Predictors of Alcohol Use after Bariatric Surgery

Patients undergoing bariatric surgery are at risk for devloping an alcohol use disorder (AUD). The purpose of this study was to investigate pre-surgical psychosocial risk factors for post-surgical alcohol consumption and hazardous drinking. Participants (N = 567) who underwent bariatric surgery between 2014 and 2017 reported their post-surgical alcohol use. Information was collected from the pre-surgical evaluation including history of alcohol use, psychiatric symptoms, and maladaptive eating behaviors (i.e., binge eating, purging, and emotional eating). Younger age and pre-surgical alcohol use predicted post-surgical alcohol use and hazardous drinking. In addition, higher levels of depressive symptoms and maladaptive eating patterns predicted post-surgical binge drinking. Clinicians conducting pre-surgical psychosocial evaluations should be aware of the multiple risk factors related to post-surgical problematic alcohol use. Future research should evaluate whether preventive interventions for high-risk patients decrease risk for post-surgical alcohol misuse

Weighing the Association Between BMI Change and Suicide Mortality

OBJECTIVE: Suicide rates continue to rise, necessitating the identification of risk factors. Obesity and suicide mortality rates have been examined, but associations among weight change, death by suicide, and depression among adults in the United States remain unclear. METHODS: Data from 387 people who died by suicide in 2000-2015 with a recorded body mass index (BMI) in the first and second 6 months preceding their death ( index date ) were extracted from the Mental Health Research Network. Each person was matched with five people in a control group (comprising individuals who did not die by suicide) by age, sex, index year, and health care site (N=1,935). RESULTS: People who died by suicide were predominantly male (71%), White (69%), and middle aged (mean age=57 years) and had a depression diagnosis (55%) and chronic health issues (57%) (corresponding results for the control group: 71% male, 66% White, 14% with depression diagnosis, and 43% with chronic health issues; mean age=56 years). Change in BMI within the year before the index date statistically significantly differed between those who died by suicide (mean change=-0.72±2.42 kg/m(2)) and the control group (mean change=0.06±4.99 kg/m(2)) (p\u3c0.001, Cohen\u27s d=0.17). A one-unit BMI decrease was associated with increased risk for suicide after adjustment for demographic characteristics, mental disorders, and Charlson comorbidity score (adjusted odds ratio=1.11, 95% confidence interval=1.05-1.18, p\u3c0.001). For those without depression, a BMI change was significantly associated with suicide (p\u3c0.001). CONCLUSIONS: An increased suicide mortality rate was associated with weight loss in the year before a suicide after analyses accounted for general and mental health indicators

Receipt of medications for opioid use disorder among youth engaged in primary care: data from 6 health systems

PURPOSE: Little is known about prevalence and treatment of OUD among youth engaged in primary care (PC). Medications are the recommended treatment of opioid use disorder (OUD) for adolescents and young adults (youth). This study describes the prevalence of OUD, the prevalence of medication treatment for OUD, and patient characteristics associated with OUD treatment among youth engaged in PC. METHODS: This cross-sectional study includes youth aged 16-25 years engaged in PC. Eligible patients had ≥ 1 PC visit during fiscal years (FY) 2014-2016 in one of 6 health systems across 6 states. Data from electronic health records and insurance claims were used to identify OUD diagnoses, office-based OUD medication treatment, and patient demographic and clinical characteristics in the FY of the first PC visit during the study period. Descriptive analyses were conducted in all youth, and stratified by age (16-17, 18-21, 22-25 years). RESULTS: Among 303,262 eligible youth, 2131 (0.7%) had a documented OUD diagnosis. The prevalence of OUD increased by ascending age groups. About half of youth with OUD had documented depression or anxiety and one third had co-occurring substance use disorders. Receipt of medication for OUD was lowest among youth 16-17 years old (14%) and highest among those aged 22-25 (39%). CONCLUSIONS: In this study of youth engaged in 6 health systems across 6 states, there was low receipt of medication treatment, and high prevalence of other substance use disorders and mental health disorders. These findings indicate an urgent need to increase medication treatment for OUD and to integrate treatment for other substance use and mental health disorders

Baseline representativeness of patients in clinics enrolled in the PRimary care Opioid Use Disorders treatment (PROUD) trial: comparison of trial and non-trial clinics in the same health systems

