Association between Facial Emotion Recognition and Bullying Involvement among Adolescents with High-Functioning Autism Spectrum Disorder

Liu, Tai‐Ling; Wang, Pengwei; Yang, Yi‐Hsin; Shyi, Gary C.-W.

doi:10.3390/ijerph16245125

Cited by 14 publications

(8 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, a study found that AASD may have difficulty in emotion recognition and hostile attribution bias, which increase their risk of verbal and covert aggression toward others [ 38 ]. However, another study observed that the ASD bullying perpetrators performed significantly better on rating the intensity of emotions in the Facial Emotion Recognition Task; the bullying victims performed significantly worse on ranking the intensity of facial emotions [ 39 ]. The discrepancy between previous studies indicates that the ability to recognize bullying involvement is heterogeneous among individuals with ASD.…”

Section: Discussionmentioning

confidence: 99%

Adolescent–Caregiver Agreement Regarding the School Bullying and Cyberbullying Involvement Experiences of Adolescents with Autism Spectrum Disorder

Liu

Chen

Hsiao

et al. 2023

IJERPH

Self Cite

View full text Add to dashboard Cite

School bullying and cyberbullying victimization and perpetration are prevalent in adolescents with autism spectrum disorder (AASD). However, the levels of adolescent–caregiver agreement regarding the bullying involvement of AASD and the factors associated with these levels remain to be evaluated. In the present study, we evaluated the levels of adolescent–caregiver agreement on the school bullying and cyberbullying involvement experiences of AASD and the factors associated with the levels of agreement. This study included 219 dyads of AASD and their caregivers. The school bullying and cyberbullying involvement experiences of the participating AASD were assessed using the School Bullying Experience Questionnaire and the Cyberbullying Experiences Questionnaire, respectively. Attention-deficit/hyperactivity disorder, oppositional defiant disorder (ODD), depressive and anxiety symptoms, and autistic social impairment were also assessed. AASD and their caregivers had poor to fair levels of agreement regarding the school bullying and cyberbullying victimization and perpetration experiences of AASD. Severe inattention, hyperactivity–impulsivity, ODD, depressive and anxiety symptoms, and autistic social impairment were associated with high levels of adolescent–caregiver agreement. When assessing the bullying involvement experiences of AASD, mental health professionals should obtain information from multiple sources. In addition, the factors influencing the levels of agreement should be considered.

show abstract

Section: Discussionmentioning

confidence: 99%

Adolescent–Caregiver Agreement Regarding the School Bullying and Cyberbullying Involvement Experiences of Adolescents with Autism Spectrum Disorder

Liu

Chen

Hsiao

et al. 2023

IJERPH

Self Cite

View full text Add to dashboard Cite

show abstract

“…After reviewing the literature,5 41–55 we identified the following four preliminary categories of causes for short-term or long-term abnormal facial expressions in people: (1) gene-related factors, (2) neurological factors, (3) psychiatric conditions and (4) medication-induced triggers. Genetic-related factors, such as the presence or mutation of a certain gene, are the most studied cause for abnormal facial changes in individuals 5 7 35.…”

Section: Discussionmentioning

confidence: 99%

Deep learning-based facial image analysis in medical research: a systematic review protocol

Liang

Shi

et al. 2021

BMJ Open

View full text Add to dashboard Cite

IntroductionDeep learning techniques are gaining momentum in medical research. Evidence shows that deep learning has advantages over humans in image identification and classification, such as facial image analysis in detecting people’s medical conditions. While positive findings are available, little is known about the state-of-the-art of deep learning-based facial image analysis in the medical context. For the consideration of patients’ welfare and the development of the practice, a timely understanding of the challenges and opportunities faced by research on deep-learning-based facial image analysis is needed. To address this gap, we aim to conduct a systematic review to identify the characteristics and effects of deep learning-based facial image analysis in medical research. Insights gained from this systematic review will provide a much-needed understanding of the characteristics, challenges, as well as opportunities in deep learning-based facial image analysis applied in the contexts of disease detection, diagnosis and prognosis.MethodsDatabases including PubMed, PsycINFO, CINAHL, IEEEXplore and Scopus will be searched for relevant studies published in English in September, 2021. Titles, abstracts and full-text articles will be screened to identify eligible articles. A manual search of the reference lists of the included articles will also be conducted. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses framework was adopted to guide the systematic review process. Two reviewers will independently examine the citations and select studies for inclusion. Discrepancies will be resolved by group discussions till a consensus is reached. Data will be extracted based on the research objective and selection criteria adopted in this study.Ethics and disseminationAs the study is a protocol for a systematic review, ethical approval is not required. The study findings will be disseminated via peer-reviewed publications and conference presentations.PROSPERO registration numberCRD42020196473.

show abstract

“…Emotion recognition, ToM and empathy are affected to different degrees in various neurodevelopmental disorders, among which are autism spectrum disorder, attention‐deficit hyperactivity disorder, intellectual disability and conduct disorder among others (Khosdelazad et al, 2020; Kohls et al, 2020; Kuijper, Hartman, & Hendriks, 2015; Liu, Wang, Yang, Shyi, & Yen, 2019; Zaja & Rojahn, 2008), and depending on the disorder will be the feature and performance impairment of each domain. For example, while in autism spectrum disorder, ToM is the most affected process (Jones et al, 2018), in attention‐deficit hyperactivity disorder, it is the emotion perception but not because they are not able to identify emotions but because they tend to misinterpret them (Löytömäki, Ohtonen, Laakso, & Huttunen, 2020).…”

Section: Identify the Domains Of Social Cognition And The Instruments...mentioning

confidence: 99%

Some considerations for social cognition assessment in children

Pineda-Alhucema

Figueroa

2022

Infant and Child Development

View full text Add to dashboard Cite

Social cognition is a very important group of neurocognitive processes involved especially in social functioning; currently, the amount of research on this topic is increasing and suggests some considerations about its assessment, particularly in the child population. This article presents some of these considerations focussed on the theoretical models, the type of instrument and some suggestions for the assessment processes. Specifically, four considerations are proposed: to be clear about the purpose of the assessment, to identify the domains of social cognition and the instruments to assess them, to consider the approach to the assessment and to analyse the role of the cultural and social context, all these keeping in mind the children's benefit.

show abstract

Association between Facial Emotion Recognition and Bullying Involvement among Adolescents with High-Functioning Autism Spectrum Disorder

Cited by 14 publications

References 43 publications

Adolescent–Caregiver Agreement Regarding the School Bullying and Cyberbullying Involvement Experiences of Adolescents with Autism Spectrum Disorder

Adolescent–Caregiver Agreement Regarding the School Bullying and Cyberbullying Involvement Experiences of Adolescents with Autism Spectrum Disorder

Deep learning-based facial image analysis in medical research: a systematic review protocol

Some considerations for social cognition assessment in children

Contact Info

Product

Resources

About