bioRxiv Science⌕ Search

bioRxiv · 10.1101/867432

The socioeconomic burden of severe mental disorder in China, 2014-2017: a prevalence study

Abstract

Mental illness is a chronic disease with high morbidity and mortality rate, resulting in heavy economic burden for family and society, especially the severe ones. Chinese government has taken a series of action on the treatment and management of severe mental disorder (SMD), but the scale of economic burden caused by SMD was still unclear. In this paper, we applied prevalence-based bottom-up approach to estimate the direct and indirect economic burden of SMD in Southwest China from 2014 to 2017. We used the sampled inpatient medical record data of patient with SMD to calculate the total direct cost and estimated the indirect economic burden using human capital approach.The total ecomonic burden of SMD was USD9,733 million and direct burden was contiributed for 7.5% as USD734.5 million in four years total. The growth rate of direct medical cost was declined due to the health policy reform and total cost control policy. The indirect cost was rapidly increased in four years when estimated with DALYs reported in GBD2010 and resulting USD8,998.6 million. We next estimated the indirect burden using sample DALYs and occupation wage cost approach as sensitive analysis. We found that the indirect burden was sensitive to the key variable and the estimation approach, but the estimates share same increasing trend but with different velocity. Our study suggests that SMD in China have posed substantial economic burden at individual and social levels, with the appropriate estimation of total economic burden, our reaserch would attract more attention and be helpful for health resources distribution.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Xie, M., Ju, K., Ni, J., Zhao, X., Li, X., Pan, J., Zhou, Q.. 2019-12-06. The socioeconomic burden of severe mental disorder in China, 2014-2017: a prevalence study. https://doi.org/10.1101/867432

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Auditing Biomedical Literature with Blinded AI Peer Review: Where Peer Review Works, Where It Fails, and How to Strengthen It

Biomedical publishing has grown more than elevenfold since 1991, outstripping human peer review. Unblinded language models cannot audit this literature objectively because they recognize famous authors and journals from training memory. We built BARS (Blinded AI Review System), an automated referee that strips titles, author names, institutions, journal headers, and dates before grading full-text manuscripts on a 10-point scale covering methods, evidence, biology, and reproducibility. We used BARS to generate 1,874 blind reviews across 1,714 unique papers. BARS passed 100% of verified sound controls, caught 77% to 91% of internally flawed papers, eliminated a +0.35-point prestige boost, and more than doubled human referee consistency. Across 320 recent open-access articles (2020-2025) from eight fields, 54% failed on core scientific rigor (<5.0/10; 41% excluding megajournals). Revision at selective journals improved preprints more than twice as much as revision at commercial megajournals (+0.62 vs. +0.30 points; baseline-adjusted p = 0.033), and BARS recalled 98% of unresolved human referee critiques across 100 open-review papers. Across 915 date-blinded papers from 1991 to 2025, average scores fell from 7.6/10 to 5.8/10 as megajournals and template database studies expanded. Blinded self-audits of 238 papers by two senior authors -- and of this manuscript itself -- caught real statistical, control, and table errors in our own work. At four cents per paper, BARS offers a practical quality check for authors, journals, and readers (https://veg.github.io/BARS/).

scientific communication and education↗

From Problems to Solutions: How Self-Questions Drive Strong Scientific Reasoning

Metacognition, or awareness and control of thinking, is essential for problem solving because it helps solvers select strategies for learning and decide when to enact them (planning), check their understanding in the moment (monitoring), and assess effectiveness of solutions and learning strategies (evaluating). Most studies that examine metacognition do so retrospectively, leaving a critical gap in how metacognition is used in-the-moment for problem solving. In this study, we utilized a think-aloud interview approach to capture and characterize the metacognitive skills that senior undergraduate life science students at three institution types in the United States used spontaneously while solving challenging biology problems. We found that the students (n = 39) displayed a wide variety and quantity of monitoring, some evaluating, and nearly no planning skills while creating a solution backed with high-quality reasoning. Students frequently used self-questions to monitor and evaluate their thinking. We found that self-questioning is a critical skill for generating solutions, but it only moves problem solving forward if the student asks and correctly answers the self-question out loud. This study illustrates how self-questioning and other metacognitive regulation skills provide links to bridge the gap between a student's prior knowledge and specific features of a challenging problem. Based on our student data, we conceptualized a model of metacognitive phases during problem solving with high-quality reasoning. Finally, we present a self-question scaffold to facilitate the proposed phases (planning, monitoring, reasoning, and evaluating) so educators can equip students with metacognitive and scientific reasoning tools for effective problem solving.

scientific communication and education↗

Preprint solicitation as a natural experiment in scholarly publishing

Preprinting is a growing and increasingly recognized mechanism for scientific communication and productivity and a way to facilitate global access to science. The interplay of preprinting practices with formal peer-reviewed publication is an open question that is now tractable to targeted analysis. Here, we take advantage of nearly a decade of preprint solicitation at Proceedings B to address this question, which offers a quasi-experimental setting for comparing outcomes for solicited preprints and traditionally submitted manuscripts. We used submission records from 15,368 manuscripts from 2018-2024 to assess whether preprint solicitation affects acceptance rates, journal scope, author geographic diversity, and post-publication uptake. Solicited manuscripts were accepted at nearly twice the rate of traditional submissions and received more downloads and citations after publication. Submission topics were broadly similar between the two routes, though solicited manuscripts showed marginally greater subject diversity. Geographic disparities favoring the Global North persisted, but acceptance rates for solicited manuscripts converged across regions, narrowing the gap seen in traditional submissions. These findings extend earlier work on this initiative and indicate that editor-driven solicitation can identify high-quality preprints, broaden geographic representation, and increase research visibility, offering a replicable model for journals seeking to diversify authorship while maintaining editorial standards.

scientific communication and education↗