Evidence map›Paper›PMID 40640790›Full record

ArticleBMC public health2025

Technology anxiety in elderly patients with chronic co-morbidities: a latent profile analysis.

Qiqi Chen, Zhaohui Li, Meihong Zhao, Xueyan Huang

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Observational
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.

Qiqi ChenGeneral Surgery Department, The fifth People's Hospital of Ningxia Hui Autonomous Region, Shizuishan, Ningxia, 753000, China.
Zhaohui LiGeneral Surgery Department, Balinzuoqi Traditional Chinese Medicine and Mongolian Medicine Hospital, Balinzuoqi, Inner Mongolia, 025450, China.
Meihong ZhaoDepartment of Gerontology, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, Zhejiang, 310007, China.
Xueyan HuangDepartment of Nursing, Hangzhou TCM Hospital Affiliated to Zhejiang Chinese Medical University, Hangzhou, Zhejiang, 310007, China. huangxueyan0307@163.com.

Funding

Xueyan Huang Grant No.2025KY160
6 · The paper itself

Abstract

backgroundTechnological anxiety has a multidimensional negative effect on the medical process of elderly patients with chronic co-morbidities, which is mainly reflected in the increase of cognitive load and the decrease of doctor-patient interaction efficiency. The challenge of how elderly patients can more effectively use digital health technologies is a critical issue that both healthcare providers and patients must address. We aimed to explore technology anxiety in elderly patients with chronic co-morbidities by identifying and characterising distinct technology anxiety profiles using latent profile analysis.

methodsThis study explored the relationship between the Technology Anxiety Scale and the Self-perceived Burden Scale, as well as the different subgroups of medication literacy, using latent profile analysis. The study involved 611 elderly patients with chronic diseases. The research tools used were the Medication Literacy Scale for Elderly Patients with Chronic Diseases, the Self-perceived Burden Scale, and the Technology Anxiety Scale.

resultsLatent profile analysis revealed four distinct technology anxiety groups of elderly patients with comorbid chronic diseases: low technology anxiety type with 212 cases (34.70%), high technology anxiety type with 81 cases (13.26%), medium technology anxiety low privacy security type with 148 cases (24.22%), and medium technology anxiety high privacy security type with 170 cases (27.82%).The results of multivariate logistic regression analyses indicated that self-Perceived burden, medication literacy, personal monthly income, medical insurance type, daily exercise duration, and times of hospitalizations are significant factors influencing technology anxiety among elderly patients with comorbid chronic diseases.

conclusionThe study showed that higher scores in self-perceived burden and medication literacy, lower daily exercise duration, higher hospitalization frequency, lower personal monthly income, and self-funded medical insurance types are associated with more severe technical anxiety.It is recommended that healthcare professionals tailor interventions to address the specific vulnerabilities of each patient type, aiming to reduce technological anxiety and enhance their ability to utilize health information effectively.

Indexed as

AnxietyAgedAged, 80 and overChronic DiseaseComorbidityFemaleHealth LiteracyHumansMaleSurveys and QuestionnairesEchnology anxietyElderly patients with chronic co-morbiditiesLatent profile analysisMedication literacyPublic healthSelf-perceived burden

Identifiers

PMID40640790
PMCPMC12243416

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.