Tag: Academic research

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Willingness of Patients With Mental Disorders to Engage in Online Psychotherapy: Multicenter Cross-Sectional Survey

<strong>Background:</strong> China faces a high prevalence of mental disorders but low treatment uptake, a gap driven by limited awareness and unevenly distributed mental health resources. While online psychotherapy has the potential to expand access, patient willingness remains insufficiently explored. <strong>Objective:</strong> This study aimed to investigate the willingness of Chinese patients with mental disorders to engage in online psychotherapy and to identify associated factors. <strong>Methods:</strong> A multicenter, cross-sectional survey was conducted using a structured questionnaire to assess the attitudes and willingness of patients with mental disorders in China to engage in online psychotherapy. Willingness to engage in online psychotherapy was assessed using a 0 to 100 rating scale, with higher scores indicating greater willingness. Univariate analysis, correlation analysis, and multivariate linear regression analyses were used to identify factors influencing willingness. <strong>Results:</strong> Among 361 eligible participants, the mean willingness score for online psychotherapy was 70 (SD 28.56). In total, 86.4% (n=312) of participants preferred short-term therapy (1 to 10 sessions), while 92.5% (n=334) expected the cost per session to remain less than CNY ¥400 (US $55.50). Participants most preferred therapist-guided online individual therapy (n=142, 39.3%). Convenience (124/361, 34.3%) and perceived anonymity (“no one will know about the illness”; 119/361, 33.0%) were the 2 most commonly reported perceived benefits of online psychotherapy. The leading barrier was concerns about data security and privacy (108/303, 35.6%), followed by difficulty in establishing therapeutic rapport (60/303, 19.8%). The regression analysis revealed that age, self-stigma, satisfaction with current psychiatric medications, and satisfaction with previous online psychotherapy significantly influenced patients’ willingness to seek online psychotherapy. <strong>Conclusions:</strong> This multicenter study reveals a high level of willingness to engage in online psychotherapy among Chinese patients, with self-stigma as a key barrier. These findings support the development of tailored services, stigma reduction interventions, and infrastructure investment to enhance mental health care delivery.
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Strength of Evidence to Support Decision-Making on the Use of Digital Mental Health Technologies in NICE Evaluations: Cross-Sectional Analysis of Studies

Background: Digital mental health technologies (DMHTs) are playing an increasing role in mental health services. The quality of evidence for DMHTs is variable, and there are concerns that evidence is not sufficient to support decision-making. Objective: This study used a cross-sectional analysis of evidence supporting DMHTs included in National Institute for Health and Care Excellence (NICE) evaluations to examine the strength of evidence available for decision-making. Methods: We identified all NICE evaluations relating to DMHTs by reviewing details of published NICE evaluations on the NICE website. From each of these evaluations, we identified included DMHTs and reviewed committee documentation to identify studies that provided supporting evidence for each of these technologies. We extracted information on a series of items relating to study quality and summarized the characteristics of evidence both at the level of individual studies and across the package of evidence from multiple studies supporting DMHTs. We also identified key evidence gaps in available evidence. Results: We included nine NICE evaluations relating to anxiety, depression, psychosis, insomnia, attention deficit hyperactivity disorder (ADHD), and tic disorders. These evaluations included 30 DMHTs and referenced 78 supporting studies. We identified common evidence gaps relating to effectiveness compared to relevant comparators, use of appropriate outcomes, including health-related quality of life, cost of delivery, and impact on resource use, and reporting of adverse events. Conclusions: Our study highlights that some DMHTs have been supported by high-quality studies and that evidence to support DMHTs is likely to be developed across a series of studies. However, there are often key evidence gaps that need to be addressed to provide a stronger case for adoption. Developers should ensure that they consider these gaps while planning evidence generation, and where possible, address them earlier in the product lifecycle.
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A Gamified Pain Management Intervention for Adults With Chronic Pain in Mainland China: Single-Arm Pre-Post Pilot Study With Machine Learning Predictive Modeling

