Abstract
Introduction
Implementing pre-exposure prophylaxis (PrEP) is hindered by a significant “PrEP Cliff”, a sharp decline from willingness to uptake and adherence. This study aimed to integrate status quo bias theory with a dual-process model, seeking to understand how this bias influences the PrEP cascade among men who have sex with men (MSM) in China.
Methods
A cross-sectional survey was conducted among 1022 MSM across six provinces in China from November 2024 to February 2025. Through regression models, we tested a moderated mediation framework to examine how status quo bias influenced PrEP willingness, uptake, and adherence, focusing on the mediating role of PrEP resistance intention and the moderating role of condom-use inertia.
Results
Participants were generally young (≤ 30 years; 63.1%), mostly unmarried (88.5%), and well-educated (89% with a bachelor’s degree or higher). The “PrEP Cliff” was evident, characterized by high awareness (91.3%) and willingness among non-users (58.9%), but low uptake (46.2%) and poor adherence, with 53.4% of users self-reporting lower adherence. In the initiation phase (willingness and uptake), PrEP resistance intention significantly mediated the associations of transition costs and social norms on PrEP cascade outcomes. Condom-use inertia significantly moderated this mediation pathway by strengthening the associations of transition costs (β = 0.06, 95% CI 0.01 to 0.11) and social norms (β = − 0.05, 95% CI − 0.10 to 0.00) on PrEP resistance intention. However, the mechanism shifted during the adherence phase. Adherence was instead predominantly predicted by the direct associations of transition costs (β = − 0.44, 95% CI − 0.64 to − 0.23) and social norms (β = 0.56, 95% CI 0.38 to 0.74).
Conclusion
This study provides an evidence-based framework for clinicians and public health programs to design stage-specific interventions tailored to the distinct psychological barriers that dominate each phase.
Supplementary Information
The online version contains supplementary material available at 10.1007/s40121-025-01296-y.
Keywords: PrEP, Status quo bias, Dual-process model, MSM, Transition cost, Social norms, Condom-use inertia
Key Summary Points
| Why carry out this study? |
| The “PrEP Cliff”, a sharp decline from willingness to uptake and adherence, hinders the real-world impact of pre-exposure prophylaxis (PrEP), particularly among high-risk groups such as men who have sex with men (MSM) in China. |
| While numerous barriers to PrEP adoption are known, the underlying cognitive mechanisms that drive these gaps remain poorly understood, creating an unmet need for targeted behavioral interventions. |
| This study hypothesized that status quo bias, through transition costs and social norms, shapes the PrEP cascade via resistance intention as a mediator, with condom-use inertia as a moderator. |
| What was learned from the study? |
| The cognitive mechanisms driving the “PrEP Cliff” are stage-dependent, with resistance intention mediating initiation outcomes (willingness and uptake), while transition costs and social norms directly influence adherence. |
| This study provides an evidence-based framework for designing stage-specific interventions tailored to the distinct challenges of overcoming initial psychological resistance versus sustaining long-term action. |
Introduction
The global strategy to end the HIV epidemic is confronted by a profound paradox: despite the proven efficacy of pre-exposure prophylaxis (PrEP), a powerful biomedical prevention tool, its real-world uptake among key populations remains suboptimal globally [1, 2]. This sharp, stepwise decline from high awareness and demand to low uptake and subsequent poor adherence constitutes the “PrEP Cliff” phenomenon [3, 4]. This represents a critical public health implementation impasse, severely undermining the immense potential of PrEP as a key tool in ending the HIV epidemic. This challenge is particularly true in China, where men who have sex with men (MSM) face a disproportionately high risk of acquiring HIV. Studies have reported very high HIV incidence rates in this population, in some cases exceeding 5.0 cases per 100 person-years [5, 6]. While over 66.7% of Chinese MSM are willing to use PrEP, actual uptake rates are less than 10% and the adherence situation is even more concerning [7, 8]. Therefore, a deeper investigation into the cognitive mechanisms underlying this gap has become a critical agenda in HIV prevention.
Previous research has identified numerous barriers influencing different stages of the PrEP cascade. For the PrEP initiation phase, structural barriers such as high costs, lack of convenient clinical services, and individual-level factors such as low-risk perception and concerns about side effects have been identified as key deterrents to willingness and initial uptake [9–11]. For the PrEP maintenance phase, ongoing logistical burdens, such as the inconvenience of follow-ups and concerns about long-term side effects, are also significant barriers [12, 13]. Furthermore, studies consistently show that social norms from key referents, such as physicians, family, friends, and sexual partners, are powerful determinants [14, 15]. Perceived disapproval or negative stereotypes associated with PrEP have been shown to inhibit initial interest and disrupt long-term adherence [14, 16, 17]. However, while this body of work has successfully identified the barriers, these explorations have largely remained descriptive or correlational. Hence, it remains unclear how these different barriers are cognitively processed. Specifically, the role of resistance intention as a key psychological threshold that translates these barriers into engagement with the PrEP cascade remains underexplored.
