Improvements toothbrushing skills in children with autism spectrum disorders through point of view video modelling: pra-experimetal study

Kyle Raditya Wibowo, Asty Samiaty Setiawan, Inne Suherna Sasmita

Abstract


Introduction: Children with Autism Spectrum Disorders (ASD) experience neurodevelopmental disorders characterized by difficulties with social interaction, communication, and repetitive behavioral patterns. Brushing teeth is one of the behaviors that needs to be trained in children with ASD, and one effective method for this is Point-of-View Video Modeling (POVVM). This study aims to evaluate the changes in toothbrushing skills among children with Autism Spectrum Disorders following intervention using the POVVM method. Methods: This study used a descriptive design with a cross-sectional approach. The subjects, selected using the total sampling method were 16 children with ASD from Special Educational Needs (SEN) School Bunda Bening Selakshahati, Bandung Regency, consisting of 15 boys and 1 girl. The study was conducted in 3 stages, first, a pretest was conducted to assess toothbrushing skills using an observation sheet, which was assessed by two caregivers; Next, an intervention was conducted using the POVVM video on toothbrushing behavior, shown twice daily for five days; Third, a posttest was conducted to assess toothbrushing skills after the intervention. Results: The highest pre-intervention frequency observed was for the rinsing skill (56.25%), whereas the highest post-intervention score was achieved in the skill of brushing the lower middle teeth (93.75%). The most substantial improvement was also noted in brushing the lower middle teeth, with an increase of 43.75%. The average of toothbrushing skills increased from 36.3% to 66.4%, so the change score is 30.1%. Conclusion: The toothbrushing skills of children with ASD improved following the POVVM intervention, progressing from the moderately skilled to the skilled category.

Keywords


Autism spectrum disorders, toothbrushing skills, point of view video modelling

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DOI: https://doi.org/10.24198/pjd.vol37no2.60732

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