Assessing a Pilot Scheme of Intensive Support and Assertive Linkage in Levels of Engagement, Retention, and Recovery Capital for people in Recovery Housing using Quasi-Experimental Methods

Introduction: There is strong and ever-growing evidence highlighting the effectiveness of recovery housing to support and sustain substance use disorder (SUD) recovery augmented by intensive support comprising assertive linkages to community services.Aim: To assess a pilot intensive recovery support (IRS) intervention for individuals (n=175) entering certified Level II and III recovery residences who met at least three out of five conditions (no health insurance; no driving license; substance use in the last 14 days; currently unemployed; having less than $75 capital) and its impact on engagement, retention and changes in recovery capital for individuals compared with a business-as-usual Standard Recovery Support (SRS) approach (n=1,758).Methods: We deployed quasi-experimental techniques to create weighted and balanced counterfactual groups derived from the Recovery Capital (REC-CAP) assessment tool to compare outcomes for people receiving the pilot IRS compared to intervention against SRS.Results: After reweighting for resident demographics, service needs, and barriers to recovery, those receiving IRS exhibited improved retention rates, reduced likelihood of disengagement, and growth in recovery capital after living in the residence for 6-9 months.Conclusion: Our findings from this pilot intervention suggest that intensive recovery support incorporating assertive community linkages and enhanced recovery coaching can improve engagement, length of stay and recovery capital growth compared to a balanced counterfactual group. We suggest that this model may be particularly beneficial to those entering Level II and Level III recovery housing with lower levels of recovery capital at admission entry.<br/

Measuring recovery capital for people recovering from alcohol and drug addiction:A systematic review

Background: Recovery capital (RC) theory provides a biopsychosocial framework for identifying and measuring strengths and barriers that can be targeted to support recovery from alcohol and drug addiction. This systematic review analyzed and synthesized all quantitative approaches that have been used to measured recovery capital RC in the recent literaturesince 2016.Method: Systematic database searches were conducted in three databases to identifyThe reviewed studies were published from 2016 to 2023, . Eligible studiesand explicitly stated they measured RC recovery capital in participants recovering from alcohol and/or drug addiction. Studies focusing on other forms of addiction were excluded.Results: Sixty-nine studies met the inclusion criteria. Forty-six studies (66.7%) used one of the ten identified RC recovery capital questionnaires, and twenty-five studies (36.2%) used a measurement approach other than one of the ten RC recovery capital questionnaires. The ten RC recovery capital questionnaires are primarily developed for adult populations across clinical and community recovery settings, and between them measuredwere identified to measure altogether 41 separate RC recovery capital constructs. They, and are generally considered valid and reliable measures of RCrecovery capital. Nevertheless, a strong evidence base on the psychometric properties across diverse populations and settings is still needs to be established for all RC these questionnaires. Conclusion: The development of RC recovery capital questionnaires has been a significant advance in the addiction recovery field, in alignment with the modern emerging recovery-oriented approach to addiction recovery care. Additionally, the non-RC recovery capital questionnaire-based approaches to RC recovery capital measurement have an important place in the field. They could be used alongside RC recovery capital questionnaires to test RC theory, and in contexts where the application of the RC questionnaires is not feasible, such as analyses of data from online recovery forums

Susceptibility to interference between Pavlovian and instrumental control predisposes risky alcohol use developmental trajectory from ages 18 to 24

Pavlovian cues can influence ongoing instrumental behaviour via Pavlovian-to-instrumental transfer (PIT) processes. While appetitive Pavlovian cues tend to promote instrumental approach, they are detrimental when avoidance behaviour is required, and vice versa for aversive cues. We recently reported that susceptibility to interference between Pavlovian and instrumental control assessed via a PIT task was associated with risky alcohol use at age 18. We now investigated whether such susceptibility also predicts drinking trajectories until age 24, based on AUDIT (Alcohol Use Disorders Identification Test) consumption and binge drinking (gramme alcohol/drinking occasion) scores. The interference PIT effect, assessed at ages 18 and 21 during fMRI, was characterized by increased error rates (ER) and enhanced neural responses in the ventral striatum (VS), the lateral and dorsomedial prefrontal cortices (dmPFC) during conflict, that is, when an instrumental approach was required in the presence of an aversive Pavlovian cue or vice versa. We found that a stronger VS response during conflict at age 18 was associated with a higher starting point of both drinking trajectories but predicted a decrease in binge drinking. At age 21, high ER and enhanced neural responses in the dmPFC were associated with increasing AUDIT-C scores over the next 3 years until age 24. Overall, susceptibility to interference between Pavlovian and instrumental control might be viewed as a predisposing mechanism towards hazardous alcohol use during young adulthood, and the identified high-risk group may profit from targeted interventions

LED Lighting: Carbon Footprint Reduction and Energy Cost Savings at Prince George's County Parks and Recreational Facilities

Final project for ENSP400: Capstone Environmental Science and Policy (Fall 2021). University of Maryland, College Park.Through their work with the National Center for Smart Growth at the University of Maryland (UMD), the Maryland Department of Natural Resources (MDNR) commissioned this report from the university’s Partnership for Action Learning in Sustainability (PALS). PALS works with local jurisdictions throughout Maryland to identify projects and problems that can be taught through university courses where students focus on developing innovative, research-based solutions. The Prince George's Division of Maintenance and Development partnered with Environmental Science and Policy capstone students at the University of Maryland College Park to examine the cost and energy savings when LED lighting, and other energy-saving devices, are used at park system facilities. The facilities analysis allowed Prince George’s County Department of Parks and Recreation to uphold the values of a healthy lifestyle while still providing enriching leisure services.Prince George's County Department of Parks and Recreation (PGDPR

