Original Paper
Abstract
Background: Men who have sex with men (MSM) are increasingly using the internet to meet casual sexual partners. Those who do are at higher risk of sexually transmitted diseases. However, little is known about the rates and associations of frequent HIV testing and self-testing among such MSM.
Objective: We aimed to examine HIV serostatus communication and perceptions regarding the HIV infection risk of internet-based partners, along with their associations with frequent HIV testing and self-testing.
Methods: A cross-sectional study was conducted between May 2018 and April 2019 in Zhejiang Province, China. The study participants were assigned male at birth, were aged 18 years or older, had had casual sex with another male found through the internet in the last 6 months, and were HIV-negative. Information was obtained on HIV-testing behavior, along with demographic characteristics, HIV-related knowledge, internet-based behaviors, sexual behaviors with male partners, HIV serostatus communication, and perceptions regarding the HIV infection risk of internet-based partners. Uni- and multivariate logistic regression models were used to measure the associations of HIV testing and self-testing.
Results: The study recruited 281 individuals who had sought casual sexual partners through the internet during the previous 6 months. Of the participants, 61.9% (174/281) reported frequent HIV testing (twice or more frequently) and 50.9% (119/234; 47 with missing values) reported frequent HIV self-testing. MSM who always or usually communicated about the HIV serostatus of internet-based partners in the previous 6 months had 3.12 (95% CI 1.76-5.52) and 2.45 (95% CI 1.42-4.22) times higher odds of being frequently tested or self-tested for HIV, respectively, compared with those who communicated about this issue minimally or not at all.
Conclusions: There remains a need to improve the frequency of HIV testing and self-testing among internet-based MSM. HIV serostatus communication should be improved within the context of social networking applications to promote frequent HIV testing among internet-based MSM, especially for those who communicated about this issue minimally or not at all.
doi:10.2196/57244
Keywords
Introduction
AIDS remains an urgent public health priority worldwide. According to the Joint United Nations Program on HIV/AIDS, there were an estimated 39 million people living with HIV in 2022 worldwide [
]. However, an estimated 40% of people living with HIV worldwide [ ], and 32% in China, are unaware of their HIV status [ ]. Such people may engage in higher sexual behaviors associated with (sexually transmitted infections [STI], HIV, etc) risk than those who are aware of their HIV serostatus [ ], and in fact account for 60%-80% of all new HIV transmissions [ ]. Although much effort has been expended on identifying HIV-infected cases through facility-based testing referring to the testing of voluntary counseling and testing (VCT) and provider-initiated testing and counseling provided in clinical settings, there are barriers to such testing, including inconvenient testing systems, fear of social stigmatization, and lack of privacy. For prompt treatment and prevention of onward infection, more HIV testing strategies need to be explored in addition to facility-based testing [ ].Men who have sex with men (MSM) are disproportionately affected by HIV, both in China and globally, and they are a difficult subgroup to reach through facility-based testing [
, ]. HIV self-testing refers to a process in which a person collects their specimen (oral fluid or blood) and then interprets the result of a simple and rapid HIV test when and where they want [ ]. In randomized controlled trials, self-testing appears to promote increased frequency of HIV testing, because of its acceptability and feasibility [ , ]. MSM increasingly use the internet to socialize and meet sexual partners. Our cohort study reported that the internet-based sexual behavior in the past 6 months increased during the 6-monthly follow-up from 2018 to 2020 (unpublished). However, studies have observed more high-risk behaviors among internet-based MSM compared with non–internet-based MSM, such as more sex partners and condomless anal intercourse [ , ]. Furthermore, some studies indicate that internet-based MSM are more likely to have STIs [ ], including HIV infections [ ]. Oppositely, a study showed men were less likely to have unprotected anal sex in partnerships that they initiated on the web compared with those that they initiated offline [ ]. Even so, frequent HIV testing is important.Factors associated with the likelihood of undergoing HIV testing include age [
, ], education [ ], HIV knowledge [ , ], living in an urban area [ ], adopting a gay sexual identity [ , ], and sexual experience [ - ]. Several factors influence HIV self-testing rates among MSM, including demographics [ , ], HIV knowledge [ ], long-term drug use [ ], having self-tested friends [ ], previous HIV testing [ , ], and certain sexual behaviors, such as high number of sex partners and sexual activity with male commercial sex workers [ , ]. Previous studies have examined HIV testing and self-testing among MSM from either the internet or venues. However, little is known about the frequency of HIV testing and self-testing among internet-based MSM. Targeting MSM who seek partners through the internet should help us to understand the characteristics of at-risk MSM who are potential candidates for internet-based interventions.This study explored the rates and associations of frequent HIV testing and self-testing among MSM who seek sexual partners on the internet in Zhejiang province, building upon previous research on internet-based behaviors, HIV serostatus communication, and perceptions of the HIV infection risk posed by internet-based partners. Zhejiang province is a prosperous economic region of in China, located on the southeastern coast. Based on annual sentinel surveillance, the HIV prevalence in Zhejiang during 2018-2020 was 5.62% [
]. It is one of the 3 provinces with the highest average number of daily on the web MSM, with 72,212 MSM among the estimated provincial total of 409,108 MSM by using big data from social networking [ ]. Therefore, it is essential to conduct a study focusing on internet-based MSM in Zhejiang province. We aim to provide a scientific basis for public health education interventions targeted at internet-based MSM.Methods
Study Participants and Data Collection
A cross-sectional study was conducted between May 2018 and April 2019 in Zhejiang Province, China. The survey used baseline data collected for a cohort study from 2018 to 2020, including a 6-monthly follow-up to monitor new infections among MSM. In total, 731 MSM were recruited at baseline, with the inclusion criteria of assigned male sex at birth; having had sex with another male; age of ≥16 years and being HIV negative. Participants aged 18 years or older, who had casual sex with partners found through the internet in the last 6 months were selected. Individuals who had sought casual sexual partners through the internet in the past 6 months were defined as internet-based MSM. The analysis included a total of 281 participants.
