Evidence map›Paper›PMID 40697843›Full record

ArticleFrontiers in public health2025

Exploring the functional quality attributes of smart home for older adults based on qualitative research and Kano model.

Qin Yang, Peishan Li, Xing Liu, Chunnan Wei

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Qin YangBusiness School, Sichuan Normal University, Chengdu, China.
Peishan LiBusiness School, Sichuan Normal University, Chengdu, China.
Xing LiuBusiness School, Sichuan University, Chengdu, China.
Chunnan WeiBusiness School, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study investigates the functional attributes of smart home for older adults across different age groups, aiming to identify features that fulfill users' needs and give convenience, thereby offering scientific guidance for future smart home designs for older adults. Methods: Employing a multi-stage approach, this study commences with semi-structured interviews with older participants in China, analyzing transcripts using NVivo to guide questionnaire design. Subsequently, a questionnaire survey is administered to older adults in China, with the data processed using the Kano model incorporating the Better-Worse index with sensitivity coefficients. Results: The findings distinctly demonstrate divergent preferences among different age groups. Specifically, for older adults aged 60-69, health, life and entertainment functions emerge as top priorities, identifying two indicators classified as Must-be quality, five as One-dimensional quality, and one as Attractive quality. In contrast, among those older adults aged 70 and above, emphasis lies predominantly on health, life and emotion functions, identifying one indicator categorized as Must-be quality, six as One-dimensional quality and two as Attractive quality. Conclusion: This study highlights the existence of significant variations in the needs of different older adult age groups. Through the classification of functional attributes of smart home for older adults, development strategies can be precisely formulated to better meet the needs of different age groups.

Indexed as

Digital TechnologyHousingAgedAged, 80 and overChinaFemaleHumansInterviews as TopicMaleMiddle AgedQualitative ResearchQuality of LifeSurveys and QuestionnairesageingKano modelqualitative researchquality attributesmart home

Identifiers

PMID40697843
PMCPMC12279827

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.