A Scoping Review of Research on the Arts, Aging, and Quality of Life
Bibliographic record
Abstract
PURPOSE OF THE STUDY: Artistic engagement has been identified as a promising way to improve older adults' quality of life (QoL) and health. This has resulted in a growing, yet diverse, knowledge base. The purpose of this scoping review was to describe and map the nature and extent of research conducted on the arts, aging, and either QoL or health for well older adults. DESIGN AND METHODS: We followed scoping review procedures. Research librarians developed a comprehensive search strategy to capture published and gray literature across 16 databases. We systematically screened 9,720 titles/abstracts and extracted data. Findings were collated by tabulating frequencies and textual data organized according to themes. RESULTS: 94 articles were included, spanning nine disciplines, and most were published after 2000 (72%). Most of the studies were conducted in the United States (52%). Research teams rarely published more than one study about the arts and QoL/health. The studies used qualitative (49%), quantitative (38%), or mixed methods (10%). The most common art form examined was music (40%). Artistic engagement was usually active (70%) and frequently occurred in groups (56%). Health and QoL were conceptualized and operationalized in many different ways. IMPLICATIONS: There is a need for programs of research (instead of teams conducting only one study), the development and application of conceptual frameworks, and multiple perspectives in order to build knowledge about how the arts contribute to health and QoL for older adults.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.040 | 0.151 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.038 | 0.039 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".