Screening for social determinants of health among populations at risk for MASLD: a scoping review.

Background: Social determinants of health (SDoH) have been associated with disparate outcomes among those with metabolic dysfunction-associated steatotic liver disease (MASLD) and its risk factors. To address SDoH among this population, real-time SDoH screening in clinical settings is required, yet optimal screening methods are unclear. We performed a scoping review to describe the current literature on SDoH screening conducted in the clinical setting among individuals with MASLD and MASLD risk factors. Methods: Through a systematic literature search of MEDLINE, Embase, and CINAHL Complete databases through 7/2023, we identified studies with clinic-based SDoH screening among individuals with or at risk for MASLD that reported pertinent clinical outcomes including change in MASLD risk factors like diabetes and hypertension. Results: Ten studies (8 manuscripts, 2 abstracts) met inclusion criteria involving 148,151 patients: 89,408 with diabetes and 25,539 with hypertension. Screening was primarily completed in primary care clinics, and a variety of screening tools were used. The most commonly collected SDoH were financial stability, healthcare access, food insecurity and transportation. Associations between clinical outcomes and SDoH varied; overall, higher SDoH burden was associated with poorer outcomes including elevated blood pressure and hemoglobin A1c. Conclusion: Despite numerous epidemiologic studies showing associations between clinical outcomes and SDoH, and guidelines recommending SDoH screening, few studies describe in-clinic SDoH screening among individuals with MASLD risk factors and none among patients with MASLD. Future research should prioritize real-time, comprehensive assessments of SDoH, particularly among patients at risk for and with MASLD, to mitigate disease progression and reduce MASLD health disparities.

Implementing weight maintenance with existing staff and electronic health record tools in a primary care setting: Baseline results from the MAINTAIN PRIME trial.

BACKGROUND: There is need for interventions that can assist with long-term maintenance of healthy body weight and be sustainably integrated into existing primary care teams. The goal of MAINTAIN PRIME (Promoting Real (World) IMplEmentation) is to evaluate whether a successful electronic health record (EHR)-based weight maintenance intervention can be adapted to a new clinical setting with primary care staff serving as coaches. METHODS: EHR tools include tracking tools, standardized surveys, and standardized "SmartPhrases" for coaching. Inclusion criteria were age 18-75 years, voluntary 5% weight loss in the past 2 years with prior BMI ≥ 25 kg/m2, and no bariatric procedures in past 2 years. Participants were randomized 1:1 to tailored online coaching with EHR tracking tools (coaching) or EHR tracking tools alone (tracking). RESULTS: We screened 405 individuals between September 2021 and April 2023; 269 participants enrolled (134 coaching; 135 tracking). The most common reason for not enrolling was ineligibility (55%). At baseline, participants were 50.3 (SD 15.02) years old, 66.4% female, and 84% White; 83.7% reported moderate physical activity. Average weight and BMI at baseline were 205.0 (SD 48.9) lbs. and 33.2 (6.8) kg/m2, respectively. Participants lost an average of 10.7% (SD 5.2) of their body weight before enrolling. We recruited 39 primary care coaches over the same period. Conclusion The study successfully identified and recruited primary care patients with recent intentional weight loss for participation in a weight maintenance program that uses EHR-based tools. We also successfully recruited and trained primary care staff as coaches.

Perceived and calculated diet quality improvements in a randomized mHealth weight loss trial.

The diet quality of US adults is poor and cross-sectional analyses suggest self-perception of healthful dietary intake may be overestimated. This analysis assessed the concordance between calculated and perceived diet quality and changes in diet quality among adults seeking weight loss and enrolled in a 12-month randomized behavioral trial. Healthy Eating Index-2015 diet quality (HEI) was calculated from self-administered 24-hour recalls. Perceived diet quality (PDQ) was measured on a 100-point scale. Higher scores indicate better diet quality. Concordance was assessed using the concordance correlation coefficient and Bland-Altman plots. The one hundred and five participants with complete dietary data were mostly female and white. There was good agreement between HEI and PDQ scores at 12 months for less than a third of participants. Most of the disagreement arose from PDQ scores being higher than HEI scores. Even fewer participants had good agreement between HEI changes and PDQ changes. Participants perceived greater improvement in diet quality than indicated by HEI score changes. Concordance was low at 12 months and for change in diet quality. Despite the diet quality of adults seeking weight loss being suboptimal and not improving, many perceived their diet quality and diet quality improvements as better than calculated. Future studies might explore the effect of misperceptions on weight loss outcomes.

