Evidence map›Paper›PMID 41346983›Full record

ArticleFrontiers in medicine2025

Integrating BWM and modified VIKOR for age-friendly community park assessment in the context of mental health.

Zhi-Hao Zhang, Yi-Fan Zhang, Cheng-Cheong Lei

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Zhi-Hao ZhangSchool of Knowledge Science, Japan Advanced Institute of Science and Technology, Ishikawa, Japan.
Yi-Fan ZhangCollege of Design and Innovation, Tongji University, Shanghai, China.
Cheng-Cheong LeiFaculty of Arts and Design, Macao Polytechnic University, Macau, Macao SAR, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Late-life depression is a growing public health challenge in aging societies. Community parks are increasingly recognized as protective environments, yet evidence on which specific attributes most effectively alleviate depression among older adults remains limited. Methods: This study proposed a hybrid framework combining the Best-Worst Method (BWM) and a Modified VIKOR approach. Eight criteria (Access points, Pathways, Facilities for different activities, Open space, Amenities, Natural features, Sunlight, Incivilities) were identified through literature review. Twenty-three experts conducted BWM pairwise comparisons, with 13 valid responses retained after consistency checks. Nine community parks in Zhuhai, China, were then evaluated using gap scores and ranked via Modified VIKOR. Results: The evaluation revealed that open space (16.26%), facilities for different activities (14.27%), and public amenities (13.50%) were the most influential in reducing depression risk. Rankings showed notable disparities among the nine parks. Improvement priorities focused on expanding spaces for exercise and social interaction, upgrading seating, lighting, and waste facilities, and gradually enhancing vegetation and environmental order. Access and pathway conditions were generally adequate, requiring only localized adjustments. Conclusion: Community park environments contribute to late-life depression alleviation through differentiated mechanisms. The BWM-Modified VIKOR framework provides an evidence-based tool for prioritizing age-friendly park renovations under limited resources. Priority should be given to upgrading activity facilities, open spaces, and amenities.

Indexed as

best-worst methodcommunity parkshealthy agingmental healthVIKOR

Identifiers

PMID41346983
PMCPMC12672882

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.