Spiraling Risk: Visualizing the multilevel factors that socially pattern HIV risk among gay, bisexual & other men who have sex with men using Complex Systems Theory

PURPOSE OF REVIEW

Global disparities in HIV infection, particularly among gay, bisexual, and other men who have sex with men (GBMSM), indicate the importance of exploring the multi-level processes that shape HIV's spread. We used Complex Systems Theory and the PRISMA guidelines to conduct a systematic review of 63 global reviews to understand how HIV is socially patterned among GBMSM. The purpose was to conduct a thematic analysis of the reviews to (1) synthesize the multi-level risk factors of HIV risk, (2) categorize risk across the socioecological model, and (3) develop a conceptual model that visualizes the interrelated factors that shape GBMSMS's HIV "risk."

RECENT FINDINGS

We included 49 studies of high and moderate quality studies. Results indicated that GBMSM's HIV risk stems from the individual, interpersonal, and structural levels of the socioecological model. We identified a few themes that shape GBMSM's risk of HIV infection related to biomedical prevention methods; sexual and sex-seeking behaviors; behavioral prevention methods; individual-level characteristics and syndemic infections; lived experiences and interpersonal relationships; country-level income; country-level HIV prevalence; and structural stigma. The multi-level factors, in tandem, serve to perpetuate GBMSM's risk of HIV infection globally. The amalgamation of our thematic analyses from our systematic reviews of reviews suggests that the risk of HIV infection operates in an emergent, dynamic, and complex nature across multiple levels of the socioecological model. Applying complex systems theory indicates how multilevel factors create a dynamic and reinforcing system of HIV risk among GBMSM.

Mitigating the impact of air pollution on dementia and brain health: Setting the policy agenda

BACKGROUND

Emerging research suggests exposure to high levels of air pollution at critical points in the life-course is detrimental to brain health, including cognitive decline and dementia. Social determinants play a significant role, including socio-economic deprivation, environmental factors and heightened health and social inequalities. Policies have been proposed more generally, but their benefits for brain health have yet to be fully explored.

OBJECTIVE AND METHODS

Over the course of two years, we worked as a consortium of 20+ academics in a participatory and consensus method to develop the first policy agenda for mitigating air pollution's impact on brain health and dementia, including an umbrella review and engaging 11 stakeholder organisations.

RESULTS

We identified three policy domains and 14 priority areas. Research and Funding included: (1) embracing a complexities of place approach that (2) highlights vulnerable populations; (3) details the impact of ambient PM_2.5 on brain health, including current and historical high-resolution exposure models; (4) emphasises the importance of indoor air pollution; (5) catalogues the multiple pathways to disease for brain health and dementia, including those most at risk; (6) embraces a life course perspective; and (7) radically rethinks funding. Education and Awareness included: (8) making this unrecognised public health issue known; (9) developing educational products; (10) attaching air pollution and brain health to existing strategies and campaigns; and (11) providing publicly available monitoring, assessment and screening tools. Policy Evaluation included: (12) conducting complex systems evaluation; (13) engaging in co-production; and (14) evaluating air quality policies for their brain health benefits.

CONCLUSION

Given the pressing issues of brain health, dementia and air pollution, setting a policy agenda is crucial. Policy needs to be matched by scientific evidence and appropriate guidelines, including bespoke strategies to optimise impact and mitigate unintended consequences. The agenda provided here is the first step toward such a plan.

Understanding human encounters goes beyond explaining musculoskeletal coordination: a review

Complex systems theory has become one of the main frameworks to understand, model and explain interactional phenomena such as interpersonal coordination. In her paper, Butler (this issue) applies this approach to theorise about coordination at large, including human interactions. We argue that the all-encompassing language of complex systems theory leads to overemphasising the physical aspects that human interactions share with other coordinated systems in nature. This emphasis ultimately disregards the meaningful dimension implied in any human movement, understanding it as mechanical motion, rather than expressive actions.

Imperfect or perfect attempts at closing COVID -19 policy and planning emergent gaps

The COVID-19 pandemic has presented a new wave of health, infrastructure and built environment challenges and opportunities. The COVID-19 pandemic induced environment presents a divide between the "new and old normal" with policy and planning implications for health, transport and general socio-economic growth and development. Multiple and complex nuanced transport matters cascade all geographic scales and pervade all sectors of the economy. The extent to which existing transport systems capacities are resilient, adaptive, and optimized for complete disaster planning, management and sustainability is questioned. This paper critically reviews how the COVID-19 pandemic has stretched the resilience and adaptive transport systems capacities in South Africa. A critical question interrogated is whether on-going policy and planning interventions constitute imperfect or perfect attempts at closing COVID -19 policy and planning emergent gaps. The paper makes use of South Africa as a case study, referencing the Disaster Management Act (No. 57 of 2002) and logical Disaster Management Act: Regulations relating to COVID-19 (Government Notice 318 of 2020), with specific reference to the transport sector lockdown regulations in unravelling policy and planning implications. Drawing from the complex systems adaptive theory (CSAT), sustainability theory (ST), innovation theory (IT), transitions theory (TT), thematic COVID -19 transport planning and policy adaptation, mitigation measures in the South African transportation sector are discussed. Emergent lessons with respect to developing and advancing a new generation of resilient, adaptive, and optimized transport proof infrastructure and services including revising transport and related policies that navigates through various waves and cycles of induced pandemic and shocks is suggested.