The status quo bias theory offers a powerful lens for explaining why people resist beneficial health changes. Originating from behavioral economics, this theory posits that individuals exhibit a powerful, often non-rational, preference for maintaining their current state, thereby resisting beneficial changes. This bias is understood to stem from rational decision-making processes and psychological commitments [15, 18]. In the context of PrEP, the decision to resist adoption can be seen as a coherent choice to maintain the status quo. The rational component is captured by transition costs, which include the perceived burdens, in time, finances, and effort, required to shift from an existing prevention strategy, such as condoms, to PrEP [9, 12, 13]. The psychological commitment component is driven by social norms [19], representing the collective expectations and shared attitudes regarding PrEP use within the MSM community [14, 15]. When individuals are embedded in social networks that actively endorse or discuss PrEP use, these positive normative cues can help counteract status quo tendencies and encourage uptake of PrEP [20, 21].
To fully understand how status quo bias operates, it is necessary to examine the cognitive mechanisms through which its components influence behavior. The dual-process model provides a valuable analytical framework for this purpose, distinguishing between two systems of thought: System 1 (the heuristic system), which is fast, automatic, intuitive, and emotionally driven; and System 2 (the analytical system), which is slow, deliberate, effortful, and based on logical reasoning [22]. Consistent with prior research, social norms could be conceptualized as rapid, intuitive heuristic cues, whereby individuals make swift judgments based on the attitudes of significant others, a classic manifestation of System 1 [23]. In contrast, the deliberation over transition costs represents a quintessential System 2 process, requiring a thoughtful cost–benefit analysis [24]. This implies that these systems do not drive decisions regarding PrEP adoption in isolation but emerge from their dynamic interplay (Fig. 1).
Fig. 1.
The conceptual framework. PrEP pre-exposure prophylaxis
This conceptual framework illustrates the hypothesized relationships. The PrEP cascade outcomes include three distinct endpoints analyzed in separate models: PrEP uptake, PrEP willingness, and PrEP adherence.
Crucially, condom-use inertia does not function as just another parallel factor; it is a crucial moderating factor. As a powerful force of habit forged through long-term repetition, inertia reflects an individual’s intrinsic “stickiness” to their current behavior [25]. In the context of HIV prevention, condom use remains a widely practiced method among MSM [26]. Initiating PrEP, therefore, requires breaking from these established patterns, a shift often met with resistance [9]. Building on these insights, we hypothesize that condom-use inertia plays a critical moderating role, defining the cognitive context that alters the strength of the status quo bias inputs. Specifically, we propose that the influence of transition costs and social norms converge upon a central psychological threshold, PrEP resistance intention, and that the force of pre-existing condom-use inertia moderates the pathways leading from status quo bias to PrEP resistance intention.
Building on this integrated framework, this study aimed to test this model and provide an evidence-based foundation for health promotion strategies. First, we investigate how the inputs from status quo bias influence PrEP engagement through the mediating role of PrEP resistance intention. Second, we test the moderating effect of condom-use inertia, examining how it alters the strength of the relationships between the status quo bias inputs and the formation of PrEP resistance intention. Finally, we aim to compare whether these cognitive mechanisms operate differently across the distinct stages of the PrEP cascade, including willingness, uptake, and adherence.
Methods
Participants Recruitment
The online cross-sectional survey was administered via Sojump, a widely used Chinese social survey tool. The study team first drafted online outreach materials, including posts and posters containing the survey link. They were distributed via posts on the WeChat official accounts of collaborating partners and their social workers. Collaborating partners included community-based organizations (CBOs) and Centers for Disease Control and Prevention (CDC) offices across several provinces in China: Guangdong, Hubei, Shandong, Jiangsu, Sichuan, and Shanghai Municipality. Convenience sampling and snowball sampling were used. The data collection period ran from November 29, 2024 to February 11, 2025.
Inclusion criteria were aged ≥ 18 years, identifying as a cisgender male, and a history of sexual activity with other men, self-reported HIV negative or unaware of their HIV infection status, and willing to provide informed consent. Individuals were excluded from the study if they declined to provide informed consent or if the research team assessed them as unable to complete the survey due to severe psychiatric conditions or cognitive deficits. Electronic informed consent was obtained from all participants before they could access the questionnaire.
Ethical Approval
This study was performed in accordance with the Helsinki Declaration of 1964 and its later amendments. This study was approved by the Institutional Review Board (IRB) of Shenzhen University [PN-202400070], and all participants provided informed consent before participation.
Sample Selection
To ensure robust statistical analysis, the minimum sample size was 385, based on an anticipated PrEP initiation rate of 10%, a 95% confidence level, and a 3% margin of error (± 3%). Our sample of 1022 valid questionnaires significantly exceeded this minimum, enhancing the precision and reliability of the findings. Of these, 933 participants who reported having heard of PrEP constituted the “PrEP-Aware Sample” and completed the subsequent questionnaire. The PrEP-Aware Sample was then stratified into two subgroups based on their response to the question regarding PrEP uptake. A total of 431 participants who reported a history of PrEP uptake formed the “PrEP Users” sample. The 502 participants who reported no PrEP uptake and the 89 PrEP-unaware participants constituted the “PrEP Non-users” sample.
