Abstract:Objective To explore the efficacy of bright light therapy （BLT） as an adjunctive therapy for non-seasonal depressive disorder on the basis on drug treatment. Methods A total of 33 patients with non-seasonal depression hospitalized in the Mental Health Center of the First Hospital of Hebei Medical University from September 2020 to January 2021 were selected as the research subjects. According to the random number table method， they were divided into BLT group （17 patients） and dim light therapy group （16 patients）. Based on drug treatment， BLT adjuvant treatment and dim light treatment were given in the morning for 2 weeks. The scores of 17-item Hamilton Depression Scale （HAMD-17） and Clinical Global Impression （CGI） were compared between the two groups before treatment and at the end of the second week of the treatment； The scores of 16-Item Quick Inventory of Depressive Symptomatology Self-Report （QIDS-SR16） were compared between the two groups before treatment and at the end of the first week of treatment. The clinical response rate of the two groups at the end of the second week of treatment was compared， and the onset time of treatment was evaluated. Results 15 participants in the BLT group and 12 participants in the dim light therapy group completed this study. There were 7 patients with moderate depression and 8 patients with major depression in the BLT group， 7 patients with moderate depression and 5 patients with major depression in the dim light therapy group. Before the treatment， the score of cognitive impairment factor in BLT group was higher than that in dim light therapy group ［2.00（1.67，2.00） vs 1.33（0.75，1.90）］， and the difference is statistically significant （Z= -2.777，P＜ 0.01）. At the end of the second week of treatment， the total HAMD-17 score， anxiety somatization factor score， and disease severity score were statistically significantly lower in the BLT group than those in the dim light therapy group ［（9.40±4.15） vs （13.75±5.61）， （0.56±0.38） vs （1.00±0.53） and 2.00（1.00，3.00） vs 3.00（3.00，4.00）； P ＜ 0.05］. The change of cognitive impairment factor scores before and after treatment in the BLT group was higher than that in the dim light therapy group ［1.31（1.00，1.34） vs 0.33（0，1.17）］. The difference was statistically significant （Z=-2.680， P＜ 0.01）. The clinical response rate of BLT group was 8/15， which compared with 4/12 of the dim light therapy group， showing no statistically significant difference （P ＞ 0.05）. The onset time of treatment was 5.14 days in the BLT group. No effect was found within 1 week in the dim light therapy group. Conclusions BLT， as an adjunctive therapy， can improve depressive symptoms and reduce disease severity quickly and effectively for patients with non-seasonal depressive disorder.

Abstract:Objective To explore the clinical characteristics and related factors of somatization symptoms in patients with depression at different ages. Methods A total of 1 503 outpatients from 11 hospitals in China from September 2014 to April 2015 were selected as the research subjects. Patient Health Questionnaire-15 （PHQ-15） and Brief 16-Item Quick Inventory of Depressive Symptomatology Self-Report （QIDS-SR16） were applied to assess the somatization symptoms and the severity of depressive symptoms. PHQ- 15 score less than 5 points means no somatization symptoms， and greater than or equal to 5 points means somatization symptoms. Spearman correlation was used to analyze the relationship between somatization symptoms and general demographic data and disease-related data in patients with depression. Age stratification was carried out at 18 to 39 years old （young group）， 40 to 64 years old （middle-aged group） and over and equal to 65 years old （elderly group）. Cumulative odds Logistic regression was used to analyze the related factors of somatization symptoms in patients with depression at different ages. Results A total of 748 （49.8%） patients with depression had somatization symptoms， of which 82.6% （618/748） of the patients' somatization symptoms were fatigue or listlessness. The scores of items with back， arm， leg or joint pain， dysmenorrhea or other problems during menstruation， pain or other problems in sexual life of patients at three different ages were compared， and the difference was statistically significant （P ＜ 0.05）. Spearman correlation analysis showed that somatization symptoms in patients with depression were positively correlated with somatic diseases， types of antidepressants， sedative hypnotics， and QIDS-SR16 scores （P ＜ 0.05）， and negatively correlated with years of education， age of first attack， and antipsychotics （P ＜ 0.05）. Taking elderly group patients as a reference， cumulative odds Logistic regression analysis showed that， the types of antidepressants （OR=2.12， 95%CI=1.38-3.26）， combination with sedative hypnotics （OR=1.59， 95%CI=1.14-2.22）， combination with antipsychotics （OR=0.59， 95%CI=0.39-0.90）， and the presence of residual symptoms （OR=11.07， 95%CI=7.70-15.90） were the related factors of somatization symptoms in young patients （P＜ 0.05）. Combination with sedative hypnotics （OR=1.51， 95%CI=1.10-2.08）， combination with antipsychotics （OR=0.45， 95%CI=0.31-0.66） and residual symptoms （OR=9.59， 95%CI=6.89-13.34） were the related factors of somatization symptoms in middle-aged patients （P＜ 0.05）. Conclusions The somatization symptoms of patients with depression after treatment were different in different age groups. Identifying age-related somatization symptoms is very important for clinicians to refine the accompanying characteristics of depression and implement individualized comprehensive intervention.

