SEARCHCROSS-SECTIONALneurology, epidemiology

cross-sectional·neurology, epidemiology, public health, research methods·PMC10101441

Digital health for chronic disease management: An exploratory method to investigating technology adoption potential

PLOS ONE · 9 authors, 9 centres

AI SUMMARY

FIDELITY 100%

POPULATION990 participants from the Swiss MS Registry with Multiple Sclerosis

INTERVENTIONObservation of self-reported technology use patterns via a survey

COMPARISONComparison of clusters across sociodemographic and health status characteristics

This summary was generated by AI from a single paper. It has not been reviewed by a clinician and is not clinical advice. Verify against the source before acting on it.

AGENT 01 · STRUCTURED SUMMARY

TRACE TO SOURCE

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TL;DR

This study used factor analysis on survey data from 990 Swiss MS Registry participants to cluster them by technology use patterns. It found that only about 10% regularly use consumer technology for health-related purposes, suggesting current digital health tools may not appeal to most patients.

Full summary

937 CHARS

The study analyzed survey data from 990 individuals with Multiple Sclerosis in the Swiss MS Registry to explore technology adoption potential. Using exploratory multivariate factorial analysis on responses about technology use, the researchers identified three clusters: average users, health-interested users, and low frequency users. The central finding was that only about 10% of the sample regularly used consumer-facing technology for health-related purposes. The study concludes that most current digital health technologies for MS may only be attractive to a small proportion of patients. Limitations include the sample not being representative of all people with MS due to the registry's baseline digital literacy requirement, and the analysis being exploratory rather than a test of adoption theory. The implications suggest a need for better characterization of target populations to develop technologies for broader audiences.

PICO

PPOPULATION

990 participants from the Swiss MS Registry with Multiple Sclerosis

IINTERVENTION

Observation of self-reported technology use patterns via a survey

OOUTCOME

Identification of three clusters: average users, health-interested users, and low frequency users

STUDY TYPE

cross-sectional

SPECIALTY

neurology

SUMMARISED BY

AI pipeline

FIDELITY CHECK

100% · A

ORIGINAL PAPER

PMC10101441

Digital health for chronic disease management: An exploratory method to investigating technology adoption potential

PLOS ONE

READ THE FULL PAPER

ABSTRACT

Abstract Introduction The availability of consumer-facing health technologies for chronic disease management is skyrocketing, yet most are limited by low adoption rates. Improving adoption requires a better understanding of a target population’s previous exposure to technology. We propose a low-resource approach of capturing and clustering technology exposure, as a mean to better understand patients and target health technologies. Methods Using Multiple Sclerosis (MS) as a case study, we applied exploratory multivariate factorial analyses to survey data from the Swiss MS Registry. We calculated individual-level factor scorings, aiming to investigate possible technology adoption clusters with similar digital behavior patterns. The resulting clusters were transformed using radar and then compared across sociodemographic and health status characteristics. Results Our analysis included data from 990 respondents, resulting in three clusters, which we defined as the (1) average users, (2) health-interested users, and (3) low frequency users. The average user uses consumer-facing technology regularly, mainly for daily, regular activities and less so for health-related purposes. The health-interested user also uses technology regularly, for daily activities as well as health-related purposes. The low-frequency user uses technology infrequently. Conclusions Only about 10% of our sample has been regularly using (adopting) consumer-facing technology for MS and health-related purposes. That might indicate that many of the current consumer-facing technologies for MS are only attractive to a small proportion of patients. The relatively low-resource exploratory analyses proposed here may allow for a better characterization of prospective user populations and ultimately, future patient-facing technologies that will be targeted to a broader audience.

CITATION EXPORT

Vasileios Nittas, Chiara Zecca, Christian P Kamm et al.. Digital health for chronic disease management: An exploratory method to investigating technology adoption potential. PLOS ONE. (2023). https://doi.org/10.1371/journal.pone.0284477

AUTHORS

9 · 9 CENTRES

Vasileios Nittas, Chiara Zecca, Christian P Kamm, Jens Kuhle, Andrew Chan, Viktor von Wyl, Chidozie Emmanuel Mbada, Chidozie Emmanuel Mbada, Chidozie Emmanuel Mbada

1Biostatistics & Prevention Institute, Epidemiology, University of Zurich, Zurich, Switzerland
2Department of Health Sciences and Technology, Health Ethics and Policy Lab, ETH Zurich, Zurich, Switzerland
3Department of Neurology, Neurocenter of Southern Switzerland, EOC, Lugano, Switzerland
4Faculty of Biomedical Sciences, Università della Svizzera Italiana (USI), Lugano, Switzerland
5Department of Neurology, Inselspital, University Hospital Bern and University of Bern, Bern, Switzerland
6Neurology and Neurorehabilitation Center, Luzerner Kantonsspital, Lucerne, Switzerland
7Neurologic Clinic and Policlinic, MS Center and Research Center for Clinical Neuroimmunology and Neuroscience Basel (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
8Institute for Implementation Science in Health Care, University of Zurich, Zurich, Switzerland
9Manchester Metropolitan University - Aytoun Campus: Manchester Metropolitan University, UNITED KINGDOM