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Integrating Virtual Reality, Neurofeedback, and Cognitive Behavioral Therapy for Auditory Verbal Hallucinations (Hybrid): Protocol of a Pilot, Unblinded, Single-Arm Interventional Study

Integrating Virtual Reality, Neurofeedback, and Cognitive Behavioral Therapy for Auditory Verbal Hallucinations (Hybrid): Protocol of a Pilot, Unblinded, Single-Arm Interventional Study

Psychosis is the distinguishing feature of schizophrenia spectrum disorders and a frequent manifestation of mood and substance use disorders [1]. It is characterized by alterations in thoughts and perceptions, often taking the form of positive symptoms such as delusions, hallucinations [2], and disorganized thinking [3], as well as negative symptoms such as blunted affect, poverty of speech, and withdrawal from social and occupational activities [4].

Jessica Spark, Elise Rowe, Mario Alvarez-Jimenez, Imogen Bell, Linda Byrne, Ilvana Dzafic, Carli Ellinghaus, Suzie Lavoie, Jarrad Lum, Brooke McLean, Neil Thomas, Andrew Thompson, Greg Wadley, Thomas Whitford, Stephen Wood, Hok Pan Yuen, Barnaby Nelson

JMIR Res Protoc 2025;14:e63405

Prompt Engineering an Informational Chatbot for Education on Mental Health Using a Multiagent Approach for Enhanced Compliance With Prompt Instructions: Algorithm Development and Validation

Prompt Engineering an Informational Chatbot for Education on Mental Health Using a Multiagent Approach for Enhanced Compliance With Prompt Instructions: Algorithm Development and Validation

To showcase the proposed methodology, we developed a GPT-4–powered schizophrenia informational chatbot, hereafter referred to as CAFIbot, which conveys the content of the Learning to Live With Schizophrenia manual. This manual was produced by the Global Alliance of Mental Illness Advocacy Network Europe patient advocacy group [11], who we are collaborating with in an ongoing clinical project (called TRUSTING) involving patients with mental health problems [12].

Per Niklas Waaler, Musarrat Hussain, Igor Molchanov, Lars Ailo Bongo, Brita Elvevåg

JMIR AI 2025;4:e69820

Telehealth-Based vs In-Person Aerobic Exercise in Individuals With Schizophrenia: Comparative Analysis of Feasibility, Safety, and Efficacy

Telehealth-Based vs In-Person Aerobic Exercise in Individuals With Schizophrenia: Comparative Analysis of Feasibility, Safety, and Efficacy

Sedentary lifestyle and low aerobic fitness are highly ubiquitous among individuals with schizophrenia [1,2] and are associated with a wide range of medical and psychiatric health indicators including cardiopulmonary and metabolic problems [3-5], high symptom burden, and depression [6], as well as poor neurocognition and daily functioning [1].

David Kimhy, Luz H Ospina, Melanie Wall, Daniel M Alschuler, Lars F Jarskog, Jacob S Ballon, Joseph McEvoy, Matthew N Bartels, Richard um Buchsba, Marianne Goodman, Sloane A Miller, T Scott Stroup

JMIR Ment Health 2025;12:e68251

Utility of Digital Phenotyping Based on Wrist Wearables and Smartphones in Psychosis: Observational Study

Utility of Digital Phenotyping Based on Wrist Wearables and Smartphones in Psychosis: Observational Study

Movement data estimated from a 3-axis accelerometer were negatively correlated with negative symptoms assessed with the Positive and Negative Syndrome Scale (PANSS) in patients with schizophrenia [17]. The number of steps was negatively correlated with PANSS positive-factor, negative-factor, general subscales, and total score, in patients with schizophrenia in an inpatient setting [18].

Zixu Yang, Creighton Heaukulani, Amelia Sim, Thisum Buddhika, Nur Amirah Abdul Rashid, Xuancong Wang, Shushan Zheng, Yue Feng Quek, Sutapa Basu, Kok Wei Lee, Charmaine Tang, Swapna Verma, Robert J T Morris, Jimmy Lee

JMIR Mhealth Uhealth 2025;13:e56185

Estimating the Prevalence of Schizophrenia in the General Population of Japan Using an Artificial Neural Network–Based Schizophrenia Classifier: Web-Based Cross-Sectional Survey

Estimating the Prevalence of Schizophrenia in the General Population of Japan Using an Artificial Neural Network–Based Schizophrenia Classifier: Web-Based Cross-Sectional Survey

The estimated lifetime prevalence of schizophrenia is 0.59%, according to a secondary analysis of the 2019 cross-sectional Japan National Health and Wellness Survey [6]. However, this study may produce underestimation since it only depended on physician diagnoses. Individuals with schizophrenia hardly self-identify as having schizophrenia because of stigma and lack of awareness of schizophrenia and its symptoms [7-13].

