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Alcohol use increases non-adherence to antiretroviral therapy (ART) among persons living with HIV (PLWH). Dynamic longitudinal associations are understudied. Veterans Aging Cohort Study (VACS) data 2/1/2008-7/31/16 were used to fit linear regression models estimating changes in adherence (% days with ART medication fill) associated with changes in alcohol use based on annual clinically-ascertained AUDIT-C screening scores (range - 12 to + 12, 0 = no change) adjusting for demographics and initial adherence. Among 21,275 PLWH (67,330 observations), most reported no (48%) or low-level (39%) alcohol use initially, with no (55%) or small (39% ≤ 3 points) annual change. Mean initial adherence was 86% (SD 21%), mean annual change was - 3.1% (SD 21%). An inverted V-shaped association was observed: both increases and decreases in AUDIT-C were associated with greater adherence decreases relative to stable scores [p

BackgroundAlcohol use influences HIV disease severity through multiple mechanisms. Whether HIV disease severity is sensitive to changes in alcohol use among people with HIV (PWH) is understudied.SettingNational Veterans Health Administration.MethodsPairs of AUDIT-C screens within 9-15 months (February 1, 2008-September 30, 2014) were identified among PWH from the Veterans Aging Cohort Study (VACS). Initial and follow-up VACS Index 2.0 pairs obtained 0-270 days after initial and follow-up AUDIT-Cs, respectively, determined change in VACS Index 2.0, a composite HIV severity measure. Change in VACS Index 2.0 was regressed on AUDIT-C change scores (-12 to +12) adjusted for demographics, initial VACS Index 2.0, and days between VACS Index measures.ResultsAmong 23,297 PWH (76,202 observations), most had no (51%) or low-level (38%) alcohol use initially. Most (54%) had no subsequent change; 21% increased and 24% decreased drinking. Initial VACS Index 2.0 scores ranged from 0 to 134, change scores ranged from -65 to +73, with average improvement of 0.76 points (SD 9.48). AUDIT-C change was associated with VACS Index 2.0 change (P < 0.001). Among those with stable alcohol use (AUDIT-C change ≤ │1│ point), VACS Index 2.0 improvements ranged 0.36-0.60 points. For those with maximum AUDIT-C increase (change from 0 to 12), VACS Index 2.0 worsened 3.74 points (95% CI: -4.71 to -2.78); for those with maximum AUDIT-C decrease (change from 12 to 0), VACS Index 2.0 changed minimally [-0.60 (95% CI: -1.43 to 0.23)].ConclusionsIn this national sample, improvement in HIV severity was generally greatest among those with stable alcohol use (primarily those with no use).

Background: Addressing modifiable risk factors such as physical inactivity and social isolation could reduce risk of Alzheimer's disease and all-cause dementia, but little is known about which factors individuals are most willing to address or how they prefer to address them. Objective: To examine and describe behavior change goals set by participants during the Systematic Multi-domain Alzheimer's Risk Reduction Trial (SMARRT). Methods: In SMARRT, older adults worked with a health coach and nurse over 2 years to set incremental, personalized goals to reduce dementia risk. We performed quantitative analyses to summarize the numbers of goals per risk factor and qualitative content analyses of health coach and nurse notes to describe types of goals and useful strategies. Results: 82 dementia-free adults (70 to 89 years) with at least two dementia risk factors participated in the SMARRT intervention arm (mean age, 76 ± 5 years; 72% women; 11% Black/African American, 4% Asian, 3% Hispanic, 7% another non-White race). Participants set a median of 12 health coach goals and 1 nurse goals. The risk factors participants chose to work on most frequently were physical activity (95%), hypertension (72%), and cognitive activity (60%). Participants reported that the most useful strategies included support and accountability from the health coach/nurse, setting small goals, and learning to manage setbacks. Conclusions: When given support, older adults at increased risk for dementia set a wide range of goals to reduce dementia risk. A flexible, personalized approach that focuses on setting feasible goals and managing setbacks provides a useful framework for dementia risk reduction. [ABSTRACT FROM AUTHOR]

We evaluated associations between levels of alcohol use and HIV care continuum components using national Veterans Aging Cohort Study data for all patients with HIV and AUDIT-C screening (2/1/2008-9/30/2014). Poisson regression models evaluated associations between alcohol use levels (non-drinking, low-, medium-, high-, and very high-level drinking) and: (1) engagement with care (documented CD4 cells/µl or viral load copies/ml labs), (2) ART treatment (≥ 1 prescription), and (3) viral suppression (HIV RNA

ObjectivesTo investigate whether gender is associated with three recommended stages of the HIV care continuum and whether gender modifies known associations between level of alcohol use and HIV care among US veterans.DesignRetrospective cohort.MethodsVeterans Aging Cohort Study data were used to identify Veterans Health Administration (VA) patients with HIV and AUDIT-C alcohol screening from 1 February 2008 to 30 September 2014. Modified Poisson regression models estimated the relative risk and predicted prevalences of engagement in HIV care (documented CD4 cells/μl or viral load copies/ml lab values), ART treatment (at least one prescription), and viral suppression (HIV RNA

