Relationships between Green Space Perceptions, Green Space Use, and the Multidimensional Health of Older People: A Case Study of Fuzhou, China
Bibliographic record
Abstract
Urban green spaces are vital for older people’s health. However, most studies have only focused on their relationship with single-dimensional health outcomes. This study introduced a theoretical model to explore how perceptions of green spaces influence older people’s multidimensional health, mediated by the use of these spaces. Using a literature review, interviews, and surveys, we developed and refined a measurement scale for older people’s perceptions of urban greenery. Using data from 513 seniors in Fuzhou’s urban parks, structural equation modeling was used to examine the relationships between their multidimensional health, usage, and perceptions of green spaces. The results showed that older people’s positive evaluations of green spaces, especially those with facilities, significantly increased their usage. This increased usage positively influences their physical, mental, and social health, with the most pronounced benefits for social health. The total impact of green space perception on multidimensional health was beneficial and significantly impacted social health, even though the direct impacts of quality perception on physical health and facility perception on social health were minimal. These findings enhance our understanding of the impact of green spaces on the health of older individuals and provide a theoretical basis for developing urban green spaces that maximize health advantages for older people.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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".