Abstract
With PrEP demonstration projects planned for MSM in India, we assessed: 1) associations between guideline-informed PrEP eligibility, HIV risk perception (Health Belief Model), and perceived PrEP benefits and costs (Rational Choice Theory), with willingness to use PrEP (WTUP); and 2) correlates of non-willingness to use PrEP among PrEP-eligible MSM. From December 2016 to March 2017, we conducted an interviewer-administered survey among MSM recruited from “cruising” sites in Mumbai and Chennai. PrEP eligibility criteria included condomless anal sex, sex work, >1 male partner (all past month), physician-diagnosed sexually transmitted infection (past-year), or alcohol use before last anal sex. Perceived benefits and costs of PrEP were assessed with Likert-type scales (Cronbach’s alphas >.85). Participants’ (n=197) mean age was 26.6 (SD 6.6); 34% completed college-degree education and 49% engaged in sex work. Three-fourths (77%) reported they would “definitely use” PrEP. Among the 93% who met ≥1 PrEP-eligibility criterion, 79% (n=145/183) reported WTUP. In logistic regression analyses, PrEP eligibility (aOR=5.31, 95% CI 1.11, 25.45), medium (aOR = 2.41, 95% CI 1.03, 5.63) or high (aOR =13.08, 95% CI 1.29, 132.27) perceived HIV risk, and greater perceived benefits (aOR=1.13, 95% CI 1.03, 1.24) were associated with higher odds of WTUP. Among PrEP-eligible MSM, non-willingness to use PrEP was associated with low HIV risk perception (aOR=2.77, 95% CI 1.15 to 6.69, p=.02) and lower perceived benefits (aOR=.85, 95% CI .77, .95, p=.005). Facilitating accurate risk assessment and promoting awareness of PrEP benefits and eligibility criteria may increase PrEP uptake among MSM in India.
Keywords: HIV prevention, Pre-exposure prophylaxis, Perceived risk, MSM, India
Introduction
HIV pre-exposure prophylaxis (PrEP) is safe and highly effective if taken as prescribed. 1 The World Health Organisation 2 recommends PrEP for individuals at “substantial risk,” including men who have sex with men (MSM). India has a concentrated HIV epidemic, with high national HIV prevalence estimates (~2.9–7.0%) among MSM, ranging from 2.9% to 13.1% across individual study sites. 3–5 PrEP demonstration projects in India have been conducted among female sex workers, 6,7 with projects among MSM in planning stages.
Numerous studies have assessed willingness to use PrEP in Western countries, but little information is available on MSM’s awareness of and willingness to use PrEP in India. A survey among MSM and transgender women (n=400) in South India reported that 93% had no prior PrEP awareness; but once information on PrEP was provided, 99% reported willingness to use it. 8 Neither perceived HIV risk nor “calculated HIV risk” significantly predicted willingness to use PrEP; however, “calculated risk” was a score developed from sexual behavior variables that were not based on available PrEP guidelines. 8 One qualitative study among MSM in India highlighted potential barriers to PrEP uptake, such as PrEP stigma, sexual stigma, and concerns about side-effects. 9 Anecdotal evidence suggests that some MSM in metro cities, such as Mumbai, who can afford PrEP are taking it as prescribed by private practitioners or from over-the-counter purchases.
HIV risk perception, a key construct in several behavior change models (e.g., Health Belief Model), may be an important factor in PrEP uptake. 10 However, the relationship between perceived HIV risk and actual risk is not always concordant. 11,12 Several studies suggest that high perceived HIV risk and/or actual risk may, or may not, predict willingness to use PrEP. For example, in an earlier study in New York City, 78% of MSM participants (n = 629) who were eligible for PrEP did not perceive themselves to be at sufficiently high risk to need PrEP. 13 Similarly, a qualitative study in Toronto reported that many at-risk MSM did not perceive themselves to be in need of PrEP. 14 In addition to risk perception, empirical findings based on rational choice theory have shown that perceived benefits (e.g., stealth use; user-controlled administration) and perceived costs (e.g., need to undergo HIV testing, side-effects, anticipated PrEP-related stigma) influence willingness to use PrEP. 9,15
The identification of factors that contribute to willingness to use PrEP (WTUP) and that explain why some at-risk but PrEP-eligible MSM are not willing to use PrEP may support the development of tailored interventions to increase PrEP uptake in India. Accordingly, we assessed: 1) the associations between guideline-informed PrEP eligibility, HIV risk perception, and perceived benefits and costs of using PrEP, with hypothetical WTUP (see Figure 1); and 2) correlates of non-willingness to use PrEP among PrEP-eligible MSM.