The relationships between Physical activity and asthma control and Body Mass Index (BMI) in patients with asthma.

OBJECTIVE: Asthma is one of the most common chronic conditions in developed countries. We examined whether physical activity (PA) is related to asthma control and body mass index (BMI) in asthma patients. METHODS: Cross-sectional data collected on PA (ActiGraph GT3X-BT), asthma control (the Asthma Control Questionnaire; ACQ), and BMI were examined in 206 adults (mean[sd] age 47.2[13.8] years; 49.5% had an obese BMI) with clinically diagnosed asthma. Relationships between PA and continuous BMI and asthma control were assessed using linear regression. Differences in PA across obesity (non-obese: <30 Kg/m2/obese: ≥30 Kg/m2) and asthma control categories (controlled: ≤0.75/uncontrolled: >0.75 ACQ score) were also examined. RESULTS: Median (p25, p75) steps counts and peak cadence were 6035 (4248, 8461) steps/day and 123 (115, 133) steps in a minute, respectively. There were nearly 2000 fewer steps/day among those with uncontrolled asthma versus controlled and among those with obese BMI versus nonobese, respectively (both p < 0.05). In regression models adjusted for relevant covariates each 1-unit increase in ACQ score was associated with -686 [95%CI -997, -13] (p ≤ 0.05) average steps/day. The statistical significance of these findings was attenuated (p ≥ 0.05) when BMI was added to the model. However, the point estimate was not reduced (-766 [95%CI -1060, 34]. CONCLUSIONS: Overall step counts were low in this population despite peak cadence values suggesting that most participants could perform moderate intensity activity. Increasing step counts should be considered an important lifestyle intervention goal in obese and non-obese asthma patients with low PA levels.

Sleep Technology Intervention to Target Cardiometabolic Health (STITCH): a randomized controlled study of a behavioral sleep extension intervention compared to an education control to improve sleep duration, blood pressure, and cardiometabolic health among adults with elevated blood pressure/hypertension.

BACKGROUND: Short sleep duration, defined as < 7 h sleep on weeknights, affects 40% of the US adult population, contributing to the increased risk for cardiometabolic diseases, decreased safety, and poorer mental health. Despite the prevalence of short sleep duration, few studies have tested interventions to extend sleep duration. The objective of this study is to test the effects of a behavioral sleep extension intervention on sleep duration, blood pressure, and other measures of cardiometabolic health among adults with elevated blood pressure or hypertension. METHODS: This is a single-blind, randomized controlled trial to determine the impact of a behavioral sleep extension intervention on sleep duration and cardiometabolic health among individuals with short sleep duration (< 7 h per night) and elevated blood pressure or hypertension (SBP 120-150 mmHg or DBP 80-90 mmHg). After completing the screening, participants will be randomly assigned to either a sleep coaching (intervention) or health education (control) group. The participants will have weekly contact for either coaching or education for 8 weeks (intervention period) followed by monthly coaching or education for the next 2 months (maintenance period). Participants will complete assessment visits, actigraphy, and 24-h ambulatory blood pressure recording at baseline/screening, 8 weeks, and 6 and 12 months. The primary outcome is sleep duration at 8 weeks, and the secondary outcome is blood pressure at 8 weeks. DISCUSSION: The results of this study will determine the effects of behavioral sleep extension on sleep and cardiometabolic health among adults with short sleep duration and elevated BP/hypertension. The results will inform the feasibility and efficacy of behavioral sleep extension and provide information needed for future multi-site effectiveness studies. TRIAL REGISTRATION: ClinicalTrials.gov NCT04766424. Registered on 21 February 2021.

Influence of Recent Standing, Moving, or Sitting on Daytime Ambulatory Blood Pressure.

