eHealth for Patient Engagement: A Systematic Review
Open accessAbstract
eHealth interventions are recognized to have a tremendous potential to promote patient engagement. To date, the majority of studies examine the efficacy of eHealth in enhancing clinical outcomes without focusing on patient engagement in its specificity. This paper aimed at reviewing findings from the literature about the use of eHealth in engaging patients in their own care process. We undertook a comprehensive literature search within the peer-reviewed international literature. Eleven studies met the inclusion criteria. eHealth interventions reviewed were mainly devoted to foster only partial dimensions of patient engagement (i.e., alternatively cognitive, emotional or behavioral domains related to healthcare management), thus failing to consider the complexity of such an experience. This also led to a great heterogeneity of technologies, assessed variables and achieved outcomes. This systematic review underlines the need for a more holistic view of patient needs to actually engage them in eHealth interventions and obtaining positive outcomes. In this sense, patient engagement constitute a new frontiers for healthcare models where eHealth could maximize its potentialities.
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The construct of effective engagement differs conceptually from both engagement and adherence, which have historically been used interchangeably.
“The construct of effective engagement differs conceptually from both engagement and adherence, which have historically been used interchangeably [16].”
From A Library of Analytic Indicators to Evaluate Effective Engagement with Consumer mHealth Apps for Chronic Conditions: Scoping Review (2019) · cites this paper as [16]
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- Authors
- Barello, S., Triberti, S., Graffigna, G., Libreri, C., Serino, S., Hibbard, J., & Riva, G.
- Affiliations
- Università Cattolica del Sacro Cuore (IT)
- IRCCS Istituto Auxologico Italiano (IT)
- University of Oregon (US)
- Corresponding author
- Barello, Serena
- ORCID
- Venue
- Frontiers in Psychology
- Publisher
- Frontiers Media SA
- Published
- 2016-01-08
- Volume
- 6
- Pages
- 2013-2013
- ISSN
- 1664-1078 (ISSN-L)
- PMC
- PMC4705444
- OpenAlex
- W2273501727
- Cited by
- 411
- References
- 71
- Citations by year
- 2026: 18 · 2025: 31 · 2024: 51 · 2023: 40 · 2022: 40 · 2021: 51 · 2020: 53 · 2019: 40 · 2018: 47 · 2017: 23 · 2016: 17
- FWCI
- 8.08
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Psychology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (acceptedVersion)
- Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) (submittedVersion, other-oa)
- BOA (University of Milano-Bicocca) (submittedVersion, other-oa)
- PubliCatt (Università Cattolica del Sacro Cuore) (submittedVersion, cc-by)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- digital health interventions, patient engagement, patient-centered care, self-management, cognitive engagement, emotional engagement, behavioral engagement, health technology, patient needs
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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