BACKGROUND: Despite advances in research on psychopathology and social media use, no comprehensive review has examined published papers on this type of research and considered how it was affected by the coronavirus disease 2019 (COVID-19) outbreak.
OBJECTIVE: To explore the status of research on psychopathology and social media use before and after the COVID-19 outbreak.
METHODS: We used Bibliometrix (an R software package) to conduct a scientometric analysis of 4588 relevant studies drawn from the Web of Science Core Collection, PubMed, and Scopus databases.
RESULTS: Such research output was scarce before COVID-19, but exploded after the pandemic with the publication of a number of high-impact articles. Key authors and institutions, located primarily in developed countries, maintained their core positions, largely uninfluenced by COVID-19; however, research production and collaboration in developing countries increased significantly after COVID-19. Through the analysis of keywords, we identified commonly used methods in this field, together with specific populations, psychopathological conditions, and clinical treatments. Researchers have devoted increasing attention to gender differences in psychopathological states and linked COVID-19 strongly to depression, with depression detection becoming a new trend. Developments in research on psychopathology and social media use are unbalanced and uncoordinated across countries/regions, and more in-depth clinical studies should be conducted in the future.
CONCLUSIONS: After COVID-19, there was an increased level of concern about mental health issues and a changing emphasis on social media use and the impact of public health emergencies.

OBJECTIVE: The aim of this study is to identify available reporting guidelines for traditional Chinese medicine (TCM), delineate their fundamental characteristics, assess the scientific rigor of their development process, and evaluate their dissemination.
METHODS: A search was conducted in Medline (via PubMed), China National Knowledge Infrastructure (CNKI), SinoMed, WANFANG DATA, and the EQUATOR Network to identify TCM reporting guidelines. A preprepared Excel database was used to extract information on the basic characteristics, development process, and dissemination information. The development process quality of TCM reporting guidelines was assessed by evaluating their compliance with the Guidance for Developers of Health Research Reporting Guidelines (GDHRRG). The extent of dissemination of these guidelines was analyzed by examining the number of citations received.
RESULTS: A total of 26 reporting guidelines for TCM were obtained from 20 academic journals, with 61.5% of them published in English journals. Among the guidelines, 14 (53.8%) were registered in the EQUATOR Network. On average, the compliance rate of GDHRRG guidelines was reported to be 63.3% ranging from 22.2% to 94.4%. Three steps showed poor compliance, namely guideline endorsement (23.1%), translated guidelines (19.2%), and developing a publication strategy (19.2%). Furthermore, the compliance rate of GDHRRG guidelines published in English journals was higher than that in Chinese journals. In terms of the dissemination, 15.4% of the guidelines had been cited over 100 times, while 73.1% had been cited less than 50 times.
CONCLUSIONS: The development of TCM reporting guidelines still has limitations in terms of regarding scientific rigor and follow-up dissemination. Therefore, it is important to ensure adherence to the scientific process in the development of TCM reporting guidelines and to strengthen their promotion, dissemination, and implementation.

BACKGROUND: Continual evidence surveillance is an integral feature of living guidelines. The Australian Stroke Guidelines include recommendations on 100 clinical topics and have been \'living\' since 2018.
OBJECTIVE: To describe the approach for establishing and evaluating an evidence surveillance system for the living Australian Stroke Guidelines.
METHODS: We developed a pragmatic surveillance system based on an analysis of the searches for the 2017 Stroke Guidelines and evaluated its reliability by assessing the potential impact on guideline recommendations. Search retrieval and screening workload are monitored monthly, together with the frequency of changes to the guideline recommendations.
RESULTS: Evidence surveillance was guided by practical considerations of efficiency and sustainability. A single PubMed search covering all guideline topics, limited to systematic reviews and randomised trials, is run monthly. The search retrieves about 400 records a month of which a sixth are triaged to the guideline panels for further consideration. Evaluations with Epistemonikos and the Cochrane Stroke Trials Register demonstrated the robustness of adopting this more restrictive approach. Collaborating with the guideline team in designing, implementing and evaluating the surveillance is essential for optimising the approach.
CONCLUSIONS: Monthly evidence surveillance for a large living guideline is feasible and sustainable when applying a pragmatic approach.

