Npj mental health research最新文献

Retraining the veterans health administration's REACH VET suicide risk prediction model for patients involved in the legal system. 重新培训退伍军人健康管理局的REACH VET自杀风险预测模型，用于涉及法律系统的患者。

Npj mental health research Pub Date : 2025-07-10 DOI: 10.1038/s44184-025-00143-9

Esther L Meerwijk, Andrea K Finlay, Alex H S Harris

{"title":"Retraining the veterans health administration's REACH VET suicide risk prediction model for patients involved in the legal system.","authors":"Esther L Meerwijk, Andrea K Finlay, Alex H S Harris","doi":"10.1038/s44184-025-00143-9","DOIUrl":"10.1038/s44184-025-00143-9","url":null,"abstract":"Although patients with criminal legal system involvement have among the highest rates of suicide, the model that identifies patients at high risk of suicide at the United States Veterans Health Administration (VHA) does not include predictors specific to criminal legal system involvement. We explored whether the model's predictive ability would be improved (1) by retraining the model for legal-involved veterans and (2) by adding additional predictors associated with legal-involvement. For a combined outcome of suicide attempt or suicide death, the retrained models showed a positive predictive value (PPV) of 0.124 and false negative rate (FNR) of 0.527. Adding additional predictors associated with being legal-involved did not improve predictive accuracy. Retraining the VHA suicide risk prediction model for legal-involved patients improves the model's predictive ability for this group of high-risk patients, more so than adding predictors associated with being legal-involved. A similar approach for other high-risk patients is worth exploring.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":"4 1","pages":"29"},"PeriodicalIF":0.0,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12246187/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144610535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Psychosocial dynamics of suicidality and nonsuicidal self-injury: a digital linguistic perspective. 自杀和非自杀自伤的社会心理动态：数字语言学视角。

Npj mental health research Pub Date : 2025-07-08 DOI: 10.1038/s44184-025-00142-w

Charlotte Entwistle, Katie Hoemann, Sophie J Nightingale, Ryan L Boyd

{"title":"Psychosocial dynamics of suicidality and nonsuicidal self-injury: a digital linguistic perspective.","authors":"Charlotte Entwistle, Katie Hoemann, Sophie J Nightingale, Ryan L Boyd","doi":"10.1038/s44184-025-00142-w","DOIUrl":"10.1038/s44184-025-00142-w","url":null,"abstract":"Self-harm-encompassing suicidality and nonsuicidal self-injury (NSSI)-presents a critical public health concern, particularly as it is a major risk factor of death by suicide. Understanding the psychosocial dynamics of self-harm is imperative. Accordingly, in a large-scale, naturalistic study, we leveraged modern language analysis methods to provide a comprehensive perspective on suicidality and NSSI, specifically in the context of borderline personality disorder (BPD), where self-harm is particularly prevalent. We utilised natural language processing techniques to analyse Reddit data (i.e., BPD forum posts) of 992 users with self-identified BPD (combined N posts = 66,786). The present findings generated further insight into the psychosocial dynamics of suicidality and NSSI, while also uncovering meaningful interactions between the online BPD community and these behaviours. By integrating advanced computational methods with psychological theory, our findings provide a nuanced understanding of self-harm, with implications for clinical practice, clinical and personality theory, and computational social science.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":"4 1","pages":"28"},"PeriodicalIF":0.0,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12238424/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144593105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Personalized game-based digital intervention for relieving depression and anxiety symptoms: a pilot RCT. 缓解抑郁和焦虑症状的个性化基于游戏的数字干预：一项试点随机对照试验

Npj mental health research Pub Date : 2025-07-03 DOI: 10.1038/s44184-025-00141-x

Xiaojun Shao, Lu Liu, Xiaotong Zhu, Chunsheng Tian, Dai Li, Liqun Zhang, Xiang Liu, Yanru Liu, Gang Zhu, Lingjiang Li

