Facility-level program components leading to population impact: a coincidence analysis of obesity treatment options within the Veterans Health Administration.

Obesity is a well-established risk factor for increased morbidity and mortality. Comprehensive lifestyle interventions, pharmacotherapy, and bariatric surgery are three effective treatment approaches for obesity. The Veterans Health Administration (VHA) offers all three domains but in different configurations across medical facilities. Study aim was to explore the relationship between configurations of three types of obesity treatments, context, and population impact across VHA using coincidence analysis. This was a cross-sectional analysis of survey data describing weight management treatment components linked with administrative data to compute population impact for each facility. Coincidence analysis was used to identify combinations of treatment components that led to higher population impact. Facilities with higher impact were in the top two quintiles for (1) reach to eligible patients and (2) weight outcomes. Sixty-nine facilities were included in the analyses. The final model explained 88% (29/33) of the higher-impact facilities with 91% consistency (29/32) and was comprised of five distinct pathways. Each of the five pathways depended on facility complexity-level plus factors from one or more of the three domains of weight management: comprehensive lifestyle interventions, pharmacotherapy, and/or bariatric surgery. Three pathways include components from multiple treatment domains. Combinations of conditions formed "recipes" that lead to higher population impact. Our coincidence analyses highlighted both the importance of local context and how combinations of specific conditions consistently and uniquely distinguished higher impact facilities from lower impact facilities for weight management.

Obesity can contribute to increased rates of ill health and earlier death. Proven treatments for obesity include programs that help people improve lifestyle behaviors (e.g., being physically active), medications, and/or bariatric surgery. In the Veterans Health Administration (VHA), all three types of treatments are offered, but not at every medical center­in practice, individual medical centers offer different combinations of treatment options to their patients. VHA medical centers also have a wide range of population impact. We identified high-impact medical centers (centers with the most patients participating in obesity treatment who would benefit from treatment AND that reported the most weight loss for their patients) and examined which treatment configurations led to better population-level outcomes (i.e., higher population impact). We used a novel analysis approach that allows us to compare combinations of treatment components, instead of analyzing them one-by-one. We found that optimal combinations are context-sensitive and depend on the type of center (e.g., large centers affiliated with a university vs. smaller rural centers). We list five different "recipes" of treatment combinations leading to higher population-level impact. This information can be used by clinical leaders to design treatment programs to maximize benefits for their patients.

National Veterans Health Administration MOVE! Weight Management Program Participation During the COVID-19 Pandemic.

INTRODUCTION: In response to COVID-19, the Veterans Health Administration (VHA) converted appropriate outpatient visits to virtual care, including MOVE! Weight Management Program for Veterans (MOVE!) visits. Before the pandemic, most veterans participated in MOVE! in person, with several telehealth modalities available. We sought to describe national trends in MOVE! participation during the pandemic (March 2020-January 2021) overall and by modality and to compare participation to prepandemic levels. METHODS: We conducted a national retrospective cohort study of veterans who participated in MOVE! from January 2018 through January 2021. We examined MOVE! participation across VHA aggregated at the national level by month, including the number of visits, participants, and new participants in person and via telehealth, including telephone, clinic-to-clinic synchronous video, anywhere-to-anywhere (eg, provider home to patient home) synchronous video, and remote education and monitoring. We also determined the percentage of all MOVE! visits attributable to each modality and the monthly percentage change in participation during the pandemic compared with monthly averages in prior years. RESULTS: Before March 2020, 20% to 30% of MOVE! was delivered via telehealth, which increased to 90% by April 2020. Early in the pandemic, telephone-delivered MOVE! was the most common modality, but anywhere-to-anywhere synchronous video participation increased over time. Compared with the same months in prior years, total monthly MOVE! participation remained 20% to 40% lower at the end of 2020 and into January 2021. CONCLUSION: The VHA MOVE! program rapidly shifted to telehealth delivery of weight management services in response to the pandemic. However, a gap remained in the number of veterans receiving these services compared with prior years, suggesting potential unmet needs for weight management.

Facility-level conditions leading to higher reach: a configurational analysis of national VA weight management programming.