Background There are no recommendations for being seated versus nonseated during ambulatory blood pressure (BP) monitoring (ABPM). The authors examined how recent standing or moving versus sitting affect average daytime BP on ABPM. Methods and Results This analysis used baseline assessments from a clinical trial in desk workers with office systolic BP (SBP) 120 to 159 mm Hg or diastolic BP (DBP) 80 to 99 mm Hg. ABPM was measured every 30 minutes with a SunTech Medical Oscar 2 monitor. Concurrent posture (standing or seated) and moving (steps) were measured via a thigh-worn accelerometer. Linear regression determined within-person BP variability explained (R2) by standing and steps before ABPM readings. Mean daytime BP and the prevalence of mean daytime BP >135/85 mm Hg from readings after sitting (seated) or after recent standing or moving (nonseated) were compared with all readings. Participants (n=266, 59% women; age, 45.2±11.6 years) provided 32.5±3.9 daytime BP readings. Time standing and steps before readings explained variability up to 17% for daytime SBP and 14% for daytime DBP. Using the 5-minute prior interval, seated SBP/DBP was lower (130.8/79.7 mm Hg, P<0.001) and nonseated SBP/DBP was higher (137.8/84.3 mm Hg, P<0.001) than mean daytime SBP/DBP from all readings (133.9/81.6 mm Hg). The prevalence of mean daytime SBP/DBP ≥135/85 mm Hg also differed: 38.7% from seated readings, 70.3% from nonseated readings, and 52.6% from all readings (P<0.05). Conclusions Daytime BP was systematically higher after standing and moving compared with being seated. Individual variation in activity patterns could influence the diagnosis of high BP using daytime BP readings on ABPM.

Aspects of Program Engagement in an Online Physical Activity Intervention and Baseline Predictors of Engagement.

PURPOSE: Participant engagement in an online physical activity (PA) intervention is described and baseline factors related to engagement are identified. DESIGN: Longitudinal Study Within Randomized Controlled Trial. SETTING: Online/Internet. SAMPLE: Primary care patients (21-70 years). INTERVENTION: ActiveGOALS was a 3-month, self-directed online PA intervention (15 total lessons, remote coaching support, and a body-worn step-counter). MEASURES: Engagement was measured across six outcomes related to lesson completion (total number and time to complete), coach contact, and behavior tracking (PA, sedentary). Self-reported baseline factors were examined from seven domains (confidence, environment, health, health care, demographic, lifestyle, and quality of life). ANALYSIS: General linear and nonlinear mixed models were used to examine relationships between baseline factors and engagement outcomes within and across all domains. RESULTS: Seventy-nine participants were included in the sample (77.2% female; 74.7% white non-Hispanic). Program engagement was high (58.2% completed all lessons; PA was tracked ≥3 times/week for 11.3 ± 4.0 weeks on average). Average time between completed lessons (days) was longer than expected and participants only contacted their coach about 1 of every 3 weeks. Individual predictors related to health, health care, demographics, lifestyle, and quality of life were significantly related to engagement. CONCLUSION: Examining multiple aspects of engagement and a large number of potential predictors of engagement is likely needed to determine facilitators and barriers for high engagement in multi-faceted online intervention programs.

The Association between Neighborhood Walkability and Physical Activity in a Behavioral Weight Loss Trial Testing the Addition of Remotely Delivered Feedback Messages to Self-Monitoring.

Adding feedback messages (FB) to self-monitoring (SM) may reinforce behavior change. However, socio-environmental conditions (e.g., limited access to parks or low walkability) may limit one's ability to respond to FB focused on physical activity (PA). In this analysis, we hypothesized that high neighborhood walkability will positively modify the treatment effect of FB on PA, and residents of high walkability neighborhoods will achieve higher PA levels at 12 months than those in low walkability neighborhoods. The study is a secondary analysis of a 12-month behavioral weight-loss trial. Adults with overweight/obesity were randomized to SM + FB (n = 251) or SM alone (n = 251). SM + FB group received smartphone pop-up messages thrice/week tailored to their PA SM data. The assessment included neighborhood walkability via Walk Score (low [<50] vs. high [≥50]), moderate to vigorous PA (MVPA) and step count via Fitbit Charge 2™, and weight via smart scale. We report adjusted linear regression coefficients (b) with standard errors (SE). The analysis included participants who were primarily white, female, and with obesity. In adjusted models, neighborhood walkability did not moderate the effect of treatment assignment on log-transformed (ln) MVPA or steps count over 12 months. The SM + FB group had greater lnMVPA than the SM group, but lnMVPA and steps were similar between walkability groups. There were no significant interactions for group and time or group, time, and walkability. These findings suggest that adding FB to SM had a small but significant positive impact on PA over 12 months, but neighborhood walkability did not moderate the treatment effect of FB on PA.

