Behavioral weight management use in the Veterans Health Administration: Sociodemographic and health correlates.

INTRODUCTION: Over 40 % of United States Veterans Health Administration (VHA) primary care patients have obesity. Few patients use VHA's flagship weight management program, MOVE! and there is little information on other behavioral weight management program use. METHODS: The national United States cohort included over 1.5 million primary care patients with obesity, age 18-79, based on VHA administrative data. Gender stratified multivariable logistic regression identified correlates of weight management use in the year after a patient's first primary care appointment (alpha of 0.05). Weight management use was defined as MOVE! or nutrition clinic visits. RESULTS: The cohort included 121,235 women and 1,521,547 men with 13 % and 7 % using weight management, respectively. Point estimates for specific correlates of use were similar between women and men, and across programs. Black patients were more likely to use weight management than White patients. Several physical and mental health diagnoses were also associated with increased use, such as sleep apnea and eating disorders. Age and distance from VHA were negatively associated with weight management use. CONCLUSIONS: When assessing multiple types of weight management visits, weight management care in VHA appears to be used more often by some populations at higher risk for obesity. Other groups may need additional outreach, such as those living far from VHA. Future work should focus on outreach and prevention efforts to increase overall use rates. This work could also examine the benefits of tailoring care for populations in greatest need.

Black Veterans Experiences with and Recommendations for Improving Weight-Related Health Care: A Photovoice Study.

BACKGROUND: Non-Hispanic Black or African American (hereafter Black) veterans lose less weight than other users of the Veterans Health Administration's (VHA) weight management program (MOVE!), despite higher enrollment. OBJECTIVE: To understand factors that affect weight loss disparities between Black veterans and other veterans. DESIGN: Qualitative study using Photovoice methods. PARTICIPANTS: Self-identified Black veterans in MOVE! across the USA (two women, seven men). APPROACH: We conducted six virtual Photovoice sessions with Black veterans. Session one provided orientation to the goal of understanding factors that might affect weight loss disparities. Participants chose missions related to weight management and VHA care, bringing photos or other media (e.g., poems) to discuss during remaining sessions. Facilitators/participants identified themes related to each session in real time. Between and after sessions, facilitators/investigators conducted rapid qualitative analysis of transcripts/audio to group similar themes, identify illustrative quotes/photos/other media, and prepare dissemination products (e.g., this manuscript). Participants provided feedback on the manuscript during an additional session. KEY RESULTS: Themes were identified across three categories: (1) Food in Our Lives and Health Care; (2) Body Image; and (3) Healthcare Bias and Discrimination. The emotional impact of food and the negative effects of bias and discrimination on health care quality and trust were especially salient. Participants provided recommendations for weight-related and general care. Notable recommendations included the need for VHA to hire and retain providers-especially Black providers-who understand and respect Black patients and are committed to delivering evidence-based, culturally sensitive care. In addition, weight management care should be tailored to individual patients' diets and health beliefs and deemphasize body mass index. CONCLUSIONS: Photovoice resulted in concrete targets that could reduce health disparities. Institutions should consider Photovoice and similar approaches to build trust with and incorporate input from marginalized communities. This approach requires sustained commitment from leaders to engage stakeholders and implement solutions.

Engagement and Use of a Blended mHealth Intervention for Health Behavior Change.

BACKGROUND: Blended mHealth interventions (mHealth interventions including a facilitator) promote user engagement and increase effectiveness of health behavior change interventions. Little is known about how blended mHealth interventions are used outside the research context. METHODS: In the present work, we characterized patterns of app use among users of a blended mHealth intervention in real-world conditions. Program users were Veterans Health Administration (VHA) primary care patients (n = 56) who received an invite code for a blended mHealth intervention between 2019 and 2021. Cluster analysis was used to examine user engagement with health coach visits and program features. RESULTS: Of patients who received an invite code, 34% initiated the program. Most users were men (63%) and white (57%). The mean number of health conditions was 5 (68% with obesity). The mean age was 55. Cluster analysis suggested that most users did sustain engagement at either moderate (57%) or very high levels (13%). The remaining 30% of users were low engaged users. Users completing any health coach visit (about half) reported more overall engagement than their counterparts who did not. Weight was the most frequently tracked metric. Of users entering weights in the first and last month of the program (n = 18), the mean percent body weight change was 4.0% (SD = 3.6). CONCLUSIONS: A blended mHealth intervention may be a scalable option to extend the reach of health behavior change interventions for those that use it. However, a significant portion of users do not initiate these interventions, choose not to use the health coach feature, or engage at lower levels. Future research should examine the role of health coaching visits in promoting sustained engagement.