Figure 1. Conceptual framework showing potential associations between hypothesized predictors and willingness to use PrEP.
Methods
In the first quarter of 2017, we conducted an interviewer-administered Tablet-Assisted Survey Interview (TASI) among 600 MSM recruited through community-based organizations (CBOs) in Mumbai (n=300) and Chennai (n=300), India. Participants in each city were randomly assigned to a discrete choice experiment to identify acceptability and preferences for one of three new HIV prevention technologies (PrEP, HIV vaccines, and rectal microbicides). The data for the current analysis are drawn from the PrEP arm of the DCE (n=200).
Participants were recruited using respondent-driven sampling. Trained peer outreach workers at the participating study sites recruited initial seeds based on their personal peer network size and eligibility. Eligible participants included those who were 18 years of age or older, sexually active in the previous month, willing to provide consent for participation and willing to refer their peers. Participants were paid an honorarium of 300 INR (~ $4 USD) for their participation in the 35- to 45-minute survey interview and INR 50 for each successful referral. The study protocol was approved by the Institutional Review Boards of the University of Toronto, Ontario, Canada, and The Humsafar Trust, Mumbai, India.
Measures
Demographic characteristics
Demographic characteristics included age, education, occupation, personal monthly income, marital status, and self-reported sexual (gay-/bisexual-identified men) or sexual role-based identities: kothi (feminine/receptive), double-decker (insertive and receptive) and panthi (masculine/insertive). 16
Sexual risk behavior
Sexual risk behavior measures assessed: number and types of male partners in the past month, frequency of anal sex, consistency of condom use with different types of male partners in the past month, alcohol use before last anal sex, diagnosis of sexually transmitted infections (STIs) in the past year, HIV testing frequency, and perceived risk of contracting HIV. A dichotomous variable for inconsistent condom use (no vs. yes) with any type of male partner was created from responses to four items on condom use with different types (regular, casual, paying, and paid) of male partners.
PrEP eligibility criteria
We used five indicators of PrEP eligibility based on international guidelines (USA, UK, Europe and South Africa): 1) condomless anal sex (past-month), 17–19 2) STI diagnosis (past-year), 17–19 3) sex work (past-month), 17,20 4) >1 male partner (past-month) 18 and 5) alcohol use before last anal sex. 20 If participants screened positive for any one of these criteria they were categorized as PrEP eligible. WHO guidelines specify epidemiological criteria for initiating PrEP in various geographical regions and populations, but do not provide individual-level eligibility criteria; these may be defined differently by countries based on local contexts.
HIV risk perception
Each participant was asked to assess “My chances of getting infected with HIV are” using a six-point scale: 1=zero, 2=almost zero, 3=small, 4=moderate, 5=large, 6=very large. For analysis, we created a categorical variable: low perceived HIV risk (1 and 2), medium risk (3 and 4) and high risk (5 and 6).
PrEP awareness and source of information
Prior PrEP-related awareness was assessed by asking “Before taking part in this interview, have you heard or read anything about antiretroviral drugs used for HIV prevention?” This was followed by a question “From where did you get information about PrEP?” A brief description of PrEP based on AIDS Vaccine Advocacy Coalition 21 and US Centers for Disease Control and Prevention 22 factsheets was then provided to all participants before proceeding to the next section of the questionnaire.
Perceived benefits and costs of taking PrEP
We measured perceived benefits of taking PrEP using a 6-item scale (e.g., “It could prevent me from getting HIV” and “It would reduce my worry about getting HIV”) (see Table 1). Perceived costs were measured by 5 items (e.g., “I would worry about what my [MSM] friends think of me” and “I would worry that people would think I am HIV-positive if I am on PrEP”). Each scale exhibited good reliability (Cronbach’s alphas 0.86 and 0.85, respectively). One dichotomous item assessed “Would you take PrEP if you still had to use condoms?”
