Patterns of adverse childhood experiences and suicidal behaviors in adolescents: A four-province study in China

This is an accepted manuscript of a paper published by Elsevier on 23/02/2021, available online at: https://doi.org/10.1016/j.jad.2021.02.045 The accepted manuscript of the publication may differ from the final published version.Background:: Adverse childhood experiences (ACEs) are associated with increased suicidal behaviors in adolescents and most research has been restricted to certain types of or cumulative exposure to ACEs. Few studies have examined the association between patterns of ACEs and suicidal behaviors. Objective:: To identify the contributions of type and pattern of exposure to ACEs to suicidal behaviors and their gender differences among middle school students in China. Methods:: A school-based health survey was conducted in four provinces in China between 2017 and 2018. 14 500 students aged 10–20 years completed standard questionnaires, to record details of ACEs, suicide ideation, suicide plan, and suicide attempt. Results:: Latent class analysis indicated four distinct patterns of ACEs exposure: high ACEs (6.3%), high abuse and neglect (21.4%), high neglect (45.5%), and low ACEs (26.8%). Logistic analyses showed that, compared with low ACEs, the high ACEs were more likely to report suicidal behaviors. No gender differences were found in the independent effects of ACEs type or pattern on suicidal behaviors, except for the emotional neglect associated with suicidal behaviors in girls than boys. Limitations:: The study was cross-sectional and used self-reported questionnaires. Thus, it is difficult to establish a causal relationship between patterns of ACEs and suicidal behaviors. Conclusion:: Our findings addressed the need for a comprehensive consideration of ACEs in preventive healthcare work to identify children exposed to the most problematic ACE patterns. The study provided the evidence of targeted intervention to preempt the emergence of suicide behavior in at-risk students in adolescents.Funding for the project was provided by National Natural Science Foundation of China (82073576 & 81773453).Published versio

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe