Skills-Based Programs Used to Reduce Physician Burnout in Graduate Medical Education: A Systematic Review

ABSTRACT Background Physician burnout is pervasive within graduate medical education (GME), yet programs designed to reduce it have not been systematically evaluated. Effective approaches to burnout, aimed at addressing the impact of prolonged stress, may differ from those needed to improve wellness. Objective We systematically reviewed the literature of existing educational programs aimed to reduce burnout in GME. Methods Following the PRISMA guidelines, we identified peer-reviewed publications on GME burnout reduction programs through October 2019. Titles and abstracts were reviewed for relevance, and full-text studies were acquired for analysis. Article quality was assessed using the Medical Education Research Study Quality Instrument (MERSQI). Results A total of 3534 articles met the search criteria, and 24 studies were included in the final analysis. Article quality varied, with MERSQI assessment scores varying between 8.5 and 14. Evaluation was based on participant scores on burnout reduction scales. Eleven produced significant results pertaining to burnout, 10 of which yielded a decrease in burnout. Curricula to reduce burnout among GME trainees varies. Content taught most frequently included stress management (n = 8), burnout reduction (n = 7), resilience (n = 7), and general wellness (n = 7). The most frequent pedagogical methods were discussion groups (n = 14), didactic sessions (n = 13), and small groups (n = 11). Most programs occurred during residents' protected education time. Conclusions There is not a consistent pattern of successful or unsuccessful programs. Further randomized controlled trials within GME are necessary to draw conclusions on which components most effectively reduce burnout.

A practical guide to data analysis in general literature reviews

Academic theses at the bachelor’s and master’s levels in nursing, physiotherapy, occupational therapy, public health and related fields often take the form of general reviews of published research on a relevant clinical issue. While there are many guides to doing literature searches and evaluating article quality, there are to our knowledge no published detailed guides of how to do the actual data analysis in such general literature reviews, particularly that are applicable to students. This article seeks to describe a systematic method of data analysis appropriate for undergraduate research theses, where the data consists of the results from available published research. We present a step-by-step guide with authentic examples and practical tips.

ADDITIONAL INFORMATION IN BOXES AND PHOTOS IN INTERVIEW ARTICLES IN DA NANG NEWSPAPER

An interview article is considered a dialogue between a journalist and an interviewee about an event, a current issue or a figure of public interest. Interview articles consist of key information (topic, interviewee, questions, answers, title, and lead-in) and additional information (data boxes and photos). The additional information is used to support, illustrate, and highlight the key information. In many cases, the additional information has to be "eye-catching" and hold readers’ attention, urging them to explore the article. This paper is aimed to study the current status of using additional information, provided in boxes and photos, in interview articles in printed Da Nang Newspaper during 2017, 2018, and 2019, and then to make recommendations on the use of boxes and photos to improve article quality for readers’ increasing need of information.

Relating Wikipedia article quality to edit behavior and link structure

Currently, the relation between edit behavior, link structure, and article quality is not well-understood in our community, notwithstanding that this relationship may facilitate editing processes and content quality on Wikipedia. To shed light on this complex relation, we classify article edits and perform an in-depth analysis of editing sequences for 4941 articles. Additionally, we build a network of internal Wikipedia hyperlinks between articles. Using this data, we compute parsimonious metrics to quantify editing and linking behavior. Our analysis unveils that conflicted articles differ substantially from others in almost all metrics, while we also detect slight trends for high-quality articles. With our network analysis we find evidence indicating that controversial and edit war articles frequently span structural holes in the Wikipedia network. Finally, in a prediction experiment we demonstrate the usefulness of edit behavior patterns and network properties in predicting conflict and article quality. With our work, we assist online collaboration communities, especially Wikipedia, in long-term improvement of content quality by offering valuable insights about the interplay of article quality, controversies and edit wars, editing behavior, and network properties via sequence-based edit and network-based article metrics.