Table 1. Perceived benefits and costs of PrEP among MSM (n=197).
| Perceived benefits of PrEP | Strongly Disagree n (%) | Disagree n (%) | Neutral n (%) | Agree n (%) | Strongly Agree n (%) |
|---|---|---|---|---|---|
| It could prevent me from getting HIV | 4 (2.0) | 3 (1.5) | 8 (4.1) | 83 (42.1) | 99 (50.3) |
| It would reduce my worry about getting HIV | 1 (.5) | 11 (5.6) | 13 (6.6) | 79 (40.1) | 93 (47.2) |
| It would prevent me from getting HIV from forced sex | 4 (2.0) | 15 (7.6) | 9 (4.6) | 89 (45.2) | 80 (40.6) |
| I could tell my partners that I am protected against HIV | 4 (2.0) | 16 (8.1) | 6 (3.0) | 91 (46.2) | 80 (40.6) |
| It would allow me to have sex with a partner who is HIV-positive | 48 (24.4) | 55 (27.9) | 24 (12.2) | 30 (15.2) | 40 (20.3) |
| It would allow me to have sex with more sexual partners | 8 (4.1) | 46 (23.4) | 32 (16.2) | 59 (29.9) | 52 (26.4) |
| Perceived costs of PrEP | |||||
| I would worry about what my MSM friends thinks of me | 109 (55.3) | 71 (36.0) | 6 (3.0) | 8 (4.1) | 3 (1.5) |
| I would worry about what my family thinks of me | 91 (46.2) | 70 (35.5) | 10 (5.1) | 23 (11.7) | 3 (1.5) |
| I would worry about what my regular male sex partner thinks of me | 91 (46.2) | 76 (38.6) | 7 (3.6) | 20 (10.2) | 3 (1.5) |
| I would worry that I have to get an HIV test before getting PrEP | 59 (29.9) | 69 (35.0) | 16 (8.1) | 45 (22.8) | 8 (4.1) |
| I would worry that people would think I am HIV-positive if I am on PrEP | 73 (37.1) | 87 (44.2) | 13 (6.6) | 19 (9.6) | 5 (2.5) |
Willingness to use PrEP
Willingness to use PrEP was assessed by asking “Would you use PrEP as soon as it becomes available?” Participants responded using a 4-point Likert scale (1=yes, definitely; 2=yes, probably; 3=no, probably not; 4=no, definitely not). For logistic regression analysis, responses were dichotomized as “yes, definitely” (1=yes) vs. the remaining responses (0=no).
Data Analysis
The analysis was restricted to 197 MSM, after excluding three MSM who self-reported as HIV positive. Descriptive statistics were calculated for socio-demographic characteristics, behavioral indications for PrEP, HIV risk perception, perceived benefits and costs of PrEP, and willingness to use PrEP. Logistic regression models were fitted to examine the associations between PrEP eligibility, perceived HIV risk, perceived benefits of PrEP and willingness to use PrEP. Adjusted odds ratios (aOR) and 95% confidence intervals (CIs) were estimated. As interactions between perceived risk of contracting a disease and perceived benefits of a prevention tool have been reported, 23 we examined potential interactions between perceived HIV risk and perceived benefits of PrEP by adding a cross-product term of these variables in a separate logistic regression model. Given that WTUP was a common outcome (>10%), for sensitivity analyses we used log-binomial and Poisson regression with robust variance to check whether the findings were similar to logistic regression models. 24
We used a linear regression model to assess whether PrEP eligibility scores (0–5) were associated with perceived HIV risk scores (1–6). A logistic regression model was fitted to identify factors associated with non-willingness to use PrEP among PrEP-eligible MSM. Covariates included in the regression models were age, marital status, identity, HIV testing history, and use of PrEP if one still needed to use condoms. The latter two variables were included as independent predictors since HIV testing history may be associated with perceived HIV risk and need to use condoms may be associated with WTUP. In sensitivity analyses, the regression results did not change when these two variables were removed from the model. All analyses were performed using Stata 16 (StataCorp, 2019. College Station, TX).
Results
Sample Characteristics
Participants’ mean age was 26.5 years (SD 6.5) and mean monthly income was INR 12,195 ($161 USD). One-third (33.5%) completed a college degree, and 81.2% were currently single. About two-thirds (68.0%) self-identified as kothi, double-decker, or gay (see Table 2). Over one-third (36.5%; n=72/197) reported having heard of PrEP prior to the survey; of these, 80.5% (n=58/72) received information about PrEP from their peers, and 51.3% (n=37/72) from CBOs.