Measures
PrEP Cascade Outcomes
The PrEP cascade outcomes in this study comprised three outcomes: PrEP willingness, PrEP use, and PrEP adherence.
PrEP Willingness PrEP non-users were asked, “If you have not taken PrEP yet, would you like to take it?” The responses were dichotomized, with ‘No’ coded as 0 and ‘Yes’ coded as 1.
PrEP Use Respondents in the PrEP-aware sample were asked, “Have you ever taken PrEP?” The responses were dichotomized, with ‘No’ coded as 0 and ‘Yes’ coded as 1.
PrEP Adherence PrEP adherence was assessed among PrEP users using two ‘regimen-agnostic’ items adapted from Pasipanodya et al. (2020): “In the last 30 days, how good of a job did you do at taking your PrEP medication in the way you were supposed to?” and “In the last 30 days, how often did you take PrEP medication in the way you were supposed to?” Responses were captured on a 7-point Likert scale, anchored from 0 (“Not used in the past 30 days”) to 6 (“Excellent”/“Always”). Good concordance has been previously established between this self-report measure and objective biological markers of adherence [27, 28]. The average score of the two items was calculated to create a single continuous measure of self-reported adherence [27, 28]. This continuous score was dichotomized for descriptive and visualization analyses based on its mean value (4.04) (0 = lower adherence group, 1 = higher adherence group).
Key Constructs
To test our theoretical framework, we measured four key constructs. All items were measured on a seven-point Likert scale, ranging from “strongly disagree” (1) to “strongly agree” (7). A detailed list of all items is available in Supplementary Table 1 in the Supplementary Material.
Transition Costs Transition costs were defined as the perceived burdens (time, finances, side effects, and hassles) associated with switching from prior HIV prevention methods, such as condoms, to PrEP [9, 12, 13].
Social Norms. Social norms measured perceived expectations from physicians, family/friends, and sexual partners regarding the respondents’ use of PrEP [14, 15].
Condom-use Inertia. The condom-use inertia captured routine, emotional, and cognitive inertia related to condom use [18].
PrEP Resistance Intention. To assess the central psychological threshold in our model, items for PrEP resistance intention were developed specifically for each PrEP cascade outcome (willingness, uptake, and adherence).
As shown in Supplementary Table 2, all constructs demonstrated excellent internal consistency, with both Cronbach’s alpha (α) and composite reliability (CR) values surpassing the stringent 0.8 threshold. Furthermore, average variance extracted (AVE) values exceeded the 0.5 criterion, confirming robust construct reliability and validity [29]. Convergent validity was confirmed [30], with all item loadings significant and most > 0.70. Two items with loadings above 0.66 were retained as acceptable [31]. To address potential construct overlap, discriminant validity was confirmed via the Fornell–Larcker criterion (Supplementary Table 3). Full psychometric details, including factor loadings, model fit, and the correlation matrix, are provided in Supplementary Table 2.
Covariates
The covariates were selected based on established literature identifying them as significant predictors of PrEP-related behaviors and potential confounders [32, 33]. These included age, sexual orientation, marital status, highest education level, monthly income, number of regular male partners in the past 6 months, and number of casual male partners in the past 6 months. Substance use in the past 12 months was assessed explicitly with a checklist (marijuana, cocaine, opium/‘white powder,’ methamphetamine, poppers, ecstasy, LSD, psilocybin, GHB/GBL). Any use during sex was coded 1 (yes), otherwise 0 (no).
Statistical Analysis
The reliability and validity of the Status Quo Bias scale were assessed using the full sample. All subsequent analyses were performed on the specified analytic samples. Specifically, analyses predicting PrEP use were based on the PrEP-aware sample, analyses of PrEP willingness were restricted to PrEP non-users, and PrEP adherence was limited to PrEP users. Descriptive statistics were used to summarize the characteristics of the specified analytic samples, with continuous variables described by their means and standard deviations (SD), and categorical variables by their frequencies and percentages. Independent samples t tests were conducted to assess the mean score differences in status quo bias variables between the ‘Yes’ and ‘No’ groups for each of the three PrEP cascade outcomes.
Regression-based path analyses were conducted to test the hypothesized theoretical framework. First, after controlling for covariates, multivariable logistic regression and linear models were used to predict the associations between the status quo bias variables and the respective PrEP cascade outcomes. The KHB method was employed to decompose the total association of the status quo bias variables via PrEP resistance intention on the PrEP cascade outcomes into direct and indirect pathways, with 95% confidence intervals [34]. Then, the multiple linear regression model was constructed with PrEP resistance intention as the dependent variable, including terms for transition costs, social norms, condom-use inertia, and the corresponding interaction terms (visualized at ± 2 SD). Finally, this analytical framework was run separately within the three independent analytic samples to explore the pattern of these behavioral mechanisms within each stage of the PrEP cascade. All statistical analyses were performed using STATA 17 (College Station, TX: StataCorp LLC), and a two-tailed p value of less than 0.05 was considered statistically significant.