Abstract:Objective To explore the impact of alcohol use disorder （AUD） family history on male risk drinking behaviors and prevalence of AUD. Methods A total of 1 379 male staff from 10 companies in Gaocheng District， Shijiazhuang， Hebei Province were recruited from January to December 2016 by stratified random sampling method. All the research subjects were divided into positive family history （PFH） group （n=452） and no family history （NFH） group （n=927）. The general demographic characteristics and alcohol use were investigated by self-made questionnaire and self-report. The Alcohol Use Disorders Identification Test （AUDIT） and the Alcohol Dependence Scale （ADS） were used to evaluate the subjects' drinking risk level and alcohol dependence degree respectively. The fourth edition of Diagnostic and Statistical Manual of Mental Disorders （DSM- Ⅳ） was used to diagnose alcohol dependence and alcohol abuse. Self-rating Depression Scale， Selfrating Anxiety Scale and Pittsburgh Sleep Quality Index were used to evaluate the subjects' depression， anxiety and sleep. Multivariate Logistic regression was used to analyze the risk factors of AUD. Results The age of first drinking in PFH group was lower than that in NFH group， and the difference was statistically significant （t=2.519，P ＜ 0.05）. The prevalence of regular drinking， drinking alone， drinking on an empty stomach， drinking quickly， drinking sullenly， drinking more than six days a week in recent one year， drinking moderate Baijiu， drinking heavily， getting drunk after drinking and binge drinking of PFH group was higher than that of NFH group， and the differences were statistically significant （χ2 =50.930，11.856，19.165，26.808，11.809， 49.897，39.483，19.534，63.310，21.643；P＜ 0.01）. The prevalence of high risk drinking， alcohol dependence and AUD of PFH group was higher than that of NFH group ［56.9%（257/452） vs 34.1%（316/927）， 14.4% （65/452） vs 6.8%（63/927）， 52.0% （235/452） vs 30.5%（283/927）］， and the differences were statistically significant （χ2 =64.866，20.757，59.678；P＜ 0.01）. Multiple Logistic regression analysis showed that after controlling for age， education level， occupation， and other factors， having family history of AUD was the risk factor of AUD prevalence of male staff （OR=1.838， 95%CI=1.430-2.364）. Conclusions Individuals with family history of AUD are more likely to develop bad drinking behavior. Family history of AUD is an independent risk factor for the occurrence of AUD.

Abstract:Objective To investigate difference between Mood Disorder Questionnaire （MDQ） and 32 Items Hypomania Check List （HCL-32） in screening manic/hypomanic symptoms in patients with depressive disorders in psychiatric hospitals and detection rate， as well as the difference in clinical characteristics between negative and positive patients. Methods A total of 105 patients with depressive disorders in the inpatient department and outpatient of Beijing Anding Hospital Affiliated to Capital Medical University from September 2014 to December 2015 were selected as the research subjects. MDQ and HCL-32 were applied to investigate previous hypomanic/manic symptoms. The total score of MDQ ≥ 7 and the total score of HCL- 32 ≥ 14 were positive for previous hypomanic/manic symptoms. The positive detection rate of the two scales and the clinical characteristics of positive and negative patients were compared. The reliability of the scale was tested by Cronbach's α. Results The Cronbach's α of the MDQ was 0.784 （95%CI=0.718-0.840， P ＜ 0.01）； the Cronbach's α of the HCL-32 was 0.943 （95%CI=0.926-0.958， P ＜ 0.01）. The positive rate of MDQ screening was 15.24% （16/105）， which is lower than that of HCL-32 screening positive rate 40.95% （43/105）， and the difference was statistically significant （P ＜ 0.01）. The consistency of the two scales is low，and the difference is statistically significant （Kappa=0.281， P＜ 0.01）. Among the positive patients screened by MDQ， 7/16 was accompanied by suicidal ideas， attempts or behaviors， and 6/16 was accompanied by atypical depressive symptoms， which was higher than 29.21% （26/89） and 13.48% （12/89） of the negative patients， and the difference was statistically significant （P＜ 0.05）. Conclusions The detection rate of previous hypomania/ mania symptoms in patients with depression by HCL-32 is higher than that of MDQ， and depression patients with positive screening have a high risk of suicide， accompanied by atypical depression characteristics.