Participants were enrolled using convenience sampling from MSM venues and the internet by volunteers at nongovernmental organization or community-based organizations as well as VCT staff. Participants enrolled from MSM venues were recruited using published posters in VCT clinics and outreach services (eg, bathrooms, bars, and gardens). Participants enrolled from the internet were recruited through advertisements regarding the study in chat groups on Blued (Beijing Blue City Brothers Culture Media), WeChat (Shenzhen Tencent Computer Systems), and Tencent (Shenzhen Tencent Computer Systems). All participants completed an electronic questionnaire by scanning a 2D code.
Measurements
The questionnaire covered demographic characteristics, experience with HIV testing services, sexual behaviors with male partners, internet-based behaviors, HIV serostatus communication, perceptions of the HIV risk posed by internet-based partners and HIV-related knowledge. Casual sexual behavior was evaluated by asking “Did you have casual sex in the last 6 months with someone you met through the Internet?” Participants who replied “yes” were recruited, even if they had other types of partners. The main outcome measure (number of times one was HIV tested and self-tested) was assessed through the question “How many times have you undergone a HIV test and how many times have you performed an HIV self-test during your lifetime?” For the analysis, the data were transformed into a binary variable (“Tested once or less” or “Tested twice or more”).
Age was categorized as 18-24, 25-34, and ≥35 years. The residence was dichotomized (Zhejiang vs other provinces). Educational attainment was dichotomized (below university vs university and above). Annual income was self-reported and was classified as ≤30,000, 30,000-80,000 and >80,000 Chinese Yuan (approximately ≤US $429, US $429- $1143 and >US $1143).
HIV-related knowledge was assessed using 3 questions: “Are men who have sex with men the group most seriously affected by AIDS in China at present?”; “Does infection with other sexually transmitted diseases (STDs) increase the risk of HIV infection?” and “Does the use of drugs such as rush, methamphetamine, ecstasy, and k powder increase the risk of HIV infection?” Replies of “Yes” were defined as correct and “No” as incorrect. The answers of each respondent were categorized as mostly wrong (2 or more wrong or unknown answers), somewhat wrong (1 wrong or unknown answer) and correct. Sexual behaviors with male partners in the last 6 months were assessed based on the sexual role (only receptive vs ever insertive sex), sex with a regular partner (no vs yes), and sex with a venue-based casual partner (no vs yes).
Internet-based behaviors were evaluated in terms of the login frequency on MSM-specific social networking applications and the viewing of erotic videos. Participants were asked, “How frequently do you log in to MSM-specific social networking applications?” The possible response included: 3-7 times a week, 1-2 times a week, once a week, and less frequency. For analysis, the option “3-7 times a week” was defined as > 2 times a week, while the remaining responses were classified as ≤ 2 times a week. The participants were also asked, “How frequently do you view erotic videos?” with the same response options.
HIV serostatus communication was evaluated through the question, “In the past 6 months, did you ask your Internet-based partners about their HIV serostatus before sex?” The possible responses were “always or usually” and “little or none.”
The perceived HIV risk of internet-based partners was determined by asking “How do you perceive the HIV risk of Internet-based partners?” with the response options of “very high,” “high,” “average,” and “low.”
