Effectiveness of a Short Computer-based Emotion Recognition Training in Different Patient Groups

Autism Spectrum Disorder Clinical Trial

Official title:

Compared Effectiveness of a Short Computer-based Emotion Recognition Training in Conduct Disorder and Autistic Spectrum Disorder Patients

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT04845243
• Other study ID #: EmoRecTraining_EVA
• Status: Not yet recruiting
• Phase: N/A
• Start date: April 15, 2021
• Est. completion date: November 30, 2021

Study information

• Verified date: April 2021
• Source: University Psychiatric Clinics Basel
• Contact: Christina Stadler, Professor
• Phone: +41 61 325 51 11
• Email: Christina.stadler[@]upk.ch
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

Emotion recognition and regulation are necessary skills for social interaction. Disrupted development of these processes severely interferes with socio-emotional development. These difficulties are commonly reported in patients with Autistic Spectrum Disorder (ASD) or Conduct Disorder (CD), with the subsequent social/interpersonal difficulties. The available evidence suggest that impaired emotion regulation processes might underlie the aggressive behaviours frequently observed in both disorders. However, no study has yet investigated the presence of disorder-specific characteristics on emotion processing between these two disorders. Different impaired emotion recognition difficulties may underlie the reported emotion dysregulation. A practical implication of this is that given that both disorders have shown difficulties during emotion recognition processes, a short, computer-based intervention to improve emotion recognition might benefit both cases, even though their aetiologies might differ.

Description:

For ASD patients, studies training facial emotion recognition have focused on increasing the active attention to the eye region, re-directing attention to facial features to facilitate facial emotion recognition. Evidence shows positive results using computer-based emotion recognition training programs with young children and adolescents with ASD. It has also been recently suggested that emotion recognition training may be a suitable intervention for patients with CD. This would be supported by some preliminary evidence in patients with severe behavioural problems, young offenders and patients with CD + CU Traits. The overall goal of this project is to investigate the compared impact of an emotion recognition training in patients with ASD or CD. This goal can be subdivided into three separate subgoals: a) identify whether the training program is effective; b) identify whether the training program has differentiated or comparable effects between both patients groups and c) investigate individual characteristics that may help identify those individuals who would benefit most from the intervention. This information is crucial to inform the design of more efficient treatments to differentially address the specific deficits associated to the disorders.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 80
• Est. completion date: November 30, 2021
• Est. primary completion date: November 30, 2021
• Accepts healthy volunteers: No
• Gender: All
• Age group: 10 Years to 18 Years

Eligibility

Inclusion Criteria:

• Diagnosis: ASD or CD
• German speaking
• IQ > 70
• Age: 10-18

Exclusion Criteria:

• Comorbid Anxiety or Depressive disorder diagnosis
• IQ < 70
• Insufficient German language skills
• Severe developmental disorders

Related Conditions & MeSH terms

• Autism Spectrum Disorder
• Conduct Disorder
• Disease

Intervention

Behavioral:
• Emotionen Verstehen und Ausdrücken (E.V.A.)
The online training is focused on the strengthening of socioemotional competences and consists of different training tasks (up to 3 million) presented to the participant as mini games. These training tasks are specifically designed according to empirical findings to match the socio-emotional recognition needs of people with ASD. During these games, an adapted Elo-Algorithm allows to automatically evaluate the participants' performance and adapts the difficulty levels throughout the users' progress in the training.

Locations

Country	Name	City	State
n/a

Sponsors (1)

Lead Sponsor	Collaborator
Prof. Christina Stadler

References & Publications (16)

Ahmed SP, Bittencourt-Hewitt A, Sebastian CL. Neurocognitive bases of emotion regulation development in adolescence. Dev Cogn Neurosci. 2015 Oct;15:11-25. doi: 10.1016/j.dcn.2015.07.006. Epub 2015 Jul 29. Review. — View Citation

Blakemore SJ. The social brain in adolescence. Nat Rev Neurosci. 2008 Apr;9(4):267-77. doi: 10.1038/nrn2353. Review. — View Citation

Cooper S, Hobson CW, van Goozen SH. Facial emotion recognition in children with externalising behaviours: A systematic review. Clin Child Psychol Psychiatry. 2020 Oct;25(4):1068-1085. doi: 10.1177/1359104520945390. Epub 2020 Jul 25. — View Citation