Results
Participant Characteristics
Table 1 presents the sociodemographic and behavioral characteristics of the PrEP-aware sample (n = 933), the non-user subgroups (n = 591), and the PrEP users (n = 431). The PrEP-aware sample was generally young (≤ 30 years: 63.1%), predominantly unmarried (88.5%), and highly educated (89% with a bachelor’s degree or higher). Over one-third reported a monthly income above 8000 yuan.
Table 1.
Participants’ sociodemographic and sexual behavior characteristics
| Characteristic | PrEP-aware sample (N = 933) | PrEP non-users (N = 591) | PrEP users (N = 431) | p valuea |
|---|---|---|---|---|
| N (%) | N (%) | N (%) | ||
| Age (years) | 0.271 | |||
| Mean (SD) | 29.9 (7.4) | 29.8 (8.3) | 29.3 (6.6) | |
| Age (years) | 0.003 | |||
| ≤ 30 | 589 (63.1) | 385 (65.1) | 273 (63.4) | |
| 31–40 | 265 (28.4) | 143 (24.2) | 135 (31.3) | |
| 41–50 | 57 (6.1) | 43 (7.3) | 19 (4.4) | |
| > 50 | 22 (2.4) | 20 (3.4) | 4 (0.9) | |
| Sexual orientation | 0.009 | |||
| Homosexual | 714 (76.5) | 424 (71.7) | 343 (79.5) | |
| Bisexual | 193 (20.7) | 151 (25.6) | 72 (16.7) | |
| Heterosexual | 22 (2.4) | 14 (2.4) | 14 (3.3) | |
| Unsure/other | 4 (0.4) | 2 (0.3) | 2 (0.5) | |
| Marriage status | < 0.001 | |||
| Never married | 826 (88.5) | 497 (84.1) | 399 (92.6) | |
| Engaged/married | 64 (6.9) | 60 (10.2) | 18 (4.2) | |
| Separated/divorced/widowed | 43 (4.6) | 34 (5.8) | 14 (3.2) | |
| Highest education level | < 0.001 | |||
| High school or below | 103 (11.0) | 94 (15.9) | 31 (7.1) | |
| Bachelor’s degree | 679 (72.8) | 410 (69.4) | 329 (76.5) | |
| Graduate degree or above | 151 (16.2) | 87 (14.7) | 71 (16.5) | |
| Monthly income (yuan) | < 0.001 | |||
| ≤ 3000 | 117 (12.5) | 91 (15.4) | 45 (10.4) | |
| 3001–5000 | 166 (17.8) | 114 (19.3) | 78 (18.1) | |
| 5001–8000 | 297 (31.8) | 201 (34.0) | 124 (28.8) | |
| > 8000 | 353 (37.8) | 185 (31.3) | 184 (42.7) | |
| Number of regular male partners | < 0.001 | |||
| 0 | 145 (15.5) | 101 (17.1) | 62 (14.4) | |
| 1 | 532 (57.0) | 362 (61.3) | 225 (52.2) | |
| > 1 | 256 (27.4) | 128 (21.7) | 144 (33.4) | |
| Number of casual male partners | < 0.001 | |||
| 0 | 277 (29.7) | 210 (35.5) | 98 (22.7) | |
| 1 | 354 (37.9) | 235 (39.8) | 163 (37.) | |
| > 1 | 302 (32.4) | 146 (24.7) | 170 (39.5) | |
| Substance use during sexual activities | < 0.001 | |||
| No | 700 (75.0) | 484 (81.9) | 285 (66.1) | |
| Yes | 233 (25.0) | 107 (18.1) | 146 (33.9) | |
PrEP pre-exposure prophylaxis
ap value for the comparison between PrEP users and non-users
Group comparisons revealed significant differences across several key characteristics between PrEP users and non-users. Compared to non-users, PrEP users were more likely to self-identify as homosexual (79.5% vs. 71.7%, p = 0.009), be never married (92.6% vs. 84.1%, p < 0.001), and have significantly higher education (bachelor’s degree or above: 93% vs. 84.1%, p < 0.001) and monthly income (> 8000 yuan: 42.8% vs. 31.3%, p < 0.001). By contrast, PrEP non-users had a comparatively lower-risk profile, with a greater proportion of individuals aged over 40 (10.7% vs. 5.3%, p = 0.003), a lower proportion of people reporting substance use during sexual activities (18.1% vs. 33.7%, p < 0.001), and a significantly greater proportion of individuals reporting no casual partners (35.5% vs. 22.6%, p < 0.001).
