How do unobserved confounding mediators and measurement error impact estimated mediation effects and corresponding statistical inferences? Introducing the R package ConMed for sensitivity analysis.

Empirical studies often demonstrate multiple causal mechanisms potentially involving simultaneous or causally related mediators. However, researchers often use simple mediation models to understand the processes because they do not or cannot measure other theoretically relevant mediators. In such cases, another potentially relevant but unobserved mediator potentially confounds the observed mediator, thereby biasing the estimated direct and indirect effects associated with the observed mediator and threatening corresponding inferences. Additionally, researchers may not know the extent to which their measures are reliable, and accordingly, measurement error may bias estimated effects and mislead statistical inferences. Given these threats, we explore how the omission of an unobserved mediator and/or using variables with measurement error biases estimates and affects inferences associated with the observed mediator. Then, building off Frank's impact threshold for a confounding variable (ITCV), we propose a correlation-based sensitivity analysis. Lastly, we provide an R package ConMed to assess the robustness of mediation inferences given the omission of an unobserved, confounding mediator and/or measurement error. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Quantifying the robustness of causal inferences: Sensitivity analysis for pragmatic social science.

Social scientists seeking to inform policy or public action must carefully consider how to identify effects and express inferences because actions based on invalid inferences may not yield the intended results. Recognizing the complexities and uncertainties of social science, we seek to inform inevitable debates about causal inferences by quantifying the conditions necessary to change an inference. Specifically, we review existing sensitivity analyses within the omitted variables and potential outcomes frameworks. We then present the Impact Threshold for a Confounding Variable (ITCV) based on omitted variables in the linear model and the Robustness of Inference to Replacement (RIR) based on the potential outcomes framework. We extend each approach to include benchmarks and to fully account for sampling variability represented by standard errors as well as bias. We exhort social scientists wishing to inform policy and practice to quantify the robustness of their inferences after utilizing the best available data and methods to draw an initial causal inference.

Hypothetical case replacement can be used to quantify the robustness of trial results.

OBJECTIVES: We apply a general case replacement framework for quantifying the robustness of causal inferences to characterize the uncertainty of findings from clinical trials. STUDY DESIGN AND SETTING: We express the robustness of inferences as the amount of data that must be replaced to change the conclusion and relate this to the fragility of trial results used for dichotomous outcomes. We illustrate our approach in the context of an RCT of hydroxychloroquine on pneumonia in COVID-19 patients and a cumulative meta-analysis of the effect of antihypertensive treatments on stroke. RESULTS: We developed the Robustness of an Inference to Replacement (RIR), which quantifies how many treatment cases with positive outcomes would have to be replaced with hypothetical patients who did not receive a treatment to change an inference. The RIR addresses known limitations of the Fragility Index by accounting for the observed rates of outcomes. It can be used for varying thresholds for inference, including clinical importance. CONCLUSION: Because the RIR expresses uncertainty in terms of patient experiences, it is more relatable to stakeholders than P-values alone. It helps identify when results are statistically significant, but conclusions are not robust, while considering the rareness of events in the underlying data.

The spatial and temporal dynamics of global meat trade networks.

Rapid increases in meat trade generate complex global networks across countries. However, there has been little research quantifying the dynamics of meat trade networks and the underlying forces that structure them. Using longitudinal network data for 134 countries from 1995 to 2015, we combined network modeling and cluster analysis to simultaneously identify the structural changes in meat trade networks and the factors that influence the networks themselves. The integrated network approach uncovers a general consolidation of global meat trade networks over time, although some global events may have weakened this consolidation both regionally and globally. In consolidated networks, the presence of trade agreements and short geographic distances between pairs of countries are associated with increases in meat trade. Countries with rapid population and income growth greatly depend on meat imports. Furthermore, countries with high food availability import large quantities of meat products to satisfy their various meat preferences. The findings from this network approach provide key insights that can be used to better understand the social and environmental consequences of increasing global meat trade.

Implementation of Evidence-Based Practice In Human Service Organizations: Implications From Agent-Based Models.

