Applied behavior analysis therapy in enhancing communication skills among children with autism spectrum disorder: A systematic literature review
DOI:
https://doi.org/10.58524/sidase.v1i1.4Keywords:
Applied behavior analysis, Autism spectrum disorder, Communication skills, Discrete trial training, Natural environment teachingAbstract
Applied behavior analysis (ABA) is an evidence-based intervention widely used to enhance communication skills in children with autism spectrum disorder (ASD). This study presents a systematic literature review aimed at analyzing the effectiveness of major ABA techniques discrete trial training (DTT), natural environment teaching (NET), and verbal behavior (VB) in improving both verbal and nonverbal communication outcomes. Relevant empirical studies were identified and synthesized to examine intervention characteristics, implementation intensity, and measured communication outcomes. The findings indicate that ABA-based interventions are generally associated with significant improvements in functional communication skills, including mands (requesting behavior), imitation skills, receptive and expressive language abilities, and generalization of communication across contexts. Intervention effectiveness appears to be influenced by several key factors, including treatment intensity, individualized assessment-based programming, quality supervision, and active parent or caregiver involvement. However, substantial heterogeneity was observed across studies in terms of research design, intervention duration, outcome measurement tools, and participant characteristics. While several studies report moderate to strong effects on language development and adaptive communication behaviors, others emphasize the necessity of structured implementation, therapist training, and interdisciplinary collaboration to ensure sustainable outcomes. Overall, the evidence supports ABA as an effective approach for improving communication skills in children with ASD. Nevertheless, future research employing rigorous experimental designs, larger sample sizes, standardized outcome measures, and long-term follow-up assessments is recommended to strengthen the empirical foundation and improve generalizability.
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