Evidence map›Paper›PMID 37269499›Full record

Trial reportJournal of autism and developmental disorders2024

Virtual Interview Training Among BIPOC Autistic Transition-Age Youth: A Secondary Analysis of an Initial Effectiveness RCT.

Ed-Dee G Williams, Matthew J Smith

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Journal of autism and developmental disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

2 authors.

Ed-Dee G WilliamsSchool of Social Work, University of Michigan, 1080 S. University Ave., Ann Arbor, MI, 48109, USA. eddeew@umich.edu.ORCID http://orcid.org/0000-0003-3037-3484
Matthew J SmithSchool of Social Work, University of Michigan, 1080 S. University Ave., Ann Arbor, MI, 48109, USA.

Funding

Virtual Job Interview Training for Transition Age Youth with ASDR34MH111531 · NIMH · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI SMITH, MATTHEW JAMES · 2017 to 2019
$734k
NIMH NIH HHS R34 MH111531
6 · The paper itself

Abstract

Black, Indigenous, and Persons of Color (BIPOC) autistic transition-aged youth (TAY) report lower rates of competitive employment compared to White autistic TAY and even greater deficits with social skills associated with positive job interviewing. A virtual job interviewing program was adapted to support and improve the job interviewing skills of autistic TAY. The current study evaluates the effectiveness of an efficacious virtual interview training program on the job interview skills, interview anxiety, and likeliness to be hired, for a subsample of 32 BIPOC autistic TAY, ages 17-26 years old from a previous randomized control trial of the program. Bivariate analyses were used to evaluate between-group differences at pre-test related to background characteristics, and whether Virtual Interview Training for Transition-Age Youth (VIT-TAY) was associated with changes between pre-test and post-test measures of job interview skills. Additionally, a Firth logistic regression was conducted to examine the relationship between VIT-TAY and competitive integrative employment at 6 months, covarying for fluid cognition, having ever had a job interview, and baseline employment status. Participants receiving pre-employment services (Pre-ETS) and virtual interview training had better job interview skills (F = 12.7,

Indexed as

Autistic DisorderAdolescentAdultEmploymentFemaleHumansInterviews as TopicMaleSocial SkillsYoung AdultAutismBIPOC youthEmployment skillsInterventionsTransition-age

Identifiers

PMID37269499
PMCPMC10759921

What OpenQuestion holds

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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.