西南农村精神分裂症患者躯体攻击行为的预测

IF 3.5 Q3 PSYCHIATRY
Alpha psychiatry Pub Date : 2025-08-26 eCollection Date: 2025-08-01 DOI:10.31083/AP46062
Dongmei Wu, Tingting Liu, Quan Song, Changwei Li, Yuchuan Yue, Junlan Yang, Tao Li, Zixiang Ye
{"title":"西南农村精神分裂症患者躯体攻击行为的预测","authors":"Dongmei Wu, Tingting Liu, Quan Song, Changwei Li, Yuchuan Yue, Junlan Yang, Tao Li, Zixiang Ye","doi":"10.31083/AP46062","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Physical aggression in schizophrenia patients carries significant societal implications. Previous studies on aggression prediction have primarily focused on hospitalized patients, overlooking specific rural community contexts in China. This study investigated multidimensional predictive factors to develop and validate a predictive model for predicting physical aggression in schizophrenia patients in rural communities in southwestern China.</p><p><strong>Methods: </strong>We used convenience sampling to select 889 confirmed patients with schizophrenia from 22 rural townships recorded by the Pengzhou Mental Health Center from September to November, 2019 for baseline survey. Sixty-two candidate factors were investigated using the Morningness-Eveningness Questionnaire, Multidimensional Fatigue Inventory, and Medication Coherence Rating Scale, and aggression was evaluated using the Modified Overt Aggression Scale during a 3-month follow-up. Logistic regression was used to construct a risk prediction model and the model was validated using the receiver operating characteristic (ROC) curve.</p><p><strong>Results: </strong>Two variable selection methods, least absolute shrinkage and selection operator and multivariate logistic regression, yielded two models: Model 1 with 27 variables and Model 2 with six variables. Both models demonstrated perfect discrimination, good calibration, and clinical utility. Model 2, with three historical and three modifiable factors, demonstrated greater utility for communities, which included physical aggression against others prior to the first episode of schizophrenia, the Modified Overt Aggression Scale score at first episode onset, mental fatigue, body mass index, experiences of discrimination, and aggression against objects before the first episode. Most predictors were non-specific to schizophrenia.</p><p><strong>Conclusion: </strong>These findings may help to alleviate the social discrimination and constraints faced by individuals with schizophrenia in rural communities, facilitating the provision of proactive mental health services. Furthermore, our results highlight body mass index, discrimination experiences, and mental fatigue as critical areas for rural community mental health nursing professionals.</p><p><strong>Clinical trial registration: </strong>No: ChiCTR1800015219. https://www.chictr.org.cn/showproj.html?proj=25941.</p>","PeriodicalId":72151,"journal":{"name":"Alpha psychiatry","volume":"26 4","pages":"46062"},"PeriodicalIF":3.5000,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12416045/pdf/","citationCount":"0","resultStr":"{\"title\":\"Predicting Physical Aggression among Schizophrenia Patients in Rural Communities of Southwestern China.\",\"authors\":\"Dongmei Wu, Tingting Liu, Quan Song, Changwei Li, Yuchuan Yue, Junlan Yang, Tao Li, Zixiang Ye\",\"doi\":\"10.31083/AP46062\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Physical aggression in schizophrenia patients carries significant societal implications. Previous studies on aggression prediction have primarily focused on hospitalized patients, overlooking specific rural community contexts in China. This study investigated multidimensional predictive factors to develop and validate a predictive model for predicting physical aggression in schizophrenia patients in rural communities in southwestern China.</p><p><strong>Methods: </strong>We used convenience sampling to select 889 confirmed patients with schizophrenia from 22 rural townships recorded by the Pengzhou Mental Health Center from September to November, 2019 for baseline survey. Sixty-two candidate factors were investigated using the Morningness-Eveningness Questionnaire, Multidimensional Fatigue Inventory, and Medication Coherence Rating Scale, and aggression was evaluated using the Modified Overt Aggression Scale during a 3-month follow-up. Logistic regression was used to construct a risk prediction model and the model was validated using the receiver operating characteristic (ROC) curve.</p><p><strong>Results: </strong>Two variable selection methods, least absolute shrinkage and selection operator and multivariate logistic regression, yielded two models: Model 1 with 27 variables and Model 2 with six variables. Both models demonstrated perfect discrimination, good calibration, and clinical utility. Model 2, with three historical and three modifiable factors, demonstrated greater utility for communities, which included physical aggression against others prior to the first episode of schizophrenia, the Modified Overt Aggression Scale score at first episode onset, mental fatigue, body mass index, experiences of discrimination, and aggression against objects before the first episode. Most predictors were non-specific to schizophrenia.</p><p><strong>Conclusion: </strong>These findings may help to alleviate the social discrimination and constraints faced by individuals with schizophrenia in rural communities, facilitating the provision of proactive mental health services. Furthermore, our results highlight body mass index, discrimination experiences, and mental fatigue as critical areas for rural community mental health nursing professionals.</p><p><strong>Clinical trial registration: </strong>No: ChiCTR1800015219. https://www.chictr.org.cn/showproj.html?proj=25941.</p>\",\"PeriodicalId\":72151,\"journal\":{\"name\":\"Alpha psychiatry\",\"volume\":\"26 4\",\"pages\":\"46062\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2025-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12416045/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Alpha psychiatry\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31083/AP46062\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/8/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q3\",\"JCRName\":\"PSYCHIATRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Alpha psychiatry","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31083/AP46062","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/8/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"PSYCHIATRY","Score":null,"Total":0}
引用次数: 0

