Interventions to Improve the Quality of Life of Patients with Chronic Obstructive Pulmonary Disease: A Global Mapping During 1990-2018.
Giap Van VuGiang Hai HaCuong Tat NguyenGiang Thu VuHai Quang PhamCarl A LatkinBach Xuan TranRoger Chun-Man HoCyrus S H HoPublished in: International journal of environmental research and public health (2020)
Chronic obstructive pulmonary disease (COPD) has been considered a significant health challenge globally in recent years, which affects different aspects of the quality-of-life (QoL). A review was conducted of research output, research topics, and landscape to have a global view of the papers mentioning the interventions to increase QoL of patients with COPD. A total of 3242 research items from Web of Science during the period 1990-2018 were downloaded and analyzed. Analyses based on the different levels of data and methods using using VOSviewer software tool (version 1.16.15, Centre for Science and Technology Studies (CWTS), Leiden University, Leiden, The Netherlands) and Latent Dirichlet allocation. By exploring the trends in research productivity and topics, an increase was found in the number of papers mentioning non-pharmacological interventions as well as mental health illness and QoL among patients with COPD. In conclusion, the research on the interventions to increase the QoL of patients with COPD has attracted scientists globally. It is suggested that more research should be conducted on the effectiveness of non-pharmacological therapies to increase QoL of patients with COPD that can be applied broadly in the community. The collaboration and support from developed countries to developing countries are needed to increase the QoL of people living with COPD.
Keyphrases
- chronic obstructive pulmonary disease
- lung function
- mental health
- physical activity
- public health
- healthcare
- randomized controlled trial
- systematic review
- cystic fibrosis
- air pollution
- climate change
- risk assessment
- mass spectrometry
- electronic health record
- machine learning
- data analysis
- health information
- deep learning