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Development of a Weight Maintenance Intervention for Bariatric Surgery Patients
Bariatric surgery is an effective treatment for patients with severe obesity. When compared to non-surgical treatment options, bariatric surgery results in greater weight loss, comorbidity remission, and quality of life improvement, and is associated with an extended lifespan. However, weight regain after bariatric surgery is a significant concern because it can be associated with recurrence of obesity-related comorbidities such as diabetes. Major factors in undesirable weight gain following bariatric surgery include poor compliance with post-operative dietary recommendations and lack of physical activity. To improve patient adherence to these recommended lifestyle behaviors, effective behavioral strategies are needed. Our team developed a theoretically informed behavioral weight loss maintenance intervention that is delivered by telephone, which enhances access, facilitates individualized problem solving compared to group-based delivery, and is scalable for the health system. This intervention led to significantly less regain following a behavioral weight loss intervention.
Our long-term goal is to extend this work to reduce weight regain in the bariatric surgery population. To prepare for a future trial, we will conduct a pilot study to refine the intervention, establish enrollment procedures, and evaluate feasibility and acceptability of the intervention for patients who undergo bariatric surgery.
This study involves a pre-post, within-subject design. Up to 30 Veterans will be enrolled one year following bariatric surgery performed at one of four VA sites. The intervention will be delivered by telephone for 16 weeks, with frequency decreasing from weekly to biweekly.
- Aim 1: Refine telephone intervention scripts to address dietary, mobility, and behavioral issues specific to bariatric surgery patients.
- Aim 2: Evaluate feasibility of conducting a multi-site trial, as indicated by recruitment and outcome assessment rates.
- Aim 3: Evaluate intervention acceptability, as indicated by intervention adherence rates, pre-post changes in weight and process measures.
Impact of Family History and Decision Support on High-risk Cancer Screening
Although FHH is commonly accepted as an important risk factor for common, chronic diseases, it is rarely used in clinical practice as part of a structured risk assessment. To facilitate use of FHH in primary care, the Genomic Medicine Model (GMM) was developed. The GMM 1) provides education to physicians, patients, and communities on the importance of FHH; 2) contains a health IT-based platform (MeTree) that uses patient-entered data to risk-stratify patients and generate risk-stratified, evidence-based preventive care recommendations for physicians and patients; and 3) provides resources to patients and providers to effectively interpret FHH information and adhere to recommendations. Collection of FHH to inform preventive care for colorectal cancer (CRC) in VA is important because patients at higher risk for CRC are not well-characterized or documented in VA and high-risk versus average-risk prevention strategies currently are not systematically assessed or measured.
The goal of this study is to evaluate the feasibility and effectiveness of the GMM for identifying patients at increased risk for CRC. This goal will be achieved in a 4-year mixed methods study with the following aims: Aim 1: Determine whether FHH collection via MeTree improves identification of patients at higher familial risk for CRC by comparing rates of high-risk identification in the medical record prior to study enrollment to rates of high-risk identification following MeTree completion. Aim 2: Evaluate whether providing decision support to patients and PCPs improves risk-appropriate PCP referrals for, and patient uptake of, CRC screening/surveillance. Aim 3: Assess experience with decision support and effects on workflow from PCPs, and obtain information to inform eventual implementation in the VA healthcare system from administrative leaders, via qualitative interviews. Aim 4: Conduct cost-consequence and budget-impact analyses of implementing FHH collection and GMM decision support in VA.
Eligible patients are aged 40-65 years, enrolled in primary care, do not have a personal history of CRC, and have some knowledge of FHH. In Aim 1, a retrospective chart review will be conducted to determine the baseline rate of documenting FHH of CRC in the medical record for patients enrolled in the Aim 2 randomized trial. In Aim 2, consented patients will be randomized to provide patient-entered FHH and receive patient and provider decision support at enrollment or 12 months later (wait-list control). The primary outcome is risk-appropriate CRC screening/surveillance referral for patients 12 months post-enrollment. Secondary outcomes include patient uptake of recommendations and referral for genetic consultation 12 months post-enrollment. In Aim 3, qualitative interviews will be conducted with physicians and clinic leaders; data will be analyzed using conventional content analysis. In Aim 4, data will be obtained from the administrative databases and patient medical records to conduct a budget impact analysis.