Influence of depression on racial and ethnic disparities in diabetes control.

INTRODUCTION: We tested the hypotheses that depression diagnoses influence racial and ethnic disparities in diabetes control and that mental health treatment moderates that relationship. RESEARCH DESIGN AND METHODS: We created a national cohort of Veterans Health Administration (VHA) patients with diabetes using administrative data (n=815 067). Cross-sectional linear mixed effects regression models tested the hypothesized indirect effect of depression on poor diabetes control (glycosylated hemoglobin >9%) and tested whether mental health treatment (visits or antidepressant prescriptions) moderated the effect of depression (α=0.05). Results represent the percentage point difference in probability of poor diabetes control. Covariates included primary care visits, sex, age, and VHA facility. RESULTS: Overall, 20% of the cohort had poor diabetes control and 22% had depression. Depression was more common among racial and ethnic minoritized groups. The probability of poor diabetes control was higher for most minoritized groups compared with White patients (largest difference: American Indian or Alaska Native patients, 5.2% (95% CI 4.3%, 6.0%)). The absolute value of the proportion of racial and ethnic disparities accounted for by depression ranged from 0.2% (for Hispanic patients) to 2.0% (for Asian patients), with similar effects when accounting for the moderating effect of mental health treatment. Patients with depression and 5+ mental health visits had a lower probability of poor diabetes control compared with those with fewer visits, regardless of antidepressant prescription status. CONCLUSIONS: The influence of depression on disparities in diabetes control was small. High rates of depression among people with diabetes, especially among those from racial and ethnic minoritized groups, highlight a need to ensure equitable and coordinated care for both conditions, as the effects of mental health treatment may extend to the control of physical health conditions.

The EMBER trial for weight management engagement: A hybrid type 1 randomized controlled trial protocol.

BACKGROUND: Almost 40% of Veterans Health Administration (VHA) users have obesity. VHA's national weight management program is associated with weight loss and improved health. However, while 94% of eligible VHA users are offered weight management programs, <8% use them. We developed EMBER - a novel, Motivational Interviewing-based, self-help tool - with the goal of Enhancing Motivation for Better Engagement and Reach for weight management. EMBER is not a weight management program; instead it engages people in existing programs by informing and guiding choices about weight management. METHODS: The EMBER Trial is a randomized hybrid type 1 effectiveness implementation trial. Participants are Palo Alto or Houston VA Health Care System users with obesity who have not used a VHA weight management program in the past two years (target N = 470). Participants are randomly assigned to EMBER or an information-only control condition, after which they receive materials on paper or digitally, per their preference. The trial's primary goal is to determine whether participants randomized to EMBER are more likely to have any weight management engagement at two-month follow-up compared to those in the control condition. Secondary outcomes include 6-month retention in weight management, weight management behaviors, weight loss, quality of life, and implementation outcomes (e.g., reach, appropriateness). CONCLUSION: EMBER is the first self-directed, Motivational Interviewing-based intervention designed to increase weight management program engagement. The study takes a low-touch, population health approach that could be modified for other programs if effective. The Hybrid Type 1 design will ensure results can be scaled and sustained.

The efficacy of tobacco cessation treatment for African American adults: a systematic review.

Despite proliferation of evidence-based tobacco cessation treatments, African American adults still suffer higher rates of tobacco-related diseases than White adults. Although tobacco cessation treatment is efficacious, there is a need to reassess the efficacy of tobacco cessation treatment for African American adults. Previous reviews of tobacco cessation treatment studies conducted through 2007 among African American adults highlight the limited research in this area and inconsistent findings on treatment characteristics impacting efficacy. This systematic review examined the efficacy of combined behavioral and pharmacological tobacco cessation treatment for African American adults. Database searches were used to identify studies examining tobacco cessation treatment for predominantly African American samples (>50%). Eligible studies were completed between 2007 and 2021 and (i) involved randomization comparing active combined treatment to a control comparison group and (ii) reported abstinence outcomes at 6 and/or 12 months. Ten studies met inclusion criteria. Active treatment groups typically consisted of a combination of nicotine replacement therapy and behavioral counseling. Abstinence rates for African American adults ranged from 10.0% to 34% in active treatment groups compared to 0.0%-40% in comparison control groups. Our results support the efficacy of combined treatment for tobacco cessation among African American adults. However, cessation rates for African American adults found in this review are lower than those in the general adult population (15%-88%). Additionally, our findings highlight the limited number of studies examining African American tobacco cessation rates and testing of tailored treatment for this population.