BACKGROUND: While the Veterans Health Administration (VHA) MOVE! weight management program is effective in helping patients lose weight and is available at every VHA medical center across the United States, reaching patients to engage them in treatment remains a challenge. Facility-based MOVE! programs vary in structures, processes of programming, and levels of reach, with no single factor explaining variation in reach. Configurational analysis, based on Boolean algebra and set theory, represents a mathematical approach to data analysis well-suited for discerning how conditions interact and identifying multiple pathways leading to the same outcome. We applied configurational analysis to identify facility-level obesity treatment program arrangements that directly linked to higher reach. METHODS: A national survey was fielded in March 2017 to elicit information about more than 75 different components of obesity treatment programming in all VHA medical centers. This survey data was linked to reach scores available through administrative data. Reach scores were calculated by dividing the total number of Veterans who are candidates for obesity treatment by the number of "new" MOVE! visits in 2017 for each program and then multiplied by 1000. Programs with the top 40 % highest reach scores (n = 51) were compared to those in the lowest 40 % (n = 51). Configurational analysis was applied to identify specific combinations of conditions linked to reach rates. RESULTS: One hundred twenty-seven MOVE! program representatives responded to the survey and had complete reach data. The final solution consisted of 5 distinct pathways comprising combinations of program components related to pharmacotherapy, bariatric surgery, and comprehensive lifestyle intervention; 3 of the 5 pathways depended on the size/complexity of medical center. The 5 pathways explained 78 % (40/51) of the facilities in the higher-reach group with 85 % consistency (40/47). CONCLUSIONS: Specific combinations of facility-level conditions identified through configurational analysis uniquely distinguished facilities with higher reach from those with lower reach. Solutions demonstrated the importance of how local context plus specific program components linked together to account for a key implementation outcome. These findings will guide system recommendations about optimal program structures to maximize reach to patients who would benefit from obesity treatment such as the MOVE!

Construction and Use of Body Weight Measures from Administrative Data in a Large National Health System: A Systematic Review.

OBJECTIVE: Administrative data are increasingly used in research and evaluation yet lack standardized guidelines for constructing measures using these data. Body weight measures from administrative data serve critical functions of monitoring patient health, evaluating interventions, and informing research. This study aimed to describe the algorithms used by researchers to construct and use weight measures. METHODS: A structured, systematic literature review of studies that constructed body weight measures from the Veterans Health Administration was conducted. Key information regarding time frames and time windows of data collection, measure calculations, data cleaning, treatment of missing and outlier weight values, and validation processes was collected. RESULTS: We identified 39 studies out of 492 nonduplicated records for inclusion. Studies parameterized weight outcomes as change in weight from baseline to follow-up (62%), weight trajectory over time (21%), proportion of participants meeting weight threshold (46%), or multiple methods (28%). Most (90%) reported total time in follow-up and number of time points. Fewer reported time windows (54%), outlier values (51%), missing values (34%), or validation strategies (15%). CONCLUSIONS: A high variability in the operationalization of weight measures was found. Improving methods to construct clinical measures will support transparency and replicability in approaches, guide interpretation of findings, and facilitate comparisons across studies.

What's the influence of social interactions on substance use and treatment initiation? A prospective analysis among substance-using probationers.

INTRODUCTION: A person's social environment greatly affects the likelihood of substance use, which in turn affects risk for criminal behavior. This study examined how people's social environment early in probation contributed to later substance use and treatment outcome, both of which predict probation success. METHODS: Data were analyzed from a randomized controlled trial of substance-using probationers (N = 316). Moderation analyses assessed the relationship between social support near the start of probation and substance use and treatment initiation after 2 and 6 months. RESULTS: Abstinence at 2-months was associated with better baseline measures of support quality (more positive support, fewer negative interactions, and reduced conflict). Similar associations were identified for 6-month abstinence including better baseline quality, more positive support, and less family and peer conflict. There were no significant associations between the baseline social support and treatment initiation at 2-months. However, poorer baseline quality support and more negative interactions predicted increased treatment initiation at 6-months. CONCLUSIONS: Social support and the quality of an offender's social network have important implications for substance use and treatment compliance. The criminal justice system emphasizes ways to minimize negative social influences among offenders (i.e., probation conditions that limit contact with other offenders). However, this study suggests that behavior change is a function of not only reducing negative influences but also increasing positive or good quality supports.

The Effect of Childhood Household Dysfunction on Future HIV Risk among Probationers.