Healthcare providers often encounter clinical trial results in the form of visual data displays. Although there is a robust literature on patient responses to data displays in medical settings, less is known about how providers comprehend and apply this information. Our study provides a scoping review of the literature on providers\' reactions to and perceptions of data displays.
We searched article databases (PubMed, PsycINFO, Web of Science, Cumulative Index to Nursing and Allied Health Literature, the Cochrane Library) supplemented by handsearching. Eligible articles were published in English from 1990 to 2020.
We identified 15 articles meeting our criteria. Studies with physicians were more prevalent (13/15) than those with other healthcare providers (6/15). Commonly assessed outcomes included objective (10/15) and subjective comprehension (4/15), preference for certain data display formats (6/15), and hypothetical decision-making around prescribing (4/15). In studies that assessed comprehension of clinical trial concepts, scores were average or below what would be considered mastery of the information. Data display formats that were preferred did not always correlate with better comprehension of information; lesser preferred formats (e.g. icon array) often resulted in better comprehension.
Our findings suggest that healthcare providers may not accurately interpret complex types of data displays, and it is unknown if such limitations affect actual decision-making. Interventions are needed to enhance comprehension of complex data displays within the context of prescription drug professional promotion.

BACKGROUND: The emerging field of epidemiological criminology studies the intersection between public health and justice systems. To increase the value of and reduce waste in research activities in this area, it is important to perform transparent research priority setting considering the needs of research beneficiaries and end users along with a systematic assessment of the existing research activities to address gaps and harness opportunities.
OBJECTIVE: In this study, we aimed to examine published research outputs in epidemiological criminology to assess gaps between published outputs and current research priorities identified by prison stakeholders.
METHODS: A rule-based method was applied to 23,904 PubMed epidemiological criminology abstracts to extract the study determinants and outcomes (ie, \"themes\"). These were mapped against the research priorities identified by Australian prison stakeholders to assess the differences from research outputs. The income level of the affiliation country of the first authors was also identified to compare the ranking of research priorities in countries categorized by income levels.
RESULTS: On an evaluation set of 100 abstracts, the identification of themes returned an F1-score of 90%, indicating reliable performance. More than 53.3% (11,927/22,361) of the articles had at least 1 extracted theme; the most common was substance use (1533/11,814, 12.97%), followed by HIV (1493/11,814, 12.64%). The infectious disease category (2949/11,814, 24.96%) was the most common research priority category, followed by mental health (2840/11,814, 24.04%) and alcohol and other drug use (2433/11,814, 20.59%). A comparison between the extracted themes and the stakeholder priorities showed an alignment for mental health, infectious diseases, and alcohol and other drug use. Although behavior- and juvenile-related themes were common, they did not feature as prison priorities. Most studies were conducted in high-income countries (10,083/11,814, 85.35%), while countries with the lowest income status focused half of their research on infectious diseases (47/91, 52%).
CONCLUSIONS: The identification of research themes from PubMed epidemiological criminology research abstracts is possible through the application of a rule-based text mining method. The frequency of the investigated themes may reflect historical developments concerning disease prevalence, treatment advances, and the social understanding of illness and incarcerated populations. The differences between income status groups are likely to be explained by local health priorities and immediate health risks. Notable gaps between stakeholder research priorities and research outputs concerned themes that were more focused on social factors and systems and may reflect publication bias or self-publication selection, highlighting the need for further research on prison health services and the social determinants of health. Different jurisdictions, countries, and regions should undertake similar systematic and transparent research priority-setting processes.

With the advancement of radiotherapy equipment, stereotactic radiotherapy (SRT) has been increasingly used. Among the many radiotherapy devices, Halcyon shows promising applications. This article reviews the dosimetric performance such as plan quality, plan complexity, and gamma passing rates of SRT plans with Halcyon to determine the effectiveness and safety of Halcyon SRT plans. This article retrieved the last 5 years of PubMed studies on the effectiveness and safety of the Halcyon SRT plans. Two authors independently reviewed the titles and abstracts to decide whether to include the studies. A search was conducted to identify publications relevant to evaluating the dosimetric performance of SRT plans on Halcyon using the key strings Halcyon, stereotactic radiosurgery, SRT, stereotactic body radiotherapy, and stereotactic ablative radiotherapy. A total of 18 eligible publications were retrieved. Compared to SRT plans on the TrueBeam, the Halcyon has advantages in terms of plan quality, plan complexity, and gamma passing rates. The high treatment speed of SRT plans on the Halcyon is impressive, while the results of its plan evaluation are also encouraging. As a result, Halcyon offers a new option for busy radiotherapy units while significantly improving patient comfort in treatment. For more accurate results, additional relevant publications will need to be followed up in subsequent studies.

This study examines the dissemination of trial results by data source (ie, ClinicalTrials.gov and PubMed) and funder type (ie, industry and nonindustry).

