Evidence map›Paper›PMID 34283166›Full record

ArticleSensors (Basel, Switzerland)2021

Internet-of-Things Devices in Support of the Development of Echoic Skills among Children with Autism Spectrum Disorder.

Krzysztof J Rechowicz, John B Shull, Michelle M Hascall, Saikou Y Diallo, Kevin J O'Brien

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. 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, top 93% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  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

5 authors at 2 institutions in 1 country.

Krzysztof J RechowiczVirginia Modeling, Analysis & Simulation Center, Old Dominion University, Suffolk, VA 23435, USA.ORCID 0000-0002-7561-9858
John B ShullVirginia Modeling, Analysis & Simulation Center, Old Dominion University, Suffolk, VA 23435, USA.
Michelle M HascallMea'Alofa Autism Support Center, Chesapeake, VA 23321, USA.
Saikou Y DialloVirginia Modeling, Analysis & Simulation Center, Old Dominion University, Suffolk, VA 23435, USA.
Kevin J O'BrienVirginia Modeling, Analysis & Simulation Center, Old Dominion University, Suffolk, VA 23435, USA.
Old Dominion University · USCenter for Autism and Related Disorders · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A significant therapeutic challenge for people with disabilities is the development of verbal and echoic skills. Digital voice assistants (DVAs), such as Amazon's Alexa, provide networked intelligence to billions of Internet-of-Things devices and have the potential to offer opportunities to people, such as those diagnosed with autism spectrum disorder (ASD), to advance these necessary skills. Voice interfaces can enable children with ASD to practice such skills at home; however, it remains unclear whether DVAs can be as proficient as therapists in recognizing utterances by a developing speaker. We developed an Alexa-based skill called ASPECT to measure how well the DVA identified verbalization by autistic children. The participants, nine children diagnosed with ASD, each participated in 30 sessions focused on increasing vocalizations and echoic responses. Children interacted with ASPECT prompted by instructions from an Echo device. ASPECT was trained to recognize utterances and evaluate them as a therapist would-simultaneously, a therapist scored the child's responses. The study identified no significant difference between how ASPECT and the therapists scored participants; this conclusion held even when subsetting participants by a pre-treatment echoic skill assessment score. This indicates considerable potential for providing a continuum of therapeutic opportunities and reinforcement outside of clinical settings.

Indexed as

Autism Spectrum DisorderVoiceChildHumansInternetautismhuman-computer interactionsinternet-of-thingslanguage therapy

Identifiers

PMID34283166
PMCPMC8272129
OpenAlexW3181595588

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.