INTRODUCTION: Adverse childhood events (ACE) can lead to numerous health risks in adulthood. ACEs coupled with increased risk-taking behaviors can lead to increased risk for HIV infection, particularly in vulnerable populations. The purpose of this study was to determine if mental health symptom severity mediates the relationship between childhood household dysfunction and adult HIV risk among a group of probationers. METHODS: T-tests were used to evaluate associations between demographic characteristics and cumulative engagement in sexual risk behaviors in 282 drug-involved probationers. A mediation analysis was conducted to determine the direct and indirect effect of cumulative household dysfunction and high-risk sexual behaviors through mental health symptom severity. RESULTS: We found significant differences in the occurrence of different childhood household dysfunction problems by probationer gender, race, and criminal risk level. Mental health symptom severity demonstrated a significant indirect mediation effect of household dysfunction adverse events and engagement in sexual risky behaviors, b = .03, 95% BCa CI [.007, .057]. CONCLUSIONS: Given the high prevalence of childhood trauma in probationers and the direct associations with mental illness and sexual risk-taking behaviors, the need for offenders to have access to and receive mental health treatment while under community supervision is evident. Mental health and substance abuse treatment services can not only reduce risks for recidivism but also HIV infection and transmission within this population.

People's reasons for wanting to complete probation: Use and predictive validity in an e-health intervention.

The criminal justice system tends to emphasize external contingencies (e.g., fees, jail time) to motivate offender compliance. However, people's reasons for desistance vary considerably. This study evaluated the acceptability, utility, and predictive validity of questions that ask about people's reasons for wanting to successfully complete probation. Substance-using probationers (N=113) participated in a web-based computer intervention that targeted substance use and treatment initiation. Questions around seven dimensions of reasons for completing probation were developed to provide tailored feedback during the web-based program. A principle components factor analysis found that survey items loaded onto two distinct factors. Factor one, "Tangible Loss" focused on external and present-focused reasons. Factor two, "Better Life" focused on internal and future-focused reasons. There was a significant negative association between Better Life scores and days of substance use after two months (ß=-0.31, SE=0.13, p<0.05). There was a significant positive association with Better Life scores and days of treatment attendance (ß=1.46, SE=0.26, p<0.001). Tangible Loss scores were no associated with substance use and treatment attendance. These findings may help to create more effective motivational tracks in e-health interventions, and may complement traditional motivation measures with an explicit focus on people's stated reasons for wanting to complete probation.

Social support quality and availability affects risk behaviors in offenders.

BACKGROUND: People involved in the justice system are at 2.5 times the risk of HIV infection compared to the general population, which is further complicated by substance abuse. The purpose of this study was to evaluate the role of social network quality and quantity on unprotected sex, criminal risk, and substance use. METHODS: We used data from 330 drug-involved offenders. Structural equation modeling (SEM) was used to model and test path directionality and magnitude between the latent constructs of social support quality and quantity on risky behaviors. RESULTS: The SEM indicated the latent construct of social support quality was significantly associated with reduced sexual risk behavior (ß = -0.27), criminal risk (ß = -0.26), and reduced substance use (ß = -0.33). Additionally, the proposed model found that social support quantity was significantly positively associated with increased sexual risk behavior (ß = 0.40) and substance use (ß = 0.20). CONCLUSIONS: Social support quality is an important predictor of risky behaviors; as the quality of an offender's social support increases, engagement in risky behaviors decreases. Probationers who had broader social support availability also had increased substance use and unprotected sex. Probation systems may be able to reduce substance use and STD/HIV infection risk in offenders by strengthening the quality of social support networks.

Motivational Interviewing Fidelity in a Community Corrections Setting: Treatment Initiation and Subsequent Drug Use.

