Background: Anxiety, depression, and sleep disorders, as psychological and emotional diseases, have serious impact on people's physical and mental health, and receive increasing academic attention. This study aimed to examine anxiety, depression, and sleep disorder of staff in a district of Shenzhen and to provide the basis for the development of targeted intervention measures to improve the psychological status of cadres.
Methods: Based on the psychological evaluation data of staff cadres in a district of Shenzhen City obtained from January to December 2020, a stratified sampling method was adopted to randomly select two streets and three communities in each street. A total of six communities were selected as investigation units. All participants filled out the Self-rating Anxiety Scale (SAS), Self-rating Depression Scale (SDS), and Pittsburgh Sleep Quality Index (PSQI). Chi-square test and multiple logistic regression analysis were performed using R4.2.0 statistical software.
Results: A total of 705 effective psychological assessment questionnaires were matched, and there were 71 (10.13%) positive results on SAS, 156 (22.13%) positive results on SDS, and 264 (37.45%) positive results on PSQI. Chi-square test results showed that the detection rates of anxiety and depression were significantly different among the staff cadres of different genders and different educational levels (p < 0.05). The detection rate of sleep disorder of government officials significantly differed among different age groups (p < 0.05). The logistic regression analysis showed that the detection rates of anxiety, depression, and sleep disorder of female cadres and workers were significantly higher than those of male cadres and workers (p < 0.05). The detection rates of anxiety and depression of the staff with bachelor's degree and graduate degree were significantly lower than those of the staff with a college degree or below (p < 0.05).
Conclusion: The detection rates of anxiety and depression are different among staff of different genders and different education levels in a district of Shenzhen, where female staff and those with lower education levels have higher detection rates.