Abstract:Objective To analyze the difference of cognitive impairment between bipolar disorder Ⅰ and Ⅱ patients in remission stage. Methods The patients in the outpatient and inpatient department of Beijing Huilongguan Hospital from January to December 2020 were selected as the research subjects. According to the diagnostic criteria of DSM-5， the patients were assigned into Bipolar disorder Ⅰ and Ⅱ group， with 30 cases in each group. At the same time， 35 healthy controls matched for gender， age， education background were recruited. The general situation questionnaire， Young's Mania Scale， Hamilton Depression Scale and MATRICS Consensus Cognitive Battery （MCCB） test were applied in the investigation. Spearman correlation was used to analyze the correlation between cognitive function and clinical data in patients with bipolar disorder. Results Comparing among the 3 groups， the differences in verbal learning ［（51.07±9.75） vs （57.07±9.67） vs （57.66±6.96）］， visual learning ［（46.17±12.03） vs （53.80±6.39） vs （55.57±7.47）］， reasoning problem solving ［（49.80±10.24） vs （55.03±5.44） vs （55.80±7.33）］and total MCCB scores ［（48.33±8.55） vs （53.10±6.97） vs （55.86±5.11）］were statistically significant （F=5.333， 9.885， 5.336， 9.636； P ＜ 0.05）. Comparing between bipolar disorder group and control group， the differences in processing speed ［（52.00±8.94） vs （60.74±7.50）］， speech learning ［（54.07±10.09） vs （57.66±6.96）］， visual learning ［（49.98±10.30） vs （55.57±7.48）］， reasoning problem solving ability ［（52.42±8.55） vs （55.80±7.33）］and total MCCB scores ［（50.72±8.10） vs （55.86±5.11）］ were statistically significant （t=4.871， 1.861， 2.806， 2.040， 3.379； P ＜ 0.05）. Spearman correlation analysis showed that the number of episodes of hypomania was positively correlated with visual learning and memory， the number of episodes of mania and reasoning was negatively correlated with problem solving ability， and the number of episodes was negatively correlated with attention/vigilance （P ＜ 0.05）. Conclusions Cognitive impairment was greater in patients with bipolar Ⅰ than in patients with bipolar Ⅱ， and the cognitive impairment remained in patients with bipolar who in remission stage.

Abstract:Objective To explore the influencing factors of cognitive dysfunction after drug treatment of adolescent patients with depression. Methods The clinical data of 212 cases of adolescent depression hospitalized in Fuyang Third People's Hospital from January 2019 to April 2022 were analyzed retrospectively. According to the score of Montreal Cognitive Assessment （MoCA） after treatment， patients were divided into cognitive dysfunction free group （n=141， score of MoCA equal and over 26） and cognitive dysfuntion group （n=71， score of MoCA under 26）. The basic data of the two groups were collected and compared， including age， gender， body mass index （BMI）， course of disease， smoking history， family history， drinking history， Social Support Rating Scale （SSRS）， 17-Items Hamilton Depression Scale （HAMD-17）， educational level， type of depression attack. Receiver operating characteristic （ROC） curve was used to analyze the value of age and SSRS score in predicting cognitive dysfunction in adolescent patients with depression after treatment. Multivariate Logistic regression was used to analyze the risk factors of cognitive dysfunction in adolescent patients with depression after treatment. Results There was no significant difference in gender， BMI， course of disease， family history， HAMD-17 score and depression attack type between the two groups （P＞ 0.05）. The age and the rates of smoking， drinking and junior high school education patients in the cognitive dysfunction group was higher than those in the cognitive dysfunction free group， while the score of SSRS in the cognitive dysfunction group were lower than those in the cognitive dysfunction free group， and the differences were statistically significant （P＜ 0.05）. The areas under the ROC curve of age and SSRS score predicting cognitive dysfunction in adolescent patients with depression after treatment were 0.896 and 0.964， respectively （P ＜ 0.05）. Multivariate Logistic regression analysis showed that age between 14 to 18 years old （OR=1.571， 95%CI=1.251-1.973）， smoking （OR=1.457， 95%CI=1.187-1.788）， drinking （OR=1.254， 95%CI=1.093-1.439）， junior high school education level （OR=1.513， 95%CI=1.178-1.943）， SSRS score under 20 （OR=1.593， 95%CI=1.251-2.028） were the risk factors of cognitive dysfunction after treatment of adolescent depression （P ＜ 0.05）. Conclusions After the treatment of adolescent depression， cognitive dysfunction is affected by age， smoking， drinking， educational level and social support. Close attention should be paid to the prevention of cognitive dysfunction.

