Risk, individual differences, and environment: an Agent-Based Modeling approach to sexual risk-taking

The Dual Control Model of Sexual Response: A Scoping Review, 2009-2022

The Dual Control Model proposes that sexual arousal and related processes are dependent on the balance between sexual excitation and sexual inhibition, and that individuals vary in their propensity for these processes. This scoping review provides an overview and discussion of the questionnaires used to measure the propensities for sexual excitation and inhibition, their translation and validation in other languages, and their application in empirical research on topics ranging from sexual desire and arousal, sexual (dys)function, sexual risk taking, asexuality, hypersexuality, and sexual aggression. A total of 152 papers, published between 2009 and 2022 and identified using online databases, were included in this review. The findings, consistent with those reviewed by Bancroft et al. (2009), suggest that sexual excitation is particularly relevant to sexual desire and responsivity and predictive of asexuality and hypersexuality. Sexual inhibition plays a role in sexual dysfunction. sexual risk taking, and sexual aggression, although often in interaction with sexual excitation. Suggestions for the further development of the model and for future studies are discussed.

Motivations and Experiences Related to Women's First Same-sex Sexual Encounters

Using women's self-identified sexual identity, the current study compares motivations for first same-sex sexual encounters as well as associated experiential outcomes. We also examine whether relations between sexual motivations and experiential outcomes differ as a function of women's sexual identity status. Participants were women (N=123), ages 18-to-29 (M=21.59, SD=3.33), who self-reported a history of same-sex sexual contact. Approximately 27% of women identified as exclusively heterosexual (i.e., EH), 35% as primarily heterosexual (i.e., 'mostly heterosexual' [MH]), and 38% as exclusively or primarily lesbian/ gay, or bisexual (i.e., LGB). Participants completed an online survey. MH and LGB women reported first same-sex sexual encounters that were more motivated by intimacy and exploration motives, relative to EH women. Compared to MH and LGB women, EH also engaged in fewer sexual activities with their first same-sex partner. Intimacy and exploration motives were related to positive experiential outcomes during first same-sex contact. Associations between motivations and experiential outcomes were not moderated by sexual identity. Findings contribute to understanding motivations and experiences related to women's first same-sex sexual encounters and show that not all women with a history of same-sex sexual contact subsequently identify with a minority sexual identity label.

Enhancing dissemination and implementation research using systems science methods

BACKGROUND

Dissemination and implementation (D&I) research seeks to understand and overcome barriers to adoption of behavioral interventions that address complex problems, specifically interventions that arise from multiple interacting influences crossing socio-ecological levels. It is often difficult for research to accurately represent and address the complexities of the real world, and traditional methodological approaches are generally inadequate for this task. Systems science methods, expressly designed to study complex systems, can be effectively employed for an improved understanding about dissemination and implementation of evidence-based interventions.

PURPOSE

The aims of this study were to understand the complex factors influencing successful D&I of programs in community settings and to identify D&I challenges imposed by system complexity.

METHOD

Case examples of three systems science methods-system dynamics modeling, agent-based modeling, and network analysis-are used to illustrate how each method can be used to address D&I challenges.

RESULTS

The case studies feature relevant behavioral topical areas: chronic disease prevention, community violence prevention, and educational intervention. To emphasize consistency with D&I priorities, the discussion of the value of each method is framed around the elements of the established Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework.

CONCLUSION

Systems science methods can help researchers, public health decision makers, and program implementers to understand the complex factors influencing successful D&I of programs in community settings and to identify D&I challenges imposed by system complexity.