Table 2. Bivariate associations between sociodemographic characteristics, sexual behaviors, HIV risk perception and PrEP eligibility with willingness to use PrEP among MSM (N=197).
| Variable | Total (N=197) n (%) | Willingness to use PrEP | χ2 value | p value | |
|---|---|---|---|---|---|
| No (n=46) | Yes (n=151) | ||||
| Age group (years) | |||||
| ≤ 25 | 105 (53.3) | 18 (39.1) | 87 (57.6) | 4.84 | .02 |
| > 26 | 92 (46.7) | 28 (60.9) | 64 (42.4) | ||
| Monthly income (INR) | |||||
| < 10000 ($138 USD) | 101 (51.3) | 56 (51.4) | 45 (51.1) | 0.001 | .97 |
| 10000 and above | 96 (48.7) | 53 (48.6) | 43 (48.9) | ||
| Education | |||||
| Higher secondary school or lower | 131 (66.5) | 28 (60.9) | 103 (68.2) | .85 | .35 |
| Graduate degree or higher | 66 (33.5) | 18 (39.1) | 48 (31.8) | ||
| Marital status | |||||
| Married | 37 (18.8) | 12 (26.1) | 25 (16.6) | 2.10 | .14 |
| Single | 160 (81.2) | 34 (73.9) | 126 (83.4) | ||
| Forced sex victimization (past year) | |||||
| No | 164 (83.2) | 37 (80.4) | 127 (84.1) | .34 | .55 |
| Yes | 33 (16.8) | 9 (19.6) | 24 (15.9) | ||
| Sexual or sexual role-based identity a | |||||
| Kothi/Double-Decker/Gay | 134 (68.0) | 30 (65.2) | 104 (68.9) | .21 | .64 |
| Others (Panthi/Bisexual) | 63 (32.0) | 16 (34.8) | 47 (31.1) | ||
| HIV test (past year) | |||||
| No | 32 (16.2) | 7 (15.2) | 25 (16.6) | .04 | .82 |
| Yes | 165 (83.8) | 39 (84.8) | 126 (83.4) | ||
| Frequency of anal sex | |||||
| Low | 125 (64.1) | 26 (59.1) | 99 (65.6) | 0.62 | .43 |
| High | 70 (35.9) | 18 (40.9) | 52 (34.4) | ||
| Prior awareness of PrEP | |||||
| No | 125 (63.5) | 35 (76.1) | 90 (59.6) | 4.13 | .04 |
| Yes | 72 (36.5) | 11 (23.9) | 61 (40.4) | ||
| HIV risk perception | |||||
| No risk | 88 (44.7) | 31 (67.4) | 57 (37.7) | 12.75 | .002 |
| Low/moderate risk | 97 (49.2) | 14 (30.4) | 83 (55.0) | ||
| High risk | 12 (6.1) | 1 (2.2) | 11 (7.3) | ||
| Guideline-informed PrEP eligibility | |||||
| No | 14 (7.1) | 8 (17.4) | 6 (4.0) | 9.61 | .002 |
| Yes | 183 (92.9) | 38 (82.6) | 145 (96.0) | ||
|
PrEP-eligibility criteria
Inconsistent condom use with any type of male partners | |||||
| No | 82 (41.6) | 22 (47.8) | 60 (39.7) | .95 | .33 |
| Yes | 115 (58.4) | 24 (52.2) | 91 (60.3) | ||
| STI diagnosis (past year) | |||||
| No | 184 (93.4) | 43 (93.5) | 141 (93.4) | .0006 | .98 |
| Yes | 13 (6.6) | 3 (6.5) | 10 (6.6) | ||
| > 1 male partner (past month) | |||||
| No | 23 (11.7) | 10 (21.7) | 13 (8.6) | 5.89 | .01 |
| Yes | 174 (88.3) | 36 (78.3) | 138 (91.4) | ||
| Alcohol use before last anal sex | |||||
| No | 131 (67.2) | 31 (70.5) | 100 (66.2) | .27 | .59 |
| Yes | 64 (32.8) | 13 (29.5) | 51 (33.8) | ||
| Sex work (past month) | |||||
| No | 93 (51.4) | 17 (43.6) | 76 (53.5) | 1.20 | .27 |
| Yes | 88 (48.6) | 22 (56.4) | 66 (46.5) | ||
Identities were dichotomised on the basis of predominant sexual orientation: kothi, double-decker and gay men (predominantly attracted towards men); and panthi and bisexual-identified men (attracted towards men and women).