Statistical Analysis
Before data analysis, variables were inspected for missing values. The proportions of missing data ranged from 0% to 3.91% among independent variables. The proportions of missing data were 0% and 16.73% for outcome measures of “frequent HIV testing” and “frequent HIV self-testing.” The demographics of the participants undergoing HIV testing and self-testing are described as frequencies. Uni- and multivariate logistic regression were used to explore the associations of HIV testing and self-testing by complete case analysis. We calculated the crude and adjusted odds ratios (ORs) and their 95% CIs. All factors in the univariate analysis were included in a multivariable regression model, together with age, education, and residence. The final multivariate logistic model was conducted using forward elimination. In addition, we used multiple imputation (5 imputations) to conduct multivariable regression models to assess the sensitivity of results to missing data. We performed these analyses using SPSS software (version 18.0; IBM Corp). We used a mixed effects logistic regression model with a random effect for the respondents ID to assess the sensitivity. We processed the analysis using R software (version 4.4.1; R Foundation for Statistical Computing).
Ethical Considerations
This study was reviewed and approved by the ethics committee of Zhejiang Provincial Center for Diseases Control and Prevention (2018-033), and all methods were performed in accordance with the relevant guidelines and regulations. Informed consent was obtained electronically from all participants. The raw data did not contain any personal identifying information that can be linked to particular individuals and was anonymized before its use. Participants were given a gift (body shampoo or facial cleanser) worth 30 Chinese Yuan (approximately US $5).
Results
Demographics
In total, 281 internet-based MSM were enrolled, among whom 93.6% (262/280) reported having sought sexual partners through MSM-specific social networking applications. The demographic characteristics are summarized in
. Most (127/281, 45.2%) were aged 25~34 years, 63.0% (177/281) had a university or higher education and 59.8% (168/281) were native to Zhejiang Province. Nearly half (126/281, 44.8%) of the respondents had annual incomes between 30,000 and 80,000 RMB and most (67.3%, 189/281) reported their sexual orientation as gay.Among participants little or none communicating about the HIV serostatus of the internet-based partner before sex, 52.1% (73/140) of the participants were 25-34 years old which is higher than that among participants always or usually communicating about the HIV serostatus (Table S1 in
). In total, 22.2% (30/140) of the participants little or none communicating about the HIV serostatus of the internet-based partner before sex acquired the average or low perspective of HIV-infected risk toward internet-based partners, higher than that among participants always or usually communicating about the HIV serostatus.Variables | Values (N=281), n (%) | |
Age (years) | ||
18-24 | 94 (33.5) | |
25-34 | 127 (45.2) | |
≥ 35 | 60 (21.4) | |
Education | ||
Below university level | 104 (37) | |
Above university level | 177 (63) | |
Residence | ||
Zhejiang | 168 (59.8) | |
Other provinces | 113 (40.2) | |
Yearly income (RMB; 1 RMB=US $0.14) | ||
≤30,000 | 68 (24.2) | |
30,000-80,000 | 126 (44.8) | |
>80,000 | 87 (31) | |
Sexual orientation | ||
Gay | 189 (67.3) | |
Bisexual | 92 (32.7) | |
Frequent HIV testing | ||
No | 107 (38.1) | |
Yes | 174 (61.9) | |
Frequent HIV self-testing | ||
No | 115 (49.1) | |
Yes | 119 (50.9) | |
Missing | 47 (0.2) |
Rates of Frequent HIV Testing and Self-Testing Among Internet-Based MSM
Of the 281 participants, 174 (61.9%) reported frequent HIV testing. Of the 234 participants who reported the information of self-testing, 50.9% (n=119) underwent frequent HIV self-testing.
