- Title
- E-technology social support programs for autistic children: can they work?
- Creator
- Wall, Natalie G.; Smith, Oliver; Campbell, Linda E.; Loughland, Carmel; Wallis, Mark; Henskens, Frans; Schall, Ulrich
- Relation
- World Journal of Psychiatry Vol. 11, Issue 12, p. 1239-1246
- Publisher Link
- http://dx.doi.org/10.5498/wjp.v11.i12.1239
- Publisher
- Baishideng Publishing Group Co.
- Resource Type
- journal article
- Date
- 2021
- Description
- Autism is a neurodevelopmental condition with associated difficulties that present differently across individuals. One such difficulty is recognizing basic and complex facial expressions. Research has previously found that there are many evidence-based support programs available for building non-verbal communication skills. These programs are frequently administered with a therapist or in a group setting, making them inflexible in nature. Programs hosted on e-technology are becoming increasingly popular, with many parents supportive of them. Applications (apps) that are hosted on technology such as iPads or mobile phones allow users to engage in building skills in real-time social settings and own what they are learning. These technologies are frequently used by autistic children, with apps typically focusing on identifying facial features. Yet at this current time, there are mixed reviews of how to design such programs and what their theoretical backing is, with many studies using a mix of observation and psychological assessments as outcome measures. Eye-tracking and electroencephalography are established methodologies that measure neural processing and gaze behaviors while viewing faces. To better support the field moving forward, objective measures such as these are a way to measure outcomes of apps that are designed for helping children on the spectrum build skills in understanding facial expressions.
- Subject
- autism; facial expression recognition; technology; eye-tracking; electroencephalography
- Identifier
- http://hdl.handle.net/1959.13/1431418
- Identifier
- uon:38960
- Identifier
- ISSN:2220-3206
- Rights
- This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
- Language
- eng
- Full Text
- Reviewed
- Hits: 2035
- Visitors: 2269
- Downloads: 241
| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | ATTACHMENT02 | Publisher version (open access) | 902 KB | Adobe Acrobat PDF | View Details Download |