Npj mental health research最新文献_第2页

Detecting and tracking depression through temporal topic modeling of tweets: insights from a 180-day study 通过tweet的时间主题建模来检测和跟踪抑郁症：来自180天研究的见解

Npj mental health research Pub Date : 2024-12-06 DOI: 10.1038/s44184-024-00107-5

Ranganathan Chandrasekaran, Suhas Kotaki, Abhilash Hosaagrahaara Nagaraja

{"title":"Detecting and tracking depression through temporal topic modeling of tweets: insights from a 180-day study","authors":"Ranganathan Chandrasekaran, Suhas Kotaki, Abhilash Hosaagrahaara Nagaraja","doi":"10.1038/s44184-024-00107-5","DOIUrl":"10.1038/s44184-024-00107-5","url":null,"abstract":"Depression affects over 280 million people globally, yet many cases remain undiagnosed or untreated due to stigma and lack of awareness. Social media platforms like X (formerly Twitter) offer a way to monitor and analyze depression markers. This study analyzes Twitter data 90 days before and 90 days after a self-disclosed clinical diagnosis. We gathered 246,637 tweets from 229 diagnosed users. CorEx topic modeling identified seven themes: causes, physical symptoms, mental symptoms, swear words, treatment, coping/support mechanisms, and lifestyle, and conditional logistic regression assessed the odds of these themes occurring post-diagnosis. A control group of healthy users (284,772 tweets) was used to develop and evaluate machine learning classifiers—support vector machines, naive Bayes, and logistic regression—to distinguish between depressed and non-depressed users. Logistic regression and SVM performed best. These findings show the potential of Twitter data for tracking depression and changes in symptoms, coping mechanisms, and treatment use.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-024-00107-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142790458","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

Exploring digital use, happiness, and loneliness in Japan with the experience sampling method 用体验抽样法探索日本的数字使用、幸福和孤独

Npj mental health research Pub Date : 2024-12-06 DOI: 10.1038/s44184-024-00108-4

Yijun Chen, Xiaochu Zhang, Rei Akaishi

引用次数: 0

Deep learning models can predict violence and threats against healthcare providers using clinical notes 深度学习模型可以根据临床记录预测针对医疗服务提供者的暴力和威胁。

Npj mental health research Pub Date : 2024-12-05 DOI: 10.1038/s44184-024-00105-7

Nicholas J. Dobbins, Jacqueline Chipkin, Tim Byrne, Omar Ghabra, Julia Siar, Mitchell Sauder, R. Michael Huijon, Taylor M. Black

{"title":"Deep learning models can predict violence and threats against healthcare providers using clinical notes","authors":"Nicholas J. Dobbins, Jacqueline Chipkin, Tim Byrne, Omar Ghabra, Julia Siar, Mitchell Sauder, R. Michael Huijon, Taylor M. Black","doi":"10.1038/s44184-024-00105-7","DOIUrl":"10.1038/s44184-024-00105-7","url":null,"abstract":"Violence, verbal abuse, threats, and sexual harassment of healthcare providers by patients is a major challenge for healthcare organizations around the world, contributing to staff turnover, distress, absenteeism, reduced job satisfaction, and worsening mental and physical health. To enable interventions prior to possible violent episodes, we trained two deep learning models to predict violence against healthcare workers 3 days prior to violent events for case and control patients. The first model is a document classification model using clinical notes, and the second is a baseline regression model using largely structured data. Our document classification model achieved an F1 score of 0.75 while our model using structured data achieved an F1 of 0.72, both exceeding the predictive performance of a psychiatry team who reviewed the same documents (0.5 F1). To aid in the explainability and understanding of risk factors for violent events, we additionally trained a named entity recognition classifier on annotations of the same corpus, which achieved an overall F1 of 0.7. This study demonstrates the first deep learning model capable of predicting violent events within healthcare settings using clinical notes, surpassing the first published baseline of human experts. We anticipate our methods can be generalized and extended to enable intervention at other hospital systems.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-024-00105-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142788036","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 psychopathological vulnerability index for screening at-risk youths: a Rasch model approach 发展的精神病理脆弱性指数筛选有风险的青年：一个Rasch模型方法。

Npj mental health research Pub Date : 2024-12-02 DOI: 10.1038/s44184-024-00106-6

Yujing Liao, Haitao Shen, Wenjie Duan, Shanshan Cui, Chunxiu Zheng, Rong Liu, Yawen Jia

