ReviewHealth economics review2026
Preferences towards digital health technologies: a scoping review.
Review in Health economics review, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDigital Health Technologies (DHTs) are expanding rapidly, offering new opportunities to support care delivery. Their adoption, however, depends on how well they match patients' needs and expectations. Accurately assessing patient preferences is challenging due to diverse user profiles and varying methods used to measure preferences. A synthesis of current evidence is needed to clarify what patients value in DHTs.
objectivesThis study synthesizes evidence on patient preferences for DHTs-including eHealth, telehealth, telemedicine, and mHealth-and examines the methods used to elicit these preferences, highlighting opportunities to improve adoption and design.
methodsWe conducted a scoping review of literature published from 2000 to 2026 following PRISMA-ScR guidelines. Searches were performed in PubMed, EMBASE, CINAHL, Scopus, and Web of Science. Two reviewers independently screened titles, abstracts, and full texts for eligibility. Data were charted and narratively synthesized, with study characteristics categorized by methodology (qualitative, quantitative, mixed methods) and preference elicitation techniques.
resultsOf 2,419 records identified, 115 underwent full-text screening and 85 met all inclusion criteria: 27 qualitative studies (31.76%), 45 quantitative studies (52.95%), and 13 mixed-methods studies (15.29%). Quantitative studies primarily applied attribute-based methods (e.g., Discrete Choice Experiments, Conjoint Analysis, Best-Worst Scaling), and six studies used the Contingent Valuation method to estimate total willingness-to-pay for DHTs. Qualitative studies employed thematic analysis, deductive, inductive, and immersion-crystallization approaches. Across studies, patients consistently emphasized cost, privacy, convenience, and personalization of DHTs as key concerns. Only a few studies estimated the relative importance of the attributes or the marginal willingness to pay for the device's features. Considerable heterogeneity in preferences was observed by DHT type, patients' health condition and age.
conclusionsQuantitative, qualitative, and mixed-method approaches provide complementary insights into how patients perceive and value DHTs. Patients consistently seek personalized, easy-to-use, secure, and affordable solutions, which is particularly important for older adults managing chronic conditions. Given the diversity of patient preferences, it is essential to consider these differences when developing digital health technologies to ensure they effectively support patients and address their needs.
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Registered trials
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.