Much of the impact of a policy depends on how it is implemented, especially as mediated by organizations such as schools or hospitals. Here, we focus on how implementation of evidence-based practices in human service organizations (e.g., schools, hospitals)is affected by intraorganizational network dynamics. In particular, we hypothesize intraorganizational behavioral divergence and network polarization are likely to occur when actors strongly identify with their organizations. Using agent-based models, we find that when organizational identification is high, external change agents who attempt to direct organizations by introducing policy aligned messages (e.g., professional development emphasizing specific teaching practices) may unintentionally contribute to divergence in practice and polarization in networks, inhibiting full implementation of the desired practices as well as reducing organizational capacity to absorb new practices. Thus, the external change agent should consider the interaction between the type of message and the intraorganizational network dynamics driven by organizational identification.

Political influences on greenhouse gas emissions from US states.

Starting at least in the 1970s, empirical work suggested that demographic (population) and economic (affluence) forces are the key drivers of anthropogenic stress on the environment. We evaluate the extent to which politics attenuates the effects of economic and demographic factors on environmental outcomes by examining variation in CO2 emissions across US states and within states over time. We find that demographic and economic forces can in part be offset by politics supportive of the environment--increases in emissions over time are lower in states that elect legislators with strong environmental records.

Do social networks influence small-scale fishermen's enforcement of sea tenure?

Resource systems with enforced rules and strong monitoring systems typically have more predictable resource abundance, which can confer economic and social benefits to local communities. Co-management regimes demonstrate better social and ecological outcomes, but require an active role by community members in management activities, such as monitoring and enforcement. Previous work has emphasized understanding what makes fishermen comply with rules. This research takes a different approach to understand what influences an individual to enforce rules, particularly sea tenure. We conducted interviews and used multiple regression and Akaike's Information Criteria model selection to evaluate the effect of social networks, food security, recent catch success, fisherman's age and personal gear investment on individual's enforcement of sea tenure. We found that fishermen's enforcement of sea tenure declined between the two time periods measured and that social networks, age, food security, and changes in gear investment explained enforcement behavior across three different communities on Nicaragua's Atlantic Coast, an area undergoing rapid globalization.

V. The differential association of adiposity and fitness with cognitive control in preadolescent children.

With the increasing prevalence of sedentary behaviors during childhood, a greater understanding of the extent to which excess adiposity and aerobic fitness relate to cognitive health is of increasing importance. To date, however, the vast majority of research in this area has focused on adiposity or fitness, rather than the possible inter-relationship, as it relates to cognition. Accordingly, this study examined the differential associations between body composition, aerobic fitness, and cognitive control in a sample of 204 (96 female) preadolescent children. Participants completed a modified flanker task (i.e., inhibition) and a switch task (i.e., cognitive flexibility) to assess two aspects of cognitive control. Findings from this study indicate that fitness and adiposity appear to be separable factors as they relate to cognitive control, given that the interaction of fitness and adiposity was observed to be nonsignificant for both the flanker and switch tasks. Fitness exhibited an independent association with both inhibition and cognitive flexibility whereas adiposity exhibited an independent association only with cognitive flexibility. These results suggest that while childhood obesity and fitness appear to both be related to cognitive control, they may be differentially associated with its component processes.

Social contexts of substance use among U.S. high school seniors: a multicohort national study.

PURPOSE: To determine the social contexts associated with the past-year substance use (multiple substances, alcohol, marijuana, and nonmedical use of prescription opioids, stimulants, and tranquilizers) among U.S. high school seniors. METHODS: A secondary analysis of nationally representative survey data from 10 cohorts (2002-2011) of the Monitoring the Future study, including 24,809 high school seniors. RESULTS: The social contexts associated with the past-year substance use varied considerably based on the substance used. The most prevalent location for alcohol, marijuana, and polydrug use was at a party, whereas nonmedical use of prescription stimulants, tranquilizers, and opioids was most likely to occur at home. Most types of substance use occurred in the presence of other people with the exception of nonmedical use of prescription stimulants, which was a more solitary behavior. CONCLUSIONS: These exploratory findings indicate that prevention efforts may need to account for differences in social contexts between types of substances used.