Pichsinee Choomung, Yupeng He, Masaaki Matsunaga, Kenji Sakuma, Taro Kishi, Yuanying Li, Shinichi Tanihara, Nakao Iwata, Atsuhiko Ota

JMIR Form Res 2025;9:e66330

Impact of a Virtual Reality Intervention on Stigma, Empathy, and Attitudes Toward Patients With Psychotic Disorders Among Mental Health Care Professionals: Randomized Controlled Trial

Impact of a Virtual Reality Intervention on Stigma, Empathy, and Attitudes Toward Patients With Psychotic Disorders Among Mental Health Care Professionals: Randomized Controlled Trial

Attitudes toward people with psychotic disorders were measured with the modified attitudes toward people with schizophrenia scale [36]. The 7-item scale is measured on a 9-point Likert scale ranging from 1 to 9. Total scores range from 7 to 63, with higher scores indicating better attitudes. Items 1 and 2 are reverse coded. An example item is “How much do you personally care about the plight of people with schizophrenia?” The internal consistency Cronbach alpha ranges from 0.76 to 0.79 [36].

Jing Ling Tay, Yuanrong Qu, Lucas Lim, Rohan Puthran, Chye Lee Robert Tan, Rajkirren Rajendran, Ker Chiah Wei, Huiting Xie, Kang Sim

JMIR Ment Health 2025;12:e66925

Barriers and Facilitators of User Engagement With Digital Mental Health Interventions for People With Psychosis or Bipolar Disorder: Systematic Review and Best-Fit Framework Synthesis

Barriers and Facilitators of User Engagement With Digital Mental Health Interventions for People With Psychosis or Bipolar Disorder: Systematic Review and Best-Fit Framework Synthesis

The costs and burdens of schizophrenia spectrum psychosis and bipolar disorder are huge and often neglected in research [1,2]. Digital mental health interventions (DMHIs) can help people with psychosis or bipolar disorder monitor, manage, and improve their symptoms and health [3-6].

Emily Eisner, Sophie Faulkner, Stephanie Allan, Hannah Ball, Daniela Di Basilio, Jennifer Nicholas, Aansha Priyam, Paul Wilson, Xiaolong Zhang, Sandra Bucci

JMIR Ment Health 2025;12:e65246

Effectiveness of a Videoconference-Based Cognitive Behavioral Therapy Program for Patients with Schizophrenia: Pilot Randomized Controlled Trial

Effectiveness of a Videoconference-Based Cognitive Behavioral Therapy Program for Patients with Schizophrenia: Pilot Randomized Controlled Trial

Schizophrenia is a psychiatric disorder that affects approximately 1% of the total population and is typically prevalent between the ages of 16 and 30 years [1,2]. Pharmacotherapy with antipsychotic drugs is the standard treatment for schizophrenia. Moreover, cognitive behavioral therapy, a psychological intervention, is recommended by the National Institute of Health and Clinical Excellence (NICE) [3].

Masayuki Katsushima, Hideki Nakamura, Yuki Shiko, Hideki Hanaoka, Eiji Shimizu

JMIR Form Res 2025;9:e59540

Analysis of Social Performance and Action Units During Social Skills Training: Focus Group Study of Adults With Autism Spectrum Disorder and Schizophrenia

Analysis of Social Performance and Action Units During Social Skills Training: Focus Group Study of Adults With Autism Spectrum Disorder and Schizophrenia

We found that AU02 is significantly activated in people with schizophrenia compared with other groups. For mean values of the action units, this implies that AU02 is significantly less for the control group than the ASD group. For AU06, schizophrenia is significantly less than the control group. For AU12, it is more evident that schizophrenia is significantly less than either the control or ASD group. Regarding SD, people with ASD have significantly activated AU02 compared with the control group.

Hiroki Tanaka, Kana Miyamoto, Jennifer Hamet Bagnou, Elise Prigent, Céline Clavel, Jean-Claude Martin, Satoshi Nakamura

JMIR Form Res 2025;9:e59261