Evidence map›Paper›PMID 37685474›Full record

ArticleHealthcare (Basel, Switzerland)2023

Long-Term Adoption or Abandonment of Smart Technology in the Chinese Elderly Home Care Environment: A Qualitative Research Study.

Jiahao Yu, Jianyuan Huang, Qi Yang

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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.

Jiahao YuPopulation Research Institute, Hohai University, Nanjing 211100, China.ORCID 0000-0001-9098-6739
Jianyuan HuangPopulation Research Institute, Hohai University, Nanjing 211100, China.
Qi YangPopulation Research Institute, Nanjing University of Posts and Telecommunications, Nanjing 210042, China.

Funding

Fundament for the Central University B230205005 & B220201053
6 · The paper itself

Abstract

China's rapidly aging population and shortage of care resources have made it difficult for its traditional model to meet the home care needs of the elderly. On this premise, China is implementing home digital health interventions based on smart technology. During implementation, instead of the expected explosion in long-term adoption, there has been a large amount of abandonment. But so far, the relationship between service experience and these behaviors has been ignored. This study aims to explore the reasons for the long-term adoption or abandonment behaviors of technology by elders in the home care environment. A qualitative study was conducted based on Golant's framework of smart technology adoption behaviors among elders. Semi-structured interviews were conducted with 26 elders who are long-term or former users of smart technology in a home care environment, and data from the interviews were analyzed using directed content analysis. This study identified three themes that influence elders' adoption behaviors of smart technology in the home care environment, including immediate effectiveness, long-term usability, and possible collateral damage. The findings indicated that the experience of the elders is the key point that affects long-term adoption behavior. For more elders to use smart technology in the home care environment, it is necessary for the government, technology developers, and nursing institutions to further reform the existing system.

Indexed as

home careolder adultqualitative studysmart technologytechnology acceptance models

Identifiers

PMID37685474
PMCPMC10486740

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.