Abstract
Objectives
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterised by persistent deficits in social communication and interaction, as well as restricted and repetitive behaviours. Early diagnosis of ASD is critical for effective interventions. This study aims to evaluate the effectiveness of interactive video-based training in increasing the awareness and knowledge of healthcare professionals regarding the early diagnosis of ASD.
Materials and Methods
A total of 8,864 primary health care workers (family physicians and health personnel) from 24 provinces of Türkiye participated in the study. The training materials included video clips demonstrating key ASD symptoms based on Autism Diagnostic Observation Schedule-II assessments. In order to evaluate the effectiveness of the video-based training, a Likert scale questionnaire was used for post-training evaluation. Data were analysed with descriptive statistics using SPSS 22 (IBM Corp., Armonk, NY, USA) software.
Results
94% of the participants were satisfied with the training, 92% stated that the content was logically structured and 94% stated that the case examples reinforced the training. The videos were found interesting by 91% and increased focus by 93%. 94% of the participants stated that the videos effectively conveyed the basic features of ASD, 93% stated that the training increased their awareness, 92% stated that the videos were more effective compared to traditional methods, and 94% suggested that similar trainings should continue.
Conclusion
Interactive video-based training was found to be an effective and engaging method to increase the awareness and knowledge levels of healthcare professionals about ASD. In line with the positive feedback received from the participants, integrating similar video-based training materials into routine medical training programmes may support early diagnosis and intervention processes of ASD.
Keywords: Autism awareness, interactive video-based training, health workers
References
American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders: DSM-5. 5th ed. Washington, DC: American Psychiatric Publishing; 2013.
Bailey A, Phillips W, Rutter M. Autism: towards an integration of clinical, genetic, neuropsychological, and neurobiological perspectives. J Child Psychol Psychiatry. 1996;37:89-126.
Elsabbagh M, Divan G, Koh YJ, Kim YS, Kauchali S, Marcín C, Montiel-Nava C, Patel V, Paula CS, Wang C, Yasamy MT, Fombonne E. Global prevalence of autism and other pervasive developmental disorders. Autism Res. 2012;5:160-179.
Wing L, Potter D. The epidemiology of autistic spectrum disorders: is the prevalence rising? Ment Retard Dev Disabil Res Rev. 2002;8:151-161.
MacDonald R, Parry-Cruwys D, Dupere S, Ahearn W. Assessing progress and outcome of early intensive behavioral intervention for toddlers with autism. Res Dev Disabil. 2014;35:3632-3644.
Sobieski M, Sobieska A, Sekułowicz M, Bujnowska-Fedak MM. Tools for early screening of autism spectrum disorders in primary health care–a scoping review. BMC Prim Care. 2022;23:46.
Sices L, Feudtner C, McLaughlin J, Drotar D, Williams M. How do primary care physicians identify young children with developmental delays? A national survey. J Dev Behav Pediatr. 2003;24:409-417.
Committee on Children With Disabilities. American Academy of Pediatrics: The pediatrician’s role in the diagnosis and management of autistic spectrum disorder in children. Pediatrics. 2001;107:1221-1226.
Chen S, Zhao J, Hu X, Tang L, Li J, Wu D, Yan T, Xu L, Chen M, Huang S, Hao Y. Children neuropsychological and behavioral scale-revision 2016 in the early detection of autism spectrum disorder. Front Psychiatry. 2022;13:893226.
Taslibeyaz E, Dursun OB, Karaman S. Interactive video usage on autism spectrum disorder training in medical education. Interact Learn Environ. 2017;25:1025-1034.
Lord C, Risi S, Lambrecht L, Cook EH Jr, Leventhal BL, DiLavore PC, Pickles A, Rutter M. The autism diagnostic observation schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism. J Autism Dev Disord. 2000;30:205-223.
Adair JE. Decision making and problem solving strategies. 9th ed. London: Kogan Page Publishers; 2007.
Ploetzner R. The effectiveness of enhanced interaction features in educational videos: a meta-analysis. Interact Learn Environ. 2024;32:1597-1612.
Mayer RE. Using multimedia for e‐learning. J Comput Assist Learn. 2017;33:403-423.
Sweller J. Cognitive load theory and educational technology. Educ Technol Res Dev. 2020;68:1-16.
Kolås L. Application of interactive videos in education. In: Proceedings of the 14th International Conference on Information Technology Based Higher Education and Training (ITHET); 2015 Jun; Lisbon, Portugal. Piscataway, NJ: IEEE; 2015. p. 1-6.
Navarrete E. A review on recent advances in video-based learning research: video features, interaction, tools, and technologies. [Internet]. Hannover (DE): Leibniz Universität Hannover; 2021 [cited 2025 Sep 24]. Available from: https://repo.uni-hannover.de/items/018cc97b-b6b0-4070-883d-4711c8185aa8
Desai T, Kulkarni D. Assessment of interactive video to enhance learning experience: a case study. J Eng Educ Transform. 2022;35:74-80.
Lin Y, Yu Z. A meta‐analysis of the effects of augmented reality technologies in interactive learning environments (2012-2022). Comput Appl Eng Educ. 2023;31:1111-1131.
Gilbert M, Gore K, Hawke M, Barbaro J. Development, delivery, and evaluation of a training program for the early identification of autism: monitoring of social attention, interaction, and communication. Front Neurol. 2023;14:1201265.
Gore K, Gilbert M, Hawke M, Barbaro J. Investigating autism knowledge, self-efficacy, and confidence following maternal and child health nurse training for the early identification of autism. Front Neurol. 2024;14:1201292.
Gros B, García-Peñalvo FJ. Future trends in the design strategies and technological affordances of e-learning. In: Gros B, García-Peñalvo FJ, editors. Learning, design, and technology: an international compendium of theory, research, practice, and policy. Cham: Springer; 2023. p. 345–367.
Ukenova A, Bekmanova G. A review of intelligent interactive learning methods. Front Comput Sci. 2023;5:1141649.
