Evidence map›Paper›PMID 33787505›Full record

ArticleJournal of medical Internet research2021

Acceptance of Technologies for Aging in Place: A Conceptual Model.

Christina Jaschinski, Somaya Ben Allouch, Oscar Peters, Ricardo Cachucho, Jan A G M van Dijk

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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  12. Psychological antecedents of telehealth acceptance: A technology readiness perspective.International journal of disaster risk reduction : IJDRR · 2023
    Article
  13. Article
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  15. eHealth Platforms to Promote Autonomous Life and Active Aging: A Scoping Review.International journal of environmental research and public health · 2022
    Article
  16. Concept development of "Aging in place": Application of hybrid model.Journal of family medicine and primary care · 2022
    Review
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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

5 authors.

Christina JaschinskiResearch Group Technology, Health & Care, Saxion University of Applied Sciences, Enschede, Netherlands.ORCID 0000-0002-7940-7684
Somaya Ben AllouchDigital Life, Amsterdam University of Applied Sciences, Amsterdam, Netherlands.ORCID 0000-0002-3502-4016
Oscar PetersSaxion University of Applied Sciences, Enschede, Netherlands.ORCID 0000-0001-7914-2463
Ricardo CachuchoLeiden Institute of Advanced Computer Science (LIACS), Leiden University, Leiden, Netherlands.ORCID 0000-0002-5975-1058
Jan A G M van DijkUniversity of Twente, Enschede, Netherlands.ORCID 0000-0001-9739-3266

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOlder adults want to preserve their health and autonomy and stay in their own home environment for as long as possible. This is also of interest to policy makers who try to cope with growing staff shortages and increasing health care expenses. Ambient assisted living (AAL) technologies can support the desire for independence and aging in place. However, the implementation of these technologies is much slower than expected. This has been attributed to the lack of focus on user acceptance and user needs.

objectiveThe aim of this study is to develop a theoretically grounded understanding of the acceptance of AAL technologies among older adults and to compare the relative importance of different acceptance factors.

methodsA conceptual model of AAL acceptance was developed using the theory of planned behavior as a theoretical starting point. A web-based survey of 1296 older adults was conducted in the Netherlands to validate the theoretical model. Structural equation modeling was used to analyze the hypothesized relationships.

resultsOur conceptual model showed a good fit with the observed data (root mean square error of approximation 0.04; standardized root mean square residual 0.06; comparative fit index 0.93; Tucker-Lewis index 0.92) and explained 69% of the variance in intention to use. All but 2 of the hypothesized paths were significant at the P<.001 level. Overall, older adults were relatively open to the idea of using AAL technologies in the future (mean 3.34, SD 0.73).

conclusionsThis study contributes to a more user-centered and theoretically grounded discourse in AAL research. Understanding the underlying behavioral, normative, and control beliefs that contribute to the decision to use or reject AAL technologies helps developers to make informed design decisions based on users' needs and concerns. These insights on acceptance factors can be valuable for the broader field of eHealth development and implementation.

Indexed as

Independent LivingTelemedicineAgedAgingHumansModels, TheoreticalTechnologyambient assisted livingassistive technologyhealthy agingstructural equation modelingtechnology adoptiontheory of planned behavior

Identifiers

PMID33787505
PMCPMC8047804

What OpenQuestion holds

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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.