Selected article for: "forward selection and linear regression"

Author: Martin, Maya; Saltzman, Leia Y; Henry, Veronica; Broussard, Crystal; Hansel, Tonya Cross
Title: Mental health and well-being for aging adults during the COVID-19 pandemic
  • Cord-id: hnhnsjfe
  • Document date: 2021_1_1
  • ID: hnhnsjfe
    Snippet: INTRODUCTION: The COVID-19 pandemic remains a significant mental health crisis. Although empirical research works to better understand the impact of COVID-19 on the mental health of the general population, some groups remain at greater risk for adverse mental health consequences. The purpose of this study is to better understand how COVID-19 experiences, food insecurities, and social support are associated with mental health and well-being for aging populations. METHODS: Data collection began Ap
    Document: INTRODUCTION: The COVID-19 pandemic remains a significant mental health crisis. Although empirical research works to better understand the impact of COVID-19 on the mental health of the general population, some groups remain at greater risk for adverse mental health consequences. The purpose of this study is to better understand how COVID-19 experiences, food insecurities, and social support are associated with mental health and well-being for aging populations. METHODS: Data collection began April 1, 2020 and continued through May 22, 2020. Study participants were recruited via website and media promotion and completed an anonymous survey. A sample of adults age 50 years and older (N = 136) were selected for the current analysis. Measures included scales of anxiety, depression, resilience, quality of life, COVID-19 experiences, interdependence, and insecurities. Three stepwise linear regression models were conducted using forward selection were estimated. RESULTS: The first model found food insecurity, community closeness, and COVID-19 experiences predicted 23% of the variance in mental health. The second model found having enough money to meet needs, COVID-19 interdependence, and age predicted 20% of the variance in resilience. The final model found having enough money to meet needs, COVID-19 experiences, community closeness, and information access predicted 45% of the variance in quality of life. DISCUSSION: Our discussion highlights the role of COVID-19 experiences, tangible resource losses, and community connection in mental health outcomes for aging populations during COVID-19. We suggest areas of future research and highlight the important role of technology in both scholarship and practice.

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