Evidence map›Paper›PMID 36829316›Full record

ArticleBehavioral sciences (Basel, Switzerland)2023

Explaining the Consumption Technology Acceptance in the Elderly Post-Pandemic: Effort Expectancy Does Not Matter.

Patricio Ramírez-Correa, Elizabeth Eliana Grandón, Muriel Ramírez-Santana, Jorge Arenas-Gaitán, F Javier Rondán-Cataluña

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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.

Patricio Ramírez-CorreaSchool of Engineering, Universidad Católica del Norte, Coquimbo 1781421, Chile.ORCID 0000-0001-7089-1505
Elizabeth Eliana GrandónDepartment of Information Systems, Universidad del Bío-Bío, Concepción 4051381, Chile.ORCID 0000-0002-8639-667X
Muriel Ramírez-SantanaPublic Health Department, Faculty of Medicine, Universidad Católica del Norte, Coquimbo 1781421, Chile.ORCID 0000-0002-3642-6965
Jorge Arenas-GaitánDepartment of Business Administration and Marketing, Universidad de Sevilla, 41004 Sevilla, Spain.ORCID 0000-0003-4635-9425
F Javier Rondán-CataluñaDepartment of Business Administration and Marketing, Universidad de Sevilla, 41004 Sevilla, Spain.ORCID 0000-0003-0368-5335

Funding

Agencia Nacional de Investigación y Desarrollo FONDECYT Regular 1210130
6 · The paper itself

Abstract

Consumer technology has been enormously boosted by the COVID-19 pandemic, with one of the primary consumers being the elderly. In this scenario, it is necessary to consider the impact of technologies on different older generational cohorts to understand the future of a data-driven digital society fully. This research aims to explain the acceptance of social networking sites, a particular consumer technology, in the post-pandemic elderly population. Data were obtained from 1555 older adults in Chile based on a consumer technology acceptance model. The respondents were grouped according to their technological predisposition and their generation into three groups. Applying a multigroup analysis based on structural equation modelling reveals significant differences in the explanatory variables of the intention and use of this technology between the groups. And more remarkably, the effort expectancy is not statistically significant as a variable to explain this acceptance globally in either of the three groups. There are two principal contributions of this study. First, it shows why adults adopt consumer technology after the pandemic. Second, it validates a classification of elderly adults who use consumption technologies that are useful in understanding the heterogeneity of this phenomenon.

Indexed as

consumer technologyeffort expectancyelderly

Identifiers

PMID36829316
PMCPMC9952286

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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.