Evidence map›Paper›PMID 40163547›Full record

ArticleJMIR human factors2025

Perception and Evaluation of a Knowledge Transfer Concept in a Digital Health Application for Patients With Heart Failure: Mixed Methods Study.

Madeleine Flaucher, Sabrina Berzins, Katharina M Jaeger, Michael Nissen, Jana Rolny, Patricia Trißler, Sebastian Eckl, Bjoern M Eskofier, Heike Leutheuser

Abstract read
In one paragraph

Article in JMIR human factors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Madeleine FlaucherMachine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Carl-Thiersch-Str. 2b, Erlangen, 91052, Germany, 49 9131 8528990.ORCID 0000-0002-8086-1112
Sabrina BerzinsMachine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Carl-Thiersch-Str. 2b, Erlangen, 91052, Germany, 49 9131 8528990.ORCID 0009-0002-8467-2359
Katharina M JaegerMachine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Carl-Thiersch-Str. 2b, Erlangen, 91052, Germany, 49 9131 8528990.ORCID 0000-0002-2478-4079
Michael NissenMachine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Carl-Thiersch-Str. 2b, Erlangen, 91052, Germany, 49 9131 8528990.ORCID 0000-0001-5472-132X
Jana RolnyProCarement GmbH, Forchheim, Germany.ORCID 0009-0002-8326-3991
Patricia TrißlerProCarement GmbH, Forchheim, Germany.ORCID 0009-0006-7661-406X
Sebastian EcklProCarement GmbH, Forchheim, Germany.ORCID 0009-0004-8986-9964
Bjoern M EskofierMachine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Carl-Thiersch-Str. 2b, Erlangen, 91052, Germany, 49 9131 8528990.ORCID 0000-0002-0417-0336
Heike LeutheuserMachine Learning and Data Analytics Lab, Department Artificial Intelligence in Biomedical Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Carl-Thiersch-Str. 2b, Erlangen, 91052, Germany, 49 9131 8528990.ORCID 0000-0001-9931-2271

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Digital health education can enhance the quality of life of patients with heart failure by providing accessible and tailored information, which is essential for effective self-care and self-management. Objective: This work aims to develop a mobile health knowledge transfer concept for heart failure in a user-centered design process grounded in theoretical frameworks. This approach centers on enhancing the usability, patient engagement, and meaningfulness of mobile health education in the context of heart failure. Methods: A user-centered design process was employed. First, semistructured stakeholder interviews were conducted with patients (n=9) and medical experts (n=5). The results were used to develop a health knowledge transfer concept for a mobile health app for heart failure. This concept was implemented as a digital prototype based on an existing German mobile health app for patients with heart failure. We used this prototype to evaluate our concept with patients with heart failure in a study composed of user testing and semistructured patient interviews (n=7). Results: Stakeholder interviews identified five themes relevant to mobile health education: individualization, content relevance, media diversity, motivation strategies, and trust-building mechanisms. The evaluation of our prototype showed that patients value the adaptation of content to individual interests and prior knowledge. Digital rewards such as badges and push notifications can increase motivation and engagement but should be used with care to avoid overload, irrelevance, and repetition. Conclusions: Our findings emphasize the importance of tailoring mobile health education to the specific needs and preferences of patients with heart failure. At the same time, they also highlight the careful implementation of motivation strategies to promote user engagement effectively. These implications offer guidance for developing more impactful interventions to improve health outcomes for this population.

Indexed as

Health Knowledge, Attitudes, PracticeHeart FailureMobile ApplicationsPatient Education as TopicTelemedicineAdultAgedDigital HealthFemaleGermanyHumansMaleMiddle AgedQualitative ResearchUser-Centered Designdevelopmentdigital health appdigital Literacyhealth literacyheart failuremHealth appmixed methods studypatient engagementusabilityuser centered deignuser-centered design

Identifiers

PMID40163547
PMCPMC11975119

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.