Depression amongst the elderly population is a worldwide public health problem, especially in China. Affected by the urban–rural dual structure, depressive symptoms of the elderly in urban and rural areas are significantly different. In order to compare depressive symptoms and its influencing factors among the elderly in urban and rural areas, we used the data from the fourth wave of the China Health and Retirement Longitudinal Study (CHARLS). A total of 7690 participants at age 60 or older were included in this study. The results showed that there was a significant difference in the prevalence estimate of depression between urban and rural elderly (χ² = 10.9.76, p < 0.001). The prevalence of depression among rural elderly was significantly higher than that of urban elderly (OR_-unadjusted = 1.88, 95% CI: 1.67 to 2.12). After adjusting for gender, age, marital status, education level, minorities, religious belief, self-reported health, duration of sleep, life satisfaction, chronic disease, social activities and having income or not, the prevalence of depression in rural elderly is 1.52 times (OR = 1.52, 95% CI: 1.32 to 1.76) than that of urban elderly. Gender, education level, self-reported health, duration of sleep, chronic diseases were associated with depression in both urban and rural areas. In addition, social activities were connected with depression in urban areas, while minorities, marital status and having income or not were influencing factors of depression among the rural elderly. The interaction analysis showed that the interaction between marital status, social activities and urban and rural sources was statistically significant (divorced: coefficient was 1.567, p < 0.05; social activities: coefficient was 0.340, p < 0.05), while gender, education level, minorities, self-reported health, duration of sleep, life satisfaction, chronic disease, social activities having income or not and urban and rural sources have no interaction (p > 0.05). Thus, it is necessary to propose targeted and precise intervention strategies to prevent depression after accurately identifying the factors’ effects.

Background: Rates of perinatal depression in China are high. The Thinking Healthy Programme is a WHO-endorsed, evidence-based psychosocial intervention for perinatal depression, requiring five days of face-to-face training by a specialist trainer. Given the paucity of specialist trainers and logistical challenges, standardized training of large numbers of nurses is a major challenge for scaling up. We developed an electronic training programme (e-training) which eliminates the need for specialist-led, face-to-face training. The aim of this study was to evaluate the effectiveness of the e-training compared to conventional face-to-face training in nursing students. Methods: A single blind, non-inferiority, randomized controlled trial was conducted. One hundred nursing students from two nursing schools were randomly assigned to either e-training or conventional face-to-face training. Results: E-training was not inferior to specialist-led face-to-face training immediately post-training [mean ENhancing Assessment of Common Therapeutic factors (ENACT) score (M) 45.73, standard deviation (SD) 4.03 vs. M 47.08, SD 4.53; mean difference (MD) −1.35, 95% CI; (−3.17, 0.46), p = 0.14]. There was no difference in ENACT scores at three months [M = 42.16, SD 4.85 vs. M = 42.65, SD 4.65; MD = −0.481, 95% CI; (−2.35, 1.39), p = 0.61]. Conclusions: E-training is a promising tool with comparative effectiveness to specialist-led face-to-face training. E-training can be used for training of non-specialists for evidence-based psychosocial interventions at scale and utilized where there is a shortage of specialist trainers, but practice under supervision is necessary to maintain competence. However, continued practice under supervision may be necessary to maintain competence.

This study was a retrospective multicentre cohort study of patients with coronavirus disease 2019 (COVID-19) diagnosed at 24 hospitals in Jiangsu province, China as of 15 March 2020. The primary outcome was the occurrence of acute respiratory failure during hospital stay. Of 625 patients, 56 (9%) had respiratory failure. Some selected demographic, epidemiologic, clinical and laboratory features as well as radiologic features at admission and treatment during hospitalisation were significantly different in patients with and without respiratory failure. The multivariate logistic analysis indicated that age (in years) (odds ratio [OR], 1.07; 95% confidence interval [CI]: 1.03–1.10; P = 0.0002), respiratory rate (breaths/minute) (OR, 1.23; 95% CI: 1.08–1.40; P = 0.0020), lymphocyte count (109/l) (OR, 0.18; 95% CI: 0.05–0.69; P = 0.0157) and pulmonary opacity score (per 5%) (OR, 1.38; 95% CI: 1.19–1.61; P < 0.0001) at admission were associated with the occurrence of respiratory failure. Older age, increased respiratory rate, decreased lymphocyte count and greater pulmonary opacity score at admission were independent risk factors of respiratory failure in patients with COVID-19. Patients having these risk factors need to be intensively managed during hospitalisation.

Objectives To determine the age-specific clinical presentations and incidence of adverse outcomes among patients with COVID-19 in Jiangsu, China. Design and setting This is a retrospective, multi-center cohort study performed at twenty-four hospitals in Jiangsu, China. Participants From January 10 to March 15, 2020, 625 patients with COVID-19 were involved. Results Of the 625 patients (median age, 46 years; 329 [52.6%] males), 37 (5.9%) were children (18 years or less), 261 (40%) young adults (19-44 years), 248 (39.7%) middle-aged adults (45-64 years), and 79 (12.6%) elderly (65 years or more). The incidence of hypertension, coronary heart disease, chronic obstructive pulmonary disease, and diabetes comorbidities increased with age (trend test, P < .0001, P = 0.0003, P < .0001, and P < .0001 respectively). Fever, cough, and shortness of breath occurred more commonly among older patients, especially the elderly, compared to children (Chi-square test, P = 0.0008, 0.0146, and 0.0282, respectively). The quadrant score and pulmonary opacity score increased with age (trend test, both P < .0001). Older patients had significantly more abnormal values in many laboratory parameters than younger patients. Elderly patients contributed the highest proportion of severe or critically-ill cases (33.0%, Chi-square test P < 0.001), intensive care unit (ICU) (35.4%, Chi-square test P < 0.001), and respiratory failure (31.6%, Chi-square test P = 0.0266), and longest hospital stay (21 days, ANOVA-test P < 0.001). Conclusions Elderly (≥65) patients with COVID-19 had the highest risk of severe or critical illness, intensive care use, respiratory failure, and the longest hospital stay, which may be due partly to that they had higher incidence of comorbidities and poor immune responses to COVID-19.