Multilevel Analysis of Child and Adolescent Subjective Well-Being Across 14 Countries: Child- and Country-Level Predictors.

This 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). Findings indicated that intercepts varied significantly across countries. The majority of variance in children's well-being was attributed to child-level rather than country-level factors. Country-level factors did not strongly predict well-being but marginally improved model fit.

Identifying risk and protective factors related to depressive symptoms among Northern Plains American Indian women cancer survivors.

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. We used a cross-sectional design with purposive sampling of 73 female cancer survivors (aged 18 years or older) between June 2014 and February 2015. Hierarchical multiple regression was used to test three sets of variables in relation to depressive symptoms: (1) sociodemographics, (2) risk factors (ACE and perceived health), and (3) protective factors (psychological resilience and social support). Approximately 47 percent of participants had probable depressive symptoms. Depressive symptoms were inversely associated with perceived health, psychological resilience, and social support. These results support bolstering existing social support among AI cancer patients and survivors as well as prevention and intervention efforts that strengthen resilience.

Validation of the eHEALTH Literacy Scale (Eheals) With Military Service Members.

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. The Internet enables individuals to access information virtually anywhere, at any place, any time, which is especially beneficial for SMs who serve around the globe, often isolated from modern health care facilities. MATERIALS AND METHODS: This study examined the utility of the eHealth literacy scale (eHeals) as a potentially valuable tool to assist commanders and medical teams for assessing the health literacy of SMs. The main objective of our study was to examine the validity of the three-factor eHEALS measure for an active duty sample, using confirmatory factorial analysis. RESULTS: Our findings support the validity of the eHEALS measure of electronic health literacy among military SMs, potentially identifying a means of measuring SMs' health literacy, and a target for intervention to increase medical readiness, well-being, and overall quality of life for individual SMs. CONCLUSIONS: The study highlights a brief 6-item assessment tool that can quickly and efficiently be added to the current validated health and well-being measures for military personnel. This brief assessment can provide a measure of knowledge, skills, and confidence regarding ehealth information leading to better-informed health care decisions in the military context. These findings are especially relevant given the military's current emphasis on modernization and the need to put people first in order to build the overall team and improve unit effectiveness.

Exploring Challenges and Strategies in Partnering With Community-Based Organizations to Advance Intervention Development and Implementation With Older Adults.

Minoritized 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. aging population, there is a great promise for gerontology researchers to partner with racial/ethnic minority organizations and underrepresented communities to develop and implement evidence-based health interventions. Community-Based Participatory Research and Implementation Science offer guidance and strategies for researchers to develop and sustain community partnerships. However, researchers partnering with community organizations continue to face challenges in these collaborations, study outcomes, and sustainability. This may be especially true for those junior in their career trajectory or new to community-engaged research. The purpose of this forum article is to detail critical challenges that can affect gerontology researcher-community partnerships and relationships from the perspective of researchers. Seven challenges (pre- or mid-intervention design, implementation, and postimplementation phases) described within the Equity-focused Implementation Research for health programs framework are identified and discussed. Potential solutions are also presented. Planning for potential obstacles of the researcher-community partnerships can inform innovative solutions that will facilitate successful partnerships, thereby promoting the advancement of collaborative research between academic institutions and community organizations to improve older adult health outcomes.

Validating the eHealth Literacy Scale in Rural Adolescents.

PURPOSE: 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. We used confirmatory factor analysis (CFA) procedures and small sample model fit guidelines to evaluate our model, and the 1-sample bootstrap algorithm with bias-corrected and accelerated 95% confidence intervals to estimate associations among eHEALS and health and technology variables. FINDINGS: A total of 137 students, or 61% of enrolled seventh-grade students, completed the study. CFA results showed eHEALS 3-factor loadings-information awareness, information seeking, and information engagement-were high (≥0.63) and statistically significant. We observed evidence of a good model fit (root mean square error of approximation [RMSEA] = 0.07, standardized root mean square residual [SRMR] = 0.03, comparative fit index [CFI] = 0.99) and results are comparable with Paige and associates' model fit (RMSEA = 0.06, SRMR = 0.08, CFI = 0.98). Correlations showed that students with more access to technology were associated with higher information seeking (r = 0.31) and higher information engagement (r = 0.23). eHealth literacy scores did not differ by level of rurality or gender. CONCLUSIONS: The 3-factor eHEALS is a reliable and valid instrument in assessing eHealth literacy in a group of rural seventh graders from Appalachian Kentucky.

Development of the Older Adult Prescription Drug Assessment Questionnaire for Case Workers.

Instruments 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. Data were subjected to exploratory factor analysis using principal axis factoring (PAF) and Promax rotation, and Horn's parallel analysis determined the number of extracted factors. PAF generated a final 11-item three-factor model accounting for 51% of total variance explained: Standard Assessment (Factor 1; four items; ∞ = .83), Assessment Belief (Factor 2; three items; ∞ = .74), and Problem Scope (Factor 3; four items; ∞ = .62). The older adult PDAQ is a brief, data-driven instrument with acceptable psychometric properties for assessing perceptions of prescription drug abuse and misuse assessment and counseling.

The need to know caregiver perspectives toward using smart home technology.

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.

A real-time system for in-home activity monitoring of elders.

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. Our experimental results demonstrate that the proposed system is efficient in indoor elder activities monitoring and easily utilized by eldercare professionals.