PrEP eligibility criteria
Of the five criteria for PrEP eligibility, 58.4% reported inconsistent condom use with male partners in the past month, 6.6% reported having physician-diagnosed STIs in the past year, 32.8% having consumed alcohol before last anal sex, 88.3% >1 male partner past month, and 48.6% engaging in sex work (see Table 1). Overall, 92.9% were PrEP-eligible based on meeting any one of these criteria.
HIV risk perception and perceived benefits and costs
Nearly half (49.2%) of participants indicated medium HIV risk perception and 6.1% high HIV risk perception. Among PrEP-eligible MSM (n=183), 57.3% (n=105/183) had medium/high risk perception. The mean score of perceived benefits of PrEP was 23.2 (SD 4.9; range, 6–30) and that of perceived costs of PrEP was 9.6 (SD 4.1; range, 5–25) (see Table 2).
Willingness to use PrEP
Three-fourths (76.6%; n=151/197) of participants reported WTUP. Among those with medium and high HIV risk perception (n=109), 86.2% (N=94/109) reported WTUP. Among PrEP-eligible MSM (n=183), 79.2% (n=145/183) reported WTUP.
Associations between PrEP eligibility, HIV risk perception, perceived benefits/costs of PrEP, and willingness to use PrEP
Three logistic regression models were fitted to examine the associations between PrEP eligibility, HIV risk perception, and WTUP (see Table 3). In Model 1, HIV risk perception was included with other predictors/covariates; in Model 2, PrEP eligibility was included; and in Model 3, both HIV risk perception and PrEP eligibility were included (see Table 3). In Model 1, medium and high HIV risk perception were significantly associated with higher odds of WTUP. In Model 2, PrEP eligibility was significantly associated with higher odds of WTUP. In Model 3, both PrEP eligibility and HIV risk perception were significantly associated with higher odds of WTUP.
Table 3. Factors associated with willingness to use PrEP (WTUP) among MSM (n=197): Multivariable logistic regression results.
| Variables | Model 1: Perceived HIV risk as the key predictor of WTUP | Model 2: PrEP eligibility criteria as the key predictor of WTUP | Model 3: Both perceived HIV risk and PrEP eligibility as key predictors of WTUP |
|---|---|---|---|
| aOR (95% CI) | aOR (95% CI) | aOR (95% CI) | |
| PrEP eligibility – Yes (vs. No) | 4.38 (1.09, 17.53)* | 5.31 (1.11, 25.45)* | |
| HIV risk perception (Ref. low risk) | |||
| Medium | 2.66 (1.16, 6.10)* | 2.41 (1.03, 5.63)* | |
| High | 10.41 (1.03, 104.52)* | 13.08 (1.29, 132.27)* | |
| Perceived benefits of PrEP (score) | 1.14 (1.04, 1.25)** | 1.13 (1.03, 1.23)** | 1.13 (1.03, 1.24)* |
| Perceived costs of PrEP (score) | .92 (.83, 1.01) | .91 (.83, 1.01) | .92 (.84, 1.02) |
| Prior awareness of PrEP Yes (vs. No) | .95 (.36, 2.48) | 1.00 (.40, 2.52) | 1.00 (.38, 2.64) |
| Age ≥26 years (vs. ≤25 years) | .71 (.30, 1.68) | .68 (.29, 1.60) | .69 (.29, 1.65) |
| Identity – panthi/bisexual (vs. kothi/gay/double-decker) | .91 (.37, 2.23) | .76 (.32, 1.81) | .96 (.39, 2.39) |
| Marital status – single (vs. married) | 2.09 (.74, 5.93) | 1.72 (.63, 4.67) | 2.37 (.82, 6.81) |
| Experience of forced sex in the past year – Yes (vs. No) | .86 (.31, 2.38) | .99 (.36, 2.75) | .76 (.26, 2.15) |
| HIV testing in the past year – Yes (vs. No) | .68 (.22, 2.09) | .67 (.22, 2.00) | .64 (.21, 1.99) |
| Frequency of anal sex – High (vs. Low) | .94 (.42, 2.09) | .72 (.32, 1.60) | .78 (.34, 1.78) |
| “Would take PrEP if still had to use condoms” – Yes (vs. No) | 2.46 (1.08, 5.61)* | 2.53 (1.12, 5.69)* | 2.68 (1.15, 6.26)* |
p < .05
p < .01
aOR = Adjusted Odds Ratio, CI = Confidence Interval
PrEP-eligible MSM had higher odds (aOR=5.31, 95% confidence interval [CI] 1.11–25.45, p=.03) of reporting WTUP compared to MSM who did not meet PrEP eligibility criteria. MSM who had medium (aOR=2.41, 95% CI 1.03–5.63, p=.04) or high risk perception (aOR=13.08, 95% CI 1.29–132.27, p=.02) had higher odds of reporting WTUP compared to those who had low HIV risk perception (see Table 3). Similarly, MSM with higher scores on perceived benefits of PrEP (aOR=1.13, 95% CI 1.03–1.24, p=.01) had higher odds of reporting WTUP. Perceived costs of PrEP, prior awareness of PrEP, forced sex victimization, age, sexual identity, HIV testing frequency, and marital status were not independently associated with WTUP. MSM who reported that they would take PrEP even if they still had to use condoms, compared to those who reported they would not, had higher odds (aOR=2.68, 95% CI 1.15–6.26, p=.02) of reporting WTUP. Sensitivity analyses using Poisson regression models provided similar results (not shown); log-binomial regression models did not converge.