Background: The widespread prevalence of chronic pain (CP) significantly impacts daily functioning worldwide. In mainland China, maintaining engagement in biopsychosocial interventions remains challenging. Gamification, designed based on self-determination theory, can enhance motivation, while machine learning (ML) algorithms can assist clinicians in dynamically optimizing pain management. Objective: This study aimed to (1) evaluate the preliminary effectiveness of a gamified pain management (GPM) program on CP and psychological outcomes and (2) identify key factors of significant pain improvements through the application of ML to guide intervention adjustments. Methods: A single-arm, pre-post study was conducted with 16 participants with CP in mainland China, recruited via social media using convenience sampling. Participants engaged in a 10-week web-based GPM intervention consisting of education, physical activities, and gamified elements, including points, avatars, and feedback. Primary outcomes were pain intensity and interference measured by the Brief Pain Inventory. Secondary outcomes included anxiety, depression, and quality of life. Analysis included paired tests, and ML models were trained to predict clinically meaningful pain reductions. Shapley additive explanations, least absolute shrinkage and selection operator regression, association rule mining, and Kaplan-Meier survival analysis were used to identify key predictors and optimal sessions and intervention durations across subgroups. Results: A total of 16 participants were engaged, with a mean age of 27.63 (SD 9.584) years. Results from paired tests reported significant improvements in pain intensity (decreased by 27.3%, 95% CI 1.061 to 3.064; =.001), pain interference (decreased by 27.3%, 95% CI 8.159-17.216; <.001), and psychological distress, including anxiety (=3.538, 95% CI 0.969 to 3.906; =.003) and depression (=4.559, 95% CI 2.230 to 6.145; <.001). The gradient boosting model demonstrated the highest predictive accuracy (area under the curve=0.89 and accuracy=0.82). Least absolute shrinkage and selection operator regression identified session 3 (β=−0.45, 95% CI −0.68 to −0.22; <.001) and session 5 (β=−0.32, 95% CI −0.59 to −0.05; =.02) as most predictive of clinical success, while association rule mining revealed effective session combinations for different patient subgroups. Time-to-event analyses indicated that individuals with low back pain and higher baseline severity required longer intervention durations for improvement (5 wk; =.03). Conclusions: This pilot study presents an innovative method that combines ML with dynamic engagement data from a GPM program during interventions, rather than relying on static baseline data in prior studies. The results show preliminary efficacy and identify specific optimal session combinations and personalized treatment durations for different pain subgroups. These exploratory findings contribute to the field by providing a data-driven method for adaptive, personalized digital health interventions that move beyond one-size-fits-all strategies, potentially enabling clinicians to modify content and dosage to improve engagement and outcomes if validated in larger sample trials. Trial Registration: Chinese Clinical Trial Registry ChiCTR2400094247; https://www.chictr.org.cn/showprojEN.html?proj=245138
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Synaptic remodeling and the female depression exposome: a mini-review of neuroendocrine, epigenetic, and social determinants

Depression is a multifactorial, chronic disorder and represents a leading cause of disability, with women exhibiting nearly twice the lifetime prevalence compared to men. Growing evidence indicates that this disparity cannot be explained by hormonal or psychosocial factors, but rather by dynamic interactions between environmental exposures, neuroendocrine signaling, and epigenetic regulation across development. This mini-narrative review aimed to examine how sex-specific exposome components interact with epigenetic mechanisms and synaptic remodeling processes to influence vulnerability to Major Depressive Disorder in women. The reviewed evidence demonstrates that fluctuations in ovarian hormones modulate HPA axis responsivity, neuroinflammatory signaling, and glutamatergic transmission through epigenetic regulation of stress-responsive genes such as NR3C1, SLC6A4, and BDNF, consequently influencing synaptic remodeling within corticolimbic circuits. Environmental and social exposures, particularly early-life adversity and psychosocial stressors, further interact with microglial activation and chromatin remodeling to produce long-lasting alterations in hippocampal and prefrontal plasticity. Collectively, these findings support a model in which sex-dependent neuroendocrine sensitivity amplifies exposome-driven epigenetic programming across the lifespan. Future research directions emerging from this synthesis include longitudinal life-course studies integrating multi-omic biomarkers, quantitative exposome assessment, and neuroimaging approaches to identify modifiable environmental targets and advance precision, sex-informed preventive and therapeutic strategies in depression.
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Stage-specific ERP correlates of audiovisual facial emotion processing across depressive tendencies

