Evidence map›Paper›PMID 39888468›Full record

ArticleJournal of medical systems2025

Mobile Applications for Longitudinal Data Collection: Web-based Survey Study of Former Intensive Care Patients.

Denise Molinnus, Anne Mainz, Angelique Kurth, Volker Lowitsch, Matthias Nüchter, Frank Bloos, Thomas Wendt, Philipp Potratz, Gernot Marx, Sven Meister and 1 more

Abstract read
In one paragraph

Article in Journal of medical systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Denise Molinnus *Department of Intensive Care Medicine, Faculty of Medicine, RWTH Aachen University, Aachen, Germany.
Anne Mainz *Health Informatics, Faculty of Health/School of Medicine, Witten/Herdecke University, Witten, Germany.
Angelique KurthDepartment of Intensive Care Medicine, Faculty of Medicine, RWTH Aachen University, Aachen, Germany.
Volker LowitschHealthcare IT Solutions GmbH, Aachen, Germany.
Matthias NüchterLIFE Management Cluster, Medical Faculty, University of Leipzig, Leipzig, Germany.
Frank BloosDepartment of Anesthesiology and Intensive Care Medicine, Jena University Hospital, Jena, Germany.
Thomas WendtInstitute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany.
Philipp PotratzCenter for Clinical Studies and Applied Healthcare Research, St. Francis Foundation Münster, Münster, Germany.
Gernot MarxDepartment of Intensive Care Medicine, Faculty of Medicine, RWTH Aachen University, Aachen, Germany.
Sven MeisterHealth Informatics, Faculty of Health/School of Medicine, Witten/Herdecke University, Witten, Germany.
Johannes BickenbachDepartment of Intensive Care Medicine, Faculty of Medicine, RWTH Aachen University, Aachen, Germany. jbickenbach@ukaachen.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeMobile health plays an important role in providing individualized information about the health status of patients. Limited information exists on intensive care unit (ICU) patients with the risk of suffering from the post-intensive care syndrome (PICS), summarizing long-term physical, mental and cognitive impairment. This web-based survey study aims to identify specific needs of former ICU patients for utilizing a newly developed, so called Post-Intensive Care Outcome Surveillance (PICOS) app to collect relevant PICS-related parameters.

methodsA prototype app was developed following interaction principles for interactive systems of usability engineering. Patients from four different German hospitals were asked about demographics, interaction with technology and their perception of the prototype regarding hedonic motivation, perceived ease of use and performance expectancy.

results123 patients participated in the survey; the majority owned and used smartphones. Nearly half of respondents would seek help from family members or caregivers using the app. There was a difference in affinity for technology for participants who own a smartphone and those who do not, t(116) = - 0.97, p = .335, and no significant difference in affinity for technology whether the participants would like support when using the app or not, t(97) = 1.81, p = .073. The average hedonic motivation for using the app was M = 4.44 (SD = 1.304).

conclusionThis app prototype was perceived as both beneficial and easy to use, indicating its success among former ICU patients. Due to aging and ongoing health impairments, every second patient would need assistance with the initial use of the app.

Indexed as

Critical CareIntensive Care UnitsInternetMobile ApplicationsAdultAgedAged, 80 and overFemaleGermanyHumansLongitudinal StudiesMaleMiddle AgedMotivationSurveys and QuestionnairesTelemedicineDigital HealthDigital SkillsICUmHealthMobile ApplicationMobile PhonePICS

Identifiers

PMID39888468
PMCPMC11785681

What OpenQuestion holds

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LicenceCC BY
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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.