Factors Associated With Frequent HIV Testing
Overview
In the univariate analysis, communication about the HIV serostatus of the internet-based partner before sex and age were significantly associated with frequent HIV testing. Respondents who always or usually communicated about HIV serostatus were more likely to be tested frequently compared with those who little or none communicated (crude OR 2.55, 95% CI 1.54-4.21). The respective ORs of frequent HIV testing were 1.82 (95% CI 1.06-3.14) and 3.00 (95% CI 1.47-6.11) times higher in participants aged 25-34 years and ≥35 years compared with those aged 18-24 years. In the multivariate analysis, significant associations of communication about the HIV serostatus of an internet-based partner before sex (adjusted OR 3.12, 95% CI 1.76-5.52), an age of 25-34 years (adjusted OR 2.71, 95% CI 1.44-5.09), and an age of ≥ 35 years (adjusted OR 4.92, 95% CI 2.19-11.06), consistent condom use with internet-based partners (adjusted OR 1.88, 95% CI 1.04-3.39) remained significantly associated with frequent HIV testing (
). Multiple imputation for missing data and mixed effects logistic regression model generated similar results (Tables S2 and S3 in ).Variables | Total (N=281), n (%) | Frequent HIV testing (n=174), n (%) | Crude ORa (95% CI) | Adjusted ORa (95% CI) | |
Age (years) | |||||
18-24 | 94 (33.5) | 47 (27) | Reference | Reference | |
25-34 | 127 (45.2) | 82 (47.1) | 1.82 (1.06-3.14)c | 2.71 (1.44-5.09)c | |
≥ 35 | 60 (21.4) | 45 (25.9) | 3.00 (1.47-6.11)c | 4.92 (2.19-11.06)d | |
Education | |||||
< University | 104 (37) | 66 (37.9) | Reference | —b | |
≥ University | 177 (63) | 108 (62.1) | 0.90 (0.55-1.49) | —b | |
Residence | |||||
Zhejiang | 168 (59.8) | 100 (57.5) | Reference | —b | |
Other provinces | 113 (40.2) | 74 (42.5) | 1.29 (0.79-2.12) | —b | |
Knowledge of HIV | |||||
Mostly wrong or unknown | 38 (13.5) | 23 (13.2) | Reference | —b | |
Somewhat wrong or unknown | 61 (21.7) | 30 (17.2) | 1.29 (0.63-2.66) | —b | |
Correct | 182 (64.8) | 121 (69.5) | 0.63 (0.28-1.44) | —b | |
Sexual role | |||||
Receptive sex | 69 (24.6) | 39 (22.4) | Reference | —b | |
Insertive sex or both | 212 (75.4) | 135 (77.6) | 1.35 (0.78-2.34) | —b | |
Regular partner | |||||
No | 39 (13.9) | 21 (12.1) | Reference | —b | |
Yes | 242 (86.1) | 153 (87.9) | 1.47 (0.75-2.91) | —b | |
Venue-based casual partners | |||||
No | 214 (77.8) | 133 (78.2) | Reference | —b | |
Yes | 61 (22.2) | 37 (21.8) | 0.94 (0.52-1.68) | —b | |
Missing data | —b | —b | —b | —b | |
Frequency of dates with internet-based partners per week | |||||
≤ 2 times | 97 (34.5) | 58 (33.3) | Reference | —b | |
> 2 times | 184 (65.5) | 116 (66.7) | 1.15 (0.69-1.90) | —b | |
Frequency of viewing erotic videos per week | |||||
≤ 2 times | 217 (77.2) | 132 (75.9) | Reference | —b | |
> 2 times | 64 (22.8) | 42 (24.1) | 1.23 (0.69-2.20) | —b | |
Communication about the HIV serostatus of internet-based partner before sex | |||||
Little or none | 140 (51.1) | 71 (42.3) | Reference | Reference | |
Always or usually | 134 (48.9) | 97 (57.7) | 2.55 (1.54-4.21)d | 3.12 (1.76-5.52)d | |
Missing data | —b | —b | —b | —b | |
Perceived HIV-infection risk of internet-based partners | |||||
Average or low | 44 (16.3) | 24 (14.3) | Reference | —b | |
High | 137 (50.7) | 81 (48.2) | 2.02 (0.96-4.27)c | —b | |
Very high | 89 (33.0) | 63 (37.5) | 1.21 (0.61-2.39) | —b | |
Missing data | —b | —b | —b | —b | |
HIV education from social networking applications | |||||
No | 78 (27.8) | 55 (31.6) | Reference | —b | |
Yes | 203 (72.2) | 119 (68.4) | 0.59 (0.34-1.04)e | —b | |
Condom use with internet-based partners | |||||
Inconsistently | 84 (30.7) | 45 (26.5) | Reference | Reference | |
Consistently | 190 (69.3) | 125 (73.5) | 1.67 (0.99-2.81)e | 1.88 (1.04-3.39)c | |
Missing data | —b | —b | —b | —b |
aOR: odds ratio.
b—: not applicable.
cP<0.05.
dP<0.001.
eP<0.1.
