future research and implementation efforts focused on the use of dMBC in emerging adult MH services.
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A Mobile App for Student Veterans With Co-Occurring Academic and Psychiatric Concerns: Pilot Usability and Feasibility Study
<strong>Background:</strong> Over 600,000 student veterans use military benefits to pursue higher education annually, with 75% enrolled as full-time students. Advancing their education is an important step toward improving their employment, financial, and social opportunities. However, student veterans also experience high rates of co-occurring psychiatric concerns like substance use disorder (SUD), posttraumatic stress disorder (PTSD), or depression. For these students, additional psychoeducation, support, and guidance may be required. To support their goals, a mobile app with targeted content for student veterans managing common psychiatric concerns could be particularly helpful. <strong>Objective:</strong> The primary aim of this pilot study was to iteratively revise and assess usability, acceptability, and feasibility of the VetEd mobile app and study procedures. The secondary aim was to explore preliminary changes from preapplication to postapplication use in academic functioning and community reintegration. <strong>Methods:</strong> This study used a mixed methods approach; pilot usability testing and iterative revisions were completed across 3 waves of participants (wave 1=4; wave 2=4; wave 3=5; total n=13). Usability was measured using the System Usability Scale (SUS), and acceptability was measured using the Acceptability E-Scale (AES). App use feasibility was collected through app engagement data from the 4 weeks of mobile app use. Study feasibility was assessed by rates of recruitment, retention, and survey completion. Secondary, exploratory measures to assess potential VetEd use outcomes included academic self-efficacy, perceived ability to cope with educational barriers, and community reintegration. Participants were also given the opportunity to complete an exit interview to provide additional feedback. <strong>Results:</strong> Study feasibility was high, with greater than projected rates of recruitment (4-5 per month), retention (13/13, 100%), and survey completion at all 3 time points (100%, 85%, and 100%, respectively). Overall, 85% (11/13) of both usability and acceptability scores were above the predefined benchmarks. Completion of assigned VetEd activities was high, with participants completing, on average, 90.8% of requested app activities. Secondary exploratory outcomes in academic self-efficacy, coping with educational barriers, and community reintegration were nonsignificant but showed feasibility for use in future fully powered randomized VetEd trials. Exit interviews highlighted that VetEd was easy to use, included pertinent information for both academic and mental health functioning, and had vital information on connecting to additional resources. <strong>Conclusions:</strong> Pilot findings suggested that the VetEd mobile app is usable and acceptable as an asynchronous resource for student veterans managing psychiatric concerns. Exit interviews suggested that veterans found app content useful, with relevant information and resources to support their academic functioning. Additional research is needed to assess its effectiveness, implementation, and impact on student veterans nationwide. <strong>Trial Registration:</strong> ClinicalTrials.gov NCT05344092: https://clinicaltrials.gov/study/NCT05344092
Therapist Skepticism and Adaptation to Teletherapy Under Enforced Uptake, With Theoretical Considerations for AI-Mediated Care: Qualitative Study
<strong>Background:</strong> Mental health care is undergoing rapid digital transformation, with continued development and implementation of digitally delivered interventions. Despite growing evidence for digital mental health interventions, implementation in routine practice has often lagged technological advances. Although teletherapy became more widely accepted during the COVID-19 pandemic, little is known about the psychological processes through which clinicians adapt to disruptive changes in treatment delivery when required to work within a novel medium. <strong>Objective:</strong> This study explored how therapists who had not previously adopted teletherapy interpreted and adapted to its enforced uptake during the COVID-19 pandemic, with particular attention to changes in expectations, perceptions of the therapeutic alliance, and professional practice. <strong>Methods:</strong> Six UK-based accredited clinical psychologists, none of whom had previously practiced video-based teletherapy, participated in semistructured interviews conducted between May and July 2021, following the rapid shift toward remote delivery. Data were analyzed using reflexive thematic analysis to explore therapists’ experiences of adaptation, belief revision, and therapeutic interactions. <strong>Results:</strong> We identified the following four themes: (1) revision of anticipatory beliefs, (2) context-medium differentiation, (3) medium affordances, and (4) relational viability and selective integration. Therapists began practicing teletherapy with concerns about accessibility, safety, therapeutic techniques, and relational quality. With sustained practice, clinicians revised many of their assumptions. Therapists also distinguished difficulties associated with implementation contexts from perceived properties of teletherapy itself. They described adapting clinical procedures and techniques, recognizing both constraints and affordances of the medium, and developing more differentiated views of when teletherapy was appropriate. Clinicians generally found teletherapy to be an acceptable therapeutic medium, but not equivalent to in-person practice. <strong>Conclusions:</strong> Adapting to teletherapy involved more than accepting a new tool. It required therapists to reconsider assumptions about therapeutic interaction, safety, and conditions needed to sustain an effective therapeutic relationship. The findings suggest an experience-based professional adaptation process in which initial assumptions became differentiated through sustained use. While these findings support teletherapy uptake specifically, they may also inform how clinicians evaluate other digital mental health technologies, while recognizing that changes to the communication medium are not equivalent to changes in the therapeutic process or agent.
