Introduction: Medical readiness of individual service members (SMs) is an integral component of operational readiness. Electronic Health (eHealth) literacy, here defined as the ability to seek out, find, evaluate, and appraise, integrate, and apply what is gained in electronic environments toward solving a health problem, is a key skill to enhance individual medical readiness. The World Health Organization (WHO) has identified health literacy as an important social determinant of health.
View Article and Find Full Text PDFMinoritized older adults face multiple health inequities and disparities, but are less likely to benefit from evidence-based health care interventions. With the increasing diversity of the U.S.
View Article and Find Full Text PDFPurpose: Given that the recent eHealth literacy literature supports the properties of the 3-factor eHealth literacy scale (eHEALS) model in samples with millennials, adults, and older adults, the appropriate next step is to establish whether the model can be reproduced in a rural adolescent sample. The purpose of this study was to evaluate the recent 3-factor model by Paige and associates with a sample of seventh-grade students.
Methods: This cross-sectional study included a subsample of students (n = 146) from 3 school districts in Appalachian Kentucky.
Cancer is the leading cause of death among American Indian and Alaska Native (AIAN) women, and depressive symptoms have been linked to higher mortality, but research on depressive symptoms among AIAN cancer patients has been scant. The purpose of this exploratory study was, using the Framework of Historical Oppression, Resilience, and Transcendence, to examine risk and protective factors related to depressive symptoms in American Indian (AI) women cancer survivors. We examined the relationships of adverse childhood experiences (ACE), perceived health status, resilience, and social support with depressive symptoms in Northern Plains AI women cancer survivors.
View Article and Find Full Text PDFThis study tests an ecological, relationship-based model of children's subjective well-being with 9- to 14-year-old children (n = 25,906) from 14 countries across Africa, Asia, Europe, North America, and South America. Children completed the Children's Worlds survey, a self-report measure of contextual and well-being indicators. Multilevel modeling was used to predict children's well-being (life satisfaction and self-image) at two levels, child (age, gender, home context, family relationships, peer relationships, school context, teacher relationships, and neighborhood quality), and country (gross domestic product and income inequality).
View Article and Find Full Text PDFInstruments assessing geriatric case managers' perceptions of prescription abuse are limited. Based on a review of current literature and pilot testing feedback, 22 items were initially assembled to form an older adult Prescription Drug Assessment Questionnaire (PDAQ). Case managers ( N = 161) at an older adult agency located in a Midwestern state were surveyed using the instrument.
View Article and Find Full Text PDFJ Soc Work Disabil Rehabil
October 2011
This article reviews the literature on adults with serious mental illness, their caregivers, and smart home technology. The article provides compelling evidence for social workers to undertake research aimed at investigating caregivers' perceptions toward using smart home technology for care of adult family members or friends with a serious mental illness. Empirical support for using smart home technologies with adults with serious mental illness is provided, and recommendations for future social work research are offered.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
April 2010
In this paper, we propose a real-time system for in-home activity monitoring and functional assessment for elder care. We describe the development of the whole system which could be used to assist the independent living of elders and improve the efficiency of eldercare practice. With this system, data is collected, silhouettes extracted, features further analyzed and visualized into graphs from which eldercare professionals are able to understand massive video monitoring data within a short period of time.
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