摘要
目的调查上海某三甲医院心理门诊职业女性精神障碍患者现状,探讨其罹患精神障碍可能存在的影响因素,为防治职业女性精神障碍提供指导。方法采用横断面调查法,选取上海市某三甲医院心理门诊122例职业女性精神障碍患者为研究对象,选用一般情况调查表、自我效能量表、9项患者健康问卷抑郁自评量表(PHQ⁃9)、7项广泛性焦虑障碍量表(GAD7)、耶鲁布朗量表(Y⁃BOCS)、轻躁狂量表(HCL⁃32)、15项患者健康问卷躯体化症状自评量表(PHQ15)、阿森斯失眠量表(AIS)及个体访谈评估患者精神状况。通过描述性统计、非参数检验及多因素logistic回归分析探讨可能导致精神障碍的影响因素。结果职业女性精神障碍患者焦虑分数12.02±4.29,抑郁分数14.91±5.53,强迫分数6.09±5.71,双相情感障碍分数7.28±5.25,躯体化症状分数13.54±6.29,失眠分数10.79±5.27,其中轻度焦虑(36.1%)、中度抑郁(36.1%)及重度躯体化症状(39.4%)占比最大,18%存在强迫,22.1%存在双相情感障碍,68.0%明显失眠。工作时长等5个因素对焦虑的程度有影响(均P<0.05);受教育程度等6个因素对抑郁的程度有影响(均P<0.05);强迫的发生与职场人际关系等7个因素有关(均P<0.05);双相情感障碍的发生与年龄等5个因素有关(均P<0.05);不同程度躯体化症状的发生与职业发展等4个因素有关(均P<0.05);不同程度失眠的发生与加班程度等6个因素有关(均P<0.05)。多元logistic回归分析结果显示:职业稳定性越差等3个因素变化,焦虑越重(均P<0.05);自我效能越低等3个因素变化,抑郁越重(均P<0.05);职场人际关系越差等3个因素变化,强迫发生率越高(均P<0.05);房租/房贷每月花销占比越多,双相情感障碍发生率越高(P<0.05);加班越多,躯体化症状越明显(P<0.05);工作时长越长等3个因素变化,失眠越重(均P<0.05)。结论职业女性罹患精神障碍主要受个体因素(年龄、婚姻状况、受教育程度、房租/房贷每月花销占比及自我效能)和工作因素(行业类型、工作时长、加班程度、职场人际关系、职业稳定性、职业发展及企业对女性员工重视程度)的影响,从个人⁃企业⁃社会多角度采取有效干预是今后防治职业女性罹患精神障碍的关键举措。
Objective To investigate the current status and influencing factors of mental disorders in working women in psychological clinic of a first⁃class hospital in Shanghai,so as to provide guidance for prevention and treatment of this disease.Methods A cross⁃sectional survey was conducted on 122 working female patients from the psychological clinic of a first⁃class hospital in Shanghai.Mental health status was assessed by General Situation Scale,Self⁃Efficacy Scale,Patient Health Questionnaire⁃9(PHQ⁃9),Generalized Anxiety Disorder⁃7(GAD⁃7),Yale⁃Brown Obsessive⁃Compulsive Scale(Y⁃BOCS),Hypomania Checklist⁃32(HCL⁃32),Patient Health Questionnaire⁃15(PHQ⁃15),AIS scale,and individual interviews.Descriptive statistics,non⁃parametric test,and multivariate logistic regression analysis were used to investigate the influencing factors of mental disorders in working women.Results The scores of anxiety,depression,compulsion,bipolar disorder,somatization symptoms,and insomnia were 12.02±4.29,14.91±5.53,6.09±5.71,7.28±5.25,13.54±6.29,and 10.79±5.27,respectively.Mild anxiety(36.1%),moderate depression(36.1%),and severe somatization(39.4%)were very common in these patients.Additionally,compulsive behaviors were found in 18.0%of the patients,bipolar disorder in 22.1%,and insomnia in 68.0%.Five factors(such as work hours)were related to anxiety(all P<0.05).Six factors(such as education level)were related to depression(all P<0.05).Seven factors(such as workplace relationships)were related to compulsions(all P<0.05).Age and four other factors were related to bipolar disorders(all P<0.05).Career development and three other factors were related to somatization(all P<0.05).Insomnia was significantly influenced by overtime work and five other factors(all P<0.05).Multivariate logistic regression analysis indicated that bad job stability and two other factors were risk factors for anxiety(all P<0.05),low self⁃efficacy and two other factors were risk factors for depression(all P<0.05),bad workplace relationships and two other factors increased compulsive behaviors(all P<0.05),more housing expenses increased bipolar disorders(P<0.05),more overtime aggravated somatization(P<0.05),and long working hours and two other factors worsened insomnia(all P<0.05).Conclusion Mental disorders in working women have become a common social issue,and are mainly influenced by individual factors(age,marital status,education level,housing expenses,and self⁃efficacy)and work⁃related factors(industry type,work hours,overtime,workplace relationships,job stability,career development,and corporate focus on female employees).Effective interventions from personal,corporate,and social perspectives are the key to preventing and treating mental disorders in working women.
作者
张佳艺
王亚婧
张艳飞
李冠雄
陆莉
柏涌海
潘霄
王一浩
Zhang Jiayi;Wang Yajing;Zhang Yanfei;Li Guanxiong;Lu Li;Bai Yonghai;Pan Xiao;Wang Yihao(Department of Medical Service,The Second Affiliated Hospital of Naval Medical University,Shanghai 200003,China)
出处
《海军医学杂志》
2024年第11期1206-1212,共7页
Journal of Navy Medicine
关键词
职业女性
精神障碍
影响因素
Working women
Mental disorders
Influencing factors