Emotional dysregulation can emerge as early as the initial stages of depression. This study aimed to examine event-related potential characteristics during the perception of negative, positive, and neutral facial expressions in healthy individuals across depressive tendencies. Twenty-six healthy participants underwent ERP measurements during emotion recognition using a facial emotion recognition task in visual and audiovisual modalities. The Emotion Regulation Questionnaire (ERQ), the Difficulties in Emotion Regulation Scale (DERS-16), and the Beck Depression Inventory II (BDI-II) assessed cognitive strategy, emotion regulation difficulties, and depression severity, respectively. Facial affect elicited larger amplitudes compared to neutral faces, from the N170 and early posterior negativity (EPN) in the temporo-occipital region to the late positive potential (LPP) in the centroparietal region. Under audiovisual conditions, P1 peak latency to negative stimuli in the temporal region exhibited significant negative correlations with DERS-16 and BDI-II scores. N170 peak latency to positive stimuli also demonstrated a significant negative correlation with BDI-II scores. Under visual conditions, EPN amplitude to negative stimuli in the occipital region exhibited a significant positive correlation with BDI-II scores. P1 and N170 latencies, or neural response speeds, and EPN amplitude, which represents emotional reaction strength, correlate with depressive tendencies in healthy individuals. These early components function as initial neural signals that may serve as electrophysiological markers of abnormal emotional processing within neuropsychological functions prior to clinical depression.
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Vitamin A status is associated with sleep, clock genes, and symptoms in children with autism spectrum disorder

BackgroundVitamin A signals through retinoic acid receptors and may influence neurodevelopment and the expression of clock genes. However, the biological pathway linking vitamin A status to sleep disturbance in ASD remains insufficiently defined. This study aimed to examine associations between vitamin A status and sleep problems, core symptoms, and clock genes in children with ASD, and to explore the mechanistic role of RARβ in regulating core clock genes.MethodsThis observational study included 361 children with ASD. Clinical symptoms were assessed using the Children’s Sleep Habits Questionnaire (CSHQ); the Childhood Autism Rating Scale (CARS) and the Social Responsiveness Scale (SRS). Peripheral blood mononuclear cell (PBMC) mRNA levels of RARβ and clock genes (BMAL1 and CLOCK) were quantified by qPCR. RARβ expression was knocked down in mice by stereotaxic injection of adeno-associated virus.ResultsChildren with lower vitamin A levels exhibited more severe sleep problems and autistic symptoms. Vitamin A levels showed a weak positive correlation with the expression of RARβ and BMAL1. RARβ knockdown reduced the expression of RARβ and clock genes in mouse brain tissue. Chromatin immunoprecipitation quantitative PCR (ChIP-qPCR) confirmed RARβ occupancy at a predicted CLOCK regulatory region.ConclusionThis study provided evidence that vitamin A status was linked to sleep problems, symptom severity, and expression of clock genes in the morning in ASD. We also found that RARβ signaling may regulate the expression of clock genes. This finding provides new insights into the mechanisms underlying sleep disturbances in ASD, but further functional studies are needed to confirm these findings.
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The Most Effective OCD Treatment Reaches Almost No One: Here’s What We Can Do About It

– Rebecca Deusser, MS, MBA and Sanjaya Saxena, MD

“It took me years to find out that what I was dealing with was OCD!”

This is a phrase all too often repeated by people living with obsessive compulsive disorder. Currently, individuals live with OCD for an average of 7 years (Dell’Osso et al, 2019) before they even receive a diagnosis, all while symptoms may intensify and daily life often becomes increasingly constrained. 

Clinicians, researchers, and advocates have long raised this concern. What has been missing is clear data behind how many people with OCD in the U.S. are missed in clinical settings or are not receiving the most effective treatment.

When the International OCD Foundation undertook this analysis, the scale of the problem became unmistakable. Millions of people in America are currently struggling with OCD without the most effective treatment.

The challenges we detail in our new white paper, America’s OCD Care Crisis: National Findings on the Failure of Effective OCD Treatment to Reach Patients, are significant, but fixable. They are symptoms of structural oversights that can be changed. Effective, evidence-based treatment for OCD exists, and through intentional action, we can dramatically change these unacceptable outcomes for people with OCD.

