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Mary E Hawk,1– 3 Ashley Chung,4 Stephanie L Creasy,1– 3 James E Egan1– 3 1Behavioral and Community Health Sciences, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; 2Center for LGBT Health Research, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; 3Evaluation Institute, Behavioral and Community Health Sciences, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA; 4Jewish Healthcare Foundation, Pittsburgh, PA, USACorrespondence: Mary E HawkBehavioral and Community Health Sciences, Graduate School of Public Health, University of Pittsburgh, 130 DeSoto Street, Pittsburgh, PA 15261, USATel +1-412-648-2342Email mary.hawk@pitt.eduPurpose: Despite marked progress in the ability to test for, treat, and prevent HIV, the epidemic remains a significant public health concern, especially among key populations including prisoners; sex workers; transgender individuals; gay, bisexual, and other men who have sex with men (MSM); and Black and Latinx MSM. This scoping review was conducted to provide an overview of the current research describing patient preferences for HIVST in the United States to understand what key populations value about HIVST and why they are willing to use it. A targeted search for published literature on patient preferences for HIVST was conducted using Ovid Medline, PsychINFO, and an HIVST research database.Results: We reviewed 700 abstracts and 139 full texts. We found 19 articles published between January 2014 and April 2020 that included findings related to HIVST preferences. Overall, HIVST was preferred to more traditional testing. Six primary factors emerged as important HIVST values including: 1) convenience, 2) type of test; 3) cost, 4) stigma reduction, 5) risk reduction, and 6) self-control. Linkage to care was also identified as a key factor when considering HIVST as an option. Much of what makes HIVST attractive to individuals is their ability to self-determine how HIVST can be best integrated into their lives as a harm reduction tool for stigma and sexual risk mitigation.Conclusion: While there is substantial evidence suggesting HIVST is feasible for use and there are aspects of HIVST that are beneficial and preferred over traditional testing approaches, there is a lack of rigorous implementation studies exploring how best to scale up HIVST in community settings. HIVST has the potential to be a powerful biobehavioral HIV prevention and harm reduction tool to empower individuals to engage with testing on their own terms while providing pathways to prevention and care support.Keywords: HIV, self-testing, HIVST, harm reduction, United States, patient preferences

Introduction: Our previous pilot work suggests relational harm reduction strengthens relationships between people with HIV (PWH) who use drugs and their healthcare providers and improves HIV health outcomes. However, there is limited research examining ways that structural (eg, strategies like syringe service programmes) and/or relational (patient-provider relationship) harm reduction approaches in HIV clinical settings can mitigate experiences of stigma, affect patient-provider relationships and improve outcomes for PWH who use drugs. Our mixed methods, multisite, observational study aims to fill this knowledge gap and develop an intervention to operationalise harm reduction care for PWH who use drugs in HIV clinical settings., Methods and Analysis: Aim 1 will explore the relationship between healthcare providers' stigmatising attitudes towards working with PWH who use drugs and providers' acceptance and practice of structural and relational harm reduction through surveys (n=125) and interviews (n=20) with providers. Aim 2 will explore the interplay between patient-perceived harm reduction, intersectional stigma and clinical outcomes related to HIV, hepatitis C (if applicable) and substance use-related outcomes through surveys (n=500) and focus groups (k=6, total n=36) with PWH who use drugs. We will also psychometrically evaluate a 25-item scale we previously developed to assess relational harm reduction, the Patient Assessment of Provider Harm Reduction Scale. Aim 3 will use human-centred design approaches to develop and pretest an intervention to operationalise harm reduction care for PWH who use drugs in HIV clinical settings., Ethics and Dissemination: This study was approved via expedited review by the University of Pittsburgh Institutional Review Board (STUDY21090002). Study findings will be presented in peer-reviewed journals and public health conferences as well as shared with patient participants, community advisory boards and harm reduction organisations., Trial Registration Number: NCT05404750., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Low levels of physical activity are associated with increased mortality risk, especially in cardiac patients, but most studies are based on self-report. Cardiac implantable electronic devices (CIEDs) offer an opportunity to collect data for longer periods of time. However, there is limited agreement on the best approaches for quantification of activity measures due to the time series nature of the data. We examined physical activity time series data from 235 subjects with CIEDs and at least 365 days of uninterrupted measures. Summary statistics for raw daily physical activity (minutes/day), including statistical moments (e.g., mean, standard deviation, skewness, kurtosis), time series regression coefficients, frequency domain components, and forecasted predicted values, were calculated for each individual, and used to predict occurrence of ventricular tachycardia (VT) events as recorded by the device. In unsupervised analyses using principal component analysis, we found that while certain features tended to cluster near each other, most provided a reasonable spread across activity space without a large degree of redundancy. In supervised analyses, we found several features that were associated with the outcome (P < 0.05) in univariable and multivariable approaches, but few were consistent across models. Using a machine-learning approach in which the data was split into training and testing sets, and models ranging in complexity from simple univariable logistic regression to ensemble decision trees were fit, there was no improvement in classification of risk over naïve methods for any approach. Although standard approaches identified summary features of physical activity data that were correlated with risk of VT, machine-learning approaches found that none of these features provided an improvement in classification. Future studies are needed to explore and validate methods for feature extraction and machine learning in classification of VT risk based on device-measured activity., Competing Interests: The authors have declared that no competing interests exist.