Evidence map›Paper›PMID 41627850›Full record

ReviewJournal of medical Internet research2026

Barriers to Digital Health Adoption in Older Adults: Scoping Review Informed by Innovation Resistance Theory.

Yosefa Birati, Roy Tzemah-Shahar

Abstract readScoping ReviewReview
In one paragraph

Review in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 4 pooled it
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1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yosefa BiratiThe Cheryl Spencer Department of Nursing, Faculty of Social Welfare and Health Sciences, University of Haifa, Haifa, Israel, 972 522684065.ORCID http://orcid.org/0000-0001-6318-4378
Roy Tzemah-ShaharThe Cheryl Spencer Department of Nursing, Faculty of Social Welfare and Health Sciences, University of Haifa, Haifa, Israel, 972 522684065.ORCID http://orcid.org/0000-0003-0474-1888

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The transformation of digital health technologies has reshaped health care delivery in primary care. Despite these benefits, older adults remain among the most resistant users. Traditional technology adoption models may not fully capture this reluctance, which is shaped not only by usability challenges but also by emotional, psychological, and identity-related concerns. Innovation resistance theory (IRT) offers a complementary framework focused on barriers to adoption rather than solely on facilitators. Objective: This study aims to map and synthesize evidence on older adults' resistance to digital health in primary care through the lens of IRT, and to examine how resistance factors align with, extend, or refine IRT's functional and psychological barriers. Methods: A scoping review with concept-driven thematic synthesis was conducted. A search for studies published between 2014 and 2025 was conducted across 5 databases: PubMed, CINAHL, Ovid Medline, Web of Science, and Scopus; the final search was completed in November 2025. Eligible studies were those that examined barriers or resistance to digital health use among adults aged 60 years and older in primary care settings. Search terms included "older adults," "digital health/eHealth," and "technology resistance." We excluded studies outside primary care and in which caregivers or health care professionals were the primary users. Data were extracted into a structured matrix and coded to the IRT domains: usage, value, risk, tradition, and image barriers. Relational integration was used to examine co-occurrence and linkages among barriers to inform the conceptual model. Results: Seventeen studies were included, comprising 6822 participants (sample sizes ranged from 11 to 4525). Most studies were conducted in high-income Western countries, predominantly with qualitative designs, alongside mixed-methods and cross-sectional surveys. Functional barriers included usability challenges, interface complexity, and age-related impairments. Psychological resistance was linked to emotional discomfort, symbolic misalignment, and concerns about the loss of relational care. Value and risk concerns included distrust in diagnostic accuracy, privacy and data security, and skepticism about care quality. Traditional preferences for face-to-face interactions and generational digital divides reinforced image-based resistance. Interactions between barriers were identified, with low self-efficacy and technology anxiety creating feedback loops that reinforce avoidance behaviors. Conclusions: Older adults' resistance to digital health is not simply a lack of adoption but a complex, emotionally grounded process involving functional, psychological, and identity-based barriers. This review applies IRT to primary care digital health, shifting the focus from adoption facilitators to resistance mechanisms and integrating co-occurrence patterns into a conceptual model. The synthesis reveals interacting factors of usability, self-efficacy, anxiety, trust, and legitimacy concerns that reinforce avoidance, suggesting that implementation strategies should extend beyond technical usability to rebuild trust, preserve relational care, and align digital solutions with older adults' values. Review limitations include the predominance of Western-based studies and limited longitudinal data on how resistance evolves.

Indexed as

Digital HealthTelemedicineAgedHumansMiddle AgedPrimary Health Caredigital healthinnovation resistance theoryolder adultsprimary health caretechnology adoptiontechnology resistancetelemedicine

Identifiers

PMID41627850
PMCPMC12863245

What OpenQuestion holds

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Registered trials

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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.