The Lively, Healing, and Intergenerational Semi-Open Spaces in Older Adults Care Homes’ Courtyard: Joyful Older Adults and Children
Bibliographic record
Abstract
The global population of older adults is rising, projected to reach 1.4 billion by 2030, surpassing the number of children by 0.1 billion and making up around 25% of the total population. Older adults are more susceptible to anxiety due to factors such as diminished self-esteem, reduced independence (both physical and financial), limited activity and mobility, loss of social connections, and chronic illnesses. Additionally, depression and loneliness are common among older adults and often go untreated. Research shows that intergenerational activities in interactive environments can enhance self-confidence, social interaction, recognition, and intellectual development for both older adults and children. \nThis study aims to create an intergenerational semi-open space within the courtyards of elderly care homes, tailored to the environmental needs and preferences of older adults and children. By integrating desirable features and elements, this space promotes mental well-being for both age groups, facilitating quality time together. To understand their environmental preferences, two theoretical frameworks were applied: Ulrich’s Supportive Design Theory (1991) and the Six Design Attributes by Windley and Scheidt (1980). \nIn the methodology, a qualitative approach using painting and writing techniques involved 25 participants, comprising 14 older adults (aged 60-95) and 9 children (aged 8-14) in Montreal. Five themes were derived from the collected data: 1. Nature, 2. Homelike, 3. Socializing, 4. Activity, and 5. Attributes of Space. The study highlighted that participants highly valued "Positive Distraction" and "Sensory Perception" as key elements in designing intergenerational spaces. "Perception of Control" was also of interest, particularly in connection with "Positive Distraction," and shared content similarities with other elements. In contrast, "Social Support" and "Sociality" were rated lower. Interestingly, all elements were mentioned by participants except for 'Legibility,' a crucial aspect of well-designed intergenerational spaces according to the 'Six Design Attributes' concept by Windley and Scheidt (1980). The study recommends that designers should still incorporate 'Legibility' into their designs, even if the participants don't mention it. Additionally, the study identified design considerations, offered recommendations, and created architectural diagrams based on the extracted themes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".