The Embeddedness of Adolescent Friendship Nominations: The Formation of Social Capital in Emergent Network Structures.

Although research on social embeddedness and social capital con-firms the value of friendship networks, little has been written about how social relations form and are structured by social institutions. Using data from the Adolescent Health and Academic Achievement study and the National Longitudinal Study of Adolescent Health, the authors show that the odds of a new friendship nomination were 1.77 times greater within clusters of high school students taking courses together than between them. The estimated effect cannot be attributed to exposure to peers in similar grade levels, indirect friendship links, or pair-level course overlap, and the finding is robust to alternative model specifications. The authors also show how tendencies associated with status hierarchy inhering in triadic friendship nominations are neutralized within the clusters. These results have implications for the production and distribution of social capital within social systems such as schools, giving the clusters social salience as "local positions."

Drivers and socioeconomic impacts of tourism participation in protected areas.

Nature-based tourism has the potential to enhance global biodiversity conservation by providing alternative livelihood strategies for local people, which may alleviate poverty in and around protected areas. Despite the popularity of the concept of nature-based tourism as an integrated conservation and development tool, empirical research on its actual socioeconomic benefits, on the distributional pattern of these benefits, and on its direct driving factors is lacking, because relevant long-term data are rarely available. In a multi-year study in Wolong Nature Reserve, China, we followed a representative sample of 220 local households from 1999 to 2007 to investigate the diverse benefits that these households received from recent development of nature-based tourism in the area. Within eight years, the number of households directly participating in tourism activities increased from nine to sixty. In addition, about two-thirds of the other households received indirect financial benefits from tourism. We constructed an empirical household economic model to identify the factors that led to household-level participation in tourism. The results reveal the effects of local households' livelihood assets (i.e., financial, human, natural, physical, and social capitals) on the likelihood to participate directly in tourism. In general, households with greater financial (e.g., income), physical (e.g., access to key tourism sites), human (e.g., education), and social (e.g., kinship with local government officials) capitals and less natural capital (e.g., cropland) were more likely to participate in tourism activities. We found that residents in households participating in tourism tended to perceive more non-financial benefits in addition to more negative environmental impacts of tourism compared with households not participating in tourism. These findings suggest that socioeconomic impact analysis and change monitoring should be included in nature-based tourism management systems for long-term sustainability of protected areas.

Race and Academic Achievement in Racially Diverse High Schools: Opportunity and Stratification.

BACKGROUND/CONTEXT: Brown v Board of Education fundamentally changed our nation's schools, yet we know surprisingly little about how and whether they provide equality of educational opportunity. Although substantial evidence suggests that African American and Latino students who attend these schools face fewer learning opportunities than their White counterparts, until now, it has been impossible to examine this using a representative sample because of lack of data. PURPOSE/OBJECTIVE/RESEARCH QUESTION/FOCUS OF STUDY: This study uses newly available data to investigate whether racially diverse high schools offer equality of educational opportunity to students from different racial and ethnic groups. This is examined by measuring the relative representation of minority students in advanced math classes at the beginning of high school and estimating whether and how this opportunity structure limits the level of achievement attained by African American and Latino students by the end of high school. SETTING: This study uses data from the Adolescent Health and Academic Achievement Study (AHAA) and its partner study, the National Longitudinal Study of Adolescent Health (Add Health), a stratified, nationally representative study of students in U.S. high schools first surveyed in 1994-1995. POPULATION/PARTICIPANTS/SUBJECTS: Two samples of racially diverse high schools were used in the analysis: one with African Americans, Whites, and Asians (26 schools with 3,149 students), and the other with Latinos, Whites, and Asians (22 schools with 2,775 students). RESEARCH DESIGN: Quantitative analyses first assess how high schools vary in the extent to which minority students are underrepresented in advanced sophomore math classes. Hierarchical multilevel modeling is then used to estimate whether racial-ethnic differences in representation in advanced math have an impact on African American and Latino students' achievement by the end of high school, relative to the Whites and Asians in the school. Specifically, we estimate the effects of Whites' and Asians' overrepresentation in sophomore-year math (or Latino or African American underrepresentation) within the school on students' senior-year grades and their postsecondary enrollment. FINDINGS/RESULTS: Findings show that schools vary in the extent to which African American and Latino students are underrepresented in advanced sophomore math classes. This pattern of racial inequality in schools is associated with lower minority senior-year grades and enrollment in 4-year postsecondary institutions, net of students' own background. CONCLUSIONS/RECOMMENDATIONS: Evidence consistently suggests that schools can play an active role in the provision of opportunities for social mobility or in the exacerbation of social inequality, depending on how they are structured. It is important to consider racial stratification within schools as a mechanism of inequality of educational opportunity.

