scholarly journals Do We Have It All Wrong? The Protective Roles of Peers and Criminogenic Risks From Family During Prison Reentry

2018 ◽  
Vol 65 (5) ◽  
pp. 681-704 ◽  
Author(s):  
Thomas J. Mowen ◽  
John H. Boman
Keyword(s):  
Social Support ◽  
Peer Relationships ◽  
Mixed Effects ◽  
Mixed Effects Models ◽  
Violent Offender ◽  
Prior Work ◽  
Protective Mechanisms ◽  
Prison Reentry ◽  
Support Theory ◽  
Family Social Support

Prior work on the process of reentry from prison has highlighted the pivotal role that family and peers play during reintegration. Families are traditionally understood as important protective mechanisms against recidivism whereas peers are typically viewed as primarily criminogenic. Yet, drawing from differential coercion and social support theory, family and peer relationships can both be supportive (and protect against recidivism) and coercive (and contribute to recidivism). Using four waves of data from the Serious and Violent Offender Reentry Initiative, results of mixed-effects models demonstrate that family, but not peer, coercion relates to increased odds of reincarceration. Peer, but not family, social support relates to decreased odds of reincarceration. Findings suggest families are primarily criminogenic, whereas peers are protective during reentry.

scholarly journals The Duality of the Peer Effect: The Interplay Between Peer Support and Peer Criminality on Offending and Substance Use During Reentry

2017 ◽  
Vol 64 (8) ◽  
pp. 1094-1116 ◽  
Author(s):  
Thomas J. Mowen ◽  
John H. Boman
Keyword(s):  
Substance Use ◽  
Peer Support ◽  
Mixed Effects ◽  
Mixed Effects Models ◽  
Violent Offender ◽  
Criminal Offending ◽  
Support Theory ◽  
Interaction Terms ◽  
Differential Association Theory ◽  
Using Data

Differential association theory and the closely linked differential coercion/social support theory suggest that peers exert both criminogenic and protective influences on individuals. Yet, little is known about how dimensions of peer criminality and peer support affect reentry outcomes independently and interdependently. Using data from the Serious and Violent Offender Reentry Initiative, mixed-effects models demonstrate that peer criminality relates to significantly higher odds of substance use and criminal offending, whereas peer support relates to significantly lower odds of substance use and offending. Interaction terms between suggest the two exert independent, and not interactive, influences on recidivism. Although peer crime exerts a more robust effect, peer support must be understood as a mechanism that drives desistance independently of peer crime.

scholarly journals Examining the Parole Officer as a Mechanism of Social Support During Reentry From Prison

2019 ◽  
Vol 66 (6-7) ◽  
pp. 1023-1051 ◽  
Author(s):  
Kyle J. Bares ◽  
Thomas J. Mowen
Keyword(s):  
Social Support ◽  
Professional Support ◽  
Mixed Effects Models ◽  
Violent Offender ◽  
Parole Officer ◽  
Professional Relationship ◽  
Policy Makers ◽  
Interpersonal Support ◽  
Correct Information ◽  
Insight Into

Emerging research has shown that the parole officer, much like friends and family, can be an important source of social support for returning persons. While this body of literature is growing, existing research provides little insight into understanding how specific types (e.g., interpersonal and/or professional) of parole officer support matter. Using panel data from the Serious and Violent Offender Reentry Initiative, results of mixed-effects models demonstrate that greater levels of parole officer support are associated with decreased odds of reincarceration. Furthermore, parole officer professional support (e.g., providing correct information) exerts a more robust effect than interpersonal support (e.g., listening and caring). Findings suggest policy makers should consider programming to strengthen the professional relationship between the parole officer and returning person.

scholarly journals Effect of tofogliflozin on arterial stiffness in patients with type 2 diabetes: prespecified sub-analysis of the prospective, randomized, open-label, parallel-group comparative UTOPIA trial

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Naoto Katakami ◽  
◽  
Tomoya Mita ◽  
Hidenori Yoshii ◽  
Toshihiko Shiraiwa ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Type 2 Diabetes ◽  
Conventional Treatment ◽  
Mixed Effects ◽  
Mixed Effects Models ◽  
Open Label ◽  
Parallel Group ◽  
History Of

