Evidence map›Paper›PMID 32979650›Full record

ReviewInternational journal of medical informatics2020

Electronic consenting for conducting research remotely: A review of current practice and key recommendations for using e-consenting.

Emily Skelton, Nicholas Drey, Mary Rutherford, Susan Ayers, Christina Malamateniou

Open access · greenAbstract readReview
In one paragraph

Review in International journal of medical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed, 1 pooled it
10.6field-weighted citation impact, top 1% of its field
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

57 citing papers in PubMed, 1 synthesis or guideline pooled it, 108 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. The Ethics of Decentralized Clinical Trials and Informed Consent: Taking Technologies' Soft Impacts into Account.Health care analysis : HCA : journal of health philosophy and policy · 2025
    Article
  10. Article
  11. Review
  12. Observational
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Article
  20. Article
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 at 2 institutions in 1 country.

Emily SkeltonDivision of Radiography and Midwifery, City, University of London, UK; Department of Perinatal Imaging and Health, King's College London, UK. Electronic address: emily.skelton@city.ac.uk.
Nicholas DreyDivision of Nursing, City, University of London, UK.
Mary RutherfordDepartment of Perinatal Imaging and Health, King's College London, UK.
Susan AyersDivision of Radiography and Midwifery, City, University of London, UK.
Christina MalamateniouDivision of Radiography and Midwifery, City, University of London, UK; Department of Perinatal Imaging and Health, King's College London, UK.
City, University of London · GBKing's College London · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundElectronic approaches are becoming more widely used to obtain informed consent for research participation. Electronic consent (e-consent) provides an accessible and versatile approach to the consenting process, which can be enhanced with audio-visual and interactive features to improve participant engagement and comprehension of study procedures. Best practice guidance underpinned by ethical principles is required to ensure effective implementation of e-consent for use in research.

aimTo identify the key considerations for successful and ethical implementation of e-consent in the recruitment of participants to research projects which are conducted remotely.

methodsElectronic database searches of CINAHL, Medline, Embase, DARE, HTA, PubMed, the Cochrane Library, Scopus, Web of Science, NHS Evidence, and hand-searches of reference lists were performed. Primary research studies of adult (≥ 18 years old) research participants using e-consent, published in English language, peer-reviewed journals between 2010-2020 were eligible for inclusion.

resultsOf the initial 665 identified studies, 18 met the inclusion criteria: 6 cohort studies, 5 qualitative studies, 4 randomised control trials, 2 mixed-methods studies and one case-control study. Critical appraisal of included studies using Critical Appraisal Skills Program (CASP) tools suggested a low to moderate risk of bias in most studies (n = 15). Key practice recommendations for researchers using e-consent were identified around five primary themes: 1) accessibility and user-friendliness of e-consent, 2) user engagement and comprehension, 3) customisability to participant preferences and demographics, 4) data security and 5) impact on research teams.

conclusionE-consenting approaches are generally well received by participants, with most studies reporting user-friendly interfaces and sufficient participant comprehension of consenting documentation. IMPLICATIONS FOR PRACTICE: E-consent may facilitate remotely-conducted research by offering a feasible and robust alternative to face-to-face consenting approaches, however paper-based options should still be offered, based on participant preference. Customising e-consenting platforms may improve accessibility for individuals with specific needs, and increase engagement with study information. Research teams must offer prospective participants opportunities to discuss study information in real-time.

Indexed as

ComprehensionInformed ConsentAdultCase-Control StudiesElectronicsHumansProspective StudiesElectronic consentingInformed consentResearch ethicsUser experience

Identifiers

PMID32979650
PMCPMC7487205
OpenAlexW3084634006

What OpenQuestion holds

Textmetadata
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.