Evidence map›Paper›PMID 42058067›Full record

ArticleFrontiers in public health2026

Designing for aging on the move: a user-needs-driven approach to an optimized recreational vehicle (RV) scheme for older Chinese using an integrated Kano-AHP-QFD framework.

Yin Jing, Sheng Yu, Yongsheng Cheng, Xinxin Yang

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. 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
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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

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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

4 authors.

Yin JingSchool of Future Design, Beijing Normal University, Zhuhai, China.
Sheng YuSchool of the English Language & Culture, Xiamen University Tan Kah Kee College, Zhangzhou, China.
Yongsheng ChengSchool of Design & Innovation, Xiamen University Tan Kah Kee College, Zhangzhou, China.
Xinxin YangSchool of Design & Innovation, Xiamen University Tan Kah Kee College, Zhangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Against the backdrop of an aging population and ongoing innovations in care models for older adults, travel-based retirement-an emerging lifestyle that integrates tourism and senior living-calls for age-friendly recreational vehicle (RV) designs to meet the diverse residential and mobility needs of older adults. In such mobile retirement contexts, this study aims to produce an optimized RV design scheme that enhances living comfort and functional adaptability for older adult users. Methods: First, data were gathered through online questionnaires and field interviews to uncover the core needs of older adult RV users. Then, these needs were classified using the Kano model into five types: must-be, one-dimensional, attractive, indifferent, and reverse. Next, the Analytic Hierarchy Process (AHP) was used to prioritize these needs within a demand evaluation system. Subsequently, Quality Function Deployment (QFD) was applied to construct a House of Quality that maps user needs to product design characteristics and identifies key design indicators. Results: Based on the integrated analysis, we distilled six core design elements and developed three RV schemes tailored to older adult users. Finally, user evaluations helped determine the optimal scheme. Our findings demonstrate that the combined Kano-AHP-QFD approach effectively quantifies the demands of older adult users, enhancing design rigor and user satisfaction. Discussion: This methodological framework shows strong practical value in age-friendly RV development and offers a foundation for integrating intelligent technologies and human-centered care into future travel-based retirement schemes.

Indexed as

AgingRecreationAgedAged, 80 and overChinaEast Asian PeopleFemaleHumansMaleRetirementSurveys and QuestionnairesAHPKano modelQFDRV designtravel-based older adult care

Identifiers

PMID42058067
PMCPMC13120922

What OpenQuestion holds

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LicenceCC BY
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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.