ArticleDigital health
Digital health and patient adherence: A qualitative study in older adults.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Technophobia and computer anxiety in older adults: a systematic review of the influencing factors.BMC public health · 2026Pooled it
- Digital health technologies for the management of sarcopenia in patients receiving maintenance hemodialysis: a narrative review.Frontiers in nutrition · 2026Review
- Intelligent mobile health management for the risk of gastrointestinal bleeding in anticoagulated patients with cardiovascular disease.Revista da Escola de Enfermagem da U S P · 2026Observational
- Perspectives and Preferences on Developing a Digital Human System for Intrinsic Capacity Monitoring Underpinned by World Health Organization's Integrated Care for Older People Guideline: Qualitative Study.Journal of medical Internet research · 2025Article
- Comment on 'Adherence to Physical Activity and Incident Mobility Disability in Older Adults With Mobility Limitations' by Alvarez-Bustos et al.Journal of cachexia, sarcopenia and muscle · 2025Article
- Challenges of smoking cessation in users of non-invasive stimulation technologies in Iran: a parallel convergent mixed-methods study.BMJ open · 2024Article
- Sociodemographic and health predictors of adherence to self-administered computerized cognitive assessment.Digital healthArticle
- The impact of digitally-enabled interventions on frailty and other age-related outcomes - Systematic review and meta-analysis.Digital healthReview
- A public value-based model to understand patients' adoption of eHealth: Theoretical underpinnings and empirical application.Digital healthArticle
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Computer confidence and computer self-efficacy can impact an individual's perceived ease of use and usefulness of technology, ultimately determining adherence to digital healthcare services. However, few studies focus on assessing the impact of non-clinical factors on the efficacy and adherence to digital healthcare platforms. Objective: We aimed to analyse the role of non-clinical factors (i.e. computer confidence and computer self-efficacy) in the interaction experience (IX) and the feasibility of a digital neuropsychological platform called NeuroVRehab.PT in a group of older adults with varying levels of computer confidence. Methods: Eight older adults (70.63 ± 6.1 years) evaluated the platform, and data was collected using the Think-Aloud method and a semi-structured interview. Sessions were audio-recorded and analysed through an inductive-deductive informed Thematic Analysis protocol. This study was conducted according to the Consolidated Criteria for Reporting Qualitative Research guidelines. Results: Three main themes were identified (Interaction Experience, Digital Literacy, and Attitudes toward NeuroVRehab.PT). Computer anxiety and fear of making errors were not uncommon, even among older adults who perceive themselves as confident in technology use, and negatively impacted IX. Moreover, some game elements (e.g. three-star system, progression bar) were not intuitive to all participants, leading to misleading interpretations. On the other hand, human support and the platform's realism seemed to impact participants' IX positively. Conclusions: This study shed light on the barriers raised by non-clinical factors in adopting and using digital healthcare services by older adults. Furthermore, a critical analysis of the platform's features that promote user adoption is done, and suggestions for overcoming limitations are presented.
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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.