Using virtual patient to assess primary health workers
10.11817/j.issn.1672-7347.2021.210139
- Author:
Chao ZHANG
1
;
Xin JIN
2
;
Dan LUO
3
;
Dong XU
4
;
Jing LIAO
5
;
Wenjie GONG
6
Author Information
1. Department of Maternal, Child and Adolescent Health, Xiangya School of Public Health, Central South University, Changsha 410005. zhangch@csu.edu.cn.
2. Department of Maternal, Child and Adolescent Health, Xiangya School of Public Health, Central South University, Changsha 410005.
3. Department of Social Medicine and Health Management, Xiangya School of Public Health, Central South University, Changsha 410005. luodan_csu_2011@126.com.
4. Center for World Health Organization Studies and Department of Health Management, School of Health Management, Southern Medical University, Guangzhou 510080.
5. Global Health Institute, School of Public Health, Sun Yat-sen University, Guangzhou 510080.
6. Department of Maternal, Child and Adolescent Health, Xiangya School of Public Health, Central South University, Changsha 410005. gongwenjie@csu.edu.cn.
- Publication Type:Journal Article
- Keywords:
competency;
postpartum depression;
recognition;
virtual patient
- MeSH:
Child;
China;
Cross-Sectional Studies;
Depression, Postpartum/diagnosis*;
Female;
Health Personnel;
Humans;
Surveys and Questionnaires
- From:
Journal of Central South University(Medical Sciences)
2021;46(10):1129-1137
- CountryChina
- Language:English
-
Abstract:
OBJECTIVES:Primary health workers are the first fine to identify postpartum depression, which is important for patients with this disease to get early specialist diagnosis and treatment. The smartphone-based virtual patient is economical, convenient and effective, and has been applied extensively to evaluate the competency to detect postpartum depression, but there is no relevant application in China. This study aims to use virtual patient to assess the current status on the competency of detecting postpartum depression among primary maternal and child health workers in Hunan Province, and to explore potential influencing factors.
METHODS:A total of 222 primary maternal and child health workers from 3 regions with low, medium, and high economic levels in Hunan Province were enrolled, and smartphone-based virtual patients with postpartum depression were used for the assessment from May to July in 2018, and a self-designed questionnaire was used to investigate their demographic characteristics. The competency to detect postpartum depression was measured by 2 indicators: diagnostic accuracy and treatment accuracy. Descriptive statistical methods were used to describe the competency to detect postpartum depression among them and their demographic characteristics. A logistic regression analysis was used to explore the possible influencing factors for the diagnostic accuracy and treatment accuracy.
RESULTS:The diagnostic accuracy rate was 64.0%. There was no significant difference between the demographic characteristics and diagnostic accuracy rate (
CONCLUSIONS:About half of the primary maternal and child health workers in Hunan Province, China have basic competency to detect postpartum depression, but the overall results are not satisfactory. The regional economic level is correlated with the competency of detecting postpartum depression, and the competency of detecting postpartum depression is stronger in more developed areas. Moreover, for the patients who have been identified as postpartum depression, the rate of correct treatment is low, which warrants particular attention in the follow-up training.
