Aims: Depression is prevalent among university students worldwide, and the prevalence appears to be increasing. As an intermediate stage between being healthy and having depression, students with subthreshold depression could develop worsening depression or recover with intervention to prevent depression. The Center for Epidemiologic Studies Depression Scale (CES-D) is a useful tool to assess subthreshold depression. The primary purpose of the current study was to evaluate the psychometric characteristics of CES-D in Chinese university students. Secondly, we aimed to describe the prevalence of subthreshold depression among the student sample and examine its demographic correlates. Methods: A total of 2,068 university students participated in the study, and they were asked to respond to the Chinese CES-D, Beck Depression Inventory-II (BDI-II), and Positive and Negative Affect Schedule (PANAS). The factor structure was evaluated by conducting exploratory (EFA) and confirmatory factor analysis (CFA) using a structural equation modeling approach. The reliability was assessed by calculating Cronbach’s alpha, inter-item correlation, and item-total correlation coefficients. The prevalence of subthreshold depression was calculated and demographic correlates of gender, grade, and major were examined by multiple regression. Results: The final sample included 1,920 participants. The EFA results suggested extraction of three factors (somatic symptoms, negative affect, and anhedonia) that account for 52.68% of total variance. The CFA results suggested that the newly derived model with 14 items was the best fit for our data. Six items were removed from the original scale (item 9, 10, 13, 15, 17, and 19). The Cronbach’s alpha of the 14-item CES-D was 0.87. The prevalence of subthreshold depression among university students reached 32.7% for the 20-item CES-D and 31% for the 14-item CES-D, although there was no significant difference of prevalence in gender, grade, and major. Conclusions: The CES-D has good reliability and validity for assessing subthreshold depression in Chinese university students.

A cross-sectional study was conducted among 249 Chinese cancer patients with multiple diagnoses to validate a Chinese version of the Brief Fatigue Inventory (BFI-C). Cronbach's coefficient alpha was 0.92 for fatigue severity items and 0.90 for fatigue interference items. Construct validity was explored by principal factor analysis and suggested a two-factor solution: fatigue severity and fatigue interference. Internal consistency reliability was excellent. Convergent validity was examined by correlating the BFI-C with 2 subscales and 2 component scores of the MOS 36-Item Short-Form Health Survey (coefficients ranged between -0.44 and -0.71, P<0.001). Known-group validity was examined by comparing fatigue severity in patients having different scores on the Eastern Cooperative Oncology Group Performance Status Scale. Approximately 60% of patients experienced moderate to severe fatigue (4 or greater on the 0-10 scale of the BFI-C "fatigue worst" item). The BFI-C is a valid, reliable instrument to measure the severity and impact of cancer-related fatigue among Chinese patients.

IntroductionThe COVID-19 pandemic caused a healthcare crisis in China and continues to wreak havoc across the world. This paper evaluated COVID-19’s impact on national and regional healthcare service utilisation and expenditure in China.MethodsUsing a big data approach, we collected data from 300 million bank card transactions to measure individual healthcare expenditure and utilisation in mainland China. Since the outbreak coincided with the 2020 Chinese Spring Festival holiday, a difference-in-difference (DID) method was employed to compare changes in healthcare utilisation before, during and after the Spring Festival in 2020 and 2019. We also tracked healthcare utilisation before, during and after the outbreak.ResultsHealthcare utilisation declined overall, especially during the post-festival period in 2020. Total healthcare expenditure and utilisation declined by 37.8% and 40.8%, respectively, while per capita expenditure increased by 3.3%. In a subgroup analysis, we found that the outbreak had a greater impact on healthcare utilisation in cities at higher risk of COVID-19, with stricter lockdown measures and those located in the western region. The DID results suggest that, compared with low-risk cities, the pandemic induced a 14.8%, 26.4% and 27.5% reduction in total healthcare expenditure in medium-risk and high-risk cities, and in cities located in Hubei province during the post-festival period in 2020 relative to 2019, an 8.6%, 15.9% and 24.4% reduction in utilisation services; and a 7.3% and 18.4% reduction in per capita expenditure in medium-risk and high-risk cities, respectively. By the last week of April 2020, as the outbreak came under control, healthcare utilisation gradually recovered, but only to 79.9%–89.3% of its pre-outbreak levels.ConclusionThe COVID-19 pandemic had a significantly negative effect on healthcare utilisation in China, evident by a dramatic decline in healthcare expenditure. While the utilisation level has gradually increased post-outbreak, it has yet to return to normal levels.

No abstract