The Social Dynamics of Mathematics Coursetaking in High School.

This study examines how high school boys' and girls' academic effort, in the form of math coursetaking, is influenced by members of their social contexts. The authors argue that adolescents' social contexts are defined, in part, by clusters of students (termed "local positions") who take courses that differentiate them from others. Using course transcript data from the recent Adolescent Health and Academic Achievement Study, the authors employ a new network algorithm to identify local positions in 78 high schools in the National Longitudinal Study of Adolescent Health. Incorporating the local positions into multilevel models of math coursetaking, the authors find that girls are highly responsive to the social norms in their local positions, which contributes to homogeneity within and heterogeneity between local positions.

Identifying positions from affiliation networks: Preserving the duality of people and events.

Frank's [Frank, K.A., 1995. Identifying cohesive subgroups. Social Networks 17, 27-56] clustering technique for one-mode social network data is adapted to identify positions in affiliation networks by drawing on recent extensions of p(*) models to two-mode data. The algorithm is applied to the classic Deep South data on southern women and the social events in which they participated with results comparable to other algorithms. Monte Carlo simulations are used to generate sampling distributions to test for the presence of clustering in new data sets and to evaluate the performance of the algorithm. The algorithm and simulation results are then applied to high school students' transcripts from one school from the Adolescent Health and Academic Achievement (AHAA) extension of the National Longitudinal Study of Adolescent Health.

The analyst's trust and therapeutic action.

The analyst's trust, a neglected topic in psychoanalytic discourse, participates in therapeutic action--through the analyst's emotional openness, "unobjectionable positive counter-transference" (see Fox 1998), the holding environment, and the promoting of adaptive internalizations, among other ways. When the analyst's trust--in the patient, in the analyst's self, and/or in the psychoanalytic process--fails, crucial interactions may occur, capable of destroying treatment, or alternatively, of restoring mutual regulatory functions and potentially leading to important mutative processes. Patients benefit from analysts' becoming sensitive to, having useful ways of thinking about, and working with their states of trust and distrust. The author presents clinical examples to illustrate these points.

Compartments revealed in food-web structure.

Compartments in food webs are subgroups of taxa in which many strong interactions occur within the subgroups and few weak interactions occur between the subgroups. Theoretically, compartments increase the stability in networks, such as food webs. Compartments have been difficult to detect in empirical food webs because of incompatible approaches or insufficient methodological rigour. Here we show that a method for detecting compartments from the social networking science identified significant compartments in three of five complex, empirical food webs. Detection of compartments was influenced by food web resolution, such as interactions with weights. Because the method identifies compartmental boundaries in which interactions are concentrated, it is compatible with the definition of compartments. The method is rigorous because it maximizes an explicit function, identifies the number of non-overlapping compartments, assigns membership to compartments, and tests the statistical significance of the results. A graphical presentation reveals systemic relationships and taxa-specific positions as structured by compartments. From this graphic, we explore two scenarios of disturbance to develop a hypothesis for testing how compartmentalized interactions increase stability in food webs.