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1.
Issues Ment Health Nurs ; 42(5): 437-450, 2021 May.
Article in English | MEDLINE | ID: mdl-32926796

ABSTRACT

Promoting health-related campaigns on Twitter has increasingly become a world-wide choice to raise awareness and disseminate health information. Data retrieved from Twitter are now being used to explore how users express their views, attitudes and personal experiences of health-related issues. We focused on Twitter discourse reproduced during Mental Health Awareness Week 2017 by examining 1,200 tweets containing the keywords 'mental health', 'mental illness', 'mental disorders' and '#MHAW'. The analysis revealed 'awareness and advocacy', 'stigmatization', and 'personal experience of mental health/illness' as the central discourses within the sample. The article concludes with some recommendations for future research on digitally-mediated health communication.


Subject(s)
Mental Disorders , Social Media , Health Promotion , Humans , Mental Health , Stereotyping
2.
Int J Nurs Pract ; 26(6): e12851, 2020 Dec.
Article in English | MEDLINE | ID: mdl-32608034

ABSTRACT

BACKGROUND: International nursing research comparisons can give a new perspective on a nation's output by identifying strengths and weaknesses. AIM: This article compares strengths in nursing research between six mainly English-speaking nations (Australia, Canada, Ireland, New Zealand, United Kingdom and United States). METHODS: Journal authorship (percentage of first authorship by nationality) and article keywords were compared for Scopus-indexed journal articles 2008-2018. Three natural language processing strategies were assessed for identifying statistically significant international differences in the use of keywords or phrases. RESULTS: Journal author nationality was not a good indicator of international differences in research specialisms, but keyword and phrase differences were more promising especially if both are used. For this, the part of speech tagging and lemmatisation text processing strategies were helpful but not named entity recognition. The results highlight aspects of nursing research that were absent in some countries, such as papers about nursing administration and management. CONCLUSION: Researchers outside the United States should consider the importance of researching specific patient groups, diseases, treatments, skills, research methods and social perspectives for unresearched gaps with national relevance. From a methods perspective, keyword and phrase differences are useful to reveal international differences in nursing research topics.


Subject(s)
Bibliometrics , Nursing Research , Australia , Authorship , Canada , Humans , Ireland , Language , New Zealand , United Kingdom , United States
3.
PLoS One ; 15(2): e0229578, 2020.
Article in English | MEDLINE | ID: mdl-32084240

ABSTRACT

Primary data collected during a research study is often shared and may be reused for new studies. To assess the extent of data sharing in favourable circumstances and whether data sharing checks can be automated, this article investigates summary statistics from primary human genome-wide association studies (GWAS). This type of data is highly suitable for sharing because it is a standard research output, is straightforward to use in future studies (e.g., for secondary analysis), and may be already stored in a standard format for internal sharing within multi-site research projects. Manual checks of 1799 articles from 2010 and 2017 matching a simple PubMed query for molecular epidemiology GWAS were used to identify 314 primary human GWAS papers. Of these, only 13% reported the location of a complete set of GWAS summary data, increasing from 3% in 2010 to 23% in 2017. Whilst information about whether data was shared was typically located clearly within a data availability statement, the exact nature of the shared data was usually unspecified. Thus, data sharing is the exception even in suitable research fields with relatively strong data sharing norms. Moreover, the lack of clear data descriptions within data sharing statements greatly complicates the task of automatically characterising shared data sets.


Subject(s)
Biometry/methods , Genome-Wide Association Study/trends , Information Dissemination/methods , Databases, Genetic/statistics & numerical data , Databases, Genetic/trends , Humans , Research Report
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