Digital Interventions for Psychological Comorbidities in Chronic Diseases—A Systematic Review
Open accessAbstract
Chronic diseases represent one of the main causes of death worldwide. The integration of digital solutions in clinical interventions is broadly diffused today; however, evidence on their efficacy in addressing psychological comorbidities of chronic diseases is sparse. This systematic review analyzes and synthesizes the evidence about the efficacy of digital interventions on psychological comorbidities outcomes of specific chronic diseases. According to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic search of PubMed, PsycInfo, Scopus and Web of Science databases was conducted. Only Randomized Controlled Trials (RCTs) were considered and either depression or anxiety had to be assessed to match the selection criteria. Of the 7636 identified records, 17 matched the inclusion criteria: 9 digital interventions on diabetes, 4 on cardiovascular diseases, 3 on Chronic Obstructive Pulmonary Disease (COPD) and one on stroke. Of the 17 studies reviewed, 14 found digital interventions to be effective. Quantitative synthesis highlighted a moderate and significant overall effect of interventions on depression, while the effect on anxiety was small and non-significant. Design elements making digital interventions effective for psychological comorbidities of chronic diseases were singled out: (a) implementing a communication loop with patients and (b) providing disease-specific digital contents. This focus on “how” to design technologies can facilitate the translation of evidence into practice.
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The number of trials on each comorbid physical disease varies, and results are inconsistent.
“At this stage, however, the number of trials on each comorbid physical disease varies, and results are inconsistent371,372.”
From Comorbidity between major depressive disorder and physical diseases: a comprehensive review of epidemiology, mechanisms and management (2023) · cites this paper as [371]
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- [85]WHO Guideline: Recommendations on Digital Interventions for Health System Strengthening World Health Organization Geneva, Switzerlands 2019 Licence: CC BY-NC-SA 3.0 IGO 31162915
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- Authors
- Maisto, M., Diana, B., Di Tella, S., Matamala-Gomez, M., Montana, J. I., Rossetto, F., Mavrodiev, P. A., Cavalera, C., Blasi, V., Mantovani, F., Baglio, F., & Realdon, O.
- Affiliations
- University of Milano-Bicocca (IT)
- IRCCS Fondazione don Carlo Gnocchi ONLUS, Via Capecelatro 66, 20148 Milan, Italy
- Don Carlo Gnocchi Foundation (IT)
- Università Cattolica del Sacro Cuore (IT)
- Corresponding author
- Realdon, Olivia
- ORCID
- Venue
- Journal of Personalized Medicine
- Publisher
- MDPI AG
- Published
- 2021-01-06
- Volume
- 11
- Issue
- 1
- Pages
- 30
- ISSN
- 2075-4426 (ISSN-L)
- PMC
- PMC7825345
- OpenAlex
- W3119209973
- Cited by
- 30
- References
- 87
- Citations by year
- 2026: 5 · 2025: 5 · 2024: 3 · 2023: 9 · 2022: 3 · 2021: 5
- FWCI
- 0.80
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Journal of Personalized Medicine (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, other-oa)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- BOA (University of Milano-Bicocca) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- PubliCatt (Università Cattolica del Sacro Cuore) (submittedVersion, cc-by)
- Funders
- Regione Lombardia (Project ID: 232549)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Keywords
- digital interventions, psychological comorbidity, chronic disease, depression, anxiety, diabetes mellitus, cardiovascular disease, chronic obstructive pulmonary disease, stroke, patient communication, technology design, digital health
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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