Factors Associated With Frequent HIV Self-Testing
There was a significant relationship between communication about the HIV serostatus of internet-based partners before sex and frequent HIV self-testing in the uni- and multivariate analyses. The adjusted OR was 2.45 times (95% CI 1.42-4.22) higher for the participants who always or usually communicated than those who little or none did. None of the other variables were significant (
). Multiple imputation for missing data and mixed effects logistic regression model generated similar results (Tables S3 and S4 in ).Variables | Total (N=234), n (%) | Frequent HIV self-testing (n=119), n (%) | Crude ORa (95% CI) | Adjusted ORa (95% CI) | |||||
Age (years) | |||||||||
18-24 | 73 (31.2) | 38 (31.9) | Reference | —b | |||||
25-34 | 108 (46.2) | 58 (48.7) | 1.07 (0.59-1.94) | —b | |||||
≥35 | 53 (22.6) | 23 (19.3) | 0.71 (0.35-1.44) | —b | |||||
Education | |||||||||
<University | 95 (40.6) | 42 (35.3) | Reference | —b | |||||
≥University | 139 (59.4) | 77 (64.7) | 1.57 (0.93-2.66)c | —b | |||||
Registered residence | |||||||||
Zhejiang | 135 (57.7) | 67 (56.3) | Reference | —b | |||||
Other provinces | 99 (42.3) | 52 (43.7) | 1.12 (0.67-1.89) | —b | |||||
Knowledge of HIV | |||||||||
Mostly wrong or unknown | 32 (13.7) | 15 (12.6) | Reference | —b | |||||
Somewhat wrong or unknown | 51 (21.8) | 31 (26.1) | 1.06 (0.49-2.28) | —b | |||||
Correct | 151 (64.5) | 73 (61.3) | 1.76 (0.72-4.29) | —b | |||||
Sexual role | |||||||||
Receptive sex | 57 (24.4) | 25 (21.0) | Reference | —b | |||||
Insertive sex or both | 177 (75.6) | 94 (79.0) | 1.45 (0.80-2.64) | —b | |||||
Regular partner | |||||||||
No | 30 (12.8) | 18 (15.1) | Reference | —b | |||||
Yes | 204 (87.2) | 101 (84.9) | 0.65 (0.30-1.43) | —b | |||||
Venue-based casual partner | |||||||||
No | 179 (77.5) | 89 (75.4) | Reference | —b | |||||
Yes | 52 (22.5) | 29 (24.6) | 1.28 (0.69-2.37) | —b | |||||
Missing data | —b | —b | —b | —b | |||||
Frequency dating internet-based partners per week | |||||||||
≤2 times | 84 (35.9) | 47 (39.5) | Reference | —b | |||||
>2 times | 150 (64.1) | 72 (60.5) | 0.73 (0.43-1.24) | —b | |||||
Frequency viewing erotic videos per week | |||||||||
≤2 times | 180 (76.9) | 89 (74.8) | Reference | —b | |||||
>2 times | 54 (23.1) | 30 (25.2) | 1.28 (0.69-2.36) | —b | |||||
Communication about the HIV serostatus of internet-based partner before sex | |||||||||
Little or none | 108 (47) | 43 (37.1) | Reference | Reference | |||||
Always or usually | 122 (53) | 73 (62.9) | 2.25 (1.33-3.82)d | 2.45 (1.42–4.22)e | |||||
Missing data | —b | —b | —b | —b | |||||
Perceived HIV-infection risk of internet-based partners | |||||||||
Average or low | 34 (15) | 17 (14.7) | Reference | —b | |||||
High | 113 (49.8) | 55 (47.4) | 1.22 (0.55-2.73) | —b | |||||
Very high | 80 (35.2) | 44 (37.9) | 0.95 (0.44-2.04) | —b | |||||
Missing data | —b | —b | —b | —b | |||||
HIV education from social networking applications | |||||||||
No | 165 (70.5) | 87 (73.1) | Reference | —b | |||||
Yes | 69 (29.5) | 32 (26.9) | 1.29 (0.73-2.27) | —b | |||||
Condom use with internet-based partners | |||||||||
Inconsistently | 69 (30.1) | 28 (23.9) | Reference | —b | |||||
Consistently | 160 (69.9) | 89 (76.1) | 1.84 (1.04-3.26)d | —b | |||||
Missing data | —b | —b | —b | —b |
aOR: odds ratio.
b—: not applicable.
cP<.10.
dP<.05.
eP<.001.
Discussion
Principal Findings
We conducted a cross-sectional survey of internet-based MSM in Zhejiang Province to describe the rates and associations of frequent HIV testing and self-testing. Overall, 61.9% of internet-based MSM underwent frequent HIV testing and 50.9% performed frequent self-testing. Communication about HIV serostatus of the internet-based partner before sex was significantly associated with frequent HIV testing and self-testing among internet-based MSM. Our results add to the literature on the associations among internet-based behaviors, HIV serostatus communication, and perceived HIV infection risk of internet-based partners with the frequency of HIV testing and self-testing.
