Evidence map›Paper›PMID 40067482›Full record

ArticleJournal of medical systems2025

Exploring Acceptance of Digital Health Technologies for Managing Non-Communicable Diseases Among Older Adults: A Systematic Scoping Review.

Sadia Azmin Anisha, Arkendu Sen, Badariah Ahmad, Chris Bain

Abstract readScoping Review
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of medical systems, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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, 1 synthesis or guideline 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

4 authors.

Sadia Azmin AnishaJeffrey Cheah School of Medicine & Health Sciences, Monash University Malaysia, Bandar Sunway, Subang Jaya, Selangor, Malaysia. sadia.anisha@monash.edu.ORCID http://orcid.org/0000-0003-0469-0494
Arkendu SenJeffrey Cheah School of Medicine & Health Sciences, Monash University Malaysia, Bandar Sunway, Subang Jaya, Selangor, Malaysia. arkendu.sen@monash.edu.ORCID http://orcid.org/0000-0002-9198-7124
Badariah AhmadJeffrey Cheah School of Medicine & Health Sciences, Monash University Malaysia, Bandar Sunway, Subang Jaya, Selangor, Malaysia.ORCID http://orcid.org/0000-0003-0063-1761
Chris BainFaculty of Information Technology, Monash University, Clayton, Melbourne, VIC, Australia.ORCID http://orcid.org/0000-0002-5281-2364

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This review explores the acceptance of digital health (DH) technologies for managing non-communicable diseases (NCDs) among older adults (≥ 50 years), with an extended focus on artificial intelligence (AI)-powered conversational agents (CAs) as an emerging notable subset of DH. A systematic literature search was conducted in June 2024 using PubMed, Web of Science, Scopus, and ACM Digital Library. Eligible studies were empirical and published in English between January 2010 and May 2024. Covidence software facilitated screening and data extraction, adhering to PRISMA-ScR guidelines. The screening process finally yielded 20 studies. Extracted data from these selected studies included interventions, participant demographics, technology types, sample sizes, study designs and locations, technology acceptance measures, key outcomes, and methodological limitations. A narrative synthesis approach was used for analysis, revealing four key findings: (1) overall positive attitudes of older adults towards DH acceptance; (2) the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT) are the most frequently used standard frameworks for evaluating technology acceptance; (3) the key facilitators of technology acceptance include perceived usefulness, ease of use, social influence, and digital or e-health literacy, while barriers involve technical challenges, usability issues, and privacy concerns; (4) the acceptance of AI-based CAs for NCD management among older adults remains inadequately evaluated, possibly due to limited adaptation of established frameworks to specific healthcare contexts and technology innovations. This review significantly contributes to the DH field by providing a comprehensive analysis of technology acceptance for NCD management among older adults, extending beyond feasibility and usability. The findings offer stakeholders valuable insights into how to better integrate these technologies to improve health outcomes and quality of life for older adults. Protocol Registration: PROSPERO (Registration ID: CRD42024540035).

Indexed as

Noncommunicable DiseasesPatient Acceptance of Health CareTelemedicineAgedArtificial IntelligenceDigital HealthHumansMiddle AgedArtificial intelligenceConversational agentsDigital healthNon-communicable disease managementOlder adultsTechnology acceptance

Identifiers

PMID40067482
PMCPMC11897087

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.