Abstract
As quality of life (QoL) is a highly interdisciplinary topic with a multitude of related research areas, it is beneficial to avail researchers of an overview of the different streams explored in the field. Furthermore, knowledge of prominent sub-domains helps researchers identify links and overlaps between QoL and their fields of interest. To meet these needs, a text-mining-based computational literature review (CLR) of the journal of Applied Research in Quality of Life (ARQOL) was conducted using a machine learning process, latent Dirichlet allocation (LDA), in combination with selection criteria for the decision on the number of topics. The outcome provides the reader with a list of the twelve most heavily discussed topics: 1) consumption & materialism, 2) character strength, 3) spirituality, religiousness & personal beliefs, 4) inequality, 5) leisure & tourism, 6) health related QoL (HRQoL) I, 7) quality of working life (QWL), 8) childhood & adolescence, 9) disparity & development, 10) disorder, 11) community issues, and 12) health related QoL (HRQoL) II. In addition, authors, titles, and publication dates are listed for the top-5-ranked papers that most typify these topics. Subsequent content summaries of these papers reveal more detailed information, such as measurement constructs and theories.