African American adults are more likely to develop disease when using tobacco products than other adults. Previous reviews of literature assessing tobacco cessation treatment have been conducted on research until 2007. Therefore, we assessed how well tobacco cessation treatments that were tested 2007­2021 work to decrease tobacco use for this population. We found that 10 studies tested tobacco cessation treatment with majority African American participants, in comparison to more standard treatment. Overall, tobacco cessation treatment that combines behavioral and pharmacological approaches decreases tobacco use for African American adults. However, quit rates among African American adults are lower than those found in the general population. Our findings indicate that very few studies have focused on African American adult tobacco cessation treatment outcomes, which has potentially contributed to health inequity.

Weight Management Treatment Representations: A Novel Use of the Common Sense Model.

We used the Common Sense Model to understand weight management treatment representations of diverse patients, conducting semistructured interviews with 24 veterans with obesity, recruited from multiple U.S. Veterans Health Administration facilities. We performed a directed content analysis to summarize representations and assess differences across demographic groups. Patients' representations were impacted by gender, socioeconomic status, and disability status, creating group differences in available treatment (e.g., disability-related limitations), negative consequences (e.g., expense), treatment timeline (e.g., men emphasized long-term lifestyle changes), and treatment models (e.g., women described medically driven models). Patients identified conventional representations aligning with medical recommendations and relating to positive consequences, long-term treatment timelines, and medically driven models. Finally, patients discussed risky representations, including undesirable attitudes related to short-term positive and negative consequences and long-term negative consequences. Applying the Common Sense Model emphasized diverse representations, influenced by patients' identities. Understanding representations may improve treatment to meet the needs of diverse preferences.

Common Sense Models of Obesity: a Qualitative Investigation of Illness Representations.

BACKGROUND: The Common Sense Model provides a framework to understand health beliefs and behaviors. It includes illness representations comprised of five domains (identity, cause, consequences, timeline, and control/cure). While widely used, it is rarely applied to obesity, yet could explain self-management decisions and inform treatments. This study answered the question, what are patients' illness representations of obesity?; and examined the Common Sense Model's utility in the context of obesity. METHODS: Twenty-four participants with obesity completed semi-structured phone interviews (12 women, 12 men). Directed content analysis of transcripts/notes was used to understand obesity illness representations across the five illness domains. Potential differences by gender and race/ethnicity were assessed. RESULTS: Participants did not use clinical terms to discuss weight. Participants' experiences across domains were interconnected. Most described interacting life systems as causing weight problems and used negative consequences of obesity to identify it as a health threat. The control/cure of obesity was discussed within every domain. Participants focused on health and appearance consequences (the former most salient to older, the latter most salient to younger adults). Weight-related timelines were generally chronic. Women more often described negative illness representations and episodic causes (e.g., pregnancy). No patterns were identified by race/ethnicity. CONCLUSIONS: The Common Sense Model is useful in the context of obesity. Obesity illness representations highlighted complex causes and consequences of obesity and its management. To improve weight-related care, researchers and clinicians should focus on these beliefs in relation to preferred labels for obesity, obesity's most salient consequences, and ways of monitoring change.

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.

Rapid conversion to virtual obesity care in COVID-19: Impact on patient care, interdisciplinary collaboration, and training.