Incentivizing Behavior Change Skills to Promote Weight Loss
Two-thirds of the United States population is now classified as obese or overweight. Despite the existence of effective behavioral weight loss interventions, many people do not adhere to them, and even people who lose significant weight regain it in the year following intervention. Novel methods are needed to improve adherence to effective weight loss interventions and promote long-term weight loss maintenance. One promising strategy is reinforcement via financial incentives. Positive reinforcement with variable-ratio schedules has received theoretical and empirical support in various behavioral domains. However, the few studies testing this type of strategy for weight loss have been largely ineffective. A key issue is whether incentives should be provided for process (e.g., dietary self-monitoring) or outcome (weight loss). Incenting dietary self-monitoring and weight loss may be more effective than incenting either alone. In previous studies, patients had to attend in-person sessions to turn in self-monitoring records and be weighed, so self-monitoring and interim weight loss were confounded with attendance. To deliver incentives in real-time for dietary self-monitoring and interim weight loss alone, data collection and processing must be automated.
We will develop an innovative information technology (IT) solution that will collate dietary self-monitoring data (input by patients via a mobile phone dietary application) and weight loss data (input by patients via remote scale). An algorithm will classify participants as achieving adequate or inadequate dietary self-monitoring and weight loss to earn intermittent rewards of varying value in real-time. Specific aims are: (1) Determine feasibility and acceptability of using automated algorithms that analyze dietary self-monitoring and interim weight loss data to provide real-time reinforcement using variable-ratio incentives; (2) Evaluate the effectiveness of various recruitment methods and describe recruitment, intervention adherence, and outcome assessment adherence rates; (3) Estimate cost of delivering the intervention and cost to patients.
In this study, obese community outpatients will participate in an effective, 24-week weight loss program delivered via biweekly group classes. Participants will be randomized to receive incentives for self-monitoring (yes vs. no) and/or interim weight loss (yes vs. no). We will calculate recruitment, retention, and intervention adherence rates as well as weight at weeks 0 and 24. This project will provide the foundation for a comprehensive effectiveness trial to test the impact of incenting dietary self-monitoring and interim weight loss on short- and longer-term weight outcomes while incentives are delivered and once they are withdrawn.
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Self-reported Medication Nonadherence Measurement
Maintenance After Initiation of Nutrition TrAINing (MAINTAIN)
Obesity is the second leading cause of preventable deaths in the United States and is associated with a wide range of diseases. In people who are obese, weight loss improves blood pressure, dyslipidemia, glycemia, and arthritis symptoms; reduces medication use for several disease processes; increases physical functioning; and enhances health-related quality of life. Despite these benefits, most patients who achieve weight loss regain much of this weight within a year, and few effective behavioral weight maintenance interventions have been identified. Thus, there is a dire need for effective interventions that can promote weight loss maintenance. Theoretical and empirical studies indicate that behavior maintenance is a distinct state that involves different psychological processes and behavioral skills than initial behavior change. The few trials that have tested weight loss maintenance interventions have not taken this distinction into account, which may partially explain their modest findings.
The purpose of this randomized controlled trial was to determine whether a theoretically informed maintenance intervention would decrease weight regain and improve caloric intake and physical activity compared to usual care.
This 3.5-year study involved a two-group, parallel, randomized trial stratified by initial weight loss (<10 kg vs. ≥10 kg), conducted from 20 August 2012 to 18 December 2015. During the run-in phase, veterans aged ≤ 75 with BMI ≥30 kg/m2 participated in a 16-week, intensive, group-based weight loss program. Participants who lost at least 4 kg by the end of 16 weeks were randomized to receive (a) usual care for 56 weeks or (b) a theoretically-informed maintenance intervention for 42 weeks, followed by 16 weeks of no further intervention contact to examine sustainability. The maintenance intervention involved three in-person group visits that transitioned to individualized telephone calls, and the frequency of contact with the interventionist gradually tapered over time. Outcomes were assessed at the time of randomization and at 14, 26, 42, and 56 weeks post-randomization.