{"title":"Development of the psychopathological vulnerability index for screening at-risk youths: a Rasch model approach","authors":"Yujing Liao, Haitao Shen, Wenjie Duan, Shanshan Cui, Chunxiu Zheng, Rong Liu, Yawen Jia","doi":"10.1038/s44184-024-00106-6","DOIUrl":"10.1038/s44184-024-00106-6","url":null,"abstract":"Accumulating research on mental health emphasizes the general factor of psychopathology (p-factor) that unites various mental health issues. This study develops a psychopathological vulnerability assessment for youths, evaluating its psychometric properties and clinical utility. An umbrella review conceptualized multifactor psychopathological vulnerability, leading to a 57-item pool. A total of 11,224 individuals participated in this study. The resulting 22-item psychopathological vulnerability index (PVI) fitted the unidimensional Rasch model, demonstrating a person separation reliability of 0.78 and a Cronbach’s alpha of 0.84. Cut-off points of 11 and 5, derived from latent class analysis, were used to distinguish vulnerable and high-protection populations. The PVI’s concurrent and predictive hit rates ranged from 36.00% to 53.57% in clinical samples. The PVI concretized the vulnerability–stress model for identifying at-risk youths and may facilitate universal interventions by integrating the theoretical foundations of bifactor S-1 models with key symptoms from network models for theoretically grounded approaches.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-16"},"PeriodicalIF":0.0,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11612436/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142775310","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

Symptomatic associations and sexual differences in depression and communication 抑郁和沟通的症状关联和性别差异

Npj mental health research Pub Date : 2024-11-30 DOI: 10.1038/s44184-024-00098-3

Yu Jin, Yinjie Fan, Jian He, Amanda Wilson, Yi Li, Jiaqi Li, Yajun Bu, Yuanyuan Wang

{"title":"Symptomatic associations and sexual differences in depression and communication","authors":"Yu Jin, Yinjie Fan, Jian He, Amanda Wilson, Yi Li, Jiaqi Li, Yajun Bu, Yuanyuan Wang","doi":"10.1038/s44184-024-00098-3","DOIUrl":"10.1038/s44184-024-00098-3","url":null,"abstract":"Previous studies have explored the associations between parental and offspring’s depression and parent-child communication. However, few studies have investigated their symptomatic associations and potential sex differences. Therefore, this study aims to examine their associations and sex differences in parents and offspring. Based on the China Family Panel Studies (CFPS)-2020 study, depressive symptoms and parent-child communication were measured by the 8-item Center for Epidemiologic Studies Depression Scale (CESD-8) and independent questions, respectively. Network analysis was used to investigate the associations and to compare the sex differences of parents and offspring. A total of 1710 adolescents were included after cleaning process (N = 28,530). There were significantly stronger associations in boys’ “anhedonia” and “arguments with parents”, and in girls’ “happiness” and parents’ “joyfulness”. Furthermore, there were same-sex depression associations between children and parents (e.g., boys’ “despair”–fathers’ “joyfulness”; girls’ “anhedonia”–mothers’ “loneliness”). These results would help us to better understand the in depression and communication nuanced associations and to develop effective strategies for improving parental and offspring’s mental health.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-024-00098-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142758096","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

Longitudinal trajectories of symptom change during antidepressant treatment among managed care patients with depression and anxiety 管理式医疗抑郁症和焦虑症患者在抗抑郁治疗期间症状变化的纵向轨迹

Npj mental health research Pub Date : 2024-11-27 DOI: 10.1038/s44184-024-00104-8

Judith Cukor, Zhenxing Xu, Veer Vekaria, Fei Wang, Mark Olfson, Samprit Banerjee, Gregory Simon, George Alexopoulos, Jyotishman Pathak

{"title":"Longitudinal trajectories of symptom change during antidepressant treatment among managed care patients with depression and anxiety","authors":"Judith Cukor, Zhenxing Xu, Veer Vekaria, Fei Wang, Mark Olfson, Samprit Banerjee, Gregory Simon, George Alexopoulos, Jyotishman Pathak","doi":"10.1038/s44184-024-00104-8","DOIUrl":"10.1038/s44184-024-00104-8","url":null,"abstract":"Despite the high correlation between anxiety and depression, little remains known about the course of each condition when presenting concurrently. This study aimed to identify longitudinal patterns during antidepressant treatment in patients with depression and anxiety, and evaluate related factors associated with these patterns. By analyzing longitudinal self-report Patient Health Questionnaire-9 (PHQ-9) and General Anxiety Disorder-7 (GAD-7) scores that tracked courses of depression and anxiety over a three-month window among the 577 adult participants, six depression and six anxiety trajectory subgroups were computationally derived using group-based trajectory modeling. Three depression subgroups showed symptom improvement, while three showed nonresponses. Similar patterns were observed in the six anxiety subgroups. Multinomial regression was used to associate patient characteristics with trajectory subgroup membership. Compared to patients in the remission group, factors associated with depressive symptom nonresponse included older age and lower depression severity.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2024-11-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-024-00104-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142737666","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