Background: The Alcohol Use Disorders Identification Test‐Consumption (AUDIT‐C) is a three‐item screening measure of unhealthy alcohol use that is widely used in healthcare settings. Evidence shows high test–retest reliability of the AUDIT‐C in research samples, but most studies had limited external validity and used small samples that could not be used to evaluate reliability across demographic subgroups and/or screening modalities. This study evaluates the test–retest reliability of the AUDIT‐C completed in routine care in a large primary care sample, including across demographic subgroups defined by age, sex, race, ethnicity, and screening modality (i.e., completed in‐clinic or online). Methods: We used electronic health record (EHR) data from Kaiser Permanente Washington. The sample included 18,491 adult primary care patients who completed two AUDIT‐C screens 1–21 days apart as part of routine care in 2021. Test–retest reliability was evaluated for AUDIT‐C total scores (0–12) and for a binary measure indicating unhealthy alcohol use (scores ≥3 women, ≥4 men). Using previously established cutoffs, we interpreted reliability coefficients >0.75 as indicating "excellent" reliability. Results: AUDIT‐C screens completed in routine care and documented in EHRs had excellent test–retest reliability for total scores (ICC = 0.87, 95% CI: 0.87–0.87) and the binary indicator of unhealthy alcohol use (κ = 0.79, 95% CI: 0.78–0.80). Reliability coefficients were good to excellent across all demographic groups and for in‐clinic and online modalities. Higher reliability was seen when both screens were completed through online patient portals (ICC = 0.93, 95% CI: 0.93–0.93) versus in‐clinic (ICC = 0.81, 95% CI: 0.79–0.82) or when one screen was completed using each modality (ICC = 0.83, 95% CI: 0.82–0.83). Lower reliability was seen in American Indian/Alaska Native (ICC = 0.82, 95% CI: 0.75–0.87) and multiracial individuals (ICC = 0.82, 95% 0.80–0.84). Conclusions: In real‐world routine care conditions, AUDIT‐C screens have excellent test–retest reliability across demographic subgroups and modalities (online and in‐clinic). Future research should examine why reliability varies slightly across modalities and demographic subgroups. [ABSTRACT FROM AUTHOR]

Background: The National Institute on Alcohol Abuse and Alcoholism (NIAAA) recommends the paper-based or computerized Alcohol Symptom Checklist to assess alcohol use disorder (AUD) symptoms in routine care when patients report high-risk drinking. However, it is unknown whether Alcohol Symptom Checklist response characteristics differ when it is administered online (eg, remotely via an online electronic health record [EHR] patient portal before an appointment) versus in clinic (eg, on paper after appointment check-in). Objective: This study evaluated the psychometric performance of the Alcohol Symptom Checklist when completed online versus in clinic during routine clinical care. Methods: This cross-sectional, psychometric study obtained EHR data from the Alcohol Symptom Checklist completed by adult patients from an integrated health system in Washington state. The sample included patients who had a primary care visit in 2021 at 1 of 32 primary care practices, were due for annual behavioral health screening, and reported high-risk drinking on the behavioral health screen (Alcohol Use Disorder Identification Test–Consumption score ≥7). After screening, patients with high-risk drinking were typically asked to complete the Alcohol Symptom Checklist—an 11-item questionnaire on which patients self-report whether they had experienced each of the 11 AUD criteria listed in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) over a past-year timeframe. Patients could complete the Alcohol Symptom Checklist online (eg, on a computer, smartphone, or tablet from any location) or in clinic (eg, on paper as part of the rooming process at clinical appointments). We examined sample and measurement characteristics and conducted differential item functioning analyses using item response theory to examine measurement consistency across these 2 assessment modalities. Results: Among 3243 patients meeting eligibility criteria for this secondary analysis (2313/3243, 71% male; 2271/3243, 70% White; and 2014/3243, 62% non-Hispanic), 1640 (51%) completed the Alcohol Symptom Checklist online while 1603 (49%) completed it in clinic. Approximately 46% (752/1640) and 48% (764/1603) reported ≥2 AUD criteria (the threshold for AUD diagnosis) online and in clinic (P =.37), respectively. A small degree of differential item functioning was observed for 4 of 11 items. This differential item functioning produced only minimal impact on total scores used clinically to assess AUD severity, affecting total criteria count by a maximum of 0.13 criteria (on a scale ranging from 0 to 11). Conclusions: Completing the Alcohol Symptom Checklist online, typically prior to patient check-in, performed similarly to an in-clinic modality typically administered on paper by a medical assistant at the time of the appointment. Findings have implications for using online AUD symptom assessments to streamline workflows, reduce staff burden, reduce stigma, and potentially assess patients who do not receive in-person care. Whether modality of DSM-5 assessment of AUD differentially impacts treatment is unknown. [ABSTRACT FROM AUTHOR]

Background: The authors tested the efficacy of the "I-STAND" intervention for reducing sitting time, a novel and potentially health-promoting approach, in older adults with obesity. Methods: The authors recruited 60 people (mean age = 68 ± 4.9 years, 68% female, 86% White; mean body mass index = 35.4). The participants were randomized to receive the I-STAND sitting reduction intervention (n = 29) or healthy living control group (n = 31) for 12 weeks. At baseline and at 12 weeks, the participants wore activPAL devices to assess sitting time (primary outcome). Secondary outcomes included fasting glucose, blood pressure, and weight. Linear regression models assessed between-group differences in the outcomes. Results: The I-STAND participants significantly reduced their sitting time compared with the controls (–58 min per day; 95% confidence interval [–100.3, –15.6]; p =.007). There were no statistically significant changes in the secondary outcomes. Conclusion: I-STAND was efficacious in reducing sitting time, but not in changing health outcomes in older adults with obesity. [ABSTRACT FROM AUTHOR]