Objective: The COVID-19 pandemic presents challenges to maintaining interdisciplinary collaboration while transitioning care to telehealth environments. This paper describes how an intensive weight management clinic rapidly transitioned from in-person only to a telehealth environment. Method: As a program evaluation project, changes to clinic procedures were tracked on a weekly basis. Patients were invited to complete phone surveys after clinic appointments from 1 May 2020 to 31 July 2020. The survey included 12 items rated on a 5-point scale ("strongly disagree" to "strongly agree"). Results: Adaptations included converting team meetings and clinical training to phone/video platforms and transferring a complex patient tracking system to an interactive virtual format. Fifty-eight patients completed phone surveys (81% response rate). All "agreed" or "strongly agreed" that they were satisfied with telehealth care; 51% "agreed" or "strongly agreed" that telephone visits were as good as in-person visits; and 53% preferred phone appointments even after pandemic restrictions are eased. Conclusions: It is feasible to rapidly transition to a telehealth clinic when supported by infrastructure and resources of a national, integrated healthcare system. Patient preferences include access to both telehealth and in-person services. A blended telehealth/in-person model that maintains interdisciplinary collaboration and training is necessary even after the COVID-19 pandemic.

Anti-Black racism and behavioral medicine: confronting the past to envision the future.

Behavioral medicine research and practice have not traditionally acknowledged the detrimental effects of anti-Black racism (and other forms of systemic oppression) on health, interventions, or research. This commentary describes four ways that behavioral medicine researchers and clinicians can address the past to envision the future of behavioral medicine to promote equitable health for all: 1) name anti-Black racism, 2) ensure interventions address structural inequities, 3) advocate for systemic change, and 4) change expectations for publications.

Adoption and Appropriateness of mHealth for Weight Management in the Real World: A Qualitative Investigation of Patient Perspectives.

BACKGROUND: Mobile health (mHealth) interventions for weight management can result in weight loss outcomes comparable to in-person treatments. However, there is little information on implementing these treatments in real-world settings. OBJECTIVE: This work aimed to answer two implementation research questions related to mHealth for weight management: (1) what are barriers and facilitators to mHealth adoption (initial use) and engagement (continued use)? and (2) what are patient beliefs about the appropriateness (ie, perceived fit, relevance, or compatibility) of mHealth for weight management? METHODS: We conducted semistructured interviews with patients with obesity at a single facility in an integrated health care system (the Veterans Health Administration). All participants had been referred to a new mHealth program, which included access to a live coach. We performed a rapid qualitative analysis of interviews to identify themes related to the adoption of, engagement with, and appropriateness of mHealth for weight management. RESULTS: We interviewed 24 veterans, seven of whom used the mHealth program. Almost all participants were ≥45 years of age and two-thirds were White. Rapid analysis identified three themes: (1) coaching both facilitates and prevents mHealth adoption and engagement by promoting accountability but leading to guilt among those not meeting goals; (2) preferences regarding the mode of treatment delivery, usability, and treatment content were barriers to mHealth appropriateness and adoption, including preferences for in-person care and a dislike of self-monitoring; and (3) a single invitation was not sufficient to facilitate adoption of a new mHealth program. Themes were unrelated to participants' age, race, or ethnicity. CONCLUSIONS: In a study assessing real-world use of mHealth in a group of middle-aged and older adults, we found that-despite free access to mHealth with a live coach-most did not complete the registration process. Our findings suggest that implementing mHealth for weight management requires more than one information session. Findings also suggest that focusing on the coaching relationship and how users' lives and goals change over time may be an important way to facilitate engagement and improved health. Most participants thought mHealth was appropriate for weight management, with some nevertheless preferring in-person care. Therefore, the best way to guarantee equitable care will be to ensure multiple routes to achieving the same behavioral health goals. Veterans Health Administration patients have the option of using mHealth for weight management, but can also attend group weight management programs or single-session nutrition classes or access fitness facilities. Health care policy does not allow such access for most people in the United States; however, expanded access to behavioral weight management is an important long-term goal to ensure health for all.

Systematic Decision-Making for Using Technological Strategies to Implement Evidence-Based Interventions: An Illustrated Case Study.