HIV testing and self-testing were not performed by approximately 40% and 50% respectively of the internet-based MSM. In a large STI clinic in the Netherlands, the proportion was 55.2% [
], while it was 57.8% among black MSM in the United States [ ], suggesting that there is room for improvement in testing frequency. The World Health Organization recommends HIV self-testing as an additional approach because of its convenience and confidentiality. The US Centers for Disease Control and Prevention recommends at least annual HIV tests for high-risk populations (eg, MSM), with some experts suggesting that more frequent (eg, every 3-6 months) testing benefits individuals at elevated HIV risk [ ]. Increasing the acceptability and feasibility of HIV self-testing for this population is considered highly desirable [ ]. However, HIV self-testing often lacks face-to-face pre- or posttest consulting, confirmatory testing, and subsequent referral to specialist care. Therefore, it is important to emphasize the benefits and limitations (eg, window period) of self-testing [ , ] when applying this approach.Of our participants, more than half reported communicating about HIV serostatus of an internet-based partner before sex. That behavior was associated with increased odds of frequent HIV testing and self-testing. Determining HIV serostatus allows individuals to make informed decisions about how to engage in sexual behaviors. However, studies have found that most disclosures occur between steady partners [
]; only a small proportion of men were informed of the HIV serostatus of their most recent casual male partner [ ]. Therefore, it is important for MSM to actively communicate their HIV serostatus with internet-based partners. However, merely knowing the HIV serostatus of sexual partners is insufficient to reduce the risk of HIV transmission; knowledge of one’s own HIV status is also important. Unfortunately, MSM who test for HIV infrequently might misperceive their positive HIV status as HIV-negative. Therefore, HIV serostatus communication and frequent testing are both urgent issues for MSM.An increasing number of MSM use the internet to find partners, especially MSM-specific social networking applications [
], making them an effective target for MSM interventions [ ]. Blued, the largest gay male–oriented social media platform and geosocial networking mobile app in China had approximately 27 million registered users and 12 million monthly users in China as of 2016 [ ]. Other MSM-specific social networking apps, such as Jack’d and Grindr, have also been downloaded by millions of people, offering new ways for MSM to engage in peer-to-peer communication [ ]. Many of the apps require information regarding HIV disclosure, basic demographics, and preferred sexual behaviors in the personal profile. Studies have shown that only 55% of the users report using the HIV disclosure option in the US [ ], and in India, few individuals disclose their HIV status on their profiles because of the stigma in the culture [ ]. Status disclosure is often easier through the internet than face-to-face. However, doubts persist regarding the authenticity of the results uploaded on apps by the users themselves. It is recommended that apps implement rules to ensure the security and the veracity of disclosures. Apps can also encourage users to regularly update the HIV test results (eg, every 3 months). In general, dating apps are valuable targets for intervention promoting HIV serostatus communication.Limitations
This study had several important limitations. First, because of its cross-sectional design, we cannot infer causality in the relationships of HIV serostatus communication with frequent HIV testing and self-testing. Second, participants were recruited through convenience sampling from MSM venues and the internet, and might not be representative of the entire MSM population. Third, information bias, especially recall bias, was possible due to the reliance on self-report methods. Finally, some important factors that could affect the testing behavior of the targeted population were not included in the questionnaire, such as social stigma, cultural diversity, and psychological factors. Future studies should address these limitations, and aim to replicate our findings in both similar populations and different sociocultural groups.
Conclusions
There is a need to improve the frequency of HIV testing and self-testing among internet-based MSM. Communication about the HIV serostatus of the internet-based partner before sex was significantly associated with frequent HIV testing and self-testing among internet-based MSM. HIV serostatus communication should be improved within the context of social networking apps to promote HIV frequent HIV testing among internet-based MSM.
Acknowledgments
The authors thank the staff of the local centers for disease control and prevention, and volunteers of the community-based organizations and nongovernmental organizations in Hangzhou, Ningbo, Wenzhou, and Shaoxing, who contributed to the field investigation. This work was supported by the National Science and Technology Major Project Foundation under the 13th Five-Year Plan of China (2017ZX10201101). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Data Availability
The datasets used and analyzed are available from the corresponding author (Xiaohong Pan, Email: xhpan@cdc.zj.cn) upon reasonable request.
Authors' Contributions
WC analyzed the data. LC and WC designed the questionnaire, ZN and WC conducted the study, WC contributed significantly toward manuscript writing. XP revised the paper. All authors have read and approved the final manuscript.
Conflicts of Interest
None declared.
Characteristics of participants by “Communication about the HIV serostatus of Internet-based partner before sex” and sensitivity analyses of multivariate regression.