Characterizing the “PrEP Cliff” and Its Associated Status Quo Bias
The distribution of participants across the PrEP cascade revealed a steep, stepwise attrition, defining the “PrEP Cliff” in this study (Fig. 2). Of the total recruited sample (N = 1022), 91.3% (n = 933) were aware of PrEP. Among these PrEP-aware individuals, the first significant drop-off occurred at uptake, with only 46.2% (n = 431) reporting ever having used PrEP. Among those who had ever used PrEP, 46.6% (n = 200) reported higher adherence. A similar gap was observed for PrEP willingness. Among the 591 individuals classified as PrEP non-users, only 58.9% (n = 348) expressed intent for future use. This cascade demonstrates that from the initial 1022 participants recruited, only 19.6% were ultimately engaged in using PrEP with higher adherence.
Fig. 2.
The PrEP cascade among participants. PrEP pre-exposure prophylaxis
Figure 3 and Supplementary Table 4 display mean status quo bias scores at each PrEP stage. In the PrEP-aware group, transition costs (p = 0.022), social norms (p < 0.001), and PrEP resistance intention (p < 0.001) all differed significantly between users and non-users. Among PrEP non-users, significant differences were observed only in social norms (p = 0.018) and resistance intention (p < 0.001), while the difference in transition costs was not pronounced between willing and unwilling groups. Among PrEP users, significant differences between the lower-adherence and higher-adherence groups were observed only for transition costs (p = 0.017) and social norms (p < 0.001).
Fig. 3.
Distribution of status quo bias variables. PrEP pre-exposure prophylaxis
Associations and Mediation Pathways of Status Quo Bias in PrEP Cascade Outcomes
Table 2 reports transition costs, social norms, condom-use inertia, and resistance intention associations with each PrEP cascade outcome, adjusting for covariates. Model 1, which predicted PrEP use, indicated that PrEP resistance intention was significantly negatively associated with PrEP use (β = − 0.29, 95% CI − 0.39 to − 0.18, p < 0.001), while social norms were positively associated (β = 0.50, 95% CI 0.36 to 0.64, p < 0.001). Model 2, predicting PrEP willingness, revealed a similar pattern: PrEP resistance intention predicted lower willingness (β = − 0.39, 95% CI − 0.54 to − 0.25, p < 0.001), and social norms predicted higher willingness (β = 0.31, 95% CI 0.14 to 0.48, p < 0.001). In model 3, transition costs were negatively associated with PrEP adherence (β = − 0.44, 95% CI − 0.64 to − 0.23, p < 0.001), and social norms were positively associated (β = 0.56, 95% CI 0.38 to 0.74, p < 0.001). PrEP resistance intention did not show a significant effect in this model.
Table 2.
Associations between status quo bias variables and PrEP cascade outcomes
| PrEP-aware sample (N = 933) | PrEP non-users (N = 591) | PrEP users (N = 431) | |
|---|---|---|---|
| Model 1: PrEP uptake β (95% CI) |
Model 2: PrEP willingness β (95% CI) |
Model 3: PrEP adherence β (95% CI) |
|
| Age (years) | − 0.01 (− 0.04, 0.01) | − 0.01 (− 0.03, 0.02) | 0.01 (− 0.02, 0.05) |
| Sexual orientation (Ref. Heterosexual) | |||
| Homosexual | − 0.23 (− 0.60, 0.13) | 0.24 (− 0.19, 0.66) | 0.26 (− 0.28, 0.80) |
| Bisexual | 1.02 (0.01, 2.04)* | − 1.02 (− 2.21, 0.17)+ | − 0.47 (− 1.87, 0.92) |
| Unsure/other | 1.07 (− 1.27, 3.42) | 0.00 (0.00, 0.00) | − 3.25 (− 6.19, − 0.31)* |
| Marriage status (Ref. Never married) | |||
| Engaged/married | − 0.81 (− 1.47, − 0.15)* | 0.10 (− 0.56, 0.77) | − 0.46 (− 1.50, 0.58) |
| Separated/divorced/widowed | − 0.34 (− 1.13, 0.45) | − 0.04 (− 0.89, 0.80) | − 0.91 (− 2.15, 0.33) |
| Highest education level (Ref. High school or below) | |||
| Bachelor’s degree | 0.46 (− 0.05, 0.96)+ | 0.03 (− 0.50, 0.56) | − 0.61 (− 1.44, 0.22) |
| Graduate degree or above | 0.52 (− 0.09, 1.14)+ | − 0.07 (− 0.74, 0.61) | − 0.44 (− 1.41, 0.52) |
| Monthly income (yuan) (Ref. ≤ 3000) | |||
| 3001–5000 | 0.54 (− 0.01, 1.09)+ | − 0.08 (− 0.68, 0.53) | − 0.25 (− 1.11, 0.61) |
| 5001–8000 | 0.33 (− 0.17, 0.83) | 0.15 (− 0.40, 0.70) | 0.18 (− 0.63, 0.99) |
| > 8000 | 0.72 (0.21, 1.23)** | − 0.11 (− 0.67, 0.46) | 0.10 (− 0.70, 0.90) |
