Evidence map›Paper›PMID 36829367›Full record

ReviewBehavioral sciences (Basel, Switzerland)2023

Self-Monitoring Intervention for Adolescents and Adults with Autism: A Research Review.

Yi-Fan Li, Suzanne Byrne, Wei Yan, Kathy B Ewoldt

Abstract readReview
In one paragraph

Review in Behavioral sciences (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Yi-Fan LiDepartment of Interdisciplinary Learning and Teaching, The University of Texas at San Antonio, San Antonio, TX 78249, USA.
Suzanne ByrneDepartment of Interdisciplinary Learning and Teaching, The University of Texas at San Antonio, San Antonio, TX 78249, USA.
Wei YanDepartment of Interdisciplinary Learning and Teaching, The University of Texas at San Antonio, San Antonio, TX 78249, USA.
Kathy B EwoldtDepartment of Interdisciplinary Learning and Teaching, The University of Texas at San Antonio, San Antonio, TX 78249, USA.ORCID 0000-0002-4832-5379

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ability to work and function independently is one of the most important skills for the achievement of ideal post-school outcomes. The use of self-monitoring to improve independence and/or reduce undesirable behaviors is an imperative need for individuals with autism. The purpose of this literature review was to examine technology-based self-monitoring interventions for individuals with autism. We used a four-step literature search process to identify studies for review. Online databases, such as ERIC, were used to search for studies. Using four inclusion criteria and PRISMA guidelines for the selection and screening process, we identified 16 studies that met the inclusion criteria. We used coding to summarize the following information from the included studies: participants who met the inclusion criteria, primary dependent variable, primary intervention, and study design. The results of the review revealed three primary functions of technology performed in self-monitoring. The included studies targeted on-task behaviors, skill acquisition, and socially relevant behaviors as primary dependent variables. The findings of the review suggested that future research could use self-monitoring interventions to support an adult with autism in employment settings and that a self-monitoring intervention could be tailored by considering individual differences.

Indexed as

autismreviewself-monitoringtechnology

Identifiers

PMID36829367
PMCPMC9952041

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.