ObjectiveTo integrate person imagery from drawing tests in screening for mental disorders through meta-analysis to identify indicators that can effectively predict mental disorders. MethodsA computerized search of CNKI, WanFang Data, VIP, PubMed, Web of Science, and EBSCO databases was conducted to collect studies related to mental disorders and drawing tests, with a search timeframe of the period from the creation of the database to May 8, 2023. Meta-analysis was performed using CMA 3.0 after two researchers independently screened the literature, extracted information, and assessed the risk of bias. ResultsA total of 43 studies were included, with 791 independent effect sizes and 8 444 subjects. Meta-analysis revealed that a total of 29 person imagery traits significantly predicted mental disorders, which could be categorized into 7 types according to the features: absent, bizarre, blackened, simplified, static, detailed, and holistic. The subgroup analysis revealed that the specific indicators of affective disorders included "excessive separation among items", "oversimplified person", "rigid and static person" and "hands behind the back". The specific indicators of thought disorders were "absence of limbs", "absence of facial features" and "disproportionate body proportions". Moreover, there were seven common indicators of mental disorders, including "oversimplified drawing", "very small drawing", "very small person", "weak or intermittent lines", "single line limb", "absence of hands or feet" and "no expression or dullness''. ConclusionThe findings could provide a reference standard for selection and interpretation of drawing indicators, promote standardization of the drawing test, and enhance the accuracy of results in screening for mental disorders.
The interaction mechanism between mental disorders and diabetes is complex, involving genetics, endocrine metabolism, inflammation, oxidative stress and other aspects, which makes it difficult to treat patients with mental disorders complicated by diabetes. Such patients mostly use drugs and non-drug interventions to relieve symptoms of mental disorders and improve blood sugar levels, but the mechanism of mental disorders and diabetes needs to be systematically summarized and needs practical means to intervene. This article starts with the pathogenesis of diabetes and then describes the interaction mechanism of schizophrenia, bipolar disorder, depression and diabetes in detail. Finally, the intervention measures for patients with mental disorders complicated by diabetes are summarized, which aims to provide a reference for medical staff engaged in related work.
The causes of mental disorders are complex, and early recognition and early intervention are recognized as effective way to avoid irreversible brain damage over time. The existing computer-aided recognition methods mostly focus on multimodal data fusion, ignoring the asynchronous acquisition problem of multimodal data. For this reason, this paper proposes a framework of mental disorder recognition based on visibility graph (VG) to solve the problem of asynchronous data acquisition. First, time series electroencephalograms (EEG) data are mapped to spatial visibility graph. Then, an improved auto regressive model is used to accurately calculate the temporal EEG data features, and reasonably select the spatial metric features by analyzing the spatiotemporal mapping relationship. Finally, on the basis of spatiotemporal information complementarity, different contribution coefficients are assigned to each spatiotemporal feature and to explore the maximum potential of feature so as to make decisions. The results of controlled experiments show that the method in this paper can effectively improve the recognition accuracy of mental disorders. Taking Alzheimer's disease and depression as examples, the highest recognition rates are 93.73% and 90.35%, respectively. In summary, the results of this paper provide an effective computer-aided tool for rapid clinical diagnosis of mental disorders.
摘要:目的:探讨重型颅脑损伤后早期精神障碍临床特征及治疗方法,以提高患者的生活质量。方法:对我院48例重型颅脑损伤后早期精神障碍患者进行回顾性分析,观察精神障碍出现的时间、精神障碍的类型及预后及颅脑损伤的部位与精神障碍的关系。结果:重型颅脑损伤后精神障碍主要出现在伤后3周内,多继发于颞叶损伤,其次为额叶。临床上主要有躁狂型、抑郁型、痴呆型、精神分裂性等四型,其中以躁狂型为多见。通过治疗后,lt;1个月精神症状痊愈25例、lt;2个月痊愈13例、治疗gt;2个月仍有精神症状10例。结论:颅脑损伤后精神障碍在原发脑损伤的有效治疗前提下,辅以抗精神障碍药物治疗、心理治疗及高压氧治疗等可取得较好疗效。