An exploration of the sleep quality and potential violence among patients with schizophrenia in community

Chen, Zi-Ting; Wang, Hsiao-Tzu; Chueh, Ke‐Hsin; Liu, I-Chao; Yang, Chien‐Ming

doi:10.1111/ppc.12589

Cited by 13 publications

(8 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Previous studies have shown that various demographic characteristics are associated with violent behavior in schizophrenia, including: male sex ( 13 , 14 ), non-adherence to treatment ( 15 ), substance abuse ( 1 , 2 , 16 – 18 ), younger age ( 13 ), history of violence ( 2 , 15 , 19 ), personality disorders ( 20 ), and childhood trauma ( 21 – 23 ). Clinical risk factors of violent behavior in patients with schizophrenia are anxiety ( 19 ), poor sleep quality ( 24 , 25 ), hallucination and delusion ( 26 , 27 ), poor insight ( 26 , 28 ), and impulsivity ( 29 ). However, conclusions are still inconsistent.…”

Section: Introductionmentioning

confidence: 99%

Violence, neurocognitive function and clinical correlates in patients with schizophrenia

Huang

Chen

et al. 2023

Front. Psychiatry

View full text Add to dashboard Cite

BackgroundSchizophrenia patients with violent behavior are a severe public health concern, but the correlates of this violent behavior are unknown. Additionally, the relationship between neurocognitive function and violent behavior in Chinese patients with schizophrenia has not yet been investigated.MethodsA total of 337 schizophrenia inpatients were recruited. The Positive and Negative Syndrome Scale (PANSS) was used to assess psychopathological symptoms. Neurocognitive functioning was evaluated using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS).ResultsThe percentage of violent behavior was 10.4% in patients with schizophrenia. Patients with violent behavior had higher PANSS-positive, excited, and total subscale scores than patients who did not show violent behavior. Patients with violent behavior also had lower RBANS language, semantic fluency, and total subscale scores. Gender (OR = 0.066∼0.819, p = 0.023), illness duration (OR = 0.876∼0.971, p = 0.002), smoking (OR = 1.127∼2.950, p = 0.014), the PANSS positive subscale (OR = 1.050∼1.197, p = 0.001), and the RBANS language subscale (OR = 0.927∼0.987, p = 0.005) significantly contributed to the development of violent behavior in schizophrenia patients.ConclusionOur findings revealed that cognitive and clinical assessments should be considered in comprehensive assessments of future risks of violence in schizophrenia patients.

show abstract

Section: Introductionmentioning

confidence: 99%

Violence, neurocognitive function and clinical correlates in patients with schizophrenia

Huang

Chen

et al. 2023

Front. Psychiatry

View full text Add to dashboard Cite

show abstract

“…Patients with schizophrenia are more likely to exhibit violent behavior, compared with the general population. The relationship of schizophrenia and violent behavior has been repeatedly reported (1)(2)(3). Violent behaviors committed by patients with schizophrenia, not only cause physical damage or death to people, but also increase the social burden (4).…”

Section: Introductionmentioning

confidence: 99%

The Prediction and Influential Factors of Violence in Male Schizophrenia Patients With Machine Learning Algorithms

Zhang

Liu

et al. 2022

Front. Psychiatry

View full text Add to dashboard Cite

BackgroundEarly to identify male schizophrenia patients with violence is important for the performance of targeted measures and closer monitoring, but it is difficult to use conventional risk factors. This study is aimed to employ machine learning (ML) algorithms combined with routine data to predict violent behavior among male schizophrenia patients. Moreover, the identified best model might be utilized to calculate the probability of an individual committing violence.MethodWe enrolled a total of 397 male schizophrenia patients and randomly stratified them into the training set and the testing set, in a 7:3 ratio. We used eight ML algorithms to develop the predictive models. The main variables as input features selected by the least absolute shrinkage and selection operator (LASSO) and logistic regression (LR) were integrated into prediction models for violence among male schizophrenia patients. In the training set, 10 × 10-fold cross-validation was conducted to adjust the parameters. In the testing set, we evaluated and compared the predictive performance of eight ML algorithms in terms of area under the curve (AUC) for the receiver operating characteristic curve.ResultOur results showed the prevalence of violence among male schizophrenia patients was 36.8%. The LASSO and LR identified main risk factors for violent behavior in patients with schizophrenia integrated into the predictive models, including lower education level [0.556 (0.378–0.816)], having cigarette smoking [2.121 (1.191–3.779)], higher positive syndrome [1.016 (1.002–1.031)] and higher social disability screening schedule (SDSS) [1.081 (1.026–1.139)]. The Neural Net (nnet) with an AUC of 0.6673 (0.5599–0.7748) had better prediction ability than that of other algorithms.ConclusionML algorithms are useful in early identifying male schizophrenia patients with violence and helping clinicians take preventive measures.

show abstract

“…Findings from schizophrenia are very relevant to delusional disorders because of the considerable overlap between the two disorders. In schizophrenia, sleep quality has been correlated with the degree of paranoid ideation [ 36 ], with hostility and violence [ 37 ], with poor quality of life [ 38 , 39 ], with memory functions [ 40 ], with physical activity [ 41 ], and with dopamine signaling [ 42 ]. These correlations may well also apply to DD.…”

Section: Sleep and Psychosismentioning

confidence: 99%

Sleep Disturbances in Patients with Persistent Delusions: Prevalence, Clinical Associations, and Therapeutic Strategies

2020

View full text Add to dashboard Cite

Sleep disturbances accompany almost all mental illnesses, either because sound sleep and mental well-being share similar requisites, or because mental problems lead to sleep problems, or vice versa. The aim of this narrative review was to examine sleep in patients with delusions, particularly in those diagnosed with delusional disorder. We did this in sequence, first for psychiatric illness in general, then for psychotic illnesses where delusions are prevalent symptoms, and then for delusional disorder. The review also looked at the effect on sleep parameters of individual symptoms commonly seen in delusional disorder (paranoia, cognitive distortions, suicidal thoughts) and searched the evidence base for indications of antipsychotic drug effects on sleep. It subsequently evaluated the influence of sleep therapies on psychotic symptoms, particularly delusions. The review’s findings are clinically important. Delusional symptoms and sleep quality influence one another reciprocally. Effective treatment of sleep problems is of potential benefit to patients with persistent delusions, but may be difficult to implement in the absence of an established therapeutic relationship and an appropriate pharmacologic regimen. As one symptom can aggravate another, comorbidities in patients with serious mental illness all need to be treated, a task that requires close liaison among medical specialties.

show abstract

An exploration of the sleep quality and potential violence among patients with schizophrenia in community

Cited by 13 publications

References 33 publications

Violence, neurocognitive function and clinical correlates in patients with schizophrenia

Violence, neurocognitive function and clinical correlates in patients with schizophrenia

The Prediction and Influential Factors of Violence in Male Schizophrenia Patients With Machine Learning Algorithms

Sleep Disturbances in Patients with Persistent Delusions: Prevalence, Clinical Associations, and Therapeutic Strategies

Contact Info

Product

Resources

About