BACKGROUND: Pragmatic primary care trials aim to test interventions in real world health care settings, but clinics willing and able to participate in trials may not be representative of typical clinics. This analysis compared patients in participating and non-participating clinics from the same health systems at baseline in the PRimary care Opioid Use Disorders treatment (PROUD) trial. METHODS: This observational analysis relied on secondary electronic health record and administrative claims data in 5 of 6 health systems in the PROUD trial. The sample included patients 16-90 years at an eligible primary care visit in the 3 years before randomization. Each system contributed 2 randomized PROUD trial clinics and 4 similarly sized non-trial clinics. We summarized patient characteristics in trial and non-trial clinics in the 2 years before randomization ( baseline ). Using mixed-effect regression models, we compared trial and non-trial clinics on a baseline measure of the primary trial outcome (clinic-level patient-years of opioid use disorder (OUD) treatment, scaled per 10,000 primary care patients seen) and a baseline measure of the secondary trial outcome (patient-level days of acute care utilization among patients with OUD). RESULTS: Patients were generally similar between the 10 trial clinics (n = 248,436) and 20 non-trial clinics (n = 341,130), although trial clinics\u27 patients were slightly younger, more likely to be Hispanic/Latinx, less likely to be white, more likely to have Medicaid/subsidized insurance, and lived in less wealthy neighborhoods. Baseline outcomes did not differ between trial and non-trial clinics: trial clinics had 1.0 more patient-year of OUD treatment per 10,000 patients (95% CI: - 2.9, 5.0) and a 4% higher rate of days of acute care utilization than non-trial clinics (rate ratio: 1.04; 95% CI: 0.76, 1.42). CONCLUSIONS: trial clinics and non-trial clinics were similar regarding most measured patient characteristics, and no differences were observed in baseline measures of trial primary and secondary outcomes. These findings suggest trial clinics were representative of comparably sized clinics within the same health systems. Although results do not reflect generalizability more broadly, this study illustrates an approach to assess representativeness of clinics in future pragmatic primary care trials

Accounting for quality improvement during the conduct of embedded pragmatic clinical trials within healthcare systems: NIH Collaboratory case studies

Embedded pragmatic clinical trials (ePCTs) and quality improvement (QI) activities often occur simultaneously within healthcare systems (HCSs). Embedded PCTs within HCSs are conducted to test interventions and provide evidence that may impact public health, health system operations, and quality of care. They are larger and more broadly generalizable than QI initiatives, and may generate what is considered high-quality evidence for potential use in care and clinical practice guidelines. QI initiatives often co-occur with ePCTs and address the same high-impact health questions, and this co-occurrence may dilute or confound the ability to detect change as a result of the ePCT intervention. During the design, pilot, and conduct phases of the large-scale NIH Collaboratory Demonstration ePCTs, many QI initiatives occurred at the same time within the HCSs. Although the challenges varied across the projects, some common, generalizable strategies and solutions emerged, and we share these as case studies. KEY LESSONS: Study teams often need to monitor, adapt, and respond to QI during design and the course of the trial. Routine collaboration between ePCT researchers and health systems stakeholders throughout the trial can help ensure research and QI are optimally aligned to support high-quality patient-centered care

PRimary Care Opioid Use Disorders treatment (PROUD) trial protocol: a pragmatic, cluster-randomized implementation trial in primary care for opioid use disorder treatment

BACKGROUND: Most people with opioid use disorder (OUD) never receive treatment. Medication treatment of OUD in primary care is recommended as an approach to increase access to care. The PRimary Care Opioid Use Disorders treatment (PROUD) trial tests whether implementation of a collaborative care model (Massachusetts Model) using a nurse care manager (NCM) to support medication treatment of OUD in primary care increases OUD treatment and improves outcomes. Specifically, it tests whether implementation of collaborative care, compared to usual primary care, increases the number of days of medication for OUD (implementation objective) and reduces acute health care utilization (effectiveness objective). The protocol for the PROUD trial is presented here. METHODS: PROUD is a hybrid type III cluster-randomized implementation trial in six health care systems. The intervention consists of three implementation strategies: salary for a full-time NCM, training and technical assistance for the NCM, and requiring that three primary care providers have DEA waivers to prescribe buprenorphine. Within each health system, two primary care clinics are randomized: one to the intervention and one to Usual Primary Care. The sample includes all patients age 16-90 who visited the randomized primary care clinics from 3 years before to 2 years after randomization (anticipated to be \u3e 170,000). Quantitative data are derived from existing health system administrative data, electronic medical records, and/or health insurance claims ( electronic health records, [EHRs]). Anonymous staff surveys, stakeholder debriefs, and observations from site visits, trainings and technical assistance provide qualitative data to assess barriers and facilitators to implementation. The outcome for the implementation objective (primary outcome) is a clinic-level measure of the number of patient days of medication treatment of OUD over the 2 years post-randomization. The patient-level outcome for the effectiveness objective (secondary outcome) is days of acute care utilization [e.g. urgent care, emergency department (ED) and/or hospitalizations] over 2 years post-randomization among patients with documented OUD prior to randomization. DISCUSSION: The PROUD trial provides information for clinical leaders and policy makers regarding potential benefits for patients and health systems of a collaborative care model for management of OUD in primary care, tested in real-world diverse primary care settings

