Given the growing population of aging adults, there is a need for research examining factors that enhance quality of life for older adults (QoL; Colby & Ortman, 2014). Changes in health, relationships, support systems, and social identity are inevitable throughout the lifespan. Therefore, research focused on lessening the negative effects of changes due to aging while also improving QoL is warranted. As such, the aim of the current research study was to examine the extent to which subjective age (SA; how old or young an individual feels), playfulness (PF; "the ability to frame or reframe everyday situations to experience them as entertaining, intellectually stimulating, and/or personally interesting" [Proyer, 2015, p. 93-94]), and depression (an emotional state ranging from mild discouragement to feelings of extreme despair [CDC, 2017; Corsini, 2002]) predict QoL ("a person's sense of well-being that stems from satisfaction or dissatisfaction with the areas of life that are important to him or her" [Ferrans, 1985, p. 15]) among adults over the age of 55. Using convenience sampling with eligibility requirements, adults (N = 1,315) 55 and older and who spoke and read English were surveyed both face-to-face (F2F) and online (e.g., Amazon Mechanical Turk and a senior educational program). Standard multiple regression was utilized, and results identified a statistically significant model with the variable of depression predicting the largest unique contribution to the model, while PF predicted a small, statistically significant contribution. Subjective age did not statistically contribute to the prediction. Implications from the findings that relate to counselors, counselor educators, and researchers are provided. In addition, the findings provide guidance and a new perspective on variables associated with QoL and aging adults.
Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-6805 |
Date | 01 January 2018 |
Creators | Saliba El Habre, Yvette |
Publisher | STARS |
Source Sets | University of Central Florida |
Language | English |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Electronic Theses and Dissertations |
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