Technology can improve implementation strategies' efficiency, simplifying progress tracking and removing distance-related barriers. However, incorporating technology is meaningful only if the resulting strategy is usable and useful. Hence, we must systematically assess technological strategies' usability and usefulness before employing them. Our objective was therefore to adapt the effort-vs-impact assessment (commonly used in systems science and operations planning) to decision-making for technological implementation strategies. The approach includes three components - assessing the effort needed to make a technological implementation strategy usable, assessing its impact (i.e., usefulness regarding performance/efficiency/quality), and deciding whether/how to use it. The approach generates a two-by-two effort-vs-impact chart that categorizes the strategy by effort (little/much) and impact (small/large), which serves as a guide for deciding whether/how to use the strategy. We provide a case study of applying this approach to design a package of technological strategies for implementing a 5 A's tobacco cessation intervention at a Federally Qualified Health Center. The effort-vs-impact chart guides stakeholder-involved decision-making around considered technologies. Specification of less technological alternatives helps tailor each technological strategy within the package (minimizing the effort needed to make the strategy usable while maximizing its usefulness), aligning to organizational priorities and clinical tasks. Our three-component approach enables methodical and documentable assessments of whether/how to use a technological implementation strategy, building on stakeholder-involved perceptions of its usability and usefulness. As technology advances, results of effort-vs-impact assessments will likely also change. Thus, even for a single technological implementation strategy, the three-component approach can be repeatedly applied to guide implementation in dynamic contexts.

Rapid review of virus risk communication interventions: Directions for COVID-19.

OBJECTIVE: In response to COVID-19, we conducted a rapid review of risk communication interventions to mitigate risk from viruses to determine if such interventions are efficacious. METHODS: We searched for risk communication interventions in four databases: Medline, PsycInfo, the ProQuest Coronavirus Research Database, and CENTRAL. The search produced 1572 articles. Thirty-one articles were included in the final review. RESULTS: Results showed risk communication interventions can produce cognitive and behavior changes around viruses. Results were more consistently positive for interventions focused on HIV/AIDS as compared to influenza. There was no consistent best intervention approach when comparing peer health, audio/visual, and intensive multi-media interventions. Tailoring risk communication toward a target population, in comparison to not tailoring, was related to better outcomes. CONCLUSION: The results suggest that risk communication interventions can be efficacious at reducing risk from viruses. They also highlight the complexity of risk communication interventions. Additional research is needed to understand the mechanisms that lead risk communication to reduce risk from viruses. PRACTICAL VALUE: Results support risk communication interventions to reduce risk from viruses.

BMI and Risk for Severe COVID-19 Among Veterans Health Administration Patients.

OBJECTIVE: The purpose of this study was to assess associations between BMI and severe coronavirus disease 2019 (COVID-19) outcomes: hospitalization, intensive care unit (ICU) admission, and mortality. A secondary aim was to investigate whether associations varied by age. METHODS: The cohort comprised patients in the Veterans Health Administration (VHA) who tested positive for COVID-19 (N = 9,347). For each outcome, we fit piecewise logistic regression models with restricted cubic splines (knots at BMI of 23, 30, and 39), adjusting for age, sex, comorbidities, VHA nursing home residence, and race/ethnicity. Supplemental analyses included age-by-BMI interaction terms (α = 0.05). RESULTS: We found evidence of a nonlinear J-curve association between BMI and likelihood of hospitalization and mortality. BMI was associated with increased odds for hospitalization, ICU admission, and mortality among patients with BMI 30 to 39 but decreased odds of hospitalization and mortality for patients with BMI 23 to 30. Patients under age 75 with BMI between 30 and 39 had increased odds for mortality with increasing BMI. CONCLUSIONS: Odds for severe outcomes with COVID-19 infection increased with increasing BMI for people with, but not without, obesity. This nonlinear relationship should be tested in future research. COVID-19 public health messages in VHA, and broadly, should incorporate information about risks associated with all classes of obesity, particularly for those under age 75.

Implementation Science to Address Health Disparities During the Coronavirus Pandemic.

The coronavirus disease 2019 (COVID-19) pandemic is disproportionally affecting racial and ethnic minorities. In the United States, data show African American, Hispanic, and Native American populations are overrepresented among COVID-19 cases and deaths. As we speed through the discovery and translation of approaches to fight COVID-19, these disparities are likely to increase. Implementation science can help address disparities by guiding the equitable development and deployment of preventive interventions, testing, and, eventually, treatment and vaccines. In this study, we discuss three ways in which implementation science can inform these efforts: (1) quantify and understand disparities; (2) design equitable interventions; and (3) test, refine, and retest interventions.

Differences in body mass index based on self-reported versus measured data from women veterans.