{"title":"Personalized game-based digital intervention for relieving depression and anxiety symptoms: a pilot RCT.","authors":"Xiaojun Shao, Lu Liu, Xiaotong Zhu, Chunsheng Tian, Dai Li, Liqun Zhang, Xiang Liu, Yanru Liu, Gang Zhu, Lingjiang Li","doi":"10.1038/s44184-025-00141-x","DOIUrl":"10.1038/s44184-025-00141-x","url":null,"abstract":"This study assessed the preliminary effectiveness of a game-based digital therapeutics (DTx) intervention for depression and anxiety using a randomized controlled trial (RCT) design to examine the role of reinforcement learning (RL) personalization. This RCT included 223 individuals with depressive symptoms, aged 18-50, divided into three groups: an RL Algorithm group (personalized treatment), an active control group (fixed treatment), and a no-intervention control group. The intervention combined cognitive bias modification and cognitive behavioral therapy, with outcomes measured by the Patient Health Questionnaire-9 and the Generalized Anxiety Disorder-7. Results showed significantly higher treatment response and recovery rates in the RL Algorithm group compared to the no-intervention group. The game-based DTx intervention, enhanced by RL personalization, effectively reduced depression and anxiety symptoms, supporting its potential for mental health treatment. The study was registered at clinicaltrials.gov (NCT06301555).","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":"4 1","pages":"27"},"PeriodicalIF":0.0,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12229681/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144562220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of the treatment prediction model in the artificial intelligence in depression - medication enhancement study. 抑郁症人工智能治疗预测模型的建立——药物增强研究。

Npj mental health research Pub Date : 2025-06-23 DOI: 10.1038/s44184-025-00136-8

David Benrimoh, Caitrin Armstrong, Joseph Mehltretter, Robert Fratila, Kelly Perlman, Sonia Israel, Adam Kapelner, Sagar V Parikh, Jordan F Karp, Katherine Heller, Gustavo Turecki

{"title":"Development of the treatment prediction model in the artificial intelligence in depression - medication enhancement study.","authors":"David Benrimoh, Caitrin Armstrong, Joseph Mehltretter, Robert Fratila, Kelly Perlman, Sonia Israel, Adam Kapelner, Sagar V Parikh, Jordan F Karp, Katherine Heller, Gustavo Turecki","doi":"10.1038/s44184-025-00136-8","DOIUrl":"10.1038/s44184-025-00136-8","url":null,"abstract":"We introduce an artificial intelligence model to personalize treatment in major depression, which was deployed in the Artificial Intelligence in Depression: Medication Enhancement Study. We predict probabilities of remission across multiple pharmacological treatments, validate model predictions, and examine them for biases. Data from 9042 adults with moderate to severe major depression from antidepressant clinical trials were used to train a deep learning model. On the held-out test-set, the model demonstrated an AUC of 0.65, outperformed a null model (p = 0.01). The model increased population remission rate in hypothetical and actual improvement testing. While the model identified escitalopram as generally outperforming other drugs (consistent with the input data), there was otherwise significant variation in drug rankings. The model did not amplify potentially harmful biases. We demonstrate the first model capable of predicting outcomes for 10 treatments, intended to be used at or near the start of treatment to personalize treatment selection.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":"4 1","pages":"26"},"PeriodicalIF":0.0,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12185704/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144478085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Applying language models for suicide prevention: evaluating news article adherence to WHO reporting guidelines. 将语言模型应用于自杀预防：评估新闻文章对世卫组织报告准则的遵守情况。

Npj mental health research Pub Date : 2025-06-20 DOI: 10.1038/s44184-025-00139-5

Zohar Elyoseph, Inbar Levkovich, Eyal Rabin, Gal Shemo, Tal Szpiler, Dorit Hadar Shoval, Yossi Levi Belz