Abstract Background Tofogliflozin, an SGLT2 inhibitor, is associated with favorable metabolic effects, including improved glycemic control and serum lipid profile and decreased body weight, visceral adipose tissue, and blood pressure (BP). This study evaluated the effects of tofogliflozin on the brachial-ankle pulse wave velocity (baPWV) in patients with type 2 diabetes (T2DM) without a history of apparent cardiovascular disease. Methods The using tofogliflozin for possible better intervention against atherosclerosis for type 2 diabetes patients (UTOPIA) trial is a prospective, randomized, open-label, multicenter, parallel-group, comparative study. As one of the prespecified secondary outcomes, changes in baPWV over 104 weeks were evaluated in 154 individuals (80 in the tofogliflozin group and 74 in the conventional treatment group) who completed baPWV measurement at baseline. Results In a mixed-effects model, the progression in the right, left, and mean baPWV over 104 weeks was significantly attenuated with tofogliflozin compared to that with conventional treatment (– 109.3 [– 184.3, – 34.3] (mean change [95% CI] cm/s, p = 0.005; – 98.3 [– 172.6, – 24.1] cm/s, p = 0.010; – 104.7 [– 177.0, – 32.4] cm/s, p = 0.005, respectively). Similar findings were obtained even after adjusting the mixed-effects models for traditional cardiovascular risk factors, including body mass index (BMI), glycated hemoglobin (HbA1c), total cholesterol, high-density lipoprotein (HDL)-cholesterol, triglyceride, systolic blood pressure (SBP), hypertension, smoking, and/or administration of drugs, including hypoglycemic agents, antihypertensive agents, statins, and anti-platelets, at baseline. The findings of the analysis of covariance (ANCOVA) models, which included the treatment group, baseline baPWV, and traditional cardiovascular risk factors, resembled those generated by the mixed-effects models. Conclusions Tofogliflozin significantly inhibited the increased baPWV in patients with T2DM without a history of apparent cardiovascular disease, suggesting that tofogliflozin suppressed the progression of arterial stiffness. Trial Registration UMIN000017607. Registered 18 May 2015. (https://www.umin.ac.jp/icdr/index.html)

The Use of Theory of Linear Mixed-Effects Models to Detect Fraudulent Erasures at an Aggregate Level

2021 ◽  
pp. 001316442199489
Author(s):  
Luyao Peng ◽  
Sandip Sinharay
Keyword(s):  
Type I Error ◽  
Real Data ◽  
Mixed Effects ◽  
Error Rates ◽  
Mixed Effects Models ◽  
Type I ◽  
Aggregate Level ◽  
Linear Mixed Effects Models ◽  
Linear Mixed Effects ◽  
Best Linear Unbiased

Wollack et al. (2015) suggested the erasure detection index (EDI) for detecting fraudulent erasures for individual examinees. Wollack and Eckerly (2017) and Sinharay (2018) extended the index of Wollack et al. (2015) to suggest three EDIs for detecting fraudulent erasures at the aggregate or group level. This article follows up on the research of Wollack and Eckerly (2017) and Sinharay (2018) and suggests a new aggregate-level EDI by incorporating the empirical best linear unbiased predictor from the literature of linear mixed-effects models (e.g., McCulloch et al., 2008). A simulation study shows that the new EDI has larger power than the indices of Wollack and Eckerly (2017) and Sinharay (2018). In addition, the new index has satisfactory Type I error rates. A real data example is also included.

scholarly journals ALLY in fighting COVID-19: magnitude of albumin decline and lymphopenia (ALLY) predict progression to critical disease

2021 ◽  
pp. jim-2020-001525
Author(s):  
Johanna S van Zyl ◽  
Amit Alam ◽  
Joost Felius ◽  
Ronnie M Youssef ◽  
Dipesh Bhakta ◽  
...  
Keyword(s):  
Medical Records ◽  
Resource Planning ◽  
Mixed Effects ◽  
Mixed Effects Models ◽  
Disease Course ◽  
Risk Models ◽  
Simple Tool ◽  
Laboratory Results ◽  
Risk Of Disease ◽  
Critical Patients

The global severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic leading to coronavirus disease 2019 (COVID-19) is straining hospitals. Judicious resource allocation is paramount but difficult due to the unpredictable disease course. Once hospitalized, discerning which patients may progress to critical disease would be valuable for resource planning. Medical records were reviewed for consecutive hospitalized patients with COVID-19 in a large healthcare system in Texas. The main outcome was progression to critical disease within 10 days from admission. Albumin trends from admission to 7 days were analyzed using mixed-effects models, and progression to critical disease was modeled by multivariable logistic regression of laboratory results. Risk models were evaluated in an independent group. Of 153 non-critical patients, 28 (18%) progressed to critical disease. The rate of decrease in mean baseline-corrected (Δ) albumin was −0.08 g/dL/day (95% CI −0.11 to −0.04; p<0.001) or four times faster, in those who progressed compared with those who did not progress. A model of Δ albumin combined with lymphocyte percentage predicting progression to critical disease was validated in 60 separate patients (sensitivity, 0.70; specificity, 0.74). ALLY (delta albumin and lymphocyte percentage) is a simple tool to identify patients with COVID-19 at higher risk of disease progression when: (1) a 0.9 g/dL or greater albumin drop from baseline within 5 days of admission or (2) baseline lymphocyte of ≤10% is observed. The ALLY tool identified >70% of hospitalized cases that progressed to critical COVID-19 disease. We recommend prospectively tracking albumin. This is a globally applicable tool for all healthcare systems.

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