Lifestyle strategies after intentional weight loss: results from the MAINTAIN-pc randomized trial.

Introduction/Purpose: Weight maintenance following intentional weight loss is challenging and often unsuccessful. Physical activity and self-monitoring are strategies associated with successful weight loss maintenance. However, less is known about the type and number of lifestyle strategies used following intentional weight loss. The purpose of this study was to determine the types and amounts of strategies associated with successful long-term weight loss maintenance. Methods: Data from the 24-month Maintaining Activity and Nutrition Through Technology-Assisted Innovation in Primary Care (MAINTAIN-pc) trial were analyzed. MAINTAIN-pc recruited adults (n=194; 53.4±12.2 years of age, body mass index (BMI): 30.4±5.9 kg/m2, 74% female) with recent intentional weight loss of ≥5%, randomized to tracking tools plus coaching (i.e., coaching group) or tracking tools without coaching (i.e., tracking-only group). At baseline, 6, 12, and 24 months, participants reported lifestyle strategies used in the past 6 months, including self-monitoring, group support, behavioral skills, and professional support. General linear models evaluated changes in the number of strategies over time between groups and the consistency of strategies used over the 24-month intervention. Results: At baseline, 100% used behavioral skills, 73% used group support, 69% used self-monitoring, and 68% used professional support in the past 6 months; at 24 months, these rates were 98%, 60%, 75%, and 61%, respectively. While the number of participants utilizing individual strategies did not change significantly over time, the overall number of strategies participants reported decreased. More strategies were used at baseline and 6 months compared to 12- and 24-month follow-ups. The coaching group used more strategies at months 6 and 12 than the tracking-only group. Consistent use of professional support strategies over the 24-month study period was associated with less weight regain. Conclusion: Weight loss maintenance interventions that incorporate continued follow-up and support from healthcare professionals are likely to prevent weight regain after intentional weight loss.

Single-Pill Combination Product Availability of the Antihypertensive Regimens Used for Intensive Systolic Blood Pressure Treatment in the Systolic Blood Pressure Intervention Trial.

BACKGROUND: Single-pill combination (SPC) antihypertensive products improve blood pressure control and medication adherence among patients with hypertension. It is unknown to what degree commercially available SPC products could be used to target an intensive systolic blood pressure goal of <120 mm Hg. METHODS: This cross-sectional analysis included participants randomized to the intensive treatment arm (goal systolic blood pressure <120 mm Hg) of the Systolic Blood Pressure Intervention Trial (SPRINT) using ≥2 antihypertensive medication classes at the 12-month postrandomization visit. Antihypertensive medication data were collected using pill bottle review by research coordinators, and regimens were categorized by the unique combinations of antihypertensive classes. We calculated the proportion of regimens used, which are commercially available as one of the 7 SPC class combinations in the United States as of January 2023. RESULTS: Among the 3833 SPRINT intensive arm participants included (median age, 67.0 years; 35.5% female), participants were using 219 unique antihypertensive regimens. The 7 regimens for which there are class-equivalent SPC products were used by 40.3% of participants. Only 3.2% of all medication class regimens used are available as a class-equivalent SPC product (7/219). There are no SPC products available with 4 or more medication classes, which were used by 1060 participants (27.7%). CONCLUSIONS: Most SPRINT participants in the intensive arm used an antihypertensive medication regimen, which is not commercially available as a class equivalent SPC product. To achieve the SPRINT results in real-world settings, maximize the potential benefit of SPCs, and reduce pill burden, improvements in the product landscape are needed. REGISTRATION: URL: https://www. CLINICALTRIALS: gov/ct2/show/NCT01206062; Unique identifier: NCT01206062.

Antihypertensive Medication Regimens Used by US Adults With Hypertension and the Potential for Fixed-Dose Combination Products: The National Health and Nutrition Examination Surveys 2015 to 2020.