Sharing the methods and results of clinical trials with full transparency is an ethical obligation for those involved in clinical research. In this regard, ClinicalTrials.gov requires reporting of results to the registry within 1 year of completion of the trial. However, a poor result reporting rate has been pointed out, with approximately half the trial results not been reported. It has been suggested that one of the reasons behind this could be the influence of sponsors who conduct the clinical trials. In the course of our previous trend analysis on regenerative medicine for stroke (STR) using ClinicalTrials.gov and the International Clinical Trials Registry Platform (ICTRP) portal site as data sources, we suspected whether the results of gene and/or cell therapy trials are poorly reported. For this reason, a multivariate analysis using data from ClinicalTrials.gov was performed to identify the factors suppressing the result reporting rate, expanding our study to four different kinds of neurological diseases and regenerative medicine as a treatment modality when small-molecule compounds and biologics were set up as controls, in addition to the sponsor type factor. As a result, we found gene and/or cell therapy (therapeutic modality) in addition to STR (disease area), trials completed in 2005-2007, and clinical phases II and IV as independent factors that suppressed the rate of reporting results to ClinicalTrials.gov. On the other hand, big pharmaceutical companies were identified as a factor that increased the reporting result rate to ClinicalTrials.gov. When we applied result reporting publications through PubMed as an index, our study data revealed that the following factors were not identified as the cause for a decrease in the reporting result rate: STR (as disease area), trials completed between 2005 and 2007, and gene/cell therapy (as treatment modality). In this context, our findings indicate that gene/cell therapy has led to the suppression of the result reporting rate to ClinicalTrials.gov. This confirmed our initial suspicion of the low result reporting rate of gene/cell therapy trials. We believe that further studies are required to elucidate the factors affecting the result reporting rate from the perspective of disease area and treatment modality. Impact Statement Several studies have addressed the poor result reporting rate of clinical trials, which still remains an issue. Regenerative medicine holds great promise for the future and the process of its practical application is expected to be challenging. Although having a limited disease area and small sample size, to the best of our knowledge, this is the first study to point out insufficient result reporting of clinical trials of regenerative medicine from the perspective of treatment modality. This report highlights an issue for discussing the path toward its translation through an overview of various factors in comparison with conventional treatment modalities.

Drug-induced suicide has been debated as a crucial issue in both clinical and public health research. Published research articles contain valuable data on the drugs associated with suicidal adverse events. An automated process that extracts such information and rapidly detects drugs related to suicide risk is essential but has not been well established. Moreover, few data sets are available for training and validating classification models on drug-induced suicide.
This study aimed to build a corpus of drug-suicide relations containing annotated entities for drugs, suicidal adverse events, and their relations. To confirm the effectiveness of the drug-suicide relation corpus, we evaluated the performance of a relation classification model using the corpus in conjunction with various embeddings.
We collected the abstracts and titles of research articles associated with drugs and suicide from PubMed and manually annotated them along with their relations at the sentence level (adverse drug events, treatment, suicide means, or miscellaneous). To reduce the manual annotation effort, we preliminarily selected sentences with a pretrained zero-shot classifier or sentences containing only drug and suicide keywords. We trained a relation classification model using various Bidirectional Encoder Representations from Transformer embeddings with the proposed corpus. We then compared the performances of the model with different Bidirectional Encoder Representations from Transformer-based embeddings and selected the most suitable embedding for our corpus.
Our corpus comprised 11,894 sentences extracted from the titles and abstracts of the PubMed research articles. Each sentence was annotated with drug and suicide entities and the relationship between these 2 entities (adverse drug events, treatment, means, and miscellaneous). All of the tested relation classification models that were fine-tuned on the corpus accurately detected sentences of suicidal adverse events regardless of their pretrained type and data set properties.
To our knowledge, this is the first and most extensive corpus of drug-suicide relations.

Translational Bioinformatics (TBI) is defined as the union of translational medicine and bioinformatics. It emerges as a major advance in science and technology by covering everything, from the most basic database discoveries, to the development of algorithms for molecular and cellular analysis, as well as their clinical applications. This technology makes it possible to access the knowledge of scientific evidence and apply it to clinical practice. This manuscript aims to highlight the role of TBI in the study of complex diseases, as well as its application to the understanding and treatment of cancer. An integrative literature review was carried out, obtaining articles through several websites, among them: PUBMED, Science Direct, NCBI-PMC, Scientific Electronic Library Online (SciELO), and Google Academic, published in English, Spanish, and Portuguese, indexed in the referred databases and answering the following guiding question: \"How does TBI provide a scientific understanding of complex diseases?\" An additional effort is aimed at the dissemination, inclusion, and perpetuation of TBI knowledge from the academic environment to society, helping the study, understanding, and elucidating of complex disease mechanics and their treatment.