Background The COVID-19 pandemic has had a detrimental effect on the mental health of older adults living in nursing homes. Very few studies have examined the effects of Internet-based Cognitive Behavioral Therapy (ICBT) on older adults living in nursing homes during the pandemic. We conducted a feasibility study using a single-group design, to explore the effectiveness of ICBT on psychological distress in 137 older adults (without cognitive impairment) from 8 nursing homes in 4 southeast cities in China, between January and March 2020. Methods Symptoms of depression, anxiety, general psychological distress, and functional disability were measured at baseline, post-treatment (5 weeks) and at a 1-month follow-up. Mixed-effects model was used to assess the effects of ICBT. Results Statistically significant changes with large effect sizes were observed from pre- to post-treatment on the PHQ-9 ( p < .001, Cohen's d = 1.74), GAD-7 ( p < .001, d = 1.71), GDS ( p < .001, d = 1.30), K-10 ( p < .001, d = 1.93), and SDS ( p < .001, d = 2.03). Furthermore, improvements in treatment outcomes were sustained at 1-month follow-up, and high levels of adherence and satisfaction were indicated. Conclusion ICBT was effective in reducing psychological distress in older adults without cognitive impairments living in nursing homes during the COVID-19 pandemic. Thus, it could be applied in improving the mental health of this vulnerable group during the pandemic.

Aim This research aimed to shed light on the relationship between the sociodemographic characteristics of front‐line medical workers and their anxiety and depression, to provide the basis and reference for targeted mental health education and for relevant departments to formulate appropriate policies during the COVID‐19 outbreak. Methods This study adopted a convenient sampling method and examined the psychological status of 150 front‐line medical workers from Zhejiang Province with questionnaire surveys using the Hamilton Anxiety and Depression Scale. Results The participants had severe anxiety and depression; the top three items under the category of anxiety were genitourinary symptoms, behavior at interview, and respiratory symptoms, whereas the top three items under depression were feelings of guilt, weight loss, and retardation. Among all personal data, the following factors influenced anxiety, in decreasing order: degree of suspicion of being infected when showing associated symptoms, degree of fear of yourself and your family being infected, and the affiliated hospital ( p < .05). As for depression, the factors were the degree of suspicion of being infected when showing associated symptoms and the degree of fear of yourself and your family being infected ( p < .05). Conclusion This study revealed that front‐line medical staff presented symptoms of anxiety and depression when dealing with the COVID‐19 outbreak and the factors influencing their psychological stress. Guiding policies and psychological interventions is crucial to maintaining their psychological well‐being. Different measures may be implemented to solve this problem.

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Background Sleep affects a wide array of health outcomes and is associated with the quality of life. Among students, sleep quality is affected by school stage and grade; however, data regarding the different sleep-related problems students experience at different school stages are limited. In this study, we aimed to explore sleep quality among a student sample ranging from elementary school to university level. Methods Overall, data were examined for 9392 subjects aged 9–22 years. Information on sociodemographic characteristics and other variables were collected through self-administered questionnaires. Sleep quality on school nights was evaluated using the standard Pittsburgh Sleep Quality Index; global score >5 was classified as poor sleep quality. For the high school sample, logistic regression analysis was used to estimate associations between sleep quality and certain factors. Results Of the elementary school, middle school, vocational high school, senior high school, and university students, 7.5%, 19.2%, 28.6%, 41.9%, and 28.5%, respectively, showed poor sleep quality. The high school students reported the highest prevalence of shorter sleep duration (70.8%), day dysfunction (84.7%), and subjective poor sleep quality (17.2%). The elementary school students showed the highest prevalence of poor sleep efficiency (17.9%). The university students showed the highest prevalence of sleep medication use (6.4%). The vocational high school students reported the highest prevalence of sleep latency (6.3%) and sleep disturbance (7.4%). Logistic regression modeling indicated that sleep quality is positively associated with school stage, grade, family atmosphere, academic pressure, and number of friends. Conclusion Sleep quality and sleep features change greatly from elementary school to university. Interventions to improve sleep quality should consider targeting the specific issues students experience at each school stage. Alarmed by the high prevalence of poor sleep quality among high school students, it is recommended that high school students should be informed of their sleep matter and the consequences.

Objectives: Understanding the effect of night shift on hypertension risk in nurses is important to improve the health of nurses and ensure patient safety. This study aimed to evaluate the effect of the frequency and pattern of night shift on hypertension risk and the interaction of them in female nurses.Methods: This cross-sectional study constituted 84 697 female nurses in 13 cities in China. The main contents of the survey included SBP, DBP, the frequency and pattern of night shift, and some other factors that might be associated with hypertension. Logistic regression analyses were used to calculate ORs and 95% CIs to estimate the effect of the frequency and pattern of night shift on hypertension risk and the interaction of them in relation to hypertension risk.Results: Having more than 5 to 10 or more than 10 night shifts per month were significantly more likely to be hypertensive (OR 1.19, 95% CI 1.10-1.28; OR 1.32, 95% CI 1.13-1.54), whereas having less than or equal to 5 night shifts per month was not (OR 1.05, 95% CI 0.95-1.16). The patterns of night shift were all associated with a higher probability of hypertension and participants engaging in rapidly rotating night shift had a lower OR (1.14) than those having slowly rotating night shift (1.23) and permanent night shift (1.46). No significant interaction was observed between the frequency and the pattern of night shift (P interaction ¼ 0.281). Conclusion:The frequency and pattern of night shift were associated with hypertension risk in female nurses and no significant interaction was observed between them.