Evidence map›Paper›PMID 27619564›Full record

Trial reportJournal of medical Internet research2016

A Web-Based Telehealth Training Platform Incorporating Automated Nonverbal Behavior Feedback for Teaching Communication Skills to Medical Students: A Randomized Crossover Study.

Chunfeng Liu, Renee L Lim, Kathryn L McCabe, Silas Taylor, Rafael A Calvo

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of medical Internet research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Creation of a Multimodal Telemedicine Curriculum for Preclinical Medical Students.MedEdPORTAL : the journal of teaching and learning resources · 2025
    Article
  6. Review
  7. Article
  8. ConverSense: An Automated Approach to Assess Patient-Provider Interactions using Social Signals.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2024
    Article
  9. Designing Communication Feedback Systems To Reduce Healthcare Providers' Implicit Biases In Patient Encounters.Proceedings of the SIGCHI conference on human factors in computing systems. CHI Conference · 2024
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Battling Bias in Primary Care Encounters: Informatics Designs to Support Clinicians.Extended abstracts on Human factors in computing systems. CHI Conference · 2022
    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.

Chunfeng LiuSchool of Electrical and Information Engineering, The University of Sydney, Sydney, Australia.ORCID 0000-0002-7274-6878

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn the interests of patient health outcomes, it is important for medical students to develop clinical communication skills. We previously proposed a telehealth communication skills training platform (EQClinic) with automated nonverbal behavior feedback for medical students, and it was able to improve medical students' awareness of their nonverbal communication.

objectiveThis study aimed to evaluate the effectiveness of EQClinic to improve clinical communication skills of medical students.

methodsWe conducted a 2-group randomized crossover trial between February and June 2016. Participants were second-year medical students enrolled in a clinical communication skills course at an Australian university. Students were randomly allocated to complete online EQClinic training during weeks 1-5 (group A) or to complete EQClinic training during weeks 8-11 (group B). EQClinic delivered an automated visual presentation of students' nonverbal behavior coupled with human feedback from a standardized patient (SP). All students were offered two opportunities to complete face-to-face consultations with SPs. The two face-to-face consultations were conducted in weeks 6-7 and 12-13 for both groups, and were rated by tutors who were blinded to group allocation. Student-Patient Observed Communication Assessment (SOCA) was collected by blinded assessors (n=28) at 2 time points and also by an SP (n=83). Tutor-rated clinical communications skill in face-to-face consultations was the primary outcome and was assessed with the SOCA. We used t tests to examine the students' performance during face-to-face consultations pre- and postexposure to EQClinic.

resultsWe randomly allocated 268 medical students to the 2 groups (group A: n=133; group B: n=135). SOCA communication skills measures (score range 4-16) from the first face-to-face consultation were significantly higher for students in group A who had completed EQClinic training and reviewed the nonverbal behavior feedback, compared with group B, who had completed only the course curriculum components (P=.04). Furthermore, at the second face-to-face assessment, the group that completed a teleconsultation between the two face-to-face consultations (group B) showed improved communication skills (P=.005), and the one that had teleconsultations before the first face-to-face consultation (group A) did not show improvement.

conclusionsThe EQClinic is a useful tool for medical students' clinical communication skills training that can be applied to university settings to improve students clinical communication skills development.

Indexed as

Clinical CompetenceCommunicationFormative FeedbackInternetNonverbal CommunicationPatient SimulationAustraliaCross-Over StudiesCurriculumEducation, Medical, UndergraduateFeedbackFemaleHumansMaleReferral and ConsultationStudents, Medicalaffective computingautomated feedbackclinical consultationcommunication skillsmedical educationnonverbal behaviornonverbal behavior detectionnonverbal communication

Identifiers

PMID27619564
PMCPMC5037316

What OpenQuestion holds

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LicenceCC BY
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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.