Background Fixed-dose combination (FDC) antihypertensive products improve blood pressure control and adherence among patients with hypertension. It is unknown to what degree commercially available FDC products meet the current hypertension management prescription patterns in the United States. Methods and Results This cross-sectional analysis of the National Health and Nutrition Examination Surveys 2015 to March 2020 included participants with hypertension taking ≥2 antihypertensive medications (N=2451). After constructing each participant's regimen according to antihypertensive classes used, we estimated the extent to which the 7 class-level FDC regimens available in the United States as of January 2023 would match the regimens used. Among a weighted population of 34.1 million US adults (mean age, 66.0 years; 52.8% women; 69.1% non-Hispanic White race and ethnicity), the proportions using 2, 3, 4, and ≥5 antihypertensive classes were 60.6%, 28.2%, 9.1%, and 1.6%, respectively. The 7 FDC regimens were among 189 total regimens used (3.7%), and 39.2% of the population used one of the FDC regimens (95% CI, 35.5%-43.0%; 13.4 million US adults); 60.8% of the population (95% CI, 57.0%-64.5%; 20.7 million US adults) were using a regimen not available as a class-equivalent FDC product. Conclusions Three in 5 US adults with hypertension taking ≥2 antihypertensive classes are using a regimen that is not commercially available as a class-equivalent FDC product as of January 2023. To maximize the potential benefit of FDCs to improve medication adherence (and thus blood pressure control) among patients taking multiple antihypertensive medications, use of FDC-compatible regimens and improvements in the product landscape are needed.

Associations of physical and social workplace characteristics with movement behaviors at work.

Introduction/Purpose: Sedentary behavior (SB) is common in desk-based work and prolonged periods of SB are associated with negative health outcomes. This study assessed associations between workplace characteristics and setting and movement patterns during working hours. Methods: This secondary analysis used baseline data from the Reducing Sedentary Behavior to Decrease Blood Pressure (RESET BP) clinical trial which enrolled inactive, desk-based workers with elevated blood pressure (n=271; mean age: 45.3±11.6 years; body mass index (BMI): 30.66±7.1 kg/m2; 59.4% women). Physical and social workplace characteristics were assessed by a study-developed questionnaire and the Office Environment and Sitting Scale (OFFESS). Participants also wore an activPAL activity monitor for 7 days and reported working hours in a diary to measure SB and physical activity (PA) specifically while working. Linear regression was used to analyze cross-sectional associations between workplace characteristics and SB and PA. A stratified analysis was also conducted to assess associations among home-based and in-office desk workers separately. Analyses were adjusted for age, gender, BMI, and work wear time. Results: Participants spent 77% of working hours in SB. Public vs. private offices, working in-office vs. at home, higher local connectivity, and greater overall connectedness were associated with lower SB and/or greater PA (all p<0.05). Higher frequency of face-to-face interactions, and greater visibility and proximity to co-workers was associated with less SB and more PA (all p<0.05). For example, home-based workers had more total SB (+17.2±8.4 mins/day), more SB bouts ≥30 mins (+39.1±12.8 mins/day), and less steps (695±201 steps/day) than in-office employees. Stratification by office setting revealed differences in associations between SB and PA and workplace characteristics. Conclusions: More public, open spaces with more social interactions and physical walkways could improve SB and PA patterns during work. Home-based workers had more SB, less PA, and unique associations of these activities with workplace characteristics, suggesting a need for tailored interventions.

Impact of electronic health record-coaching features in weight change: A secondary analysis from the MAINTAIN-pc randomized trial.

OBJECTIVE: This study aimed to evaluate whether coaching features were successfully transmitted via electronic health record (EHR) communication and to evaluate their relationship with weight change in a previously tested EHR-based coaching intervention. METHODS: A secondary analysis from the Maintaining Activity and Nutrition through Technology-Assisted Innovation in Primary Care (MAINTAIN-pc) study randomized clinical trial was conducted in nine primary care practices and one specialty practice (endocrinology) affiliated with the University of Pittsburgh Medical Center. Eligibility included age 18 to 75 years, intentional 5% weight loss in the previous 2 years, access to an internet-connected computer, and receipt of care from a University of Pittsburgh Medical Center primary care provider. Survey data were collected during the randomized clinical trial. RESULTS: Participants content with intervention delivery via the EHR and those who felt a strong connection to their coach had significantly less weight regain (p = 0.013 and p < 0.01, respectively). Participants who had needs unmet by the intervention (e.g., "in-person" support in a group setting or individual settings) regained more weight (p < 0.01). CONCLUSIONS: The data suggest heterogeneity in the patient population regarding preference for in-person versus EHR-based coaching formats. Such heterogeneity might result in the differential success of EHR-based interventions.

