The phenotype of recovery VIII: Association among delay discounting, recovery capital, and length of abstinence among individuals in recovery from substance use disorders.

INTRODUCTION: Research defines recovery capital as the amount of tangible and intangible resources (e.g., human/personal, physical, social, and cultural) available to initiate and sustain recovery from substance use disorders (SUDs). An individual's amount of recovery capital is dynamic over time and influenced by a number of factors such as baseline amount at initiation of recovery/treatment, length of abstinence, access/availability of resources, and individual factors such as the decision to utilize available resources. Research has been proposed delay discounting (DD), which reflects an individual's relative preference for immediate versus delayed rewards, as a candidate behavioral marker for SUDs but has not yet examined it in the context of recovery capital, and DD may be an important aspect of human capital. Thus, the aim of the current study was to examine associations among recovery capital, DD, and length of abstinence. METHODS: The study included in its analysis data from 111 individuals in recovery from SUDs from the International Quit and Recovery Registry, an ongoing data collection program used to further scientific understanding of recovery. The study assessed recovery capital using the Assessment of Recovery Capital (ARC) and assessed discounting rates using an adjusting-delay task. The study team performed univariate linear regression to examine the relationship between total ARC score and demographic variables, length of abstinence, and DD. The research team performed a mediation analysis to understand the role of length of abstinence in mediating the relationship between DD and ARC score. RESULTS: Total ARC score was significantly negatively associated with DD and positively associated with length of abstinence, even after adjusting for covariates. Mediation analysis indicated that length of abstinence significantly partially mediated the relationship between DD and ARC score. CONCLUSION: These findings support the characterization of DD as an important aspect of human capital and a candidate behavioral marker for SUDs. Future research may wish to investigate whether interventions designed to increase the value of future rewards also increase recovery capital.

Development and implementation of a scalable and versatile test for COVID-19 diagnostics in rural communities.

Rapid and widespread testing of severe acute respiratory coronavirus 2 (SARS-CoV-2) is essential for an effective public health response aimed at containing and mitigating the coronavirus disease 2019 (COVID-19) pandemic. Successful health policy implementation relies on early identification of infected individuals and extensive contact tracing. However, rural communities, where resources for testing are sparse or simply absent, face distinctive challenges to achieving this success. Accordingly, we report the development of an academic, public land grant University laboratory-based detection assay for the identification of SARS-CoV-2 in samples from various clinical specimens that can be readily deployed in areas where access to testing is limited. The test, which is a quantitative reverse transcription polymerase chain reaction (RT-qPCR)-based procedure, was validated on samples provided by the state laboratory and submitted for FDA Emergency Use Authorization. Our test exhibits comparable sensitivity and exceeds specificity and inclusivity values compared to other molecular assays. Additionally, this test can be re-configured to meet supply chain shortages, modified for scale up demands, and is amenable to several clinical specimens. Test development also involved 3D engineering critical supplies and formulating a stable collection media that allowed samples to be transported for hours over a dispersed rural region without the need for a cold-chain. These two elements that were critical when shortages impacted testing and when personnel needed to reach areas that were geographically isolated from the testing center. Overall, using a robust, easy-to-adapt methodology, we show that an academic laboratory can supplement COVID-19 testing needs and help local health departments assess and manage outbreaks. This additional testing capacity is particularly germane for smaller cities and rural regions that would otherwise be unable to meet the testing demand.