The choice of message and messenger to drive behavior change that averts the health impacts of wildfires: an online randomized controlled experiment.

BACKGROUND: To reduce the negative health effects from wildfire smoke exposure, effective risk and health communication strategies are vital. We estimated the behavioral effects from changes in message framing and messenger in public health messages about wildfire smoke on Facebook. METHODS: During September and October 2021, we conducted a preregistered online randomized controlled experiment in Facebook. Adult Facebook users (n = 1,838,100), living in nine wildfire-prone Western U.S. states, were randomly assigned to see one of two ad versions (narrative frame vs. informational frame) from one of two messengers (government vs. academic). We estimated the effects of narrative framing, the messenger, and their interactions on ad click-through rates, a measure of recipient information-seeking behavior. RESULTS: Narrative frame increased click-through rates by 25.3% (95% CI = 22.2, 28.4%), with larger estimated effects among males, recipients in areas with less frequent exposure to heavy wildfire smoke, and in areas where predominant political party affiliation of registered voters was Republican (although not statistically different from predominantly-Democrat areas). The estimated effect from an academic messenger compared to a government messenger was small and statistically nonsignificant (2.2%; 95% CI = - 0.3, 4.7%). The estimated interaction effect between the narrative framing and the academic messenger was also small and statistically nonsignificant (3.9%; 95% CI = - 1.1, 9.1%). CONCLUSIONS: Traditional public service announcements rely heavily on communicating facts (informational framing). Shifting from a fact-focused, informational framing to a story-focused, narrative framing could lead to more effective health communication in areas at risk of wildfires and in public health contexts more broadly. TRIAL REGISTRATION: Date registered: August 19, 2021; Registration DOI: https://doi.org/10.17605/OSF.IO/JMWUF.

Can Common Pool Resource Theory Catalyze Stakeholder-Driven Solutions to the Freshwater Salinization Syndrome?

Freshwater salinity is rising across many regions of the United States as well as globally, a phenomenon called the freshwater salinization syndrome (FSS). The FSS mobilizes organic carbon, nutrients, heavy metals, and other contaminants sequestered in soils and freshwater sediments, alters the structures and functions of soils, streams, and riparian ecosystems, threatens drinking water supplies, and undermines progress toward many of the United Nations Sustainable Development Goals. There is an urgent need to leverage the current understanding of salinization's causes and consequences─in partnership with engineers, social scientists, policymakers, and other stakeholders─into locally tailored approaches for balancing our nation's salt budget. In this feature, we propose that the FSS can be understood as a common pool resource problem and explore Nobel Laureate Elinor Ostrom's social-ecological systems framework as an approach for identifying the conditions under which local actors may work collectively to manage the FSS in the absence of top-down regulatory controls. We adopt as a case study rising sodium concentrations in the Occoquan Reservoir, a critical water supply for up to one million residents in Northern Virginia (USA), to illustrate emerging impacts, underlying causes, possible solutions, and critical research needs.

The effects of social rank and payoff structure on the evolution of group hunting.

Group hunting is common among social carnivores, and mechanisms that promote this behavior are a central topic in evolutionary biology. Increased prey capture success and decreased losses from competitors are often invoked as factors promoting group hunting. However, many animal societies have linear dominance hierarchies where access to critical resources is determined by social rank, and group-hunting rewards are shared unequally. Despite this inequality, animals in such societies cooperate to hunt and defend resources. Game theoretic models predict that rank and relative rewards from group hunting vs. solitary hunting affect which hunting strategies will evolve. These predictions are partially supported by empirical work, but data needed to test these predictions are difficult to obtain in natural systems. We use digital evolution to test how social rank and tolerance by dominants of subordinates feeding while sharing spoils from group hunting influence which hunting strategies evolve in digital organisms. We created a computer-simulated world to reflect social and hunting dynamics of spotted hyenas (Crocuta crocuta). We found that group hunting increased as tolerance increased and as the relative payoff from group hunting increased. Also, top-ranking agents were more likely to group hunt than lower-ranking agents under despotic sharing conditions. These results provide insights into mechanisms that may promote cooperation in animal societies structured by dominance hierarchies.