摘要

目的:精神分裂症患者的肢体攻击行为具有重要的社会意义。以往关于攻击行为预测的研究主要集中在住院患者身上,忽视了中国农村社区的具体情况。本研究探讨了多维预测因素,建立并验证了西南地区农村精神分裂症患者身体攻击行为的预测模型。方法:采用方便抽样的方法,选取彭州市精神卫生中心2019年9 - 11月记录的22个乡镇确诊精神分裂症患者889例进行基线调查。在3个月的随访中,采用早晚性问卷、多维疲劳量表和药物一致性评定量表对62个候选因素进行调查,并采用改良显性攻击量表对攻击行为进行评估。采用Logistic回归构建风险预测模型,并采用受试者工作特征(ROC)曲线对模型进行验证。结果:采用最小绝对收缩选择算子和多元逻辑回归两种变量选择方法,得到模型1 27变量和模型2 6变量。两种模型均表现出良好的鉴别性、良好的校准性和临床实用性。模型2包含3个历史因素和3个可修改因素,显示出社区更大的效用,包括精神分裂症首次发作前对他人的身体攻击、首次发作时的修正显性攻击量表评分、精神疲劳、体重指数、歧视经历和首次发作前对物体的攻击。大多数预测因子对精神分裂症没有特异性。结论:这些发现有助于缓解农村社区精神分裂症患者面临的社会歧视和制约,促进积极主动的精神卫生服务的提供。此外,我们的研究结果强调了身体质量指数、歧视经历和精神疲劳是农村社区精神卫生护理专业人员的关键领域。临床试验注册号:ChiCTR1800015219。https://www.chictr.org.cn/showproj.html?proj=25941。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predicting Physical Aggression among Schizophrenia Patients in Rural Communities of Southwestern China.

Objective: Physical aggression in schizophrenia patients carries significant societal implications. Previous studies on aggression prediction have primarily focused on hospitalized patients, overlooking specific rural community contexts in China. This study investigated multidimensional predictive factors to develop and validate a predictive model for predicting physical aggression in schizophrenia patients in rural communities in southwestern China.

Methods: We used convenience sampling to select 889 confirmed patients with schizophrenia from 22 rural townships recorded by the Pengzhou Mental Health Center from September to November, 2019 for baseline survey. Sixty-two candidate factors were investigated using the Morningness-Eveningness Questionnaire, Multidimensional Fatigue Inventory, and Medication Coherence Rating Scale, and aggression was evaluated using the Modified Overt Aggression Scale during a 3-month follow-up. Logistic regression was used to construct a risk prediction model and the model was validated using the receiver operating characteristic (ROC) curve.

Results: Two variable selection methods, least absolute shrinkage and selection operator and multivariate logistic regression, yielded two models: Model 1 with 27 variables and Model 2 with six variables. Both models demonstrated perfect discrimination, good calibration, and clinical utility. Model 2, with three historical and three modifiable factors, demonstrated greater utility for communities, which included physical aggression against others prior to the first episode of schizophrenia, the Modified Overt Aggression Scale score at first episode onset, mental fatigue, body mass index, experiences of discrimination, and aggression against objects before the first episode. Most predictors were non-specific to schizophrenia.

Conclusion: These findings may help to alleviate the social discrimination and constraints faced by individuals with schizophrenia in rural communities, facilitating the provision of proactive mental health services. Furthermore, our results highlight body mass index, discrimination experiences, and mental fatigue as critical areas for rural community mental health nursing professionals.

Clinical trial registration: No: ChiCTR1800015219. https://www.chictr.org.cn/showproj.html?proj=25941.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信