Exploring The Relationship Between Creative Programming and Mental/Emotional Outcomes with Older Adults in Ontario
Bibliographic record
Abstract
This qualitative research project examines the relationship between creative programming and mental and emotional outcomes in order to substantiate the hypothesis that there are benefits to creative programming in Long Term care and community centres on social and emotional levels when implemented on older adults in Ontario. Thirteen participants who worked with older adults in various long-term care and community settings were recruited to participate in an online survey. Participants shared that the value in creative programming in terms of positive socialization processes; and displays of positive mental health in older adults participating in creative programming. The unique contribution of this research is in providing specific observations about the positive impacts that creative programming can have on the mental and emotional states of older adults. The methods used to assess this inquiry was the implementation of a 10-question anonymous survey that assessed the implications towards benefits in regards to creative programming, in the domains of socialization and mental health. The findings exemplify the importance of implementing creative programming in Long Term Care and Community outreach settings so that the benefits of positive socialization and mental health benefits can be substantiated in a way that impacts older adults living in Ontario in a transformative and impactful manner.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".