Effect of an mHealth weight loss intervention on Healthy Eating Index diet quality: the SMARTER randomised controlled trial.

In the few weight loss studies assessing diet quality, improvements have been minimal and recommended calculation methods have not been used. This secondary analysis of a parallel group randomised trial (regsitered: https://clinicaltrials.gov/ct2/show/NCT03367936) assessed whether self-monitoring with feedback (SM + FB) v. self-monitoring alone (SM) improved diet quality. Adults with overweight/obesity (randomised: SM n 251, SM + FB n 251; analysed SM n 170, SM + FB n 186) self-monitored diet, physical activity and weight. Real-time, personalised feedback, delivered via a study-specific app up to three times daily, was based on reported energy, fat and added sugar intake. Healthy Eating Index 2015 (HEI-2015) scores were calculated from 24-hour recalls. Higher scores represent better diet quality. Data were collected August 2018 to March 2021 and analysed spring 2022. The sample was mostly female (78·9 %) and white (85·4 %). At baseline, HEI-2015 total scores and bootstrapped 95 % CI were similar by treatment group (SM + FB: 63·11 (60·41, 65·24); SM: 61·02 (58·72, 62·81)) with similar minimal improvement observed at 6 months (SM + FB: 65·42 (63·30, 67·20); SM: 63·19 (61·22, 64·97)) and 12 months (SM + FB: 63·94 (61·40, 66·29); SM: 63·56 (60·81, 65·42)). Among those who lost ≥ 5 % of baseline weight, HEI-2015 scores improved (baseline: 62·00 (58·94, 64·12); 6 months: 68·02 (65·41, 71·23); 12 months: 65·93 (63·40, 68·61)). There was no effect of the intervention on diet quality change. Clinically meaningful weight loss was related to diet quality improvement. Feedback may need to incorporate more targeted nutritional content.

Comparative Safety and Effectiveness of Roux-en-Y Gastric Bypass and Sleeve Gastrectomy for Weight Loss and Type 2 Diabetes Across Race and Ethnicity in the PCORnet Bariatric Study Cohort.

Importance: Bariatric surgery is the most effective treatment for severe obesity; yet it is unclear whether the long-term safety and comparative effectiveness of these operations differ across racial and ethnic groups. Objective: To compare outcomes of Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) across racial and ethnic groups in the National Patient-Centered Clinical Research Network (PCORnet) Bariatric Study. Design, Setting, and Participants: This was a retrospective, observational, comparative effectiveness cohort study that comprised 25 health care systems in the PCORnet Bariatric Study. Patients were adults and adolescents aged 12 to 79 years who underwent a primary (first nonrevisional) RYGB or SG operation between January 1, 2005, and September 30, 2015, at participating health systems. Patient race and ethnicity included Black, Hispanic, White, other, and unrecorded. Data were analyzed from July 1, 2021, to January 17, 2022. Exposure: RYGB or SG. Outcomes: Percentage total weight loss (%TWL); type 2 diabetes remission, relapse, and change in hemoglobin A1c (HbA1c) level; and postsurgical safety and utilization outcomes (operations, interventions, revisions/conversions, endoscopy, hospitalizations, mortality, 30-day major adverse events) at 1, 3, and 5 years after surgery. Results: A total of 36 871 patients (mean [SE] age, 45.0 [11.7] years; 29 746 female patients [81%]) were included in the weight analysis. Patients identified with the following race and ethnic categories: 6891 Black (19%), 8756 Hispanic (24%), 19 645 White (53%), 826 other (2%), and 783 unrecorded (2%). Weight loss and mean reductions in HbA1c level were larger for RYGB than SG in all years for Black, Hispanic, and White patients (difference in 5-year weight loss: Black, -7.6%; 95% CI, -8.0 to -7.1; P < .001; Hispanic, -6.2%; 95% CI, -6.6 to -5.9; P < .001; White, -5.9%; 95% CI, -6.3 to -5.7; P < .001; difference in change in year 5 HbA1c level: Black, -0.29; 95% CI, -0.51 to -0.08; P = .009; Hispanic, -0.45; 95% CI, -0.61 to -0.29; P < .001; and White, -0.25; 95% CI, -0.40 to -0.11; P = .001.) The magnitude of these differences was small among racial and ethnic groups (1%-3% of %TWL). Black and Hispanic patients had higher risk of hospitalization when they had RYGB compared with SG (hazard ratio [HR], 1.45; 95% CI, 1.17-1.79; P = .001 and 1.48; 95% CI, 1.22-1.79; P < .001, respectively). Hispanic patients had greater risk of all-cause mortality (HR, 2.41; 95% CI, 1.24-4.70; P = .01) and higher odds of a 30-day major adverse event (odds ratio, 1.92; 95% CI, 1.38-2.68; P < .001) for RYGB compared with SG. There was no interaction between race and ethnicity and operation type for diabetes remission and relapse. Conclusions and Relevance: Variability of the comparative effectiveness of operations for %TWL and HbA1c level across race and ethnicity was clinically small; however, differences in safety and utilization outcomes were clinically and statistically significant for Black and Hispanic patients who had RYGB compared with SG. These findings can inform shared decision-making regarding bariatric operation choice for different racial and ethnic groups of patients.