Long-term recall of social relationships related to addiction and HIV risk behaviors

BACKGROUND: Social relationships have been demonstrated as a key predictor of relapse among addicted persons and are likely to be important determinants of HIV risk behaviors also. However, the degree to which this population can reliably and consistently identify important people (IPs) in retrospect has been understudied. METHODS: Using the modified Important People and Activities questionnaire, we investigated to what degree IPs were dropped, added, or retained, and whether data about individual IPs were reported accurately on 6- and 12-month follow up periods using a sample of 50 drug or alcohol abusing participants. RESULTS: We found that IPs were largely retained, and that those retained versus dropped/added differed by their reaction to participant alcohol/drug use, as well as frequency of contact. We further found that there were differences in reliability of data describing specific IPs. While both 6- and 12-month follow up periods led to reliabilities ranging from excellent to fair, we found poorer reliability on responses to recall of frequency of contact and reactions to drinking , as well as reactions to drug use . CONCLUSION: Future investigations of reliability of social relationships recalled retrospectively should attempt to examine possible systematic biases in addition to the reliability of specific IP data. More sophisticated studies are needed on factors associated with systematic variation in reporting of aspects of social relationships that are associated with addictions or HIV risk outcomes

A Comparison of Long- vs. Short-Term Recall of Substance Use and HIV Risk Behaviors

OBJECTIVE: The Timeline Follow-back (TLFB) questionnaire has become a pre-eminent tool in substance use and human immunodeficiency virus (HIV) risk research, allowing researchers to assess fine-grained changes in risk behavior over long periods. However, data on accuracy of recall over long (12-month) periods are sparse, especially combined data on HIV risk and substance use from post-treatment samples. Studies on the development of substance use and HIV risk stand to benefit from data on the accurate recall of such behavior over longer retroactive spans of time. METHOD: The present study offers data on the test-retest reliability of current TLFB assessment versus 6- and 12-month delayed TLFB assessment, using a post-treatment sample (n = 50). RESULTS: Long-term reliability of TLFB data on HIV risk was predominantly good to excellent, with 13 of 20 assessed variables in that range. TLFB data on substance use was similar, with 22 of 26 variables resulting in good/excellent reliability. CONCLUSIONS: Our findings support the notion that, notable exceptions aside, the TLFB may be effectively used to assess retroactive HIV risk and substance use in periods of 12 months

Eating pathology and depressive symptoms as predictors of excessive weight gain during pregnancy

Excessive gestational weight gain is associated with negative outcomes and the identification of contributing psychosocial factors may be useful in prevention and intervention. Pregnant women (N = 70) completed self-report measures of eating pathology, depressive symptomatology, and gestational weight gain. Global eating pathology was positively associated with overvaluation of shape and weight, dietary restraint, frequency of binge eating, and depressive symptoms. Depressive symptoms significantly predicted excessive gestational weight gain, while global eating pathology predicted excessive gestational weight gain at a trend level. Results suggest that depressive symptoms more strongly predict excessive gestational weight gain than eating pathology

Trauma-informed parenting intervention for veterans: A preliminary uncontrolled trial of Strength at Home-Parents

Trauma exposure and posttraumatic stress disorder (PTSD) are highly prevalent in military and veteran populations and are associated with parenting difficulties. Unfortunately, there is a lack of accessible, trauma-informed, and evidence-based parenting support interventions within the Department of Veterans Affairs (VA). Strength at Home-Parents (SAHP) is a trauma-informed psychotherapy group that aims to improve parenting behaviors and overall parent-child and family functioning among U.S. military veterans with PTSD symptoms. SAHP was developed to maximize ease of use by VA providers and accessibility for parents. Here we report data from an uncontrolled trial of SAHP delivered using synchronous video technology in a sample of veterans using VA care (N = 53) who met the criteria for PTSD and parent-child functioning difficulties. Enrollment and retention rates met study goals and suggest feasibility and acceptability of study methods. Significant pre- to postintervention improvements were observed in measures of dysfunctional discipline, parenting stress, general family functioning, child psychosocial functioning, and parental PTSD and depression symptoms. Coupled with high satisfaction ratings, findings support further study of the intervention, including in an efficacy trial