137 research outputs found

    Digital Health-Enabled Community-Centered Care: Scalable Model to Empower Future Community Health Workers Using Human-in-the-Loop Artificial Intelligence

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    Digital health–enabled community-centered care (D-CCC) represents a pioneering vision for the future of community-centered care. D-CCC aims to support and amplify the digital footprint of community health workers through a novel artificial intelligence–enabled closed-loop digital health platform designed for, and with, community health workers. By focusing digitalization at the level of the community health worker, D-CCC enables more timely, supported, and individualized community health worker–delivered interventions. D-CCC has the potential to move community-centered care into an expanded, digitally interconnected, and collaborative community-centered health and social care ecosystem of the future, grounded within a robust and digitally empowered community health workforce.</p

    Psychosocial predictors of current drug use, drug problems, and physical drug dependence in homeless women

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    We examined risk and protective factors associated with three qualitatively different drug use constructs describing a continuum of drug use among a sample of 1,179 homeless women. Relationships among positive and negative sources of social support, positive and negative coping strategies, depression, and the drug constructs of current drug use, drug problems, and physical drug dependence were assessed using structural equation models with latent variables. Current drug use was predicted by more negative social support (from drug-using family/friends), depression, and less positive coping. Drug Problems were predicted by more negative coping, depression, and less positive coping. Physical Drug Dependence was predicted by more negative social support and depression, and less positive social support. Results highlighted the importance of investigating both the positive and negative dimensions of psychosocial functioning, while suggesting that empowering homeless women and offering tangible resources for coping with the stress of being homeless may be beneficial to them

    Predictors of Hepatitis Knowledge Improvement Among Methadone Maintained Clients Enrolled in a Hepatitis Intervention Program

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    This randomized, controlled study (n = 256) was conducted to compare three interventions designed to promote hepatitis A virus (HAV) and hepatitis B virus (HBV) vaccination completion, among clients undergoing methadone maintenance treatment (MMT) in Los Angeles and Santa Monica. The participants were randomized into three groups: Motivational Interviewing-Single Session (MI-Single), Motivational Interviewing-Group (MI-Group), or Nurse-Led Hepatitis Health Promotion (HHP). All three treatment groups received the 3-series HAV/HBV vaccine. The MI sessions were provided by trained therapists, the Nurse-Led HHP sessions were delivered by a research nurse. The main outcome variable of interest was improvement in HBV and HCV knowledge, measured by a 6-item HBV and a 7-item HCV knowledge and attitude tool that was administered at baseline and at 6-month follow-up. The study results showed that there was a significant increase in HBV- and HCV-related knowledge across all three groups (p < 0.0001). There were no significant differences found with respect to knowledge acquisition among the groups. Irrespective of treatment group, gender (P = 0.008), study site (P < 0.0001) and whether a participant was abused as a child (P = 0.017) were all found to be predictors of HCV knowledge improvement; only recruitment site (P < 0.0001) was found to be a predictor of HBV knowledge. The authors concluded that, although MI-Single, MI-Group and Nurse-Led HHP are all effective in promoting HBV and HCV knowledge acquisition among MMT clients, Nurse-Led HHP may be the method of choice for this population as it may be easier to integrate and with additional investigation may prove to be more cost efficient

    Predicting Patient Advocacy Engagement: A Multiple Regression Analysis Using Data From Health Professionals in Acute-Care Hospitals

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    Although literature documents the need for hospital social workers, nurses, and medical residents to engage in patient advocacy, little information exists about what predicts the extent they do so. This study aims to identify predictors of health professionals' patient advocacy engagement with respect to a broad range of patients' problems. A cross-sectional research design was employed with a sample of 94 social workers, 97 nurses, and 104 medical residents recruited from eight hospitals in Los Angeles. Bivariate correlations explored whether seven scales (Patient Advocacy Eagerness, Ethical Commitment, Skills, Tangible Support, Organizational Receptivity, Belief Other Professionals Engage, and Belief the Hospital Empowers Patients) were associated with patient advocacy engagement, measured by the validated Patient Advocacy Engagement Scale. Regression analysis examined whether these scales, when controlling for sociodemographic and setting variables, predicted patient advocacy engagement. While all seven predictor scales were significantly associated with patient advocacy engagement in correlational analyses, only Eagerness, Skills, and Belief the Hospital Empowers Patients predicted patient advocacy engagement in regression analyses. Additionally, younger professionals engaged in higher levels of patient advocacy than older professionals, and social workers engaged in greater patient advocacy than nurses. Limitations and the utility of these findings for acute-care hospitals are discussed
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