Where People With OCD Fall Through the Cracks

Well established prevalence rates for OCD indicate that nearly 10 million people in America — roughly 3% (Ruscio et al, 2010; Stein et al,2025; Ringeisen et al, 2025) — will have OCD at some point in their lives. Yet our findings suggest that 75% of them are never even identified, and up to 95% aren’t receiving the most effective treatment for the disorder.

In our analysis, we discovered significant systemic breakdowns at several key points of a patient’s journey: screening, diagnosis, referral, and treatment.

  • Screening and Diagnosis: Receiving a clinical diagnosis is an important step toward recovery as it promotes understanding and opens paths to effective treatment. Yet our findings suggest that this crucial initial step is missing for many millions of people. Of the 10.4 million patient records reviewed in our analysis, only 0.51% received a formal OCD diagnosis, far below the 3% expected prevalence rate. 
  • Referral to appropriate care: After a diagnosis is obtained, a handoff to appropriate care is needed to keep the patient from falling out of the treatment pathway. Here, too, we found an alarming gap within our sample: more than 72% of patients identified as having OCD did not receive a referral for cognitive-behavioral therapy (CBT), the most effective treatment for OCD.
  • Effective Treatment: Decades of research has established Exposure and Response Prevention (ERP) therapy, a specific form of CBT, as the most effective, first-line therapy for OCD. Yet, an astounding 95-98% of people with OCD had not received ERP treatment. Even when people seek help — and even when they are diagnosed — the vast majority never reach the treatment most likely to help them recover.

What We Can Do About It

The breakdowns seen in each step of the care pathway reinforce the focus of IOCDF’s Vision 2030, our five-year strategy to address the systemic barriers that keep effective OCD treatment out of reach.

While the findings are stark, they illuminate many opportunities for change:

  • Identify symptoms earlier by implementing routine OCD screening in primary healthcare and mental health settings.
  • Support clinicians in better understanding and treating OCD by expanding training in assessment, diagnosis, and evidence-based treatment modalities.
  • Help people receive care that works by strengthening adherence to existing professional treatment guidelines.
  • Increase the number of people with OCD who receive effective treatment  by supporting affordable access to ERP and other evidence-based therapies.
  • Let people know they’re not alone by raising accurate public awareness of what OCD really is — and that it is treatable.

Vision 2030 outlines how the IOCDF is committing its resources, partnerships, and expertise toward advancing these priorities — by increasing awareness and community, expanding access to effective treatment, and advancing research. Together, these efforts are designed to work in concert, improving clinical training, implementing screening for early identification, strengthening pathways from diagnosis to care, and increasing the likelihood that people receive evidence-based treatment.

At the same time, the scale of the problem revealed in this report makes clear that progress depends on collective action across the field. Clinicians, health systems, educators, researchers, policymakers, advocates, and people with lived experience all have a role to play. Together, these efforts can help ensure that people with OCD reach effective treatment sooner, reducing years of unnecessary confusion and distress. 

How You Can Help

Join us in building better access to effective treatment for people with OCD:

The current state of treatment for OCD in the U.S. is sobering, but it is not the end of the story. OCD is treatable, recovery is possible, and change can happen as awareness grows and access expands. With continued effort, the gap between how many are struggling and how many receive effective care can begin to close. A brighter future is possible — and we can build it together.

