Evidence map›Paper›PMID 37379058›Full record

ArticleJournal of medical Internet research2023

Exploring Functions and Predictors of Digital Health Engagement Among German Internet Users: Survey Study.

Michael Grimm, Elena Link, Martina Albrecht, Fabian Czerwinski, Eva Baumann, Ralf Suhr

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
6.1field-weighted citation impact, top 4% of its field
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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Michael Grimm *Stiftung Gesundheitswissen, Berlin, Germany.ORCID 0009-0005-4916-5628
Elena Link *Department of Communication, Johannes Gutenberg-University Mainz, Mainz, Germany.ORCID 0000-0001-6861-5288
Martina AlbrechtStiftung Gesundheitswissen, Berlin, Germany.ORCID 0009-0000-3932-5476
Fabian CzerwinskiDepartment of Journalism and Communication Research, University of Music, Drama and Media Hanover, Hanover, Germany.ORCID 0000-0003-4662-5420
Eva BaumannDepartment of Journalism and Communication Research, University of Music, Drama and Media Hanover, Hanover, Germany.ORCID 0000-0002-2357-2138
Ralf SuhrStiftung Gesundheitswissen, Berlin, Germany.ORCID 0000-0003-0830-8715
Hanover University of Music Drama and Media · DEJohannes Gutenberg University Mainz · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital health engagement may serve many support functions, such as providing access to information; checking or evaluating one's state of health; and tracking, monitoring, or sharing health data. Many digital health engagement behaviors are associated with the potential to reduce inequalities in information and communication. However, initial studies suggest that health inequalities may persist in the digital realm.

objectiveThis study aimed to explore the functions of digital health engagement by describing how frequently respective services are used for a range of purposes and how these purposes can be categorized from the users' perspective. This study also aimed to identify the prerequisites for successfully implementing and using digital health services; therefore, we shed light on the predisposing, enabling, and need factors that may predict digital health engagement for different functions.

methodsData were gathered via computer-assisted telephone interviews during the second wave of the German adaption of the Health Information National Trends Survey in 2020 (N=2602). The weighted data set allowed for nationally representative estimates. Our analysis focused on internet users (n=2001). Engagement with digital health services was measured by their reported use for 19 different purposes. Descriptive statistics showed the frequency with which digital health services were used for these purposes. Using a principal component analysis, we identified the underlying functions of these purposes. Using binary logistic regression models, we analyzed which predisposing factors (age and sex), enabling factors (socioeconomic status, health- and information-related self-efficacy, and perceived target efficacy), and need factors (general health status and chronic health condition) can predict the use of the distinguished functions.

resultsDigital health engagement was most commonly linked to acquiring information and less frequently to more active or interactive purposes such as sharing health information with other patients or health professionals. Across all purposes, the principal component analysis identified 2 functions. Information-related empowerment comprised items on acquiring health information in various forms, critically assessing one's state of health, and preventing health problems. In total, 66.62% (1333/2001) of internet users engaged in this behavior. Health care-related organization and communication included items on patient-provider communication and organizing health care. It was applied by 52.67% (1054/2001) of internet users. Binary logistic regression models showed that the use of both functions was determined by predisposing factors (female and younger age) and certain enabling factors (higher socioeconomic status) and need factors (having a chronic condition).

conclusionsAlthough a large share of German internet users engage with digital health services, predictors show that existing health-related disparities prevail in the digital realm. To make use of the potential of digital health services, fostering digital health literacy at different levels, especially in vulnerable groups, is key.

Indexed as

TelemedicineCommunicationFemaleHumansInternetSocial ClassSurveys and Questionnairesdigital health caredigital health engagementeHealthhealth information seekingmobile healthmobile phoneself-monitoring

Identifiers

PMID37379058
PMCPMC10365627
OpenAlexW4382343750

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.