OBJECTIVE: The objective was to compare differences in body mass index (BMI) calculated with self-reported versus clinically measured pre-conception data from women veterans in California. METHODS: Veterans Health Administration (VHA) and California state birth certificate data were used to develop a cohort of women who gave birth from 2007-2012 and had VHA data available to calculate BMI (N = 1,326 mothers, 1,473 births). Weighted Kappa statistics assessed concordance between self-reported and measured BMI. A linear mixed-effects model with maximum likelihood estimation, adjusted for mother as a random effect, assessed correlates of differences in BMI. RESULTS: Mean BMI was in the overweight range based on self-reported (26.2 kg/m2, SD: 5.2) and measured (26.8 kg/m2, SD: 5.2) data. Weighted Kappa statistics indicated good agreement between self-reported and measured BMI (0.73, 95% CI: 0.70, 0.76). Compared to the normal weight group, groups with overweight or obesity were significantly more likely to have lower BMIs when calculated using self-reported versus measured heights and weights, in unadjusted and adjusted models. The finding was pronounced for class 3 obesity, which was associated with a BMI underestimation of 6.4 kg/m2. CONCLUSIONS: Epidemiologic research that guides the clinical care of pregnant women should account for potential under-estimation of BMI in heavier women, and perform direct measurement where feasible.

Mental Health Diagnostic Patterns in Behavioral Weight Loss Program Attendees.

INTRODUCTION: Individuals with obesity have higher rates of mental health disorders, both singly and in combination, than individuals of normal weight. Mental health disorders may negatively impact weight loss treatment outcomes; however, little is known about the mental health burden of individuals using weight loss programs. The current study identifies common mental health diagnostic profiles among participants of MOVE!-the Veterans Health Administration's behavioral weight loss program. MATERIAL AND METHODS: We used national VHA administrative data from fiscal year 2014 to identify veteran primary care patients who participated in at least one MOVE! session the previous year (n = 110,830). Using latent class analysis, we identified patient types (classes) characterized by the presence or absence of mental health diagnoses, both overall and stratified by age and gender. RESULTS: There were several patient types (classes), including psychologically healthy, predominantly depressed, depressed with co-occurring mental disorders, and co-occurring mental disorders with no predominant psychological condition. Additional patient types were found in men of different ages. The majority of patients had at least one psychiatric disorder, particularly younger patients. CONCLUSIONS: Efforts to improve patients' engagement in the MOVE! program may need to address barriers to care associated with mental health disorders or incorporate care for both obesity and mental health diagnoses in MOVE! A holistic approach may be particularly important for younger patients who have a higher comorbidity burden and longer care horizons. Future work may address if patient types found in the current study extend to non-VHA obesity treatment seekers.

Are Common Sense Model constructs and self-efficacy simultaneously correlated with self-management behaviors and health outcomes: A systematic review.

This systematic review answered two questions among adults with chronic conditions: When included in the same statistical model, are Common Sense Model constructs and self-efficacy both associated with (1) self-management behaviors and (2) health outcomes? We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and included 29 articles. When included in the same statistical model, Common Sense Model constructs and self-efficacy were both correlated with outcomes. Self-efficacy was more consistently associated with self-management behaviors, and Common Sense Model constructs were more consistently associated with health outcomes. Findings support the continued inclusion and integration of both frameworks to understand and/or improve chronic illness self-management and outcomes.

Mental Health and Obesity Among Veterans: A Possible Need for Integrated Care.

OBJECTIVE: The goal was to examine psychiatric diagnosis rates among a national cohort of primary care patients with and without obesity. METHODS: The cohort was derived from national Veterans Health Administration data (women, N=342,262; men, N=4,524,787). Sex-stratified descriptive statistics characterized psychiatric diagnosis rates. Chi-square tests determined whether diagnosis rates differed by obesity status (α=0.001). RESULTS: Rates of any psychiatric diagnosis were higher among women than among men and among people with obesity versus without obesity (women, 53.9% vs. 50.4%; men, 37.9% vs. 35.2%). Depression and posttraumatic stress disorder diagnosis rates were higher for people with obesity, and substance use disorder diagnosis rates were lower for people with obesity. Anxiety diagnosis rates were slightly lower among women with obesity versus women without obesity. CONCLUSIONS: Programs simultaneously addressing weight management and mental health could address the psychiatric comorbidities observed among people with obesity. Women are most likely to need these services.