Health Outcomes for People With Serious Mental Illness: A Case Study

2008 ◽  
Vol 39 (1) ◽  
pp. 23-32 ◽  
Author(s):  
Terry A. Badger ◽  
Cheryl McNiece ◽  
Elizabeth Bonham ◽  
Jennifer Jacobson ◽  
Alan J. Gelenberg
Work ◽  
2009 ◽  
Vol 33 (4) ◽  
pp. 459-464 ◽  
Author(s):  
Michael Crain ◽  
Caroline Penhale ◽  
Catherine Newstead ◽  
Leigh Thomson ◽  
Tom Heah ◽  
...  

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Kimberly McKee ◽  
Lindsay K. Admon ◽  
Tyler N. A. Winkelman ◽  
Maria Muzik ◽  
Stephanie Hall ◽  
...  

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Albert Stuart Reece ◽  
Gary Kenneth Hulse

Abstract Background: Whilst many studies have linked increased drug and cannabis exposure to adverse mental health (MH) outcomes their effects on whole populations and geotemporospatial relationships are not well understood. Methods Ecological cohort study of National Survey of Drug Use and Health (NSDUH) geographically-linked substate-shapefiles 2010–2012 and 2014–2016 supplemented by five-year US American Community Survey. Drugs: cigarettes, alcohol abuse, last-month cannabis use and last-year cocaine use. MH: any mental illness, major depressive illness, serious mental illness and suicidal thinking. Data analysis: two-stage, geotemporospatial, robust generalized linear regression and causal inference methods in R. Results 410,138 NSDUH respondents. Average response rate 76.7%. When drug and sociodemographic variables were combined in geospatial models significant terms including tobacco, alcohol, cannabis exposure and various ethnicities remained in final models for all four major mental health outcomes. Interactive terms including cannabis were related to any mental illness (β-estimate = 1.97 (95%C.I. 1.56–2.37), P <  2.2 × 10− 16), major depressive episode (β-estimate = 2.03 (1.54–2.52), P = 3.6 × 10− 16), serious mental illness (SMI, β-estimate = 2.04 (1.48–2.60), P = 1.0 × 10− 12), suicidal ideation (β-estimate = 1.99 (1.52–2.47), P <  2.2 × 10− 16) and in each case cannabis alone was significantly associated (from β-estimate = − 3.43 (− 4.46 − −2.42), P = 3.4 × 10− 11) with adverse MH outcomes on complex interactive regression surfaces. Geospatial modelling showed a monotonic upward trajectory of SMI which doubled (3.62 to 7.06%) as cannabis use increased. Extrapolated to whole populations cannabis decriminalization (4.26%, (4.18, 4.34%)), Prevalence Ratio (PR) = 1.035(1.034–1.036), attributable fraction in the exposed (AFE) = 3.28%(3.18–3.37%), P < 10− 300) and legalization (4.75% (4.65, 4.84%), PR = 1.155 (1.153–1.158), AFE = 12.91% (12.72–13.10%), P < 10− 300) were associated with increased SMI vs. illegal status (4.26, (4.18–4.33%)). Conclusions Data show all four indices of mental ill-health track cannabis exposure across space and time and are robust to multivariable adjustment for ethnicity, socioeconomics and other drug use. MH deteriorated with cannabis legalization. Cannabis use-MH data are consistent with causal relationships in the forward direction and include dose-response and temporal-sequential relationships. Together with similar international reports and numerous mechanistic studies preventative action to reduce cannabis use is indicated.


2020 ◽  
Author(s):  
Kristina Schnitzer ◽  
Corrine Cather ◽  
Vanya Zvonar ◽  
Alyson Dechert ◽  
Rachel Plummer ◽  
...  

BACKGROUND In a prior study, participation in a 16-week, reverse integrated care, group behavioral and educational intervention for individuals with diabetes and serious mental illness was associated with improved glycemic control (HbA1C) and body mass index (BMI). In order to inform future implementation efforts, more information about the effective components of the intervention is needed. OBJECTIVE The goal of this study was to identify aspects of the intervention participants reported were helpful and to evaluate predictors of outcome. METHODS This study involved qualitative evaluation and post-hoc quantitative analysis of a prior intervention. Qualitative data were collected using semi-structured interviews with 24 of 35 individuals (69%) who attended one or more group sessions and 9 of 26 individuals (35%) who consented but attended no sessions. Quantitative mixed effects modeling was performed to test whether improved diabetes knowledge, diet and exercise, or higher group attendance predicted improved HbA1C and BMI. These interview and modeling outcomes were combined using a mixed methods case study framework and integrated thematically. RESULTS In qualitative interviews, participants identified application of health-related knowledge gained to real world situations, accountability for goals, positive reinforcement and group support, and increased confidence to prioritize health goals as factors contributing to success of the behavioral intervention. Improved diabetes knowledge was associated with reduced BMI (=-1.27, SD=0.40, P=0.003). No quantitative variables examined were significantly associated with improved HbA1C. CONCLUSIONS In this mixed methods analysis of predictors of success in a behavioral diabetes management program, group participants highlighted the value of positive reinforcement and group support, accountability for goals set, and real-world application of health-related knowledge gained. Improved diabetes knowledge was associated with weight loss. CLINICALTRIAL


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