References

  1. Dell’Osso, B., Benatti, B., Grancini, B., Vismara, M., De Carlo, V., Cirnigliaro, G., Albert, U., & Viganò, C. (2019). Investigating duration of illness and duration of untreated illness in obsessive compulsive disorder reveals patients remain at length pharmacologically untreated. International Journal of Psychiatry in Clinical Practice, 23(4), 311–313. https://doi.org/10.1080/13651501.2019.1621348
  2. Ruscio, A. M., Stein, D. J., Chiu, W. T., & Kessler, R. C. (2010). The epidemiology of obsessive-compulsive disorder in the National Comorbidity Survey Replication. Molecular Psychiatry, 15(1), 53-63. https://doi.org/10.1038/mp.2008.94
  3. Stein, D. J., Ruscio, A. M., Altwaijri, Y., Chiu, W. T., Sampson, N. A., Aguilar-Gaxiola, S., Al-Hamzawi, A., Alonso, J., Chardoul, S., Gureje, O., Hu, C., Karam, E. G., McGrath, J. J., Navarro-Mateu, F., Scott, K. M., Stagnaro, J. C., Torres, Y., Vladescu, C., Wciórka, J., Xavier, M., … Kessler, R. C. (2025). Obsessive-compulsive disorder in the World Mental Health surveys. Research Square, rs.3.rs-6090427. https://doi.org/10.21203/rs.3.rs-6090427/v1
  4. Ringeisen, H., Edlund, M., Guyer, H., Dever, J., Carpenter, L., Olfson, M., First, M., Geiger, P., Liao, D., Peytchev, A., Carr, C., Chwastiak, L., Dixon, L. B., Monroe-Devita, M., Scott Stroup, T., Swanson, J., Swartz, M., Gibbons, R., Stambaugh, L., Bareis, N., … Mental Health and Substance Use Disorders Prevalence Study Consortium (2025). Prevalence of past-year mental and substance use disorders, 2021-2022. Psychiatric Services (Washington, D.C.), 76(8), 720–728. https://doi.org/10.1176/appi.ps.20240329

IOCDF Training & Resources for Clinicians

When clinicians have easier access to best practices in OCD diagnosis and treatment, more people can receive effective care. The IOCDF’s Training Institute offers evidence-based programs for clinicians at every stage of practice, including:

  • A robust, on-demand webinar catalog (CE-eligible!) covering fundamentals, modalities, related disorders, and comorbidities. The catalog includes access to the free webinar, OCD Basics. 
  • IOCDF’s Training Institute offers intensive workshops and events, consultation groups, and more for clinicians of every level.
  • Professional Members at the IOCDF join a nationwide network of committed professionals, are eligible for listing on our Resource Directory, and have access to special pricing for Training Institute offerings.

The post The Most Effective OCD Treatment Reaches Almost No One: Here’s What We Can Do About It appeared first on International OCD Foundation.

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It Is the Journey, Not the Destination: Moving From End Points to Trajectories When Assessing Chatbot Mental Health Safety

Large language models are rapidly becoming embedded in everyday life through artificial intelligence (AI) chatbots that people use for practical assistance and companionship, as well as for support with mental health and emotional wellbeing. Alongside clear benefits, clinicians and public reports increasingly describe a minority of users whose interactions seem to drift over days or weeks toward strongly questionable convictions, delusions or suicidal crises. Importantly, clinically meaningful deterioration can occur even without overtly unsafe text outputs, via more insidious processes such as compulsive use and sleep disruption, as well as withdrawal from human contact and progressive narrowing of attention around the chatbot relationship. In this Viewpoint, we argue that risk often arises not at a single tipping point but through trajectory effects that accumulate across extended dialogue, and that prevailing safety evaluation approaches are misaligned with this reality because they primarily score risk at discrete conversational endpoints often reached through scripted dialogues lasting just a single turn or several turns. Mental health benchmarks and safety suites (including clinician-informed efforts) have advanced the field by testing refusal behaviour, toxicity, and adversarial prompting, but they often treat the last message as the unit of analysis and therefore miss when risk-relevant relational cues, signs of validation, contradiction handling, and shifts in certainty first emerge and how they compound. We propose that mental health safety assessment should shift from endpoints to trajectories by 1) treating the whole dialogue, not just the end result, as the focus of evaluation; 2) reporting turn-by-turn dynamics such as delusion confirmation and harm enablement, as well as timing and persistence of safety interventions; and 3) calibrating short multi-turn tests against longer, clinically realistic interaction sequences that can reveal context-length effects and drift. We further argue that transcript-only evaluation is insufficient in mental health contexts. Similar language can reflect very different internal states, and the relationship between expressed psychopathology and real-world harm is non-linear. Safety research should therefore incorporate proximal human outcomes after interactions (e.g., shifts in certainty, openness to counterevidence, arousal, urge to continue, and subsequent sleep or behaviour) and build prospective clinical surveillance infrastructure that supports consented transcript donation and linkage to health outcomes. Together, these steps would enable benchmarks that are clinically relevant and better aligned with the kinds of harms now being observed in real-world chatbot use.
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