1.Medical institutions challenged by“Broken window effect”and“Butterfly effect”in the new media era and countermeasures
Yaqian XIANG ; Wei ZHANG ; Dong HUANG
Chinese Journal of Hospital Administration 2015;(9):713-716
False and negative information has brought forth serious impacts on doctor-patient relationship in the new media era as a result of “Broken window effect”and “Butterfly effect”.The underlying reasons are herd mentality,the public’s need to vent their discontent,the subjectivity of information distribution on the Internet and lack of proper supervision and punishment mechanism.Medical Institutions should pay special attention to the new media,leveraging it to improve doctor-patient relationship by making official voice,guiding public opinion,solving problems,and providing comfortable social environment and rational public opinion environment on the Internet.
2.Associations of sleep quality trajectory and social jetlag with comorbid symptoms of anxiety and depression among college students
Chinese Journal of School Health 2024;45(5):640-643
Objective:
To describe the prevalence and the association of sleep quality trajectory, social jetlag and comorbid symptoms of anxiety and depression among college students, in order to provide a theoretical basis for improving the comorbid symptoms of anxiety and depression in college students.
Methods:
A questionnaire survey was conducted among 1 135 college students from two universities in Shangrao, Jiangxi Province and Hefei, Anhui Province from April to May 2019, and were followed up once every one year for a total of three times, with a valid sample size of 1 034 individuals after matching with the baseline survey. A selfassessment questionnaire was used to investigate the social jetlag of college students, the Generalized Anxiety Disorder-7 (GAD-7) and Patient Health Questionnaire 9 (PHQ-9) were used to evaluate anxiety and depression symptoms, respectively, while the Pittsburgh Sleep Quality Index (PSQI) was used to assess sleep quality. College students with GAD-7 score ≥5 and PHQ-9 score ≥5 were defined as having comorbid anxiety and depression symptoms. Latent class growth model (LCGM) was employed to analyze the sleep quality trajectory of college students, and binary Logistic regression was used to analyze the relationship between social jetlag, sleep quality trajectory and comorbid symptoms of anxiety and depression.
Results:
The detection rate of comorbid symptoms of anxiety and depression among college students was 16.9%, and the detection rate of social jetlag ≥2 h was 13.8%. The sleep quality showed an overall improvement trend, and the two trajectories were good sleep quality (81.6%) and poor sleep quality (18.4%). Binary Logistic regression model showed that poor sleep quality and social jetlag ≥2 h were positively correlated with comorbid symptoms of anxiety and depression (OR=5.94, 1.84, P<0.05).
Conclusions
Poor sleep quality and social jetlag ≥2 h in college students increase the risk of comorbid symptoms of anxiety and depression. Early screening and intervention of sleep quality and reduction of social jetlag are crucial for enhancing the mental health of college students.