DOCX File , 33 KBReferences
- Global AIDS update 2024: the urgency of now: AIDS at a crossroads. UNAIDS URL: https://www.unaids.org/en [accessed 2024-10-09]
- Prevention gap report. UNAIDS; 2016. URL: https://www.unaids.org/sites/default/files/media_asset/2016-prevention-gap-report_en.pdf [accessed 2024-10-09]
- Wu ZY. The progress and challenges of promoting HIV/AIDS 90-90-90 strategies in China. Chin J Dis Control Prev. 2016;20(12):1187-1189. [FREE Full text] [CrossRef]
- Marks G, Crepaz NF, Senterfitt JW, Janssen RS. Meta-analysis of high-risk sexual behavior in persons aware and unaware they are infected with HIV in the United States: implications for HIV prevention programs. J Acquir Immune Defic Syndr. 2005;39(4):446-453. [CrossRef] [Medline]
- Phillips AN, Cambiano V, Nakagawa F, Brown AE, Lampe F, Rodger A, et al. Increased HIV incidence in men who have sex with men despite high levels of ART-induced viral suppression: analysis of an extensively documented epidemic. PLoS One. 2013;8(2):e55312. [FREE Full text] [CrossRef] [Medline]
- Qin Q, Guo W, Tang W, Mahapatra T, Wang L, Zhang N, et al. Spatial analysis of the human immunodeficiency virus epidemic among men who have sex with men in china, 2006-2015. Clin Infect Dis. 2017;64(7):956-963. [FREE Full text] [CrossRef] [Medline]
- Beyrer C, Baral SD, Collins C, Richardson ET, Sullivan PS, Sanchez J, et al. The global response to HIV in men who have sex with men. Lancet. 2016;388(10040):198-206. [CrossRef] [Medline]
- Guidelines on HIV self-testing and partner notification: supplement to consolidated guidelines on HIV testing services. World Health Organization; 2016. URL: https://iris.who.int/bitstream/handle/10665/251655/9789241549868-eng.pdf?sequence=1 [accessed 2024-10-09]
- Jamil MS, Prestage G, Fairley CK, Grulich AE, Smith KS, Chen M, et al. Effect of availability of HIV self-testing on HIV testing frequency in gay and bisexual men at high risk of infection (FORTH): a waiting-list randomised controlled trial. Lancet HIV. 2017;4(6):e241-e250. [CrossRef] [Medline]
- Wray TB, Chan PA, Simpanen E, Operario D. A pilot, randomized controlled trial of HIV self-testing and real-time post-test counseling/referral on screening and preventative care among men who have sex with men. AIDS Patient Care STDS. 2018;32(9):360-367. [FREE Full text] [CrossRef] [Medline]
- Xu J, Yu H, Tang W, Leuba SI, Zhang J, Mao X, et al. The effect of using geosocial networking apps on the HIV incidence rate among men who have sex with men: eighteen-month prospective cohort study in shenyang, china. J Med Internet Res. 2018;20(12):e11303. [FREE Full text] [CrossRef] [Medline]
- Guo Z, Feng A, Zhou Y, Gao Y, Sun Y, Chen Y, et al. Geosocial networking mobile applications use and HIV and other sexually transmitted infections among men who have sex with men in Southern China: a cross-sectional study. Front Public Health. 2023;11:1063993. [FREE Full text] [CrossRef] [Medline]
- Wang HD, Zhang L, Zhou Y, Wang K, Zhang X, Wu J, et al. The use of geosocial networking smartphone applications and the risk of sexually transmitted infections among men who have sex with men: a systematic review and meta-analysis. BMC Public Health. 2018;18(1):1178. [FREE Full text] [CrossRef] [Medline]
- Knox J, Chen YN, He Q, Liu G, Jones J, Wang X, et al. Use of geosocial networking apps and HIV risk behavior among men who have sex with men: case-crossover study. JMIR Public Health Surveill. 2021;7(1):e17173. [FREE Full text] [CrossRef] [Medline]
- Nelson KM, Pantalone DW, Gamarel KE, Carey MP, Simoni JM. Correlates of never testing for HIV among sexually active internet-recruited gay, bisexual, and other men who have sex with men in the United States. AIDS Patient Care STDS. 2018;32(1):9-15. [FREE Full text] [CrossRef] [Medline]
- Mustanski B, Moskowitz DA, Moran KO, Rendina HJ, Newcomb ME, Macapagal K. Factors associated with HIV testing in teenage men who have sex with men. Pediatrics. 2020;145(3):e20192322. [FREE Full text] [CrossRef] [Medline]
- Dillon FR, Eklund A, Ebersole R, Ertl MM, Martin JL, Verile MG, et al. Heterosexual self-presentation and other individual- and community-based correlates of HIV testing among latino men who have sex with men. Psychol Men Masc. 2019;20(2):238-251. [FREE Full text] [CrossRef] [Medline]
- Ren XL, Wu ZY, Mi GD, McGoogan JM, Rou KM, Zhao Y, et al. HIV care-seeking behaviour after HIV self-testing among men who have sex with men in Beijing, China: a cross-sectional study. Infect Dis Poverty. 2017;6(1):112. [FREE Full text] [CrossRef] [Medline]