| Number of regular male partners (Ref. 0) | |||
| 1 | 0.03 (− 0.39, 0.46) | − 0.19 (− 0.69, 0.30) | 0.02 (− 0.61, 0.66) |
| > 1 | 0.35 (− 0.12, 0.82) | − 0.05 (− 0.67, 0.57) | 0.06 (− 0.59, 0.71) |
| Number of casual male partners (Ref. 0) | |||
| 1 | 0.47 (0.11, 0.83)* | 0.03 (− 0.39, 0.45) | 0.96 (0.40, 1.51)*** |
| > 1 | 0.51 (0.11, 0.92)* | 0.24 (− 0.30, 0.79) | 0.86 (0.28, 1.44)** |
| Substance use during sexual activities (Ref. No) | |||
| Yes | 0.83 (0.49, 1.18)*** | 0.71 (0.22, 1.20)** | 0.37 (− 0.08, 0.83) |
| PrEP resistance intention | − 0.29 (− 0.39, − 0.18)*** | − 0.39 (− 0.54, − 0.25)*** | 0.07 (− 0.07, 0.22) |
| Transition costs | − 0.11 (− 0.26, 0.04) | 0.12 (− 0.07, 0.32) | − 0.44 (− 0.64, − 0.23)*** |
| Social norms | 0.50 (0.36, 0.64)*** | 0.31 (0.14, 0.48)*** | 0.56 (0.38, 0.74)*** |
| Condom-use inertia | − 0.07 (− 0.20, 0.05) | − 0.07 (− 0.23, 0.10) | − 0.00 (− 0.16, 0.16) |
Coefficients are shown with 95% confidence intervals in parentheses
PrEP pre-exposure prophylaxis
+p < 0.10, *p < 0.05, **p < 0.01, ***p < 0.001
Table 3 shows the mediation of PrEP resistance intention between status quo bias factors and PrEP outcomes. In the PrEP-aware sample, transition costs indirectly reduced PrEP use via PrEP resistance intention (β = − 0.08, 95% CI − 0.12 to − 0.04, p < 0.001), accounting for 41.8% of the total effect. Conversely, social norms indirectly increased PrEP use by lowering PrEP resistance intention (β = 0.05, 95% CI 0.02 to 0.08, p < 0.01), accounting for 11.2% of the total effect. Among PrEP non-users, transition costs indirectly reduced the willingness to use PrEP (β = − 0.05, 95% CI − 0.10 to − 0.00, p < 0.05), accounting for 58.56% of the total effect. Social norms indirectly increased willingness (β = 0.11, 95% CI 0.06 to 0.16, p < 0.001), explaining 64.26% of the total effect. However, among PrEP users, neither transition costs nor social norms showed significant indirect effects on adherence via PrEP resistance intention (p > 0.05).
Table 3.
Mediation analyses of status quo bias on PrEP cascade outcomes
| PrEP-aware sample (N = 933) | PrEP non-users (N = 591) | PrEP users (N = 431) | ||||
|---|---|---|---|---|---|---|
| Outcome: PrEP uptakea | Outcome: PrEP willingnessb | Outcome: PrEP adherencec | ||||
| β (95% CI) | Mediation (%) | β (95% CI) | Mediation (%) | β (95% CI) | Mediation (%) | |
| Transition costs → PrEP resistance intention → Outcome | ||||||
| Total effect | − 0.19 (− 0.34, − 0.05)* | 0.07 (− 0.11, 0.26) | − 0.49 (− 0.59, − 0.20)*** | |||
| Direct effect | − 0.11 (− 0.26, 0.04) | 0.13 (− 0.05, 0.32) | − 0.44 (− 0.64, − 0.23)*** | |||
| Indirect effect | − 0.08 (− 0.12, − 0.04)*** | 41.78% | − 0.05 (− 0.10, − 0.00)* | 58.56% | − 0.05 (− 0.10, − 0.00) | 0.08% |
| Social norms → PrEP resistance intention → Outcome | ||||||
| Total effect | 0.55 (0.31, 0.58)** | 0.42 (0.04, 0.35)* | 0.55 (0.41, 0.76)*** | |||
| Direct effect | 0.50 (0.36, 0.64)**** | 0.31 (0.14, 0.47)*** | 0.56 (0.38, 0.74)*** | |||
| Indirect effect | 0.05 (002, 0.08)** | 11.17% | 0.11 (0.06, 0.16)*** | 64.26% | − 0.01 (− 0.01, 0.06) | 4.46% |
All models control for demographic and behavioral covariates
PrEP pre-exposure prophylaxis, CI confidence interval
*p < 0.05, **p < 0.01, ***p < 0.001
aPseudo R2 = 0.13, Hosmer–Lemeshow (p value) = 3.95 (0.862), AIC = 1156.94, mean VIF = 1.67
bPseudo R2 = 0.08, Hosmer–Lemeshow (p value) = 12.37 (0.136), AIC = 775.39, mean VIF = 1.56
cPseudo R2 = 0.11, Hosmer–Lemeshow (p value) = NA, AIC = 1376.16, mean VIF = 2.02
Moderation and Interaction Analyses for PrEP Resistance Intentions
