Evidence map›Paper›PMID 32952451›Full record

ArticleSocial work in mental health2020

Virtual Patient Simulations for Brief Assessment of Mental Health Disorders in Integrated Care Settings.

Micki Washburn, Danielle E Parrish, Patrick S Bordnick

Open access · greenAbstract read
In one paragraph

Article in Social work in mental health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 15% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 61 citations in OpenAlex.

  1. Virtual patients in undergraduate psychiatry education: a systematic review and synthesis.Advances in health sciences education : theory and practice · 2024
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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 at 2 institutions in 1 country.

Micki WashburnGraduate College of Social Work, University of Houston, Houston, Texas, USA.
Danielle E ParrishGraduate College of Social Work, University of Houston, Houston, Texas, USA.
Patrick S BordnickSchool of Social Work, Tulane University, New Orleans, Louisiana, USA.
University of Houston · USTulane University · US

Funding

University of Houston Drug Abuse Research Development Program IIR24DA019798 · NIDA · UNIVERSITY OF HOUSTON · PI TORRES-HOSTOS, LUIS R · 2007 to 2019
$3.4M
NIDA NIH HHS R24 DA019798
6 · The paper itself

Abstract

This mixed methods pilot investigation evaluated the use of virtual patient simulations for increasing self-efficacy and diagnostic accuracy for common behavioral health concerns within an integrated care setting. A two by three factorial design was employed to evaluate three different simulated training conditions with a sample of 22 Masters level behavioral health students. Results support engagement in virtual patient simulation training to increase students' self-efficacy in brief clinical assessment, and support the use of virtual patient simulations to improve diagnostic accuracy. Results further indicate that virtual patient simulations have sufficient levels of usability and acceptability as a tool for developing brief clinical interviewing skills, and that participants found this method of instruction to be a valuable adjunct to traditional classroom or field based training. Future directions and next steps for the integration of technology enhanced simulations in clinical social services education are explored.

Indexed as

integrated caremental healthself-efficacysimulation based learningvirtual patients

Identifiers

PMID32952451
PMCPMC7500537
OpenAlexW2622090070

What OpenQuestion holds

Textmetadata
LicenceTDM
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.