In logistic regression modelling, a significant interaction was found between HIV risk perception and perceived benefits of PrEP (interaction term aOR=1.07, 95% CI 1.001–1.15, p=.04) in predicting WTUP, as shown in Figure 2. At higher scores of perceived benefits of PrEP any increase in HIV risk perception substantially increases the probability of WTUP. In the linear regression model to predict the perceived HIV risk score from the PrEP eligibility score, PrEP eligibility (b=.17, 95% CI .005–.35, p=.04) was identified as a significant predictor. Other covariates, such as age, marital status, forced sex victimization, and frequency of anal sex were not significantly associated with perceived HIV risk.
Figure 2. Contour plot: Interaction between perceived HIV risk and perceived benefits of PrEP in predicting willingness to use PrEP.
Factors associated with non-willingness to use PrEP among PrEP-eligible MSM
Among PrEP-eligible MSM (n=183/197; 92.9%), those who reported low HIV risk perception had higher odds of reporting non-willingness to use PrEP (aOR=2.77, 95% CI 1.15–6.69, p=.02) compared to those who reported medium HIV risk perception. Further, those who had higher scores on perceived benefits of PrEP had lower odds of reporting non-willingness to use PrEP (aOR=.85, 95% CI .77–.95, p=.005) (Table 4).
Table 4. Factors associated with non-willingness to use PrEP among MSM (n=197): multivariable logistic regression results.
| Variables | Adjusted Odds Ratio (aOR) | 95% Confidence Interval (CI) | p value |
|---|---|---|---|
| HIV risk perception (Ref. low risk) | |||
| Medium risk | 2.77 | 1.15, 6.69 | .02 |
| High risk | .25 | .02, 2.86 | .26 |
| Perceived benefits of PrEP (score) | .85 | .77, .95 | .005 |
| Perceived costs of PrEP (score) | 1.08 | .97, 1.20 | .14 |
| Prior awareness of PrEP | 1.01 | .35, 2.87 | .97 |
| Age ≥26 years (vs. ≤25 years) | 1.22 | .49, 3.05 | .65 |
| Identity –panthi/bisexual (vs. kothi/gay/double-decker) | .73 | .27, 1.95 | .53 |
| Marital status – single (vs. married) | .36 | .12, 1.08 | .07 |
| Forced sex victimization (past year) – Yes (vs. No) | 1.26 | .44, 3.61 | .65 |
| HIV testing (past year) – Yes (vs. No) | .98 | .29, 3.20 | .97 |
| “Would take PrEP if still had to use condoms” – Yes (vs. No) | .37 | .15, .90 | .02 |
Discussion
To achieve UNAIDS targets of zero new infections by 2030, an integral part of the United Nations Sustainable Development Goals, 25 it is critical to understand factors influencing willingness to use PrEP among MSM. We found that most participants were eligible for PrEP based on international guidelines and were willing to use it. In adjusted analyses, PrEP eligibility and perceived HIV risk were significantly and independently associated with WTUP. However, a subgroup of PrEP-eligible MSM reported non-willingness to use PrEP, which was associated with low HIV risk perception and low perceived benefits of PrEP.
In the present study, PrEP eligibility significantly predicted HIV risk perception, possibly indicating correct self-assessment of HIV risk behaviors. While several studies have shown discordance between HIV risk perception and “objective risk”, 13,26 other studies have shown concordance 27 or no association. 8 In terms of risk behaviors, several studies have reported that high-risk MSM are willing to use PrEP. 28–31 Participants in this study were primarily recruited from cruising sites served by CBOs; it is possible that communication with HIV prevention outreach workers may have contributed to their accurate self-assessment of risk.