Natural hazards compound COVID-19 impacts on small businesses disproportionately for historically underrepresented group operators.

In the wake of the COVID-19 pandemic small businesses made headlines as hard hit by customer losses, revenue declines, and business closures. Yet, the impacts have been felt disproportionately by small businesses that suffered interruption due to pre-existing socioeconomic stressors and/or concurrent natural hazards experienced during the pandemic. To illuminate those compound impacts, we conducted a survey of over 1350 U S.-based small businesses. Our findings indicate that those businesses that experienced concurrent natural hazards during the pandemic were associated with relatively greater negative impacts. But importantly, enterprises that are historically underrepresented group operated (HUGO)-minority, women, and veteran-operated businesses- saw largely amplified negative impacts from COVID-19. In terms of the magnitude of COVID-19 impacts, the effect size of belonging to HUGO was more than twice as large as the effect size of experiencing a concurrent natural hazard during the pandemic. These results provide evidence for the disproportionate impacts that HUGOs face due to the pandemic, which are exacerbated when compounded by natural hazards. Given these results, there is evidence that the opportunity gap between HUGO and non-HUGO businesses is significant ahead of additional stressors or shocks. This opportunity gap is further accelerated when compounded with other events, here the compounding of natural hazards and COVID-19. Additional interventions need to be offered to HUGO businesses in areas with high likelihood of overlapping incidents. Further work is required to address social inequity and economic fragility of HUGO businesses, especially those that face the complexity of additional shocks, such as natural hazards.

Do social identity and cognitive diversity correlate in environmental stakeholders? A novel approach to measuring cognitive distance within and between groups.

Groups with higher cognitive diversity, i.e. variations in how people think and solve problems, are thought to contribute to improved performance in complex problem-solving. However, embracing or even engineering adequate cognitive diversity is not straightforward and may even jeopardize social inclusion. In response, those that want to promote cognitive diversity might make a simplified assumption that there exists a link between identity diversity, i.e. range of social characteristics, and variations in how people perceive and solve problems. If this assumption holds true, incorporating diverse identities may concurrently achieve cognitive diversity to the extent essential for complex problem-solving, while social inclusion is explicitly acknowledged. However, currently there is a lack of empirical evidence to support this hypothesis in the context of complex social-ecological systems-a system wherein human and environmental dimensions are interdependent, where common-pool resources are used or managed by multiple types of stakeholders. Using a fisheries example, we examine the relationship between resource stakeholders' identities and their cognitive diversity. We used cognitive mapping techniques in conjunction with network analysis to measure cognitive distances within and between stakeholders of various social types (i.e., identities). Our results empirically show that groups with higher identity diversity also demonstrate more cognitive diversity, evidenced by disparate characteristics of their cognitive maps that represent their understanding of fishery dynamics. These findings have important implications for sustainable management of common-pool resources, where the inclusion of diverse stakeholders is routine, while our study shows it may also achieve higher cognitive coverage that can potentially lead to more complete, accurate, and innovative understanding of complex resource dynamics.

The diversity bonus in pooling local knowledge about complex problems.

Recently, theoreticians have hypothesized that diverse groups, as opposed to groups that are homogeneous, may have relative merits [S. E. Page, The Diversity Bonus (2019)]-all of which lead to more success in solving complex problems. As such, understanding complex, intertwined environmental and social issues may benefit from the integration of diverse types of local expertise. However, efforts to support this hypothesis have been frequently made through laboratory-based or computational experiments, and it is unclear whether these discoveries generalize to real-world complexities. To bridge this divide, we combine an Internet-based knowledge elicitation technique with theoretical principles of collective intelligence to design an experiment with local stakeholders. Using a case of striped bass fisheries in Massachusetts, we pool the local knowledge of resource stakeholders represented by graphical cognitive maps to produce a causal model of complex social-ecological interdependencies associated with fisheries ecosystems. Blinded reviews from a scientific expert panel revealed that the models of diverse groups outranked those from homogeneous groups. Evaluation via stochastic network analysis also indicated that a diverse group more adequately modeled complex feedbacks and interdependencies than homogeneous groups. We then used our data to run Monte Carlo experiments wherein the distributions of stakeholder-driven cognitive maps were randomly reproduced and virtual groups were generated. Random experiments also predicted that knowledge diversity improves group success, which was measured by benchmarking group models against an ecosystem-based fishery management model. We also highlight that diversity must be moderated through a proper aggregation process, leading to more complex yet parsimonious models.

