Evidence map›Paper›PMID 38145470›Full record

ArticleJMIR formative research2023

Preferences in the Willingness to Download an mHealth App: Discrete Choice Experimental Study in Spain, Germany, and the Netherlands.

Frans Folkvord, Nadine Bol, Giacomo Stazi, Lutz Peschke, Francisco Lupiáñez-Villanueva

Abstract read
In one paragraph

Article in JMIR formative research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 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

6 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Article
  5. Article
  6. 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

5 authors.

Frans FolkvordTilburg School of Humanities and Digital Sciences, Tilburg University, Tilburg, Netherlands.ORCID https://orcid.org/0000-0001-7602-3792
Nadine BolTilburg School of Humanities and Digital Sciences, Tilburg University, Tilburg, Netherlands.ORCID https://orcid.org/0000-0002-6895-9512
Giacomo StaziOpen Evidence, Barcelona, Spain.ORCID https://orcid.org/0000-0001-6525-2522
Lutz PeschkeDepartment of Communication and Design, Bilkent University, Ankara, Turkey.ORCID https://orcid.org/0000-0002-9513-3257
Francisco Lupiáñez-VillanuevaPredictBy, Barcelona, Spain.ORCID https://orcid.org/0000-0001-5361-7678

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the worldwide growth in mobile health (mHealth) tools and the possible benefits for both patients and health care providers, the adoption of mHealth is low, and only a limited number of studies have examined the intention to download mHealth apps.

objectiveIn this study, we investigated individuals' preferences in the adoption of a health app.

methodsWe conducted a discrete choice experimental study in 3 countries (Spain: n=800, Germany: n=800, and the Netherlands: n=416) with 4 different attributes and levels (ie, price: €1.99 vs €4.99 [a currency exchange rate of €1=US $1.09 is applicable] vs for free, data protection: data protection vs no information, recommendation: patients' association vs doctors, and manufacturer: medical association vs pharmaceutical company). Participants were randomly assigned. For the analyses, we used the conditional logistic model separately for each country.

resultsThe results showed that price and data protection were considered important factors that significantly increased the probability to download an mHealth app. In general, the source of the recommendation and the manufacturer affected the probability to download the mHealth app less. However, in Germany and the Netherlands, we found that if the app was manufactured by a pharmaceutical company, the probability to download the mHealth app decreased.

conclusionsmHealth tools are highly promising to reduce health care costs and increase the effectiveness of traditional health interventions and therapies. Improving data protection, reducing costs, and creating sound business models are the major driving forces to increase the adoption of mHealth apps in the future. It is thereby essential to create trustworthy standards for mobile apps, whereby prices, legislation concerning data protection, and health professionals can have a leading role to inform the potential consumers.

Indexed as

adoptiondiscrete choice taskeffectivenesshealth care costmHealthmHealth adoptionmHealth toolsmobile appmobile appsmobile healthmobile health appmobile phoneself-monitoringwillingness

Identifiers

PMID38145470
PMCPMC10775037

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.