Evidence map›Paper›PMID 31115340›Full record

SynthesisJournal of medical Internet research2019

Theories Predicting End-User Acceptance of Telemedicine Use: Systematic Review.

Lorenz Harst, Hendrikje Lantzsch, Madlen Scheibe

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

Synthesis in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 148 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
148citing papers in PubMed, 8 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

148 citing papers in PubMed, 8 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Getting Connected to M-Health Technologies through a Meta-Analysis.International journal of environmental research and public health · 2023
    Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Pooled it
  9. Trial
  10. Trial
  11. Trial
  12. Trial
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

88 more citing papers are in PubMed but not listed here.

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

3 authors.

Lorenz Harst *Research Association Public Health, Center of Evidence-based Healthcare, University Clinic Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.ORCID 0000-0002-6004-2670
Hendrikje Lantzsch *Master Program Health Sciences / Public Health, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.ORCID 0000-0003-0374-9837
Madlen ScheibeCenter for Evidence-Based Healthcare, University Clinic Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.ORCID 0000-0001-8292-7675

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOnly a few telemedicine applications have made their way into regular care. One reason is the lack of acceptance of telemedicine by potential end users.

objectiveThe aim of this systematic review was to identify theoretical predictors that influence the acceptance of telemedicine.

methodsAn electronic search was conducted in PubMed and PsycINFO in June 2018 and supplemented by a hand search. Articles were identified using predefined inclusion and exclusion criteria. In total, two reviewers independently assessed the title, abstract, and full-text screening and then individually performed a quality assessment of all included studies.

resultsOut of 5917 potentially relevant titles (duplicates excluded), 24 studies were included. The Axis Tool for quality assessment of cross-sectional studies revealed a high risk of bias for all studies except for one study. The most commonly used models were the Technology Acceptance Model (n=11) and the Unified Theory of Acceptance and Use of Technology (n=9). The main significant predictors of acceptance were perceived usefulness (n=11), social influences (n=6), and attitude (n=6). The results show a superiority of technology acceptance versus original behavioral models.

conclusionsThe main finding of this review is the applicability of technology acceptance models and theories on telemedicine adoption. Characteristics of the technology, such as its usefulness, as well as attributes of the individual, such as his or her need for social support, inform end-user acceptance. Therefore, in the future, requirements of the target group and the group's social environment should already be taken into account when planning telemedicine applications. The results support the importance of theory-guided user-centered design approaches to telemedicine development.

Indexed as

Cross-Sectional StudiesFemaleHumansMalePatient ComplianceTelemedicinepatient compliancesystematic reviewtechnologytelemedicine

Identifiers

PMID31115340
PMCPMC6547771

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.