Impact of pandemic-related worries on mental health in India from 2020 to 2022 2020 至 2022 年大流行相关担忧对印度心理健康的影响

Npj mental health research Pub Date : 2024-11-24 DOI: 10.1038/s44184-024-00101-x

Youqi Yang, Anqi Sun, Lauren Zimmermann, Bhramar Mukherjee

引用次数: 0

Using hidden Markov modelling to reveal in-session stages in text-based counselling 使用隐马尔可夫模型揭示基于文本的咨询中的会话阶段。

Npj mental health research Pub Date : 2024-11-21 DOI: 10.1038/s44184-024-00103-9

Ziru Fu, Yu Cheng Hsu, Christian S. Chan, Joyce Liu, Paul S. F. Yip

{"title":"Using hidden Markov modelling to reveal in-session stages in text-based counselling","authors":"Ziru Fu, Yu Cheng Hsu, Christian S. Chan, Joyce Liu, Paul S. F. Yip","doi":"10.1038/s44184-024-00103-9","DOIUrl":"10.1038/s44184-024-00103-9","url":null,"abstract":"Counselling sessions have multiple stages, each with its themes and objectives. This study aimed to apply Hidden Markov Models (HMMs) to analyse counselling sessions from Open Up, an online text-based counselling platform in Hong Kong. The focus was on inferring latent stages over word distributions and identifying distinctive patterns of progression in more versus less satisfying sessions. Transcripts from 2589 sessions were categorized into more satisfying sessions ( $$n=mathrm{1993}$$ ) and less satisfying sessions ( $$n=596$$ ) based on post-session surveys. A message-level HMM identified five distinct stages: Rapport-building, Problem-identification, Problem-exploration, Problem-solving, and Wrap-up. Compared with less satisfying sessions, more satisfying sessions saw significantly more efficient initial rapport building (7.5% of session duration), problem introduction (20.2%), problem exploration (28.5%), elaborated solution development (46.6%), and concise conclusion (8.2%). This study offers insights for improving the efficiency and satisfaction of text-based counselling services through efficient initial engagement, thorough issue exploration, and focused problem-solving.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-024-00103-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142689893","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

Infrastructure development in children’s behavioral health systems of care: essential elements and implementation strategies 儿童行为健康护理系统的基础设施建设：基本要素和实施策略。

Npj mental health research Pub Date : 2024-11-14 DOI: 10.1038/s44184-024-00102-w

Jeffrey J. Vanderploeg

引用次数: 0

Mental health care needs of caregivers of people with Alzheimer’s disease from online forum analysis 从网上论坛分析老年痴呆症患者照顾者的心理保健需求。

Npj mental health research Pub Date : 2024-11-14 DOI: 10.1038/s44184-024-00100-y

Jiyeong Kim, Zhuo Ran Cai, Michael L. Chen, Shawheen J. Rezaei, Sonia Onyeka, Carolyn I. Rodriguez, Tina Hernandez-Boussard, Vladimir Filkov, Rachel A. Whitmer, Eleni Linos, Yong K. Choi

{"title":"Mental health care needs of caregivers of people with Alzheimer’s disease from online forum analysis","authors":"Jiyeong Kim, Zhuo Ran Cai, Michael L. Chen, Shawheen J. Rezaei, Sonia Onyeka, Carolyn I. Rodriguez, Tina Hernandez-Boussard, Vladimir Filkov, Rachel A. Whitmer, Eleni Linos, Yong K. Choi","doi":"10.1038/s44184-024-00100-y","DOIUrl":"10.1038/s44184-024-00100-y","url":null,"abstract":"Informal caregivers of people with Alzheimer’s disease and related dementias (ADRD) are at risk of poor mental health. This study aimed to investigate the feasibility and validity of studying caregivers’ mental stressors using online caregiving forum data (March 2018–February 2022) and natural language processing and machine learning (NLP/ML). NLP/ML topic modeling generated eight prominent topics, which we compared with qualitatively defined themes and the existing caregiving framework to assess validity. Among a total of 60,182 posts, 5848 were mental distress-related; for the ADRD patients (symptoms, medication, relocation, care duty share, diagnosis, conversation strategy) and the caregivers (caregiving burden and support). While we observed novel topics from NLP/ML-defined topics, mostly those were aligned with the existing framework. For feasibility assessment, qualitative title screening was done. The findings shed new light on the potential of NLP/ML text analysis of the online forum for informal caregivers to prepare tailored support for this vulnerable population.","PeriodicalId":74321,"journal":{"name":"Npj mental health research","volume":" ","pages":"1-8"},"PeriodicalIF":0.0,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44184-024-00100-y.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142634094","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