Of 504 patients in the initial program, 222 lost at least 4 kg of body weight and were randomly assigned to maintenance (n = 110) or usual care (n = 112). Retention was 85%. Patients were 61.8 years old on average; 58% were White, 37% were Black, and 85% were male. Mean weight loss during initiation was 7.2 kg (SD, 3.1); mean weight at randomization was 103.6 kg (SD, 20.4). Estimated mean weight regain was statistically significantly lower in the intervention (0.75 kg) than the usual care (2.36 kg) group (estimated mean difference, 1.60 kg [95% CI, 0.07 to 3.13 kg]; P = 0.04). No statistically significant differences in secondary outcomes were seen at 56 weeks. No adverse events directly attributable to the intervention were observed. Intervention cost was $88.58 per participant for the group-based initiation intervention and $276.19 per participant for the individual maintenance intervention.
An intervention focused on maintenance-specific strategies and delivered in a resource-conserving way modestly slowed the rate of weight regain in obese adults. The next step in this program of research is to refine the intervention to help patients maintain weight loss following weight loss surgery. Ultimately, sustained weight loss could reduce obesity-related health care utilization and costs.
Genetic Testing for Type 2 Diabetes
Type 2 diabetes mellitus (DM) is debilitating, deadly, and costly whose prevalence is increasing. Although the development of DM can be delayed or prevented by lifestyle changes, changes initiated too late may not delay DM onset indefinitely. Therefore, it is imperative to intervene earlier and to find new ways to increase motivation to initiate and maintain lifestyle changes. Risk communication is a key part of effective lifestyle behavior change strategies. Risk for DM has traditionally been estimated using patient age, sex, race, body mass index (BMI), family history of DM, and fasting plasma glucose (FPG) level. Genetic polymorphisms associated with the incidence of DM have been discovered and may further personalize risk, particularly because lifestyle changes can prevent DM even in patients with the polymorphisms. The ability of genetic test results to demonstrate improvement in patients’ health outcomes is unknown, posing a major obstacle to translation.
In this randomized trial, we examined whether supplementing conventional DM risk counseling with communication of DM-related genetic test results affected clinical and behavioral outcomes.
Participants were Veteran outpatients aged 21-65 with body mass index (BMI) ≥ 27 and without DM. At baseline, fasting plasma glucose (FPG), family history of DM, and lifetime DM risk (based on age, sex, race, and BMI) were assessed. Patients were randomized to the genetic test (CR+G) or attention control eye disease counseling (CR+EYE) arm; randomization was stratified by family history of DM (unknown/low vs. moderate/high) and BMI (<35 vs. ≥35). Two to four weeks following enrollment, participants attended a DM risk counseling session conducted by a genetic counselor. Participants received personalized DM risk estimates based on their baseline FPG, family history, and lifetime risk; for each risk factor, participants were classified as being at low, moderate, or high risk. The genetic counselor then opened an envelope to reveal the randomization assignment; participants received either DM genetic test results or attention control eye disease counseling immediately thereafter. The session concluded with brief goal setting related to weight loss, diet, and physical activity, followed by assessment of perceived risk and illness representations. Three and 6 months post-baseline, participants returned for outcome assessments. The primary outcome was weight at 3 months. Secondary outcomes included perceived risk immediately following counseling; HOMA-IR, self-reported dietary intake and physical activity, and perceived risk at 3 and 6 months; and weight at 6 months. Linear mixed models were fit for weight, perceived risk, HOMA-IR, and dietary variables; generalized linear mixed models using a negative binomial distribution with a log link were used for walking and moderate physical activity. Outcomes were transformed when necessary to meet normal distributional assumptions. Models included a common intercept, time effect, time*treatment interaction, and randomization stratification variables (family history and BMI).