Similar to the present findings, several studies have identified an association between perceived benefits of PrEP and WTUP. 32,33 Although in our study, perceived cost of PrEP was not associated with WTUP, others have reported that perceived barriers to using PrEP may decrease WTUP. 15 Our finding that perceived HIV risk interacted with perceived benefits of PrEP was novel: when both were high, the chances of reporting WTUP were very high. Simultaneously focusing on improving accurate self-risk assessment and providing education on PrEP benefits may act synergistically to improve uptake among PrEP-eligible MSM. However, the ‘dual-process model’ (cognition- and emotion-based paths) of decision-making suggests that promoting accurate self-risk assessment alone may be insufficient to increase PrEP uptake, as prior negative emotional experiences, such as discrimination in health care settings, may influence even PrEP-eligible MSM not to use PrEP. 34
Our finding that MSM who have medium/high HIV risk perception are more likely to meet PrEP-eligibility criteria and more willing to use PrEP suggests that once a national PrEP program is initiated in India, it is likely to be accessed by at-risk MSM. However, given persistent sexual stigma—even after decriminalization of adult consensual same-sex relations in India in 2018 35 —it is crucial to create an enabling environment for MSM by ensuring that they receive non-discriminatory, culturally-competent services in accessing PrEP programs. The associations of low perceived HIV risk and low perceived benefits of PrEP, respectively, with non-willingness to use PrEP is consistent with studies across low-, middle- and high-income countries. 15,36 Given the lack of prior awareness of PrEP among MSM in this study, consistent with studies from other LMICs, 15 PrEP awareness campaigns using peer outreach workers, traditional media and online communications are needed in India.
Limitations and strengths
This study has several limitations. Although respondent-driven sampling was used in the larger survey of preferences for new HIV prevention technologies, selection of the dataset for this analysis renders it a convenience sample of MSM who attend cruising sites in Mumbai and Chennai. The findings may not be generalizable to all MSM who visit cruising sites. Nevertheless, this is a diverse high-risk population of MSM for whom PrEP would be beneficial. The level of prior awareness of PrEP among this sample is higher than that reported by other studies from India, 8,9 possibly reflecting participants’ interactions with CBOs or increases in awareness over time. However, prior awareness and WTUP may be lower among MSM who are not engaged with CBOs. HIV risk perception was assessed with a single item; however, this is similar to several other studies of HIV risk. 11,12 Finally, stated intention to use PrEP may not translate into actual uptake; nevertheless, it is important to assess WTUP in advance of availability in order to develop and disseminate evidence-informed interventions to accelerate uptake.
Conclusion
HIV risk perception and guideline-indicated PrEP eligibility were individually and jointly associated with willingness to use PrEP among MSM recruited from cruising sites in India. However, among a subgroup of PrEP-eligible MSM, low HIV risk perception and low perceived benefits of PrEP were associated with non-willingness to use PrEP. Promoting accurate self-assessment of risk and educating MSM on potential benefits of PrEP as well as potential risks may support uptake. Individual-level programs to accelerate PrEP uptake should be complemented by structural interventions that promote culturally competent and non-discriminatory environments for MSM in healthcare settings, 16,37,38 and provide resources for free or subsidized PrEP 9 to maximize coverage among at-risk MSM.
Acknowledgements
We thank our community partner Thozhi for supporting implementation of this study in Chennai.
Funding information
This study was funded, in part, by grants from the Canadian Institutes of Health Research (MOP-102512; THA-118570; Newman, PI). Dr. Venkatesan Chakrapani was supported, in part, by the Wellcome Trust/DBT India Alliance Senior Fellowship (IA/CPHS/16/1/502667).
Footnotes
Author Disclosure Statement
The authors declare that they have no competing interests.
Authors’ Contributions
V.C. and P.A.N. conceptualized and designed the study, and acquired funding. M.S., R.N., S.R., and D.B. conducted data collection. V.C. and M.S. conducted data analysis. V.C. critically reviewed data analysis and findings, and drafted the initial manuscript. P.A.N. revised the manuscript in its present form. All authors made contributions to interpretation of data, critically reviewed the manuscript for important intellectual content, and gave final approval for the article in its present form.
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