Comparative efficacy of neuromodulation techniques for Alzheimer’s disease: a systematic review and network meta-analysis of randomized controlled trials
BackgroundNeuromodulation techniques (NMTs) have shown potential therapeutic value in Alzheimer’s disease (AD), but the comparative efficacy of different modalities remains unclear. This study aimed to systematically compare and rank available NMTs to identify their relative benefits across cognitive, functional, and neuropsychiatric outcomes.ObjectiveTo evaluate and rank the efficacy of NMTs in improving cognitive function, activities of daily living (ADLs), and neuropsychiatric symptoms in AD patients, thereby providing evidence-based guidance for clinical intervention strategies.MethodsEnglish-language literature was systematically searched in PubMed, Web of Science, Cochrane Library, and EMBASE from database inception to February 2026. Inclusion criteria were randomized controlled trials (RCTs) of AD patients aged ≥18 years. Interventions included repetitive transcranial magnetic stimulation (rTMS), transcranial alternating current stimulation (tACS), transcranial direct current stimulation (tDCS), photobiomodulation (PBM), transcutaneous electrical stimulation (TES), transcranial ultrasound stimulation (TUS), transcranial pulse stimulation (TPS), deep brain stimulation (DBS), and sham stimulation (Sham). Outcome measures included Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Alzheimer’ s Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), Alzheimer’ s Disease Cooperative Study-Activities of Daily Living (ADCS-ADL), Boston Naming Test (BNT), Neuropsychiatric Inventory (NPI), and Geriatric Depression Scale (GDS). Data extraction and risk-of-bias assessment followed Cochrane guidelines. Network meta-analysis (NMA) was conducted in Stata 17.0, with effect sizes ranked by the surface under the cumulative ranking curve (SUCRA).ResultsA total of 36 RCTs involving 1,445 patients were included in the analysis. Compared with Sham, TPS significantly improved MMSE (MD = 3.92, 95% CI: 1.57 to 6.35; SUCRA = 97.50%), MoCA (MD = 4.99, 95% CI: 2.26 to 7.72; SUCRA = 69.25%), and BNT scores (MD = 4.02, 95% CI: 1.81 to 6.23; SUCRA = 81.8%). rTMS also showed favorable effects on ADAS-Cog scores (MD = −11.10, 95% CI: −14.51 to −7.71; SUCRA = 91.00%). Regarding activities of daily living, TES ranked highest on the ADCS-ADL scale (SUCRA = 71.00%). In terms of neuropsychiatric symptoms, TPS achieved the highest ranking for improving NPI scores (SUCRA = 92.3%), whereas tACS showed the best performance on GDS scores (SUCRA = 69.5%).ConclusionNeuromodulation interventions demonstrated domain-specific benefits in AD, with no single approach showing universal superiority. TPS demonstrated the greatest potential for improving global cognitive outcomes, while rTMS showed advantages in ADAS-Cog performance. Nevertheless, limited sample sizes, heterogeneous stimulation protocols, and insufficient long-term evidence restrict the generalizability of current findings. Future multicenter RCTs with standardized protocols and prolonged follow-up are needed to confirm these results and guide clinical implementation.Systematic review registrationPROSPERO, CRD420261364193.