A complex systems approach to the study of change in psychotherapy

BACKGROUND

A growing body of research highlights the limitations of traditional methods for studying the process of change in psychotherapy. The science of complex systems offers a useful paradigm for studying patterns of psychopathology and the development of more functional patterns in psychotherapy. Some basic principles of change are presented from subdisciplines of complexity science that are particularly relevant to psychotherapy: dynamical systems theory, synergetics, and network theory. Two early warning signs of system transition that have been identified across sciences (critical fluctuations and critical slowing) are also described. The network destabilization and transition (NDT) model of therapeutic change is presented as a conceptual framework to import these principles to psychotherapy research and to suggest future research directions.

DISCUSSION

A complex systems approach has a number of implications for psychotherapy research. We describe important design considerations, targets for research, and analytic tools that can be used to conduct this type of research.

CONCLUSIONS

A complex systems approach to psychotherapy research is both viable and necessary to more fully capture the dynamics of human change processes. Research to date suggests that the process of change in psychotherapy can be nonlinear and that periods of increased variability and critical slowing might be early warning signals of transition in psychotherapy, as they are in other systems in nature. Psychotherapy research has been limited by small samples and infrequent assessment, but ambulatory and electronic methods now allow researchers to more fully realize the potential of concepts and methods from complexity science.

Measuring resilience prospectively as the speed of affect recovery in daily life: a complex systems perspective on mental health

INTRODUCTION

There is growing evidence that mental disorders behave like complex dynamic systems. Complex dynamic systems theory states that a slower recovery from small perturbations indicates a loss of resilience of a system. This study is the first to test whether the speed of recovery of affect states from small daily life perturbations predicts changes in psychopathological symptoms over 1 year in a group of adolescents at increased risk for mental disorders.

METHODS

We used data from 157 adolescents from the TWINSSCAN study. Course of psychopathology was operationalized as the 1-year change in the Symptom Checklist-90 sum score. Two groups were defined: one with stable and one with increasing symptom levels. Time-series data on momentary daily affect and daily unpleasant events were collected 10 times a day for 6 days at baseline. We modeled the time-lagged effect of daily unpleasant events on negative and positive affect after each unpleasant event experienced, to examine at which time point the impact of the events is no longer detectable.

RESULTS

There was a significant difference between groups in the effect of unpleasant events on negative affect 90 min after the events were reported. Stratified by group, in the Increase group, the effect of unpleasant events on both negative (B = 0.05, p < 0.01) and positive affect (B = - 0. 08, p < 0.01) was still detectable 90 min after the events, whereas in the Stable group this was not the case.

CONCLUSION

Findings cautiously suggest that adolescents who develop more symptoms in the following year may display a slower affect recovery from daily perturbations at baseline. This supports the notion that mental health may behave according to the laws of a complex dynamic system. Future research needs to examine whether these dynamic indicators of system resilience may prove valuable for personalized risk assessment in this field.

Dynamic ecological system analysis: A holistic analysis of compartmental systems

This article develops a new mathematical method for holistic analysis of nonlinear dynamic compartmental systems in the context of ecology. The method is based on the novel dynamic system and subsystem partitioning methodologies through which compartmental systems are decomposed to the utmost level. The dynamic system and subsystem partitioning enable tracking the evolution of the initial stocks, environmental inputs, and intercompartmental system flows, as well as the associated storages derived from these stocks, inputs, and flows individually and separately within the system. Moreover, the transient and the dynamic direct, indirect, acyclic, cycling, and transfer (diact) flows and associated storages transmitted along a given flow path or from one compartment, directly or indirectly, to any other are analytically characterized, systematically classified, and mathematically formulated. Further, the article develops a dynamic technique based on the diact transactions for the quantitative classification of interspecific interactions and the determination of their strength within food webs. Major concepts and quantities of the current static network analyses are also extended to nonlinear dynamic settings and integrated with the proposed dynamic measures and indices within the proposed unifying mathematical framework. Therefore, the proposed methodology enables a holistic view and analysis of ecological systems. We consider that this methodology brings a novel complex system theory to the service of urgent and challenging environmental problems of the day and has the potential to lead the way to a more formalistic ecological science.

Research topics and trends in medical education by social network analysis

BACKGROUND

As studies analyzing the networks and relational structures of research topics in academic fields emerge, studies that apply methods of network and relationship analysis, such as social network analysis (SNA), are drawing more attention. The purpose of this study is to explore the interaction of medical education subjects in the framework of complex systems theory using SNA and to analyze the trends in medical education.

METHODS

The authors extracted keywords using Medical Subject Headings terms from 9,379 research articles (162,866 keywords) published in 1963-2015 in PubMed. They generated an occurrence frequency matrix, calculated relatedness using Weighted Jaccard Similarity, and analyzed and visualized the networks with Gephi software.

RESULTS

Newly emerging topics by period units were identified as historical trends, and 20 global-level topic clusters were obtained through network analysis. A time-series analysis led to the definition of five historical periods: the waking phase (1963-1975), the birth phase (1976-1990), the growth phase (1991-1996), the maturity phase (1997-2005), and the expansion phase (2006-2015).

CONCLUSIONS

The study analyzed the trends in medical education research using SNA and analyzed their meaning using complex systems theory. During the 53-year period studied, medical education research has been subdivided and has expanded, improved, and changed along with shifts in society's needs. By analyzing the trends in medical education using the conceptual framework of complex systems theory, the research team determined that medical education is forming a sense of the voluntary order within the field of medicine by interacting with social studies, philosophy, etc., and establishing legitimacy and originality.