Evidence map›Paper›PMID 35770149›Full record

ArticleHeliyon2022

Using clinical history taking chatbot mobile app for clinical bedside teachings - A prospective case control study.

Michael Co, Tsz Hon John Yuen, Ho Hung Cheung

Abstract read
In one paragraph

Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Trial
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  11. Using a Virtual Patient via an Artificial Intelligence Chatbot to Develop Dental Students' Diagnostic Skills.International journal of environmental research and public health · 2022
    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

3 authors.

Michael CoCentre for Education and Training, Department of Surgery, Queen Mary Hospital, University of Hong Kong, Hong Kong.
Tsz Hon John YuenDepartment of Computer Science, University of Hong Kong, Hong Kong.
Ho Hung CheungCentre for Education and Training, Department of Surgery, Queen Mary Hospital, University of Hong Kong, Hong Kong.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: A novel chatbot mobile app for training of undergraduate medical students' clinical history taking skills was developed in 2021. Students were able to take clinical history from the virtual patient for bedside teaching. A case-control study was conducted to evaluate the effectiveness of learning with chatbot mobile app, versus conventional bedside teachings with real patients. Methods: 132 final year medical students were randomized into two groups - Conventional bedside teaching with clinical history taken from a real patient, and Bedside teaching with clinical history taken from the Chatbot. Independent blinded assessment of students' history taking skills was conducted. Students' performance were assessed by standardized marking scheme. Results: Median age was 23 years old (Range 21-30 years old). There were 62 female and 70 male students.64 students were randomized into conventional group while 68 students were randomized into the chatbot group. Baseline demographic data were comparable between the two groups.Blinded assessment of students' performance in clinical history taking were comparable between the conventional group and chatbot group (p > 0.05). Conclusion: With the promising results we have demonstrated in this study, we believe training of history taking skills by chatbot will be a feasible alternative to conventional bedside teaching.

Indexed as

Clinical educationComputersNew technologySimulation

Identifiers

PMID35770149
PMCPMC9234591

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.