The Effect of Tailored, Daily, Smartphone Feedback to Lifestyle Self-Monitoring on Weight Loss at 12 Months: the SMARTER Randomized Clinical Trial.

BACKGROUND: Self-monitoring (SM) is the centerpiece of behavioral weight loss treatment, but the efficacy of smartphone-delivered SM feedback (FB) has not been tested in large, long-term, randomized trials. OBJECTIVE: The aim of this study was to establish the efficacy of providing remote FB to diet, physical activity (PA), and weight SM on improving weight loss outcomes when comparing the SM plus FB (SM+FB) condition to the SM-only condition in a 12-month randomized controlled trial. The study was a single-site, population-based trial that took place in southwestern Pennsylvania, USA, conducted between 2018 and 2021. Participants were smartphone users age ≥18 years, able to engage in moderate PA, with a mean BMI between 27 and 43 kg/m2. METHODS: All participants received a 90-minute, one-to-one, in-person behavioral weight loss counseling session addressing behavioral strategies, establishing participants' dietary and PA goals, and instructing on use of the PA tracker (Fitbit Charge 2), smart scale, and diet SM app. Only SM+FB participants had access to an investigator-developed smartphone app that read SM data, in which an algorithm selected tailored messages sent to the smartphone up to 3 times daily. The SM-only participants did not receive any tailored FB based on SM data. The primary outcome was percent weight change from baseline to 12 months. Secondary outcomes included engagement with digital tools (eg, monthly percentage of FB messages opened and monthly percentage of days adherent to the calorie goal). RESULTS: Participants (N=502) were on average 45.0 (SD 14.4) years old with a mean BMI of 33.7 (SD 4.0) kg/m2. The sample was 79.5% female (n=399/502) and 82.5% White (n=414/502). At 12 months, retention was 78.5% (n=394/502) and similar by group (SM+FB: 202/251, 80.5%; SM: 192/251, 76.5%; P=.28). There was significant percent weight loss from baseline in both groups (SM+FB: -2.12%, 95% CI -3.04% to -1.21%, P<.001; SM: -2.39%, 95% CI -3.32% to -1.47%; P<.001), but no difference between the groups (-0.27%; 95% CI -1.57% to 1.03%; t =-0.41; P=.68). Similarly, 26.3% (66/251) of the SM+FB group and 29.1% (73/251) of the SM group achieved ≥5% weight loss (chi-square value=0.49; P=.49). A 1% increase in FB messages opened was associated with a 0.10 greater percent weight loss at 12 months (b=-0.10; 95% CI -0.13 to -0.07; t =-5.90; P<.001). A 1% increase in FB messages opened was associated with 0.12 greater percentage of days adherent to the calorie goal per month (b=0.12; 95% CI 0.07-0.17; F=22.19; P<.001). CONCLUSIONS: There were no significant between-group differences in weight loss; however, the findings suggested that the use of commercially available digital SM tools with or without FB resulted in a clinically significant weight loss in over 25% of participants. Future studies need to test additional strategies that will promote greater engagement with digital tools. TRIAL REGISTRATION: Clinicaltrials.gov NCT03367936; https://clinicaltrials.gov/ct2/show/NCT03367936.

