Digging into the experiences of therapeutic gardening for people with dementia: An interpretative phenomenological analysis
Bibliographic record
Abstract
Gardening programmes aim to promote improved engagement and quality of life in persons with dementia. Although a substantial literature has amassed documenting the overall positive outcomes associated with therapeutic gardening and horticulture for persons with dementia, little is known about the specific aspects of the gardening process that engender these benefits, and how and why they are important. The purpose of this research was to explore, using interpretative phenomenological analysis, the experiences of therapeutic gardening for persons with dementia, and their perspectives on the senses and emotions elicited in the gardening process that promote well-being. The themes that emerged in our analysis are to varying degrees substantiated in the literature: the usefulness of activating the senses, particularly those of touch and smell; the significance of being occupied in meaningful, productive work; the importance of cultivating a sense of curiosity, wonder, and learning; the positive gains derived from socialization in a group context; the peace and hope derived from being 'in the moment'; and the positive mental and physical well-being derived from participating in the outdoor garden. Our findings support the integration of therapeutic gardening as a valuable practice for people with dementia.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| 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".