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Predictive factors of success in neurofeedback training for children with ADHD
- Source :
- Developmental neurorehabilitation. 22(1)
- Publication Year :
- 2017
-
Abstract
- Neurofeedback (NF) training aims the enhancement of self-regulation over brain activities. While it is largely recognized as an effective treatment for attention deficit hyperactivity disorder (ADHD), the existence of non-learners has also been reported. The present study explored pre-training assessment indices that could predict learners prior to NF training.Twenty-two children with ADHD participated in slow cortical potential (SCP) NF training and completed pre- and post-training assessments. Participants were classified into learners or non-learners based on their progress in the SCP regulation, and pre-training indices that differentiate the two groups were examined by decision tree analysis.The learner rate in NF training was 45.5%. Learners were predicted by pre-training cognitive and neurophysiological measures regarding Stroop tasks, which suggested relatively intact executive function as their characteristics. Given that NF training is not universally effective for children with ADHD, further studies are necessary to establish application criteria.
- Subjects :
- Male
030506 rehabilitation
Adolescent
education
03 medical and health sciences
Developmental Neuroscience
medicine
Attention deficit hyperactivity disorder
Effective treatment
Humans
Learning
0501 psychology and cognitive sciences
Child
05 social sciences
Rehabilitation
Cognition
General Medicine
Neurofeedback
medicine.disease
Treatment Outcome
Attention Deficit Disorder with Hyperactivity
Pediatrics, Perinatology and Child Health
Female
0305 other medical science
Psychology
Outcome prediction
human activities
050104 developmental & child psychology
Clinical psychology
Stroop effect
Subjects
Details
- ISSN :
- 17518431
- Volume :
- 22
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- Developmental neurorehabilitation
- Accession number :
- edsair.doi.dedup.....19dbb01d180b6d9e3758e800125422b6