Abstract:Schizophrenia is a severe mental disorder in which the structure and function of the brain are abnormal. Early detection and intervention in the prodromal stage of schizophrenia can greatly improve their prognosis. At present， there is still a few of objective indicators for the early identification of clinical high risk of psychosis （CHR）. With the development of neuroimaging technology， many studies are committed to finding biomarkers of CHR gray matter through brain structural magnetic resonance imaging. Related studies have reported the abnormalities of cortical and subcortical imaging in CHR， but there are few consistent conclusions. This paper reviews the research progress of CHR structural magnetic resonance imaging， to provide reference for clinical practice and future research.

Abstract:In clinical practice， bipolar depression is often misdiagnosed as unipolar depression， and the misdiagnosis rate is high. Only about 20% of bipolar depression patients can be definitive diagnosed in the first year， and most patients need 7 to 10 years to be diagnosed after the first episode. Now the differentiation between two affective disorders is still mainly based on clinical symptoms and characteristics. This paper reviews the difference between unipolar and bipolar depression and the prediction of its curative effect through eventrelated potential， hoping to find an objective index that can guide the clinical differentiation and prediction of the two diseases.

Abstract:Patients with attention deficit hyperactivity disorder（ADHD） have impairments in attention， impulsivity control and emotion regulation. Cognitive behavioral therapy （CBT） can improve their functions by attending to negative cognition and providing compensatory behavioral strategies. This paper reviews domestic and foreign research of CBT， including its conceptual model， curative efficacy progress， evolution and neural mechanisms.

Abstract:With the continuous development of evidence-based medicine， psychotherapy is also developing in the direction of evidence-based and objective， gradually changing from standardized treatment at the overall level to customized treatment at the individual level. In this review， we describe the framework of measurement-based psychotherapy， and introduce the choice of psychotherapy decision-making， as well as the evaluation， progress monitoring and adjustment of the treatment process， in order to provide reference for promoting accurate individualized treatment， identify and reduce the risk of treatment failure， and maximize the benefits of psychotherapy.

Abstract:Cognitive bias is one of the important reasons for the emergence， development and persistence of depressive symptoms. More and more researchers combine multiple cognitive biases for in-depth exploration. The cognitive bias of patients with depression mainly includes attention， interpretation and memory bias， which are independent and related to each other. Some studies have shown that attention bias is directly or indirectly related to memory bias through interpretation bias， and the combination of multiple cognitive biases can more significantly predict depressive symptoms than single cognitive bias. This paper summarizes the cognitive bias of patients with depression， the related theories of combined cognitive bias， the specific relationship between various cognitive biases and its impact on depressive symptoms

Abstract:It is a common clinical imaging manifestation that new abnormal high density image appears on brain CT immediately after mechanical thrombectomy in patients with acute cerebral infarction. CT high density imaging usually includes contrast enhancement， contrast extravasation or cerebral hemorrhage， among which cerebral hemorrhage is a more serious complication. It is found that CT high density imaging has certain predictive value on final infarct volume， intracranial hemorrhage transformation and functional prognosis. The presence of high-density CT images often predicts a higher risk of intracranial hemorrhage transformation and poor prognosis （90 d modified Rankin scale ≤ 2 points）. The occurrence mechanism of CT high density shadow is very complex and has not been fully understood. Currently， it is generally believed that the occurrence and development of CT high density shadow is related to the destruction of the blood-brain barrier， the application of anticoagulants， ischemia-reperfusion injury， the injury of vascular wall by interventional instruments， the toxic and side effects of contrast agents and many other factors. It is of great significance to explore the related mechanisms of intracranial hemorrhage to reduce the incidence and improve the prognosis of patients. This paper reviews the research progress on the mechanism of high density imaging after mechanical thrombectomy in patients with acute cerebral infarction.

Abstract:Psychiatry is one of the earliest majors in China to carry out therapeutic drug monitoring （TDM）. Although TDM has played an essential role in individualized treatment， some issues in clinical application are still controversial. Led by the Division of Therapeutic Drug Monitoring， Chinese Pharmacological Society， joined with three other academic organizations， we developed the Expert Consensus on Clinical Application of Psychiatric Therapeutic Drug Monitoring in China （2022 Edition）. This consensus involves issues about practical aspects， results interpretation， clinical decision-making， and special populations. This consensus will improve the clinical application of TDM in psychopharmacological treatment