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. 2025 May 12:27:e69696.
doi: 10.2196/69696.

Stigma Attitudes Toward HIV/AIDS From 2011 Through 2023 in Japan: Retrospective Study in Japan

Yi Piao  1 , Nao Taguchi  1 , Keisuke Harada  1 , Kunihiro Hirahara  1 , Yosuke Takaku  2 , John Austin  3 , KuanYeh Lee  1 , Yui Shiozawa  4 , Yunfei Cheng  4 , Yoji Inoue  5
Affiliations

Stigma Attitudes Toward HIV/AIDS From 2011 Through 2023 in Japan: Retrospective Study in Japan

Yi Piao et al. J Med Internet Res. .

Abstract

Background: Stigma associated with HIV/AIDS continues to be a major barrier to prevention, management, and care. HIV stigma can negatively influence health behaviors. Surveys of the general public in Japan also demonstrated substantial gaps in knowledge of HIV/AIDS. Tweets from the social networking service X (formerly known as Twitter) have been studied to identify stigmas in other disorders but have not yet been used to study HIV stigma in Japan.

Objective: The aim of the study is to examine the variations in stigma related to HIV over an extended period using tweets from X and to investigate the stigma toward people with HIV associated with various demographic segments.

Methods: Japanese tweets from X related to HIV/AIDS were retrospectively collected; the phase 1 feasibility study collected tweets from 2011, 2014, and 2017, and the phase 2 analysis included tweets from each third year from 2011 through 2023. Individual tweets were labeled with the messages they conveyed (stigma and corresponding antistigma types included labels, marks, responsibility, peril, insults, and fear; tweets without stigma or antistigma messages were considered general education or neutral) along with demographic characteristics and locations; phase 1 results were used to develop a machine learning model to apply in phase 2. The labeled data from phase 2 were used to answer research questions concerning yearly changes in HIV stigma and proportions of stigma across population segments.

Results: A total of 2,016,826 tweets related to HIV/AIDS were identified over the study period; 1,648,556 (81.7%) were from individual accounts, with the remainder from organizational accounts. In total, 574,687 (28.5%) tweets indicated stigma attitudes, while 1,119,852 (55.5%), 207,320 (10.3%), and 114,967 (5.7%) showed neutral, antistigma, or general education attitudes, respectively. Tweets including peril, fear, or insult comprised 502,134 (87.4%) of tweets with stigma. The greatest numbers of tweets were made by people in their 20s, whereas people in their 20s and 60s had the greatest proportions of tweets with stigma (n=9650, 35.3% and n=558, 34.5%, respectively). Peril and fear made up 5819 (60.3%) of stigma tweets from people in their 20s. The proportion of tweets with stigma (n=59,719, 20.5% in 2017) increased notably during the COVID-19 pandemic (n=217,512, 31.4% in 2020, and a similar n=175,647, 33.9% in 2023). Tweets from health care practitioners had 1.68 times the odds of having antistigma messages versus those from others.

Conclusions: This study contributes to the understanding of HIV stigma in Japan and shows the usefulness of social media for studying stigma. The extent and type of HIV stigma changed from before to after the COVID-19 pandemic. These results can be used to develop future activities and educational programs to combat HIV-related stigma.

Keywords: HIV; Twitter; X; machine learning; social media; stigma.

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Conflict of interest statement

Conflicts of Interest: YP, NT, K Harada, K Hirahara, and KL are employees of Gilead Sciences KK and shareholders of Gilead Sciences, Inc. JA is an employee of Gilead Sciences, Inc. YS and YC are employees of Deloitte Tohmatsu Consulting LLC. YI and YT report no conflicts of interest.

Figures

Figure 1
Figure 1
Quantification of tweets identified in the analysis of stigma from 2011 through 2023 in Japan.
Figure 2
Figure 2
Receiver operating characteristic curves showing the evaluation of (top panel) stigma model and (bottom panel) antistigma model used in the analysis of tweets from 2011 through 2023 in Japan. The performance of the machine learning models was found to have an AUC of 0.72 for the stigma model and 0.77 for the antistigma model, indicating moderate performance. AUC: area under the curve.
Figure 3
Figure 3
Message classification trends for analysis of tweets from 2011 through 2023 in Japan: (top panel) number and percentage of tweets with stigma, neutral, general education, or antistigma labels; (middle panel) number and percentage of tweets with different types of stigma; and (bottom panel) number and percentage of tweets with type of antistigma label. Toward the end of 2023, the proportion of tweets with stigma substantially exceeded the pre–COVID-19 pandemic level.
Figure 4
Figure 4
Characteristics associated with stigma messages in analysis of tweets from 2011 through 2023 in Japan: (top center) overall, (top of left column) label, (middle of left column) mark, (bottom of left column) responsibility, (top of right column) peril, (middle of right column) fear, and (bottom of right column) insult. HCP: health care practitioner; OR: odds ratio.
Figure 5
Figure 5
Characteristics associated with (top) general education and (bottom) antistigma in the analysis of tweets from 2011 through 2023 in Japan. HCP: health care practitioner; OR: odds ratio.
See this image and copyright information in PMC

References

    1. Tsuda H, Koga M, Nojima M, Senkoji T, Kubota M, Kikuchi T, Adachi E, Ikeuchi K, Tsutsumi T, Koibuchi T, Yotsuyanagi H. Changes in survival and causes of death among people living with HIV: three decades of surveys from Tokyo, one of the Asian metropolitan cities. J Infect Chemother. 2021;27(7):949–956. doi: 10.1016/j.jiac.2021.02.003. https://linkinghub.elsevier.com/retrieve/pii/S1341-321X(21)00034-9 S1341-321X(21)00034-9 - DOI - PubMed
    1. Broyles LN, Luo R, Boeras D, Vojnov L. The risk of sexual transmission of HIV in individuals with low-level HIV viraemia: a systematic review. Lancet. 2023;402(10400):464–471. doi: 10.1016/s0140-6736(23)00877-2. - DOI - PMC - PubMed
    1. Public opinion survey on HIV infection and AIDS. Government Public Relations Office Cabinet Office Government of Japan. 2018. [2025-04-12]. https://survey.gov-online.go.jp/hutai/h29/h29-hivg.pdf .
    1. Kanamori R, Umemura F, Uemura K, Miyagami T, Valenti S, Fukui N, Yuda M, Saita M, Mori H, Naito T. Web-based search volume for HIV tests and HIV-testing preferences during the COVID-19 pandemic in Japan: infodemiology study. JMIR Form Res. 2024;8:e52306. doi: 10.2196/52306. https://formative.jmir.org/2024//e52306/ v8i1e52306 - DOI - PMC - PubMed
    1. Golub SA, Gamarel KE. The impact of anticipated HIV stigma on delays in HIV testing behaviors: findings from a community-based sample of men who have sex with men and transgender women in New York City. AIDS Patient Care STDS. 2013;27(11):621–627. doi: 10.1089/apc.2013.0245. https://europepmc.org/abstract/MED/24138486 - DOI - PMC - PubMed

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