Does the peer-led Honest, Open, Proud program reduce stigma’s impact for everyone? An individual participant data meta-regression analysis

Purpose Many people with mental illness experience self-stigma and stigma-related stress and struggle with decisions whether to disclose their condition to others. The peer-led Honest, Open, Proud (HOP) group program supports them in their disclosure decisions. In randomized controlled trials, HOP has shown positive effects on self-stigma and stigma stress on average. This study examined individual predictors of HOP outcomes and tested the hypothesis that stigma stress reduction at the end of HOP mediates positive HOP effects at follow-up. Methods Six RCTs were included with data at baseline, post (after the HOP program) and at 3- or 4-week follow-up. Baseline variables were entered in meta-regression models to predict change in self-stigma, stigma stress, depressive symptoms and quality of life among HOP participants. Mediation models examined change in stigma stress (post) as a mediator of HOP effects on self-stigma, depressive symptoms, and quality of life at follow-up. Results More shame at baseline, and for some outcomes reduced empowerment, predicted reduced HOP effects on stigma stress, self-stigma, depressive symptoms, and quality of life. Younger age was related to greater improvements in stigma stress after the HOP program. Stigma stress reductions at the end of HOP mediated positive effects on self-stigma, depressive symptoms and quality of life at follow-up. Conclusion Participants who are initially less burdened by shame may benefit more from HOP. Stigma stress reduction could be a key mechanism of change that mediates effects on more distal outcomes. Implications for the further development of HOP are discussed

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