{"title":"Applying language models for suicide prevention: evaluating news article adherence to WHO reporting guidelines.","authors":"Zohar Elyoseph, Inbar Levkovich, Eyal Rabin, Gal Shemo, Tal Szpiler, Dorit Hadar Shoval, Yossi Levi Belz","doi":"10.1038/s44184-025-00139-5","DOIUrl":"10.1038/s44184-025-00139-5","url":null,"abstract":"The responsible reporting of suicide in media is crucial for public health, as irresponsible coverage can potentially promote suicidal behaviors. This study examined the capability of generative artificial intelligence, specifically large language models, to evaluate news articles on suicide according to World Health Organization (WHO) guidelines, potentially offering a scalable solution to this critical issue. The research compared assessments of 40 suicide-related articles by two human reviewers and two large language models (ChatGPT-4 and Claude Opus). Results showed strong agreement between ChatGPT-4 and human reviewers (ICC = 0.81-0.87), with no significant differences in overall evaluations. Claude Opus demonstrated good agreement with human reviewers (ICC = 0.73-0.78) but tended to estimate lower compliance. These findings suggest large language models' potential in promoting responsible suicide reporting, with significant implications for public health. The technology could provide immediate feedback to journalists, encouraging adherence to best practices and potentially transforming public narratives around suicide.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":"4 1","pages":"25"},"PeriodicalIF":0.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12181428/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144337308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessing the mental health impact of China's housing boom through national and city-level data analysis. 通过国家和城市层面的数据分析评估中国房地产繁荣对心理健康的影响。

Npj mental health research Pub Date : 2025-06-03 DOI: 10.1038/s44184-025-00135-9

Yige Xiao, Xin Liu, Lijie Ren, Shufang Lai

引用次数: 0

Exploring the link between adverse childhood experiences and cancer development - insights and intervention recommendations from a scoping review. 探索不良童年经历与癌症发展之间的联系-来自范围审查的见解和干预建议。

Npj mental health research Pub Date : 2025-06-02 DOI: 10.1038/s44184-025-00138-6

Bethany Karnes, Alise Hanissian, Brianna M White, Jason A Yaun, Arash Shaban-Nejad, David L Schwartz

引用次数: 0

Transition and dynamic reconfiguration in late-life depression based on hidden Markov model. 基于隐马尔可夫模型的老年抑郁症的转变与动态重构。

Npj mental health research Pub Date : 2025-05-27 DOI: 10.1038/s44184-025-00137-7

Hairong Xiao, Caili Kang, Wei Zhao, Shuixia Guo

{"title":"Transition and dynamic reconfiguration in late-life depression based on hidden Markov model.","authors":"Hairong Xiao, Caili Kang, Wei Zhao, Shuixia Guo","doi":"10.1038/s44184-025-00137-7","DOIUrl":"10.1038/s44184-025-00137-7","url":null,"abstract":"Late-life depression is characterized by persistent emotional distress and cognitive dysfunction, yet understanding the specific brain dynamics and molecular mechanisms involved remains limited. Here, we employed a hidden Markov model to analyze resting-state functional magnetic resonance imaging data from 154 patients with late-life depression and 147 healthy controls. This analysis revealed 12 recurring brain states with distinct spatiotemporal patterns and identified atypical dynamic features across several networks. Notably, patients exhibited significantly higher transition probabilities for entering, exiting, and maintaining in the positive activation state of the default mode network, with genes linked to this state mainly enriched in regulation of neuronal synaptic plasticity and cognitive processes. Hierarchical clustering further found a critical entry and exit point between two high-level meta-states with opposing activation patterns, highlighting large-scale network dysfunction and potential molecular mechanisms associated with late-life depression through the decoding of brain states.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":"4 1","pages":"22"},"PeriodicalIF":0.0,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12106808/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144152949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mental health impacts of particulate matter exposure and non-optimal temperature among rural and urban children in eastern China. 中国东部城乡儿童颗粒物暴露和非最适温度对心理健康的影响

Npj mental health research Pub Date : 2025-05-19 DOI: 10.1038/s44184-025-00132-y

Yangyang Wu, Jing Wei, Biran Cheng, Hong Sun, Yidong Zhou, Chen Li, Peng Wang, Hao Zhang, Yiyi Wang, Lei Huang, Kai Chen