A total of 601 participants were enrolled; 303 were randomized to CR+G and 298 to CR+G. Mean age was 54 years, 42% were White, 53% were Black, 80% were male, 30% had BMI ≥ 35, and 52% had moderate/high family-history-based DM risk. Estimated mean weight did not differ between arms at 3 months [(CR+G)−(CR+EYE) = 0.2 kg, 95 % CI: −0.3, 0.7; p = 0.44] or at 6 months (mean difference = 0.4 kg, 95 % CI: −0.3, 1.1; p = 0.27), nor did insulin resistance (HOMA2-IR) (p = 0.19 and 0.12 at 3 and 6 months, respectively). Daily calorie intake was lower in the CR+G arm than the CR+EYE arm at 3 months (p =0.05), but there was no difference between arms at 6 months (p = 0.20). The percentage of calories from carbohydrates, protein, fat, and saturated fat intake did not differ between arms at 3 or 6 months (all p ≥ 0.07). Monounsaturated fat and polyunsaturated fat were lower in the CR+G than the CR+EYE arm at 3 months (all p ≤ 0.04) but not at 6 months (all p ≥ 0.26). There were no between-arm differences in the estimated duration of moderate-intensity physical activity or walking at 3 or 6 months (all p > 0.22). Given an estimated $7.00 per session in overhead costs, genetic testing cost of $125, and blood draw cost of $3.00 per participant, the total intervention cost was $207.03 for the first genetic counselor and $178.78 for the second.
Providing patients with genetic test results was not more effective in changing patient behavior to reduce the risk of DM compared to conventional risk counseling. Because genetic testing for DM did not make a clinically important impact on patients at risk for DM, it may not be appropriate for widespread implementation.
A Patient-Spouse Intervention for Self-Managing High Cholesterol (CouPLES)
Coronary heart disease is a leading cause of death and nonfatal heart attacks. Self-management of common risk factors such as elevated low-density lipoprotein cholesterol (LDL-C) is important for reducing risk for future coronary events. Patient self-management interventions involving significant lifestyle changes have shown limited effectiveness. The effectiveness could be enhanced by targeting spouses, who function as informal caregivers.
We conducted a randomized, controlled trial to determine whether a spouse-supported, self-management intervention would improve LDL-C and related health behaviors in patients with elevated LDL-C.
255 veterans who were married and had LDL-C > 76 mg/dL were randomized with their spouses to the usual care or intervention arm. The intervention involved monthly phone calls from a nurse involving goal setting (for patients) or providing support for goal achievement (spouses). The primary outcome was LDL-C at 11 months. Secondary outcomes were dietary intake and frequency and duration of moderate intensity exercise. Linear mixed modeling was used to compare outcomes between arms adjusting for baseline randomization stratification variables (White vs. Black race and low vs. medium/high coronary heart disease risk level). Because the distributions of the dietary variables were skewed, a square root transformation was conducted to normalize model residuals.
Patients were 95% male and 65% White. Mean (SD) baseline LDL-C was 126.3 (26.3) mg/dL. LDL-C did not differ between groups (mean difference=2.3 mg/dL, 95% CI=−3.6, 8.3, p=0.44), nor did the odds of meeting goal LDL-C (OR=0.95, 95% CI=0.6, 1.7; p=0.87). Intakes of calories (p=0.03), total fat (p=0.02), and saturated fat (p=0.02) were lower for the intervention group. Cholesterol and fiber intake did not differ between groups (p=0.11 and 0.26, respectively). The estimated rate of frequency and duration of physical activity was 20% higher (Incidence Rate Ratio (IRR)=1.2, 95%CI=1.0, 1.5; p=0.06) and 10% higher (IRR=1.1, 95%CI=0.9, 1.4; p=0.37), respectively, for the intervention than the usual care group at 11 months. Most participants did not experience a change in cholesterol medication usage during the study period in the intervention (71.7%) and usual care (78.9%) groups. The cost of the intervention was $148 per couple.
A low-cost, nurse-delivered, telephone-based, spousal support intervention focusing on lifestyle changes was insufficient for improving LDL-C but resulted in important dietary changes and modestly improved physical activity. The intervention tested in this trial directly addresses two important VA priorities: caregiving and access. The intervention aimed to improve the quality of informal caregiving around lifestyle changes for a common chronic disease and required little time burden from caregivers. Because the intervention is delivered by telephone, it could have wide reach, not requiring travel burden by veterans and their informal caregivers.