Implementing a Dutch Physical Therapy Intervention Into a U.S. Health System: Selecting Strategies Using Implementation Mapping.

Background: Coach2Move is a person-centered physical therapy intervention that has demonstrated success in changing physical activity behaviors among older adults in the Netherlands. In this manuscript, we describe how we developed an implementation plan for Coach2move in a U.S. population and healthcare system using Implementation Mapping. Methods: We established an implementation planning team of researchers, patients, and clinicians. The Consolidated Framework for Implementation Research provided an overall structure for consideration of the context for implementation. Implementation Mapping guided the planning process. The implementation planning team worked sequentially through the five tasks of Implementation Mapping (1) Identify needs, program adopters and implementers; (2) Identify adoption and implementation outcomes, performance objectives, determinants, and matrices of change; (3) Choose theoretical models and implementation strategies; (4) Produce implementation protocols; (5) Evaluate implementation outcomes. In this manuscript, we identify our evaluation plan but not results as data collection is ongoing. Results: Clinic managers and physical therapists were identified as program adopters and implementors. Performance objectives necessary steps to achieving implementation outcomes were linked to Coach2Move fidelity indicators with implementation by the physical therapist. These included delivery of person-centered care, motivational interviewing, meaningful goal setting, shared decision-making in planning, and systematic monitoring and follow-up. Determinants linked to these performance objectives included knowledge, outcome expectations, skills and self-efficacy, and perceived norms. Implementation strategies were selected based on a review of methods effective for influencing these determinants. This resulted in four primary strategies (1) educational meetings and dynamic training, (2) peer-assessment meetings, (3) changing the electronic health record template, and (4) reminders and prompts. Measures of intervention acceptability, appropriateness, and feasibility will be collected after training and early in implementation. Fidelity and effectiveness measures will be collected over the next 12-months. Conclusion: Implementation mapping provided a systematic process for identifying what physical therapists would need to implement Coach2Move with fidelity. The result was a matrix linking behavioral determinants and performance objectives. These matrices of change allowed for systematic identification and tailoring of implementation strategies to the needs of our population and setting. The process was acceptable to diverse stakeholders, facilitated communication across stakeholders.

Patient-centered quality measurement for opioid use disorder: Development of a taxonomy to address gaps in research and practice.

Background: Evidence-based treatment is provided infrequently and inconsistently to patients with opioid use disorder (OUD). Treatment guidelines call for high-quality, patient-centered care that meets individual preferences and needs, but it is unclear whether current quality measures address individualized aspects of care and whether measures of patient-centered OUD care are supported by evidence. Methods: We conducted an environmental scan of OUD care quality to (1) evaluate patient-centeredness in current OUD quality measures endorsed by national agencies and in national OUD treatment guidelines; and (2) review literature evidence for patient-centered care in OUD diagnosis and management, including gaps in current guidelines, performance data, and quality measures. We then synthesized these findings to develop a new quality measurement taxonomy that incorporates patient-centered aspects of care and identifies priority areas for future research and quality measure development. Results: Across 31 endorsed OUD quality measures, only two measures of patient experience incorporated patient preferences and needs, while national guidelines emphasized providing patient-centered care. Among 689 articles reviewed, evidence varied for practices of patient-centered care. Many practices were supported by guidelines and substantial evidence, while others lacked evidence despite guideline support. Our synthesis of findings resulted in EQuIITable Care, a taxonomy comprised of six classifications: (1) patient Experience and engagement, (2) Quality of life; (3) Identification of patient risks; (4) Interventions to mitigate patient risks; (5) Treatment; and (6) Care coordination and navigation. Conclusions: Current quality measurement for OUD lacks patient-centeredness. EQuIITable Care for OUD provides a roadmap to develop measures of patient-centered care for OUD.