- Liu Y, Wu GH, Lu RR, Ou R, Hu L, Yin Y, et al. Facilitators and barriers associated with uptake of HIV self-testing among men Who have sex with men in Chongqing, China: a cross-Sectional survey. Int J Environ Res Public Health. 2020;17(5):1634. [FREE Full text] [CrossRef] [Medline]
- Yan HJ, Yang HT, Raymond HF, Li J, Shi L, Huan X, et al. Experiences and correlates of HIV self-testing among men who have sex with men in Jiangsu province, China. AIDS Behav. 2015;19(3):485-491. [FREE Full text] [CrossRef] [Medline]
- He J, Li J, Jiang S, Cheng W, Jiang J, Xu Y, et al. Application of machine learning algorithms in predicting HIV infection among men who have sex with men: Model development and validation. Front Public Health. 2022;10:967681. [FREE Full text] [CrossRef] [Medline]
- Hu M, Xu C, Wang J. Spatiotemporal analysis of men who have sex with men in Mainland China: social app capture-recapture method. JMIR Mhealth Uhealth. 2020;8(1):e14800. [FREE Full text] [CrossRef] [Medline]
- Vriend HJ, Stolte IG, Heijne JCM, Heijman T, De Vries HJC, Geskus RB, et al. Repeated STI and HIV testing among HIV-negative men who have sex with men attending a large STI clinic in Amsterdam: a longitudinal study. Sex Transm Infect. 2015;91(4):294-299. [CrossRef] [Medline]
- Liu Y, Silenzio VMB, Nash R, Luther P, Bauermeister J, Vermund SH, et al. Suboptimal recent and regular HIV testing among black men who have sex with men in the United states: implications from a meta-analysis. J Acquir Immune Defic Syndr. 2019;81(2):125-133. [FREE Full text] [CrossRef] [Medline]
- DiNenno EA, Prejean J, Irwin K, Delaney KP, Bowles K, Martin T, et al. Recommendations for HIV screening of gay, bisexual, and other men who have sex with men - United States, 2017. MMWR Morb Mortal Wkly Rep. 2017;66(31):830-832. [FREE Full text] [CrossRef] [Medline]
- Xiu X, Qin Y, Bao Y, Chen Y, Wu H, Huang X, et al. The practice and potential role of HIV Self-testing in China: systematic review and meta-analysis. JMIR Public Health Surveill. 2022;8(12):e41125. [FREE Full text] [CrossRef] [Medline]
- Wright AA, Katz IT. Home testing for HIV. N Engl J Med. 2006;354(5):437-440. [CrossRef] [Medline]
- Frith L. HIV self-testing: a time to revise current policy. Lancet. 2007;369(9557):243-245. [CrossRef] [Medline]
- Marcus U, Schink SB, Sherriff N, Jones A, Gios L, Folch C, et al. Sialon II Network. HIV serostatus knowledge and serostatus disclosure with the most recent anal intercourse partner in a european MSM sample recruited in 13 cities: results from the sialon-II study. BMC Infect Dis. 2017;17(1):730. [FREE Full text] [CrossRef] [Medline]
- Tang WM, Liu CC, Cao BL, Pan SW, Zhang Y, Ong J, et al. SESH Study Group. Receiving HIV serostatus disclosure from partners before sex: results from an online survey of Chinese men who have Sex with men. AIDS Behav. 2018;22(12):3826-3835. [FREE Full text] [CrossRef] [Medline]
- Macapagal K, Moskowitz DA, Li DH, Carrión A, Bettin E, Fisher CB, et al. Hookup app use, sexual behavior, and sexual health among adolescent men who have sex with men in the United States. J Adolesc Health. 2018;62(6):708-715. [FREE Full text] [CrossRef] [Medline]
- Wang LM, Podson D, Chen ZH, Lu H, Wang V, Shepard C, et al. Using social media to increase HIV testing among men who have sex with men - Beijing, China, 2013-2017. MMWR Morb Mortal Wkly Rep. 2019;68(21):478-482. [FREE Full text] [CrossRef] [Medline]
- Yang GL, Long J, Luo D, Xiao S, Kaminga AC. The characteristics and quality of mobile phone apps targeted at men who have sex with men in China: a window of opportunity for health information dissemination? JMIR Mhealth Uhealth. 2019;7(3):e12573. [FREE Full text] [CrossRef] [Medline]
- Medina MM, Crowley C, Montgomery MC, Tributino A, Almonte A, Sowemimo-Coker G, et al. Disclosure of HIV serostatus and pre-exposure prophylaxis use on internet hookup sites among men who have sex with men. AIDS Behav. 2019;23(7):1681-1688. [FREE Full text] [CrossRef] [Medline]
- Rhoton J, Wilkerson JM, Mengle S, Patankar P, Rosser BS, Ekstrand ML. Sexual preferences and presentation on geosocial networking apps by Indian men who have sex with men in maharashtra. JMIR Mhealth Uhealth. 2016;4(4):e120. [FREE Full text] [CrossRef] [Medline]
Abbreviations
MSM: men who have sex with men |
OR: odds ratio |
STD: sexually transmitted disease |
STI: sexually transmitted infection |
VCT: voluntary counseling and testing |
Edited by A Mavragani; submitted 08.02.24; peer-reviewed by Y Zhao, V Pravosud; comments to author 24.04.24; revised version received 29.06.24; accepted 16.09.24; published 14.11.24.
Copyright©Wanjun Chen, Lin Chen, Zhikan Ni, Lin He, Xiaohong Pan. Originally published in JMIR Formative Research (https://formative.jmir.org), 14.11.2024.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.