Objective:To analyze the influencing factors of music relaxation therapy to improve symptoms of depressive disorder and the construction of the corresponding prediction model.Methods:A total of 226 patients with depression who visited Shandong Mental Health Center from January 2018 to January 2020 were selected and treated with music relaxation therapy.According to the reduction rate of BPRS score after music relaxation therapy, patients were divided into effective group (reduction rate greater than or equal to 25%) and ineffective group (reduction rate less than 25%), and the factors influencing symptom improvement of patients in the two groups were analyzed.Positive and negative Symptom Scale (PANSS score) was used to evaluate the disease severity of patients. Patients with PANSS score less than 4 were classified as mild, PANSS score of 5 to 6 was classified as moderate, and PANSS score greater than 6 was classified as severe.Logistic multifactor regression method was used to analyze the influencing factors of music relaxation therapy on the improvement of symptoms in patients with depressive disorder, establish the prediction model of influencing factors, verify the authenticity and reliability of the model, and draw the prediction column chart of music relaxation therapy on the improvement of symptoms in patients with depressive disorder.Results:There were statistically significant differences between the two groups in gender, education level, family history of mental illness and severity of illness before treatment ( P<0.05). Logistic multifactor analysis showed that gender, family history of mental illness, severity of illness before treatment, HAMD score and HAMA score were the related factors affecting the therapeutic effect of music relaxation therapy on patients with depressive disorder ( P<0.05). The predictive model of the influence factors of music relaxation therapy on the improvement of symptoms of patients with mental disorders was constructed with female, no family history of mental illness, mild condition before treatment, HAMD score (less than7 points) and HAMA score (less than 8 points). The AUC (95% CI) was 0.631 (0.555~0.762), indicating a high accuracy of the predictive model. The predicted incidence of symptom improvement was consistent with the actual incidence. Conclusions:Female, no family history of mental illness, and mild symptoms of mental disorder before treatment respond better to music relaxation therapy. The predictive model constructed by the research can provide a reference for the selection of treatment options for patients with mental disorders.

目的:探讨品管圈(QCC)质量管理方法对心理科住院患者晚间熄灯后使用手机时间的影响。方法:对使用智能手机的15～40岁住院患者310例进行目的性抽样，于2017年10月10～23日进行现状调查，用鱼骨图进行原因分析，经真因验证后拟定对策，并干预12 w；于2018年3月19日至4月1日对使用智能手机15～40岁的住院患者298例进行调查，分析干预效果。结果:住院患者晚间熄灯后手机使用时间由活动前每人每天1.62 h下降为活动后每人每天0.53 h晨间患者按时服药率和圈成员综合能力得分高于活动前，差异均有统计学意义( P<0.05)。 结论:运用QCC质量管理方法制定的护理干预措施能有效降低心理科住院患者晚间熄灯后使用手机时间、人数，增加患者晨间按时服药率，利于疾病的快速康复，为其节约时间成本和经济成本。

目的 探讨精神分裂症患者实施家庭护理干预在改善生活质量和社会功能方面的临床效果.方法 方便选取2014年1月—2015年6月从山东省精神卫生中心精神科门诊接诊的205例精神分裂症患者作为研究对象,并将其随机分为观察组(常规治疗联合家庭护理)和对照组(常规治疗),并进行1年随访,比较两组患者社会功能和生活质量.结果 干预前,两组患者SDSS[(14.1±2.4)分vs(14.2±2.1)分]和SF-36[躯体功能(52.8±1.4)分vs(51.1±2.3)分;社会功能(53.2±0.9)分vs(52.8±1.1)分],差异无统计学意义(P>0.05),干预后3﹑6及12个月,两组SDSS[3月:(12.7±1.2)分vs(13.2±1.7)分;6个月(10.1±0.4)分vs(11.7±0.8)分;12个月(8.3±2.6)分vs(10.2±4.5)分]和SF-36评分[躯体功能3个月:(59.9±6.1)分vs(54.8±2.7)分;6月(65.3±3.1)分vs(58.1±2.7)分;12个月(70.2±7.3)分vs(62.1±3.5)分;社会功能:3个月(58.2±2.1)分vs(54.1±2.3)分;6个月(58.3±2.2)分vs(55.2±1.1)分;12月(62.4±5.2)分vs(58.1±0.6)分]较干预前差异有统计学意义(P<0.05),且组间差异有统计学意义(P<0.05).结论 对精神分裂症患者实施家庭护理,有助于其社会功能的恢复,并不断改善其生活质量,具有较高的应用价值.