Interaction of Aspirin (Acetylsalicylic Acid) with Lipid Membranes

We studied the interaction of Aspirin (acetylsalicylic acid) with lipid membranes using x-ray diffraction for bilayers containing up to 50 mol% of aspirin. From 2D x-ray intensity maps that cover large areas of reciprocal space we determined the position of the ASA molecules in the phospholipid bilayers and the molecular arrangement of the molecules in the plane of the membranes. We present direct experimental evidence that ASA molecules participate in saturated lipid bilayers of DMPC (1,2-dimyristoyl-sn-glycero-3-phosphocholine) and preferably reside in the head group region of the membrane. Up to 50 mol% ASA molecules can be dissolved in this type of bilayer before the lateral membrane organization is disturbed and the membranes are found to form an ordered, 2D crystal-like structure. Furthermore, ASA and cholesterol were found to co-exist in saturated lipid bilayers, with the ASA molecules residing in the head group region and the cholesterol molecules participating in the hydrophobic membrane core

Enumerating pelvic recurrence following radical cystectomy for bladder cancer: A canadian multi-institutional study

Introduction: We aimed to enumerate the rate of pelvic recurrence following radical cystectomy at university-affiliated hospitals in Canada. Methods: Canadian, university-affiliated hospitals were invited to participate. They were asked to identify the first 10 consecutive patients undergoing radical cystectomy starting January 1, 2005, who had urothelial carcinoma stages pT3/T4 N0-2 M0. The first 10 consecutive cases starting January 1, 2005 who met these criteria were the patients submitted by that institution with information regarding tumour stage, age, number of nodes removed, and last known clinical status in regard to recurrence and patterns of failure. Results: Of the 111 patients, 80% had pT3 and 20% pT4 disease, with 62% being node-negative, 14% pN1, and 27% pN2; 57% had 10 or more nodes removed. Cumulative incidence of pelvic relapse was 40% among the entire group Conclusions: This review demonstrates a high rate of pelvic tumour recurrence following radical cystectomy for pT3/T4 urothelial cancer

Measuring self-regulation in everyday life: reliability and validity of smartphone-based experiments in alcohol use disorder

Self-regulation, the ability to guide behavior according to one’s goals, plays an integral role in understanding loss of control over unwanted behaviors, for example in alcohol use disorder (AUD). Yet, experimental tasks that measure processes underlying self-regulation are not easy to deploy in contexts where such behaviors usually occur, namely outside the laboratory, and in clinical populations such as people with AUD. Moreover, lab-based tasks have been criticized for poor test–retest reliability and lack of construct validity. Smartphones can be used to deploy tasks in the field, but often require shorter versions of tasks, which may further decrease reliability. Here, we show that combining smartphone-based tasks with joint hierarchical modeling of longitudinal data can overcome at least some of these shortcomings. We test four short smartphone-based tasks outside the laboratory in a large sample (N = 488) of participants with AUD. Although task measures indeed have low reliability when data are analyzed traditionally by modeling each session separately, joint modeling of longitudinal data increases reliability to good and oftentimes excellent levels. We next test the measures’ construct validity and show that extracted latent factors are indeed in line with theoretical accounts of cognitive control and decision-making. Finally, we demonstrate that a resulting cognitive control factor relates to a real-life measure of drinking behavior and yields stronger correlations than single measures based on traditional analyses. Our findings demonstrate how short, smartphone-based task measures, when analyzed with joint hierarchical modeling and latent factor analysis, can overcome frequently reported shortcomings of experimental tasks

Measuring self-regulation in everyday life: Reliability and validity of smartphone-based experiments in alcohol use disorder

Self-regulation, the ability to guide behavior according to one's goals, plays an integral role in understanding loss of control over unwanted behaviors, for example in alcohol use disorder (AUD). Yet, experimental tasks that measure processes underlying self-regulation are not easy to deploy in contexts where such behaviors usually occur, namely outside the laboratory, and in clinical populations such as people with AUD. Moreover, lab-based tasks have been criticized for poor test-retest reliability and lack of construct validity. Smartphones can be used to deploy tasks in the field, but often require shorter versions of tasks, which may further decrease reliability. Here, we show that combining smartphone-based tasks with joint hierarchical modeling of longitudinal data can overcome at least some of these shortcomings. We test four short smartphone-based tasks outside the laboratory in a large sample (N = 488) of participants with AUD. Although task measures indeed have low reliability when data are analyzed traditionally by modeling each session separately, joint modeling of longitudinal data increases reliability to good and oftentimes excellent levels. We next test the measures' construct validity and show that extracted latent factors are indeed in line with theoretical accounts of cognitive control and decision-making. Finally, we demonstrate that a resulting cognitive control factor relates to a real-life measure of drinking behavior and yields stronger correlations than single measures based on traditional analyses. Our findings demonstrate how short, smartphone-based task measures, when analyzed with joint hierarchical modeling and latent factor analysis, can overcome frequently reported shortcomings of experimental tasks