To better understand and interpret the trends in cutaneous research, we carried out a network analysis of all the titles of the submitted abstracts of the annual meetings of the European Society of Dermatological Research (ESDR), including the International Investigative Dermatology (IID) meetings between 2010 and 2019. Network analysis is a data science tool to process, analyze, and visualize big sets of data. As expected, psoriasis was the frontrunner in each of the annual meetings, followed by dermatitis and melanoma. Interestingly, alopecia, acne, squamous cell carcinoma, pruritus, basal cell carcinoma, and hidradenitis suppurativa were among the next most frequently named diseases and/or terms. We also looked at diversity to assess how broad the interest of the submitting community is and to identify whether "blockbusters" such as psoriasis and atopic dermatitis expand in expense of other interests. In contrast to our expectations, the diversity of submissions to the ESDR annual meetings remained high over the 10 years of our observation period. Interestingly, the diversity increased in the years of the IID, indicating an outreach to other research areas worldwide compared with the ESDR meetings. This is true for both 2013 in Edinburgh, UK, and 2018 in Orlando, USA. During these meetings, this rise in diversity was associated with a relative decrease of the three most often named diseases. Network analysis thus may be a useful tool for research societies like the ESDR to identify trends and allocate resources such as reviewers and sessions accordingly. In addition, it can serve as quality control monitoring whether the ESDR continues to offer a platform for all researchers in cutaneous biology or implements or focuses on emerging fields.
Objectives: We compared the magnitude and direction of associations between forgiveness and pain, mental and physical health, quality of life, and anger in a sample of fibromyalgia (FMS) patients and healthy controls. In addition, we compared FMS and controls on mean levels of these variables. Discussion: Forgiveness of self and others is beneficially associated with pain, health, quality of life, and anger in FMS patients at levels that are of similar size and direction as in healthy controls. However, FMS patients manifest lower levels of forgiveness of self and others. Therapeutic promotion of forgiveness as a psychosocial coping strategy may help patients with FMS to better manage psychological and physical symptoms, thereby enhancing well-being. Methods
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BACKGROUND Every two years, German-speaking dermatologic specialist groups gather in Berlin to share the latest developments at Germany´s largest dermatologic conference, the Annual Meeting of the Germany Society of Dermatology (DDG). Because this conference has a lasting effect on dermatologic practice and research, understanding what is moving the specialist groups means understanding what is driving dermatology in Germany. OBJECTIVE The objective of the article is to introduce the medical scientific community to a data visualization method, which will help understand more sophisticated data analysis and processing approaches in the future. METHODS We used word network analysis to compile and visualize the information embedded in the contribution titles to the DDG Annual Meeting in 2019. We extracted words, contributing cities and inter-connections. The data was standardized, visualized using network graphs and analyzed using common network analysis parameters. RESULTS A total of 5509 words were extracted from 1150 contribution titles. The most frequently used words were “therapy”, “patients”, and “psoriasis”. The highest number of contributions came from Hamburg, Berlin and Munich. High diversity in research topics was found, as well as a well-connected research network. CONCLUSIONS Focus of the well-connected German-speaking dermatology community meeting 2019 was patient and therapy centered and lies especially on the diseases psoriasis and melanoma. Network graph analysis can provide helpful insights and help planning future congresses. It can facilitate the choice which contributors to include as imbalances become apparent. Moreover, it can help distributing the topics more evenly across the whole dermatologic spectrum.
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A network analysis of the EADV 2019 conference Editor In 2019, the annual congress of the European Academy of Dermatology and Venereology (EADV) was held in Madrid, Spain, with around 13 000 visitors from over 100 countries, providing a jaw-dropping number of 1280 lectures and 1941 posters. 1 Because of the sheer volume, it is hard to grasp which topics were especially focused on and which, conversely, were rather underrepresented. An upcoming computational method to process, analyse and visualize big data of any size to make it accessible for interpretation is network analysis, which is widely used in social and political sciences 2,3 but rarely in the medical field. 4,5 To gain an in-depth insight into the EADV 2019, its collaborators and themes, we performed a network analysis based on the titles of all lectures and posters. Data were extracted from the official program pdf file using tabula v1.2.1 open-source software 6 and then preprocessed using custom-written python code. The extracted data were first split into titles, countries, cities and authors, cleaned from filling words like 'and' and standardized, e.g. 'Acne inversa' and 'Hidradenitis suppurativa'. Figure 1 Visualization of the geographical origins of the submissions in Google Maps. The areas are colour coded in shades of yellow and red, depending on the number of contributions. Red indicates an area with particular activity. An interactive map can be accessed by QR code.
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