High Crime Neighborhoods as a Driver for Toxic Stress Leading to Asthma

BACKGROUND: Social determinants of health and allostatic load theory suggest social environment can drive asthma diagnoses via the mechanism of toxic stress, the prolonged activation of stress response systems. While research has linked neighborhood crime to asthma, multivariate causal modeling has not been used to test toxic stress as the mechanism that links the two. The current study investigates neighborhood crime as a driver of pediatric asthma diagnoses via toxic stress. METHODS: A retrospective geospatial analysis of health and crime data was conducted. Health data was collected from the OU-Tulsa General Pediatric Clinic’s Electronic Medical Record while crime data was collected from the Tulsa Police Department. All variables were mapped geospatially using census tract as the unit of analysis. Structural equation modeling was used to test the causal model. Neighborhood crime indicators included homicide, rape, and narcotic-related offenses. Diagnoses of conduct, attention deficit, and other anxiety disorders were used in the analysis as toxic stress indicators. Asthma diagnoses were the outcome variable. To further test the model, data from 2016 was used as a calibration sample while data from 2017 was used as a validation sample. RESULTS: A full mediation model of high crime neighborhoods (n = 134) as a driver of toxic stress resulting in increased asthma diagnoses fit the 2016 data well (Χ2 = 15.6, p =.27; df = 13; RMSEA = .04 [90% CI: .00, .10]; CFI: .99; SRMR = .04). The results indicated the model accounted for 78% (R2 = .78) of the variance in asthma diagnoses. The model also provided a good fit to the 2017 data (X2= 23.6, p<.001; df= 13; RMSEA = .08 [90% CI: .02, .13]; CFI: .96; SRMR=.06). CONCLUSION: The results of the current study have important practice and research implications. While clinicians and researchers have become increasingly aware of the impact of social determinants of health, there has been little focus on improving clinical practices. Physicians interested in alleviated the burden of toxic stress and asthma should explore ways to reduce neighborhood crime at the policy level while also being aware of each of their patients’ unique circumstances in relation to where they live.N

Predicting reliability through structured expert elicitation with the repliCATS (Collaborative Assessments for Trustworthy Science) process

As replications of individual studies are resource intensive, techniques for predicting the replicability are required. We introduce the repliCATS (Collaborative Assessments for Trustworthy Science) process, a new method for eliciting expert predictions about the replicability of research. This process is a structured expert elicitation approach based on a modified Delphi technique applied to the evaluation of research claims in social and behavioural sciences. The utility of processes to predict replicability is their capacity to test scientific claims without the costs of full replication. Experimental data supports the validity of this process, with a validation study producing a classification accuracy of 84% and an Area Under the Curve of 0.94, meeting or exceeding the accuracy of other techniques used to predict replicability. The repliCATS process provides other benefits. It is highly scalable, able to be deployed for both rapid assessment of small numbers of claims, and assessment of high volumes of claims over an extended period through an online elicitation platform, having been used to assess 3000 research claims over an 18 month period. It is available to be implemented in a range of ways and we describe one such implementation. An important advantage of the repliCATS process is that it collects qualitative data that has the potential to provide insight in understanding the limits of generalizability of scientific claims. The primary limitation of the repliCATS process is its reliance on human-derived predictions with consequent costs in terms of participant fatigue although careful design can minimise these costs. The repliCATS process has potential applications in alternative peer review and in the allocation of effort for replication studies