Evidence map›Paper›PMID 34499044›Full record

ArticleJMIR mHealth and uHealth2021

Toward a Better Understanding of the Intention to Use mHealth Apps: Exploratory Study.

Pedro R Palos-Sanchez, Jose Ramon Saura, Miguel Ángel Rios Martin, Mariano Aguayo-Camacho

2 registry-linked trialsAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JMIR mHealth and uHealth, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 38 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 3 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.

NCT05912439 naunknown statusnot on this map

Smartphone Based Health Behaviour Intervention for Adolescents; Usage and Daily Attrition Rates.

TypeinterventionalSponsorUniversity of IcelandRan2017 to 2023Enrolled670ConditionsHealthy Adolescents in School-based PopulationArmsSidekickHealth
NCT06226207 completednot on this mapstarted 2023, after this paper: background citation

Validity and Reliability of Turkish Version of Physiotherapy Mobile Acceptance Questionnaire

TypeobservationalSponsorKarabuk UniversityRan2023 to 2024Enrolled421ConditionsReliability and Validity
3 · Its place in the literature

Who cites it

38 citing papers in PubMed, 3 syntheses or guidelines 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

4 authors.

Pedro R Palos-Sanchez *Department of Financial Economy and Operations Management, Faculty of Economic and Business Sciences, University of Seville, Seville, Spain.ORCID 0000-0001-9966-0698
Jose Ramon Saura *Department of Business Economics, Rey Juan Carlos University, Madrid, Spain.ORCID 0000-0002-9457-7745
Miguel Ángel Rios Martin *Department of Financial Economy and Operations Management, Faculty of Economic and Business Sciences, University of Seville, Seville, Spain.ORCID 0000-0002-6276-2655
Mariano Aguayo-Camacho *Department of Financial Economy and Operations Management, Faculty of Economic and Business Sciences, University of Seville, Seville, Spain.ORCID 0000-0002-1375-3007

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAn increasing number of mobile health (mHealth) apps are becoming available for download and use on mobile devices. Even with the increase in availability and use of mHealth apps, there has still not been a lot of research into understanding the intention to use this kind of apps.

objectiveThe purpose of this study was to investigate a technology acceptance model (TAM) that has been specially designed for primary health care applications.

methodsThe proposed model is an extension of the TAM, and was empirically tested using data obtained from a survey of mHealth app users (n=310). The research analyzed 2 additional external factors: promotion of health and health benefits. Data were analyzed with a PLS-SEM software and confirmed that gender moderates the adoption of mHealth apps in Spain. The explanatory capacity (R

resultsThe results show the importance of healthy habits developed by using mHealth apps. In addition, communication campaigns for these apps should be aimed at transferring the usefulness of eHealth as an agent for transforming attitudes; additionally, as more health benefits are obtained, ease of use becomes greater. Perceived usefulness (PU; β=.415, t

conclusionsmHealth apps could be used to predict the behavior of patients in the face of recommendations to prevent pandemics, such as COVID-19 or SARS, and to track users' symptoms while they stay at home. Gender is a determining factor that influences the intention to use mHealth apps, so perhaps different interfaces and utilities could be designed according to gender.

Indexed as

COVID-19Mobile ApplicationsTelemedicineHumansIntentionSARS-CoV-2COVID-19eHealthmHealth appsmobile appsPLS–SEMpromotion of healthTAM

Identifiers

PMID34499044
PMCPMC8461538

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.