Figure 4 and Supplementary Material summarize the moderation and interaction analyses predicting PrEP resistance intention, adjusted for covariates. In the PrEP-aware sample (Fig. 4a; Supplementary Table 5A), high levels of condom-use inertia amplified the positive association between transition costs and PrEP resistance intention (β = 0.06, 95% CI 0.01 to 0.11, p < 0.05) and strengthened the negative association from social norms (β = − 0.05, 95% CI − 0.10 to − 0.00, p < 0.05). Conversely, high social norms attenuated the positive effect of transition costs on PrEP resistance intention (β = − 0.09, 95% CI − 0.14 to − 0.03, p < 0.01). These patterns were replicated and more pronounced among PrEP users (Fig. 4c; Supplementary Table 5C). In this group, high condom-use inertia similarly amplified the effect of transition costs (β = 0.18, 95% CI 0.10 to 0.25, p < 0.05) and strengthened the effect of social norms (β = − 0.14, 95% CI − 0.21 to − 0.08, p < 0.05), while high social norms also showed a more substantial attenuating effect on the cost–resistance relationship (β = − 0.18, 95% CI − 0.26 to − 0.10, p < 0.05). However, no moderation or interaction associations reached significance in the PrEP non-user sample (Fig. 4b; Supplementary Table 5B).
Fig. 4.
Moderation and interaction analyses of PrEP resistance intentions. PrEP pre-exposure prophylaxis
Integrated Path Diagrams of Status Quo Bias Across the PrEP Cascade
Figure 5 summarizes the results of the sequential analyses by visually integrating the key pathways from the mediation analyses and the moderation analyses for each of the three samples. In the PrEP-aware sample (Fig. 5a), transition costs and social norms each had significant indirect associations with PrEP use, which were mediated by PrEP resistance intention. Additionally, condom-use inertia significantly moderated both transition cost–PrEP resistance intention and social norms–PrEP resistance intention pathways. Among PrEP non-users (Fig. 5b), while transition costs had no direct effect on willingness, they indirectly reduced willingness through PrEP resistance intention. Social norms had a direct positive effect on PrEP willingness and an indirect positive effect by reducing PrEP resistance intention. A fundamental shift in mechanism was observed among PrEP users (Fig. 5c). In this group, PrEP resistance intention no longer mediated either factor. Instead, transition costs and social norms showed strong direct associations with PrEP adherence.
Fig. 5.
Integrated path diagrams of status quo bias mechanisms across the PrEP cascade. The figure summarizes the final results of the moderated mediation analyses for each stage: a The PrEP-aware sample (N = 933), showing the moderated pathways for PrEP uptake; b The PrEP non-user sample (N = 591), showing the moderated pathways for PrEP willingness; and c The PrEP user sample (N = 431), showing the moderated pathways for PrEP adherence. Note: Coefficients are standardized betas. *p < 0.05, **p < 0.01, ***p < 0.001. PrEP pre-exposure prophylaxis
Discussion
This study provides a theory-driven explanation for the “PrEP Cliff,” a persistent clinical and public health failure, from a behavioral economics perspective. We move beyond simply listing barriers to deconstruct the underlying psychological mechanisms that impede the therapeutic effectiveness of PrEP. Our key finding is that these mechanisms are stage-dependent; the cognitive barriers to initiating PrEP are different from those driving long-term adherence. This study provides a crucial evidence-based framework, demonstrating that public health practice should adopt stage-specific interventions to improve PrEP’s real-world impact.
Our most significant practice-oriented implication is that the mechanisms underlying status quo bias are stage-dependent within the PrEP care continuum. This echoes the distinction in implementation frameworks such as RE-AIM between “Adoption” and “Maintenance” [35]. We found the initiation phase is an internal, psychological struggle, where costs and norms operate indirectly via resistance intention. In contrast, in the maintenance phase, this psychological resistance dissipates, and PrEP adherence is determined directly by experienced treatment burdens and the availability of normative or social support. This finding directly challenges prior research that treats barriers in aggregate [1, 36]. It offers actionable guidance for designing therapeutic and service-delivery interventions: initiation strategies must target cognitive resistance to starting PrEP, while adherence strategies must focus on reducing ongoing treatment burdens and strengthening external facilitation.