Large language models for late-life depression: a blinded benchmark of clinical safety, geriatric appropriateness, and triage
BackgroundGeneral-purpose large language models are increasingly used by patients and caregivers to obtain mental health information and guidance about when professional care is required. In late-life depression, broadly accurate information may nevertheless be unsafe when cognitive change, multimorbidity, frailty, polypharmacy, self-neglect, caregiver dependence, or suicide risk is not adequately recognized. This study compared the clinical accuracy, safety, geriatric-specific appropriateness, triage performance, and response consistency of three large language models when answering patient- and caregiver-centered questions about late-life depression.MethodsWe conducted a blinded, paired benchmarking study using 90 questions covering six geriatric psychiatry domains and equally distributed across low-, moderate-, and high-risk strata. Each question was submitted independently to GPT-5.5 Instant via ChatGPT, Gemini 3.5 Flash via Gemini, and Seed2.0 Pro via Doubao, generating 270 primary-round responses. A stratified subset of 30 questions was resubmitted in separate conversations to assess test-retest consistency, yielding 360 responses overall. Two psychiatrists independently evaluated anonymized outputs against prespecified item-specific reference standards, with clinically important disagreements adjudicated by a third senior psychiatrist. The primary outcome was the proportion of clinically acceptable responses, defined using accuracy, clinical safety, geriatric appropriateness, warning-sign recognition, and triage criteria.ResultsClinically acceptable responses were generated for 78.9% of questions by ChatGPT, 72.2% by Gemini, and 60.0% by Doubao (overall P<0.001). The difference between ChatGPT and Gemini was not statistically significant, whereas both outperformed Doubao. This model ranking remained unchanged under alternative core-safety and more stringent optimal-response definitions. Complete geriatric-specific appropriateness was achieved in 64.4%, 55.6%, and 43.3% of responses, respectively. Major safety errors occurred in 5.6% of ChatGPT responses, 10.0% of Gemini responses, and 16.7% of Doubao responses (raw P = 0.015; FDR-adjusted q=0.023). Performance declined substantially with increasing clinical risk. In exploratory post hoc caregiver-centered analyses, clinical acceptability was 76.7% for ChatGPT, 70.0% for Gemini, and 53.3% for Doubao, while explicit caregiver-directed action was present in 80.0%, 70.0%, and 53.3% of responses, respectively. Among high-risk questions, clinically acceptable response rates were 63.3%, 50.0%, and 36.7%, while under-triage occurred in 16.7%, 26.7%, and 36.7% of responses, respectively. Test-retest clinical consistency was highest for ChatGPT (90.0%), followed by Gemini (83.3%) and Doubao (73.3%).ConclusionsThe three models answered many late-life depression questions accurately and safely, but none demonstrated consistently reliable performance across complex or high-risk scenarios. Clinically important weaknesses involved geriatric-specific interpretation, recognition of indirect risk signals, crisis-response completeness, under-triage, and response stability. General-purpose large language models may support selected low-risk educational tasks but should not independently guide emergency triage, medication changes, suicide-risk management, or other safety-critical decisions in older adults.
Recovery-phase symptoms after COVID-19 infection and anxiety levels among college students
ObjectiveThis study examines the relationship between physical symptoms during the recovery phase after COVID-19 infection and anxiety levels among college students, with the aim of providing empirical evidence for post-pandemic mental health screening and health management in universities.MethodsThe study used online survey data collected from college students in March 2023. After excluding straight-line responses, 394 valid questionnaires were retained. Among 372 students with a clear infection status, we examined the association between confirmed COVID-19 infection and anxiety. Among 298 students with confirmed infection, we further analyzed the associations of the number of physical symptoms during recovery, recovery time, and specific physical symptoms with anxiety.ResultsConfirmed COVID-19 infection itself was not significantly associated with a higher anxiety level. Among infected students, however, the number of physical symptoms during recovery was positively associated with higher anxiety levels, whereas recovery time was not significantly associated with anxiety level. Analyses of specific symptoms showed that memory decline and chest pain were significantly associated with higher anxiety levels.ConclusionPost-infection mental health screening in universities should not focus only on whether students have been infected. Greater attention should be paid to the burden of physical symptoms during recovery. Symptom count, cognitive changes, and chest discomfort may serve as useful supplementary indicators for post-infection follow-up and psychological risk identification.