{"title":"Mental health impacts of particulate matter exposure and non-optimal temperature among rural and urban children in eastern China.","authors":"Yangyang Wu, Jing Wei, Biran Cheng, Hong Sun, Yidong Zhou, Chen Li, Peng Wang, Hao Zhang, Yiyi Wang, Lei Huang, Kai Chen","doi":"10.1038/s44184-025-00132-y","DOIUrl":"10.1038/s44184-025-00132-y","url":null,"abstract":"Over 100 million children worldwide suffer from mental distress, with incidence rates steadily increasing. However, the combined impacts of air pollution and non-optimal temperature on schoolchildren's mental health, as well as the disparities across urban and rural schools and between genders, remain insufficiently explored. Utilizing 95,658 mental distress records from school children in eastern China, we developed nine composite exposure scenarios to evaluate the mental health impacts of short-term (0-14 days) exposure to particulate matter (PM) air pollution (i.e., PM1, PM2.5, PM10), average temperature, and temperature variability (including both intra-day and inter-day temperature fluctuations). We found that children's mental distress was significantly associated with PM pollution, particularly in urban schools, with rising risk trends and intensified hazards for finer particles (PM10 < PM2.5 < PM1). For each 10 μg/m³ increase, the relative risks of mental distress absenteeism for PM1, PM2.5, and PM10 were 1.017, 1.011, and 1.008, respectively. Polluted days coupled with warming temperature >10 °C and large intra-day (>10 °C) and inter-day fluctuations (<-2.5 or >0 °C) consistently exhibited higher and increasing risks, with relative risks ranging from 1.031 to 1.534 (p < 0.05). Girls, constituting 61.4% of the cases examined, exhibited greater vulnerability than boys, with higher threats and rising trends across all scenarios. Among the affected children, 77.9% didn't receive medical assistance. Given the global warming trend, it's crucial to address the combined impacts of extreme weather and PM pollution on schoolchildren's mental health, particularly for girls and in rapidly urbanizing areas.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":"4 1","pages":"21"},"PeriodicalIF":0.0,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12089432/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144103304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Randomized trial testing a self-guided digital mental health intervention teaching calming skills for Ukrainian children. 随机试验测试一种自我引导的数字心理健康干预，为乌克兰儿童教授镇静技巧。

Npj mental health research Pub Date : 2025-05-16 DOI: 10.1038/s44184-025-00134-w

Joshua S Steinberg, Jingxuan Sun, Katherine E Venturo-Conerly, Gauri Sood, Patrick Mair, Oksana Davydenko, Robert Porzak, Dennis Ougrin, John R Weisz

{"title":"Randomized trial testing a self-guided digital mental health intervention teaching calming skills for Ukrainian children.","authors":"Joshua S Steinberg, Jingxuan Sun, Katherine E Venturo-Conerly, Gauri Sood, Patrick Mair, Oksana Davydenko, Robert Porzak, Dennis Ougrin, John R Weisz","doi":"10.1038/s44184-025-00134-w","DOIUrl":"10.1038/s44184-025-00134-w","url":null,"abstract":"Ukraine's war-exposed youth face a myriad of barriers to receiving mental health services, perhaps most notably a dearth of mental health professionals. Experts recommend evaluating digital mental health interventions (DMHIs), which require minimal clinician support. Based on the content of empirically supported treatments for war-exposed youth (e.g., Teaching Recovery Techniques), one strategy that might be useful is self-calming (e.g., paced breathing, progressive muscle relaxation). In this pre-registered randomized controlled trial (ClinicalTrials.gov Record: NCT06217705 ; first submitted January 12, 2024), we assessed the acceptability, utility, and clinical efficacy of one such DMHI (Project Calm) relative to a usual schoolwork control among a sample of Ukrainian students in grades 4-11. We analyzed outcomes for the full sample and subsamples with elevated symptoms at baseline. Although Calm was perceived favorably, there were no significant between-group differences in the full sample (N = 626); differences in subsample analyses demonstrated that while internalizing, externalizing, and trauma symptoms held steady for the Calm group, control participants' symptoms reduced. We generated potential explanations for these results (e.g., interference with youths' natural coping skills or fear extinction) through a focus group with school staff. Given that we found no evidence that calming skills taught via DMHI are effective for Ukrainian youth, we suggest that researchers test other strategies delivered by DMHI and that calming skills continue to be taught in provider-guided formats.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":"4 1","pages":"20"},"PeriodicalIF":0.0,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12084600/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144087085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0