American journal of preventive medicine
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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.
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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.
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Peer providers with lived experiences of mental health and substance use are a growing component of the workforce responsible for the prevention and treatment of behavioral health disorders. This systematic literature review aims to better define the roles of peers and their unique contributions to behavioral health care. ⋯ Peers are effective providers of behavioral health treatment and relapse prevention services who encourage recovery through resilience building, empowerment, and self-advocacy. There remains a need for more evidence-based interventions on the efficacy of peers in substance use disorder treatment and the impact of formalized certification and training opportunities.
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Peer providers with lived experiences of mental health and substance use are a growing component of the workforce responsible for the prevention and treatment of behavioral health disorders. This systematic literature review aims to better define the roles of peers and their unique contributions to behavioral health care. ⋯ Peers are effective providers of behavioral health treatment and relapse prevention services who encourage recovery through resilience building, empowerment, and self-advocacy. There remains a need for more evidence-based interventions on the efficacy of peers in substance use disorder treatment and the impact of formalized certification and training opportunities.