An Evidence-Based AI Virtual Assistant for Young People With Attention Deficit Hyperactivity Disorder: Co-Design and Prototype Development
<strong>Background:</strong> Though attention deficit hyperactivity disorder (ADHD) is thought to be the most prevalent neurodevelopmental disorder in young people worldwide, there are inequalities in access to psychoeducation and health care support. One way to improve access, potentially increase engagement, reduce health care inequalities, and enhance care is by co-developing digital responsive interventions. These have the potential to support long-term condition management and to act as an adjunct to usual care. Virtual assistants that use large language models can provide information in response to questions and learn to tailor communication to suit an individual user’s needs. This can be especially valuable for people with ADHD who often struggle to regulate attention and can experience communication challenges. Involving people with lived experience in the co-design process is crucial for the development of effective digital interventions. Therefore, this article explores the views and preferences of young people with ADHD and their supporters from the United Kingdom who collaborated with researchers to co-design a prototype chatbot. <strong>Objective:</strong> This study aimed to co-develop an evidence-based chatbot prototype, intended to help young people with ADHD thrive through improved access to health care information, psychoeducation, and self-management strategies. <strong>Methods:</strong> An interdisciplinary team was established, including researchers, software developers, clinicians, and lived experience collaborators. Research advisory and working groups were set up in ways that facilitated flexible involvement. Following the person-based approach, guiding principles were established, and workshops were held with young people with ADHD and supporters of young people with ADHD to co-develop an early prototype. Feedback was sought via think-aloud interviews with lived experience collaborators. <strong>Results:</strong> In total, 9 experts by lived experience and 3 health care professionals chose to engage in workshops, and this feedback informed the development of a SmartADHD chatbot prototype. An off-the-shelf chatbot (GPT-4o hosted on Convai) was trained using resources from the National Health Service (NHS). Overall, 6 experts by lived experience engaged with think-aloud interviews, providing feedback on the prototype conversational flow and feel, the avatar, the text-to-speech, the chatbox feature, and the content of the messages. Seven recommendations are made for future development, which will inform the SmartADHD program of work. <strong>Conclusions:</strong> These findings provide rich data on the preferences of people with ADHD. Specific recommendations for a chatbot for young adults with ADHD have not been investigated before with young people, making this study a novel contribution to the field. These findings provide an excellent foundation for chatbot development for this group and may be relevant for those developing digital tools for people with ADHD across the lifespan and other neurodevelopmental conditions. Further work is required to elucidate the views of health care professionals and identify the limits of the technology before subsequent evaluation. <strong>Trial Registration:</strong>
Tool or Companion? Reframing Conversational AI to Prevent Psychological Harm
People increasingly turn to conversational AI for companionship, emotional support, and well-being, using both purpose-built companion apps, such as Replika and Character.AI, and general-purpose assistants, such as ChatGPT and Claude. While some evidence suggests potential benefits, including short-term reductions in loneliness and mood improvement, several adverse outcomes have been reported in both clinical and nonclinical populations, including emotional dependence, exacerbation of symptoms, and self-harm. The fluent and apparently empathic responses from these models lead users to engage with them not only as tools but also as if they were social entities. This framing is conceptually misleading and may pose risks across different user profiles, particularly for vulnerable individuals. Drawing on research in AI, psychiatry, psychology, and network science, we highlight mechanisms through which emotional reliance develops and the boundary between tool and companion erodes. Design choices that evoke personality and warmth encourage users to anthropomorphize these systems. Simulated empathy, generated through probabilistic language patterns rather than genuine emotional experience, creates a structurally asymmetric interaction, in which the user discloses and the system responds, but without reciprocity, vulnerability, or accountability. Overvalidation and sycophancy can reinforce maladaptive cognitions, delusional ideation, and distorted perceptions of reality, as they tend to reinforce people’s beliefs, even at the expense of the accuracy of models’ responses. These mechanisms are not incidental: they emerge from alignment procedures that reward responses perceived as warm and empathic. The result is a self-reinforcing feedback loop between the model and the user that may amplify maladaptive beliefs, delusional ideation, and emotional distress, even in those who engage for largely functional purposes. Understanding these dynamics requires an examination of both what these agents can do—considering their technical limitations and implementations—and what humans believe they can do, including social and psychological impacts. We argue that conversational AI should be treated primarily as a tool supporting human systems rather than as a substitute for human relationships. Perhaps more importantly, reviewing the current hype surrounding AI interactions can help reformulate a paradigm that contributes to human well-being and societal value, while minimizing misconceptions, maladaptive interactions, or social disintegration.
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