The impact of gerontology-focused competencies on recreation therapists’ expectations of aging
Bibliographic record
Abstract
As the United States (US) population continues to age rapidly, healthcare professionals—including recreation therapists (RTs)—must be prepared to meet the complex needs of older adults. Despite the high percentage of certified therapeutic recreation specialists working with geriatric populations, gerontology-focused education is not currently required for certification. This quantitative study surveyed 410 RTs across the US and Canada to examine whether the completion of a university-level gerontology course influenced perceptions of aging. Using the Expectations Regarding Aging-12 survey, the study found that participants who had completed a 3-credit gerontology course reported significantly more positive perceptions of aging (mean = 71.38) than those who had not (mean = 69.67), with results reaching statistical significance (t(204) = 2.24, p = .026). While the effect size was small, findings suggest that gerontology coursework may positively shape RTs’ attitudes toward aging. The study underscores the need for the National Council for Therapeutic Recreation Certification to consider incorporating gerontology-specific competencies into certification requirements. Doing so could help reduce ageism in care settings and enhance therapeutic outcomes for the growing population of older adults.
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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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".