A Biophilic Therapeutic Framework for Ageing Well in Care Settings
Bibliographic record
Abstract
Access to nature is fundamental to human health and wellbeing, yet opportunities for direct and frequent engagement with natural environments are often restricted for individuals in the 80+ age category, particularly those in care settings or living in remote locations. There is therefore an urgent need to enhance nature connections in care settings and provide personalised, restorative experiences that reflect individuals preferred natural features. This prefeasibility pilot study developed a framework to inform the design of therapeutic care settings, grounded in the principles of biophilic neuroarchitecture and designed to support ageing well. Conducted over six months in two care environments, the study applied the biophilic pattern of Complexity and Order to simulate Natural Analogues within immersive virtual settings. Mixed methods combining wearable sensor data and self-reported wellbeing measures were used to assess psychophysiological, emotional, and cognitive responses among participants aged 80 and above. Findings revealed that VR content aligned with individual nature preferences elicited higher levels of engagement, relaxation, and positive affect. This study demonstrates the potential for implementing biophilic design applications to develop therapeutic care settings which promote wellbeing and healthy ageing, particularly where access to real nature is infrequent or limited.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".