Our findings provide a critical insight for public health practice by deconstructing how status quo bias influences resistance intentions toward PrEP engagement. While prior work confirms that costs and norms are barriers [32, 37, 38], our model further elucidates the underlying cognitive mechanism. Among PrEP non-users, our results suggest that transition costs, including financial burdens, time, and side effects, primarily suppress willingness and uptake by amplifying resistance intentions, which serve as a critical mediating barrier to adoption [39]. For existing PrEP users, however, transition costs exert a direct inhibitory association with adherence. This finding has immediate clinical relevance, suggesting strategies must target the psychological resistance and practical burdens driven by transition costs. Future intervention design should employ co-design methods, such as crowdsourcing or nudgeathons [40–42], to translate these specific cognitive insights into impactful public health practices.
Our findings on interaction and moderation offer specific levers for intervention design. We demonstrate that stronger social norms could buffer the negative impact of transition costs, providing a clear rationale for clinical programs to integrate community-building and peer-support elements. Furthermore, this study operationalizes condom-use inertia as a key moderator in PrEP engagement, which we found magnifies perceived barriers. This has direct translational implications, suggesting that clinicians cannot simply inform patients of the benefits of PrEP. Interventions must actively disrupt the powerful, ingrained habit of condom use by positioning PrEP use as a compatible HIV prevention strategy. This challenges purely rational models of PrEP choice [43], underscoring the need for behaviorally informed strategies.
Several limitations warrant consideration for our study. First, the cross-sectional design precludes causal inference; the observed pathways require confirmation through longitudinal studies. Second, reliance on self-reported data introduces potential social desirability and recall biases. Third, our sample comprises well-educated Chinese MSM, limiting generalizability to other cultural contexts or key populations. Fourth, our model may underemphasize the role of structural determinants, such as healthcare system accessibility, regional policy variations, or economic precarity, that may interact with the cognitive biases we identified. Future research could benefit from integrating our status quo bias model with frameworks that explicitly account for these structural barriers, such as those focused on the Social Determinants of Health (SDOH), thereby providing a more comprehensive understanding of the “PrEP Cliff”.
Conclusion
This study deconstructs the “PrEP Cliff” phenomenon, characterized by significant drop-offs in willingness, uptake, and adherence among Chinese MSM, by integrating status quo bias theory with a dual-process model. Our findings reveal that the impact of status quo bias on the PrEP cascade and its underlying mechanisms is stage-dependent. By demonstrating the stage-dependent nature of this status quo bias’s impact on the PrEP cascade, this study provides clear theoretical guidance and a crucial evidence base for public health practice. To effectively bridge the know–do gap, PrEP implementation strategies must adopt theory-informed, stage-specific interventions tailored to the distinct mechanisms that dominate each phase.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
We thank the participants of the study. We would also like to express our sincere gratitude to the Social Entrepreneurship for Sexual Health (SESH) team for their invaluable efforts in data collection for this study.
Author Contributions
Min Zhao, Weiming Tang, and Lei Zhang were responsible for the study conception and design. Min Zhao and Xiang Zhao designed the methodology. Min Zhao, Xiang Zhao, and Fanpu Ji conducted the validation. Zhuoheng Yin was responsible for the investigation. Zhuoheng Yin and Weiming Tang carried out data curation. Min Zhao performed the formal analysis. Min Zhao wrote the original draft of the manuscript. Xiang Zhao, Ye Zhang, Zhuoheng Yin, Fanpu Ji, Jason J. Ong, Weiming Tang, and Lei Zhang reviewed and revised the manuscript. Weiming Tang managed the project administration. Lei Zhang supervised the writing and secured the funding. All authors have read and approved the final manuscript.
Funding
This work was supported by the Ministry of Education of the People’s Republic of China Project of Humanities and Social Sciences (grant number 24YJC840051), and the Natural Science Foundation of Shaanxi Province (grant number 2025JC-YBQN-1106), the Ministry of Science and Technology of the People’s Republic of China (grant numbers 2022YFC2304900, 2022YFC2304905), the National Key Research and Development Programme of China (grant numbers 2022YFC2505100, 2022YFC2505103). The journal’s Rapid Service Fee was funded by the Second Affiliated Hospital of Xi’an Jiaotong University.
Data Availability
Due to the sensitive and privacy-related nature of the data, the datasets generated and analyzed during the current study are securely stored by the Social Entrepreneurship for Sexual Health (SESH) team. Reasonable requests for access to the de-identified data will be considered and can be directed to the corresponding author.
Declarations
Conflict of Interest
Min Zhao, Xiang Zhao, Ye Zhang, Zhuoheng Yin, Fanpu Ji, Jason J. Ong, Weiming Tang, and Lei Zhang declare that they have no competing interests.
Ethical Approval
This study was performed in accordance with the Helsinki Declaration of 1964 and its later amendments. The study protocol was approved by the Institutional Review Board (IRB) of Shenzhen University [PN-202400070]. All participants provided informed consent for their anonymized data to be used for research purposes and publication.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Due to the sensitive and privacy-related nature of the data, the datasets generated and analyzed during the current study are securely stored by the Social Entrepreneurship for Sexual Health (SESH) team. Reasonable requests for access to the de-identified data will be considered and can be directed to the corresponding author.