Evidence map›Paper›PMID 40247864›Full record

ArticleFrontiers in public health2025

Exploring the factors influencing the adoption of online medical services by older adults: a modified UTAUT2 based study.

He Huang, Jiayi Zhu, Juhua Chen, Yuxin Qin, Shuguang Chen

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
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

5 authors.

He HuangCollege of Art and Design, Changzhou University, Changzhou, China.
Jiayi ZhuCollege of Art and Design, Changzhou University, Changzhou, China.
Juhua ChenDepartment of Encephalopathy, Changzhou Traditional Chinese Medicine Hospital, Changzhou, China.
Yuxin QinCollege of Art and Design, Changzhou University, Changzhou, China.
Shuguang ChenCollege of Art and Design, Changzhou University, Changzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The adoption rate of online medical services (OMS) among older adults remains notably low. Existing literature on OMS has rarely focused on older adults and the influences of individual characteristics within this population remain underexplored. To explore the factors influencing the adoption of OMS by older adults in China, this study proposes a modified Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model by integrating technology anxiety, trust, and perceived risk and adding new moderating variables such as education level and health status. Method: Data was collected through a face-to-face survey, which included 379 valid questionnaires. Structural equation modeling (SEM) was used to analyze the data and test the research hypotheses. Results: For older adults, performance expectancy ( Discussion: Our empirical research discovers the drivers and barriers influencing the adoption of OMS by older adults. Based on the findings, we provide some recommendations to promote the adoption of OMS among older adults. Our findings and recommendations can aid providers, developers, policymakers, market practitioners, and managers of OMS in developing better services and strategies to successfully implement OMS among the older population.

Indexed as

InternetPatient Acceptance of Health CareTelemedicineAgedAged, 80 and overChinaFemaleHumansMaleMiddle AgedSurveys and QuestionnairesTrustolder adultsonline medical servicesstructural equation modelingtechnology acceptanceUTAUT2

Identifiers

PMID40247864
PMCPMC12003354

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.