American journal of preventive medicine
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Clinical preventive services can reduce mortality and morbidity, but Americans receive only half of the recommended care. Although wellness visits protect time for clinicians to review needs and discuss care with patients, studies have not shown that having a wellness visit improves health outcomes. This study seeks to understand the types of discussions and volume of care delivered during wellness visits. ⋯ Wellness visits are an important time for patients and clinicians to discuss prevention strategies and to deliver recommended clinical preventive services, leading to the identification of previously unrecognized diagnoses. This will improve patients' health. Policies and incentives that promote wellness visits are important, and efforts are needed to deliver them to those most in need.
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Adults from racial and ethnic minorities and low-income groups are disproportionately affected by vaccine-preventable diseases. The objective of this study is to examine the trends in adult vaccination coverage in the U.S. by race/ethnicity and SES from 2010 to 2019. ⋯ Racial and ethnic disparities in vaccine uptake persisted over the last decade. Socioeconomic disparities in influenza vaccine coverage narrowed among adults aged 18-64 years; however, disparities persisted among adults aged ≥65 years. Efforts are urgently needed to achieve equity in immunization rates.
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Suboptimal and differential participant engagement in randomized trials-including retention at primary outcome assessments and attendance at intervention sessions-undermines rigor, internal validity, and trial conclusions. ⋯ The Methods-Motivational Interviewing approach shows promise for increasing the rigor of randomized trials and is readily adaptable to in-person, webinar, and conference call formats.
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Cardiovascular disease is the leading cause of death worldwide, and cardiovascular disease burden is increasing in low-resource settings and for lower socioeconomic groups. Machine learning algorithms are being developed rapidly and incorporated into clinical practice for cardiovascular disease prediction and treatment decisions. Significant opportunities for reducing death and disability from cardiovascular disease worldwide lie with accounting for the social determinants of cardiovascular outcomes. This study reviews how social determinants of health are being included in machine learning algorithms to inform best practices for the development of algorithms that account for social determinants. ⋯ Given their flexibility, machine learning approaches may provide an opportunity to incorporate the complex nature of social determinants of health. The limited variety of sources and data in the reviewed studies emphasize that there is an opportunity to include more social determinants of health variables, especially environmental ones, that are known to impact cardiovascular disease risk and that recording such data in electronic databases will enable their use.