Dadds MR, Cauchi AJ, Wimalaweera S, Hawes DJ, Brennan J. Outcomes, moderators, and mediators of empathic-emotion recognition training for complex conduct problems in childhood. Psychiatry Res. 2012 Oct 30;199(3):201-7. doi: 10.1016/j.psychres.2012.04.033. Epub 2012 Jun 15. — View Citation

Hubble K, Bowen KL, Moore SC, van Goozen SH. Improving Negative Emotion Recognition in Young Offenders Reduces Subsequent Crime. PLoS One. 2015 Jun 29;10(6):e0132035. doi: 10.1371/journal.pone.0132035. eCollection 2015. — View Citation

Hunnikin LM, van Goozen SHM. How can we use knowledge about the neurobiology of emotion recognition in practice? Journal of Criminal Justice. 2019 Nov;65:101537.

Kouo JL, Egel AL. The Effectiveness of Interventions in Teaching Emotion Recognition to Children with Autism Spectrum Disorder. Rev J Autism Dev Disord. 2016 Sep;3(3):254-65.

Moebert, T. & Lucke, U., (2019). E.V.A. - Emotionen Verstehen und Ausdrücken. In: Pinkwart, N. & Konert, J. (Hrsg.), DELFI 2019. Bonn: Gesellschaft für Informatik e.V.. (S. 289-290). DOI: 10.18420/delfi2019_324

Ramdoss S, Machalicek W, Rispoli M, Mulloy A, Lang R, O'Reilly M. Computer-based interventions to improve social and emotional skills in individuals with autism spectrum disorders: a systematic review. Dev Neurorehabil. 2012;15(2):119-35. doi: 10.3109/17518423.2011.651655. Review. — View Citation

Schlegel K, Grandjean D, Scherer KR. Introducing the Geneva emotion recognition test: an example of Rasch-based test development. Psychol Assess. 2014 Jun;26(2):666-72. doi: 10.1037/a0035246. Epub 2013 Dec 2. — View Citation

Silver M, Oakes P. Evaluation of a new computer intervention to teach people with autism or Asperger syndrome to recognize and predict emotions in others. Autism. 2001 Sep;5(3):299-316. — View Citation

Somerville LH, Casey BJ. Developmental neurobiology of cognitive control and motivational systems. Curr Opin Neurobiol. 2010 Apr;20(2):236-41. doi: 10.1016/j.conb.2010.01.006. Epub 2010 Feb 16. Review. — View Citation

Tanaka JW, Sung A. The "Eye Avoidance" Hypothesis of Autism Face Processing. J Autism Dev Disord. 2016 May;46(5):1538-52. doi: 10.1007/s10803-013-1976-7. Review. — View Citation

Wells AE, Hunnikin LM, Ash DP, van Goozen SHM. Improving emotion recognition is associated with subsequent mental health and well-being in children with severe behavioural problems. Eur Child Adolesc Psychiatry. 2020 Sep 30. doi: 10.1007/s00787-020-01652-y. [Epub ahead of print] — View Citation

Wieckowski AT, White SW. Attention Modification to Attenuate Facial Emotion Recognition Deficits in Children with Autism: A Pilot Study. J Autism Dev Disord. 2020 Jan;50(1):30-41. doi: 10.1007/s10803-019-04223-6. — View Citation

Zoerner D, Schutze J, Kirst S, Dziobek I, Lucke U. Zirkus Empathico: Mobile Training of Socio-Emotional Competences for Children with Autism. In: 2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT) [Internet]. Austin, TX, USA: IEEE; 2016 [cited 2021 Feb 10]. p. 448-52. Available from: http://ieeexplore.ieee.org/document/7757020/

* Note: There are 16 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Change in performance accuracy in Geneva Emotion Recognition Test (GERT)	Percentage of accuracy to stimuli showing facial emotions	Change in performance before and after the emotion recognition training, after 1 month (pre/post measure)
Primary	Change in performance response times in Geneva Emotion Recognition Test (GERT)	Response times to stimuli showing facial emotions	Change in performance before and after the emotion recognition training, after 1 month (pre/post measure)
Primary	Change in performance reaction times in Social decision-making task	Reaction times for each of the facial emotions shown	Change in Performance before and after the emotion recognition training, after 1 month (pre/post measure)
Primary	Change in choices in Social decision-making task	The proportion of choices that maximise their self-gain for each of the facial emotions shown	Change in choices before and after the emotion recognition training, after 1 month (pre/post measure)