Late positive potential to explicit sexual images associated with the number of sexual intercourse partners

Risky sexual behaviors typically occur when a person is sexually motivated by potent, sexual reward cues. Yet, individual differences in sensitivity to sexual cues have not been examined with respect to sexual risk behaviors. A greater responsiveness to sexual cues might provide greater motivation for a person to act sexually; a lower responsiveness to sexual cues might lead a person to seek more intense, novel, possibly risky, sexual acts. In this study, event-related potentials were recorded in 64 men and women while they viewed a series of emotional, including explicit sexual, photographs. The motivational salience of the sexual cues was varied by including more and less explicit sexual images. Indeed, the more explicit sexual stimuli resulted in enhanced late positive potentials (LPP) relative to the less explicit sexual images. Participants with fewer sexual intercourse partners in the last year had reduced LPP amplitude to the less explicit sexual images than the more explicit sexual images, whereas participants with more partners responded similarly to the more and less explicit sexual images. This pattern of results is consistent with a greater responsivity model. Those who engage in more sexual behaviors consistent with risk are also more responsive to less explicit sexual cues.

Investigating biocomplexity through the agent-based paradigm

Capturing the dynamism that pervades biological systems requires a computational approach that can accommodate both the continuous features of the system environment as well as the flexible and heterogeneous nature of component interactions. This presents a serious challenge for the more traditional mathematical approaches that assume component homogeneity to relate system observables using mathematical equations. While the homogeneity condition does not lead to loss of accuracy while simulating various continua, it fails to offer detailed solutions when applied to systems with dynamically interacting heterogeneous components. As the functionality and architecture of most biological systems is a product of multi-faceted individual interactions at the sub-system level, continuum models rarely offer much beyond qualitative similarity. Agent-based modelling is a class of algorithmic computational approaches that rely on interactions between Turing-complete finite-state machines--or agents--to simulate, from the bottom-up, macroscopic properties of a system. In recognizing the heterogeneity condition, they offer suitable ontologies to the system components being modelled, thereby succeeding where their continuum counterparts tend to struggle. Furthermore, being inherently hierarchical, they are quite amenable to coupling with other computational paradigms. The integration of any agent-based framework with continuum models is arguably the most elegant and precise way of representing biological systems. Although in its nascence, agent-based modelling has been utilized to model biological complexity across a broad range of biological scales (from cells to societies). In this article, we explore the reasons that make agent-based modelling the most precise approach to model biological systems that tend to be non-linear and complex.

A complex systems approach to evaluate HIV prevention in metropolitan areas: preliminary implications for combination intervention strategies

BACKGROUND

HIV transmission among injecting and non-injecting drug users (IDU, NIDU) is a significant public health problem. Continuing propagation in endemic settings and emerging regional outbreaks have indicated the need for comprehensive and coordinated HIV prevention. We describe the development of a conceptual framework and calibration of an agent-based model (ABM) to examine how combinations of interventions may reduce and potentially eliminate HIV transmission among drug-using populations.

METHODOLOGY/PRINCIPAL FINDINGS

A multidisciplinary team of researchers from epidemiology, sociology, geography, and mathematics developed a conceptual framework based on prior ethnographic and epidemiologic research. An ABM was constructed and calibrated through an iterative design and verification process. In the model, "agents" represent IDU, NIDU, and non-drug users who interact with each other and within risk networks, engaging in sexual and, for IDUs, injection-related risk behavior over time. Agents also interact with simulated HIV prevention interventions (e.g., syringe exchange programs, substance abuse treatment, HIV testing) and initiate antiretroviral treatment (ART) in a stochastic manner. The model was constructed to represent the New York metropolitan statistical area (MSA) population, and calibrated by comparing output trajectories for various outcomes (e.g., IDU/NIDU prevalence, HIV prevalence and incidence) against previously validated MSA-level data. The model closely approximated HIV trajectories in IDU and NIDU observed in New York City between 1992 and 2002, including a linear decrease in HIV prevalence among IDUs. Exploratory results are consistent with empirical studies demonstrating that the effectiveness of a combination of interventions, including syringe exchange expansion and ART provision, dramatically reduced HIV prevalence among IDUs during this time period.

CONCLUSIONS/SIGNIFICANCE

Complex systems models of adaptive HIV transmission dynamics can be used to identify potential collective benefits of hypothetical combination prevention interventions. Future work will seek to inform novel strategies that may lead to more effective and equitable HIV prevention strategies for drug-using populations.