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. 2019 May 19;16(10):1772.
doi: 10.3390/ijerph16101772.

Depression among Patients with HIV/AIDS: Research Development and Effective Interventions (GAPRESEARCH)

Bach Xuan Tran  1   2 , Roger C M Ho  3   4 , Cyrus S H Ho  5 , Carl A Latkin  6 , Hai Thanh Phan  7 , Giang Hai Ha  8 , Giang Thu Vu  9 , Jiangbo Ying  10 , Melvyn W B Zhang  11
Affiliations

Depression among Patients with HIV/AIDS: Research Development and Effective Interventions (GAPRESEARCH)

Bach Xuan Tran et al. Int J Environ Res Public Health. .

Abstract

Depression in people living with HIV (PLWH) has become an urgent issue and has attracted the attention of both physicians and epidemiologists. Currently, 39% of HIV patients are reported to suffer from depression. This population is more likely to experience worsening disease states and, thus, poorer health outcomes. In this study, we analyzed research growth and current understandings of depression among HIV-infected individuals. The number of papers and their impacts have been considerably grown in recent years, and a total of 4872 publications published from 1990-2017 were retrieved from the Web of Science database. Research landscapes related to this research field include risk behaviors and attributable causes of depression in HIV population, effects of depression on health outcomes of PLWH, and interventions and health services for these particular subjects. We identified a lack of empirical studies in countries where PLWH face a high risk of depression, and a modest level of interest in biomedical research. By demonstrating these research patterns, highlighting the research gaps and putting forward implications, this study provides a basis for future studies and interventions in addressing the critical issue of HIV epidemics.

Keywords: AIDS; HIV; bibliometric; depression; scientometrics.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure A1
Figure A1
Co-occurrence of most frequent topics emerging from exploratory factor analysis of abstracts’ contents.
Figure 1
Figure 1
Selection of papers.
Figure 2
Figure 2
The global network among 68 countries having co-authorships of selected papers. The size of nodes shows the proportional contribution to the number of papers and the thickness of lines indicates the percentage of the number of collaborations.
Figure 3
Figure 3
Co-occurrence of most frequent author’s keywords. Note: the colors of the nodes refer to principle components of data structure; the nodes size was scaled to the keywords’ occurrences; and the thickness of the lines was drawn based on the strength of the association between two keywords.
Figure 4
Figure 4
Proximity plots of the terms (a) “Intervention(s)” and (b) “Trial(s)” with the top 50 most frequent concurrence terms in all abstracts. The x-axis refers to the Jaccard coefficient that measures the similarity between finite sample sets and is defined as the size of the intersection divided by the size of the union of the sample sets.
Figure 4
Figure 4
Proximity plots of the terms (a) “Intervention(s)” and (b) “Trial(s)” with the top 50 most frequent concurrence terms in all abstracts. The x-axis refers to the Jaccard coefficient that measures the similarity between finite sample sets and is defined as the size of the intersection divided by the size of the union of the sample sets.
See this image and copyright information in PMC

References

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