The use of acceptance and commitment therapy among older adults in assisted living: a trend analysis and acceptability and feasibility study
Bibliographic record
Abstract
Canadian society is undergoing a major demographic shift in which a fifth of the population will be 65 years or older by 2024 (Garner et al., 2018). Professionals will need to become more adept at addressing this population’s mental health needs (Cairney et al., 2008). Prevalence rates of depression, anxiety, and chronic pain among older adults appear to vary by residential setting, with increased intensity of associated care associated with increased prevalence of mental health difficulties (Barbosa et al., 2014; Blazer, 2003; Creighton et al., 2015; Djernes, 2006; Fiske, 2009; Maxwell et al., 2013; Watson et al., 2003; Watson et al., 2006). \nAssisted living facilities are ideal sites for intervention as residents’ mental health in this setting has serious implications for earlier discharge to nursing homes and even death (Watson et al., 2003). Group-based ACT interventions offer an effective and resource efficient solution to address this population’s needs. The present study examines the impact of group-based ACT on participants’ depression, anxiety, and chronic pain and examines the intervention’s acceptability and feasibility. Trend analyses were consistent with the anticipated reduction of anxiety and, to a lesser extent, depression. While the intervention appeared to be acceptable, there were significant challenges with feasibility, particularly with regarding recruitment. Implementing different recruitment strategies, including developing longstanding relationships with participating facilities and accepting referrals from potential participants’ treatment teams, may increase feasibility in future studies.
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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 | 0.012 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".