INTRODUCTION: Although substance use is common among people in the U.S. criminal justice system, treatment initiation remains an ongoing problem. This study assessed the reliability and predictive validity of the Motivational Interviewing Treatment Integrity 3.1.1. (MITI) coding instrument in a community corrections sample. METHODS: We used data from 80 substance-using clients who were participating in a clinical trial of MI in a probation setting. We analyzed 124 MI counseling sessions using the MITI, a coding system for documenting MI fidelity. Bivariate associations and logistic regression modeling were used to determine if MI-consistent behaviors predicted substance use or treatment initiation at a 2-month follow-up. RESULTS: We found a high level of agreement between coders on behavioral utterance counts. Counselors met at least beginning proficiency on most MITI summary scores. Probationers who initiated treatment at 2-month follow-up had significantly higher ratings of clinician empathy and MI spirit than clients who did not initiate treatment. Other MITI summary scores were not significantly different between clients who had initiated treatment and those who did not. MI spirit and empathy ratings were entered into a forward logistic regression in which MI spirit significantly predicted 2-month treatment initiation (χ(2) (1)=4.10, p<.05, R(2)=.05) but counselor empathy did not. MITI summary scores did not predict substance use at 2-month follow-up. CONCLUSIONS: Counselor MI-consistent relational skills were an important predictor of client treatment initiation. Counselor behaviors such as empathy and MI spirit may be important for developing client rapport with people in a probation setting.

The relationship between electronic goal reminders and subsequent drug use and treatment initiation in a criminal justice setting.

INTRODUCTION: Opportunities to influence behavior through the use of electronic reminders has not been examined in a criminal justice population. The purpose of this study was to assess probationer preferences for short-term goals from a web-based program and evaluate the role of voluntary electronic reminders (e.g., text messaging, email) in achieving early treatment and probation tasks. METHODS: We used data from drug-involved offenders (n=76) participating in a clinical trial of a 2-session motivational computer program. As part of the program, participants could choose to receive text or email reminders about their probation and treatment goals for the next month. Poisson regression models were utilized to evaluate goal and reminder selection in relation to the days of substance use and treatment attendance at two-month follow-up. RESULTS: The most common goals were related to probation and treatment tasks, relationships, and cognitive reappraisals. Forty-five percent of probationers elected to receive electronic goal reminders at Session 1 with a slight increase at Session two (49%). Probationers who opted to receive electronic goal reminders at Session one selected significantly more goals on average (M=4.4, SD=2.1) than probationers who did not want reminders (M=3.4, SD=1.8), (t=2.41, p=.019). Reminder selection and total number of goals selected predicted days of substance use and treatment attendance at a two-month follow-up. Probationers who opted not to receive electronic reminders and those who only chose to receive reminders at one visit had more days of substance use compared to those who chose to receive reminders at both visits, 1.66 and 2.31 times respectively. Probationers who chose not to receive electronic reminders attended 56% fewer days of treatment compared to those who chose to receive reminders at both visits. CONCLUSIONS: People's choice of short-term goals and reminders can provide advance notification of the likelihood of substance use and treatment initiation. Probation systems might use such information to triage at-risk probationers to a higher level of service, before problems have emerged.

Efficacy of SMS Text Message Interventions for Smoking Cessation: A Meta-Analysis.

BACKGROUND: Mobile technology provides new opportunities for health promotion communication. The purpose of this study was to conduct a current and extensive meta-analytic review of SMS (short message service) text message-based interventions for individual smoking cessation. METHODS: Academic Search Complete, PsycINFO, PubMed, and Scopus were reviewed for articles meeting selection criteria: 1) randomized controlled trials, 2) measured smoking cessation, and 3) intervention primarily delivered through SMS text messaging. Three and 6month follow-up of 7-day point prevalence or continuous abstinence was considered from studies meeting criteria. All analyses were conducted with intention-to-treat. Both fixed and random effects models were used to calculate the global outcome measure and confidence intervals. RESULTS: Thirteen studies were identified that met inclusion criteria. The studies were found to be homogeneous [Q12=12.47, p=0.14]. Odds ratios based on the random effects models suggested that interventions generally increased quit rates compared to controls, 1.36 [95% CI=1.23, 1.51]. Intervention efficacy was higher in studies with a 3month follow-up compared to 6month follow-up. Text plus programs (e.g., text messaging plus Web or in-person intervention modalities) performed only slightly better than text only programs. Pooled results also indicate message frequency schedule can affect quit rates, in which fixed schedules performed better than decreasing or variable schedules. The use of quit status assessment messages was not related to intervention efficacy. CONCLUSION: Smoking quit rates for the text messaging intervention group were 36% higher compared to the control group quit rates. Results suggest that SMS text messaging may be a promising way to improve smoking cessation outcomes. This is significant given the relatively wide reach and low cost of text message interventions. Identifying the components that make interventions efficacious will help to increase the effectiveness of such interventions.