Building a Collaborative Model of Sacroiliac Joint Dysfunction and Pelvic Girdle Pain to Understand the Diverse Perspectives of Experts.

BACKGROUND: Pelvic girdle pain (PGP) and sacroiliac joint (SIJ) dysfunction/pain are considered frequent contributors to low back pain (LBP). Like other persistent pain conditions, PGP is increasingly recognized as a multifactorial problem involving biological, psychological, and social factors. Perspectives differ between experts and a diversity of treatments (with variable degrees of evidence) have been utilized. OBJECTIVE: To develop a collaborative model of PGP that represents the collective view of a group of experts. Specific goals were to analyze structure and composition of conceptual models contributed by participants, to aggregate them into a metamodel, to analyze the metamodel's composition, and to consider predicted efficacy of treatments. DESIGN: To develop a collaborative model of PGP, models were generated by invited individuals to represent their understanding of PGP using fuzzy cognitive mapping (FCM). FCMs involved proposal of components related to causes, outcomes, and treatments for pain, disability, and quality of life, and their connections. Components were classified into thematic categories. Weighting of connections was summed for components to judge their relative importance. FCMs were aggregated into a metamodel for analysis of the collective opinion it represented and to evaluate expected efficacy of treatments. RESULTS: From 21 potential contributors, 14 (67%) agreed to participate (representing six disciplines and seven countries). Participants' models included a mean (SD) of 22 (5) components each. FCMs were refined to combine similar terms, leaving 89 components in 10 categories. Biomechanical factors were the most important in individual FCMs. The collective opinion from the metamodel predicted greatest efficacy for injection, exercise therapy, and surgery for pain relief. CONCLUSIONS: The collaborative model of PGP showed a bias toward biomechanical factors. Most efficacious treatments predicted by the model have modest to no evidence from clinical trials, suggesting a mismatch between opinion and evidence. The model enables integration and communication of the collection of opinions on PGP.

Development of a collaborative model of low back pain: report from the 2017 NASS consensus meeting.

BACKGROUND CONTEXT: Low back pain (LBP) is a multifactorial problem with complex interactions among many biological, psychological and social factors. It is difficult to fully appreciate this complexity because the knowledge necessary to do so is distributed over many areas of expertise that span the biopsychosocial domains. PURPOSE: This study describes the collaborative modeling process, undertaken among a group of participants with diverse expertise in LBP, to build a model to enhance understanding and communicate the complexity of the LBP problem. STUDY DESIGN: The study involved generating individual models that represented participants' understanding of the LBP problem using fuzzy cognitive mapping (FCM), and 4 subsequent phases of consultation and consensus with the participants to characterize and refine the interpretation of the FCMs. METHODS: The phases consisted of: proposal of Categories for clustering of model Components; preliminary evaluation of structure, composition and focal areas of participant's FCMs; refinement of Categories and Components with consensus meeting; generation of final structure and composition of individual participant's FCMs. Descriptive statistics were applied to the structural and composition metrics of individual FCMs to aid interpretation. RESULTS: From 38 invited contributors, 29 (76%) agreed to participate. They represented 9 disciplines and 8 countries. Participants' models included 729 Components, with an average of 25 (SD = 7) per model. After the final FCM refinement process (Components from separate FCMs that used similar terms were combined, and Components from an FCM that included multiple terms were separated), there were 147 Components allocated to ten Categories. Although individual models varied in their structure and composition, a common opinion emerged that psychological factors are particularly important in the presentation of LBP. Collectively, Components allocated to the "Psychology" Category were the most central in almost half (14/29) of the individual models. CONCLUSIONS: The collaborative modeling process outlined in this paper provides a foundation upon which to build a greater understanding and to communicate the complexity of the LBP problem. The next step is to aggregate individual FCMs into a metamodel and begin disentangling the interactions among its Components. This will lead to an improved understanding of the complexity of LBP, and hopefully to improved outcomes for those suffering from this condition.