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Journal of Autism and Developmental Disorders

Gepubliceerd in:

13-06-2021 | Original Paper

The Digital Divide in Technologies for Autism: Feasibility Considerations for Low- and Middle-Income Countries

Auteurs: Aubrey J. Kumm, Marisa Viljoen, Petrus J. de Vries

Gepubliceerd in: Journal of Autism and Developmental Disorders | Uitgave 5/2022

Abstract

Digital technologies have the potential to empower individuals with autism and their families. The COVID-19 pandemic emphasized and accelerated the drive towards technology for information, communication, training, clinical care and research, also in the autism community. However, 95% of individuals with autism live in low- and middle-income countries (LMIC) where access to electricity, internet and the ever-increasing range of digital devices may be highly limited. The World Bank coined the term ‘the digital divide’ to describe the disparities in access to digital technologies between high-income and LMIC contexts. Here we evaluated the feasibility of six emerging technologies for autism spectrum disorders, and reflected on key considerations for implementation in LMIC contexts to ensure that we do not inadvertently widen the pre-existing digital divide.

vorige artikel Evaluating Teacher Language Within General and Special Education Classrooms Serving Elementary Students with Autism

volgende artikel Motherhood: Female Perspectives and Experiences of Being a Parent with ASC

Aarons, G. A., Sklar, M., Mustanski, B., Benbow, N., & Brown, C. H. (2017). “Scaling-out” evidence-based interventions to new populations or new health care delivery systems. Implementation Science, 12(1), 111. https://doi.org/10.1186/s13012-017-0640-6CrossRefPubMedPubMedCentral

Alozie, N. O., & Akpan-Obong, P. (2017). The digital gender divide: Confronting obstacles to women’s development in Africa. Development Policy Review, 35(2), 137–160. https://doi.org/10.1111/dpr.12204CrossRef

Amaral, D. G., & de Vries, P. J. (2020). COVID-19 and autism research: Perspectives from around the globe. Autism Research, 13(6), 844–869. https://doi.org/10.1002/aur.2329CrossRefPubMedPubMedCentral

American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders: DSM-5. American Psychiatric Association.CrossRef

Bakare, M. O., Agomoh, A. O., Ebigbo, P. O., Eaton, J., Okonkwo, K. O., Onwukwe, J. U., & Onyeama, G. M. (2009). Etiological explanation, treatability and preventability of childhood autism: A survey of Nigerian healthcare workers’ opinion. Annals of General Psychiatry, 8(1), 6. https://doi.org/10.1186/1744-859X-8-6CrossRefPubMedPubMedCentral

Bartneck, C., Suzuki, T., Kanda, T., & Nomura, T. (2007). The influence of people’s culture and prior experiences with Aibo on their attitude towards robots. AI & SOCIETY, 21(1), 217–230. https://doi.org/10.1007/s00146-006-0052-7CrossRef

Bauminger-Zviely, N., Eden, S., Zancanaro, M., Weiss, P. L., & Gal, E. (2013). Increasing social engagement in children with high-functioning autism spectrum disorder using collaborative technologies in the school environment. Autism, 17(3), 317–339. https://doi.org/10.1177/1362361312472989CrossRefPubMed

Ben-Sasson, A., Lamash, L., & Gal, E. (2013). To enforce or not to enforce? The use of collaborative interfaces to promote social skills in children with high functioning autism spectrum disorder. Autism, 17(5), 608–622. https://doi.org/10.1177/1362361312451526CrossRefPubMed

Boccanfuso, L., Scarborough, S., Abramson, R. K., Hall, A. V., Wright, H. H., & O’Kane, J. M. (2017). A low-cost socially assistive robot and robot-assisted intervention for children with autism spectrum disorder: Field trials and lessons learned. Autonomous Robots, 41(3), 637–655. https://doi.org/10.1007/s10514-016-9554-4CrossRef

Boujarwah, F. A., Hong, H., Abowd, G. D., Arriaga, R. I. (2011). Towards a framework to situate assistive technology design in the context of culture. Paper presented at the proceedings of the 13th international ACM SIGACCESS conference on Computers and accessibility. Doi: https://doi.org/10.1145/2049536.2049542

Bradshaw, J., Steiner, A. M., Gengoux, G., & Koegel, L. K. (2015). Feasibility and effectiveness of very early intervention for infants at-risk for autism spectrum disorder: A systematic review. Journal of Autism and Developmental Disorders, 45(3), 778–794. https://doi.org/10.1007/s10803-014-2235-2CrossRefPubMed

Cabibihan, J. J., Javed, H., Aldosari, M., Frazier, T. W., & Elbashir, H. (2017). Sensing technologies for autism spectrum disorder screening and intervention. Sensors (Basel, Switzerland), 17(1), 46. https://doi.org/10.3390/s17010046CrossRef

Colby, K. M. (1973). The rationale for computer-based treatment of language difficulties in nonspeaking autistic children. Journal of Autism and Childhood Schizophrenia, 3(3), 254–260. https://doi.org/10.1007/BF01538283CrossRefPubMed

Colby, K. M., & Smith, D. C. (1971). Computers in the treatment of nonspeaking autistic children. Current Psychiatric Therapies, 11, 1–17.PubMed

Constantino, J. N., Kennon-McGill, S., Weichselbaum, C., Marrus, N., Haider, A., Glowinski, A. L., Gillespie, S., Klaiman, C., Klin, A., & Jones, W. (2017). Infant viewing of social scenes is under genetic control and is atypical in autism. Nature, 547(7663), 340–344. https://doi.org/10.1038/nature22999CrossRefPubMedPubMedCentral

Daley, T. C. (2004). From symptom recognition to diagnosis: Children with autism in urban India. Social Science and Medicine, 58(7), 1323–1335. https://doi.org/10.1016/S0277-9536(03)00330-7CrossRefPubMed

Dautenhahn, K., & Werry, I. (2004). Towards interactive robots in autism therapy: Background, motivation and challenges. Pragmatics & Cognition, 12(1), 1–35. https://doi.org/10.1075/pc.12.1.03dauCrossRef

David, D. O., Costescu, C. A., Matu, S., Szentagotai, A., & Dobrean, A. (2020). Effects of a robot-enhanced intervention for children with ASD on teaching turn-taking skills. Journal of Educational Computing Research, 58(1), 29–62. https://doi.org/10.1177/0735633119830344CrossRef

Dawson, G., Jones, E. J., Merkle, K., Venema, K., Lowy, R., Faja, S., Kamara, D., Murias, M., Greenson, J., Winter, J., Smith, M., Rogers, S. J., & Webb, S. J. (2012). Early behavioral intervention is associated with normalized brain activity in young children with autism. Journal of the America Academy of Child & Adolescent Psychiatry, 51(11), 1150–1159. https://doi.org/10.1016/j.jaac.2012.08.018CrossRef

Dawson-Squibb, J. J., & de Vries, P. J. (2019). Developing an evaluation framework for parent education and training in autism spectrum disorder: Results of a multi-stakeholder process. Journal of Autism and Developmental Disorders, 49(11), 4468–4481. https://doi.org/10.1007/s10803-019-04176-wCrossRefPubMed

de Vries, P. J. (2016). Thinking globally to meet local needs: Autism spectrum disorders in Africa and other low-resource environments. Current Opinion in Neurology, 29(2), 130–136. https://doi.org/10.1097/WCO.0000000000000297CrossRefPubMed

Dickstein-Fischer, L., Alexander, E., Yan, X., Su, H., Harrington, K., & Fischer, G. S. (2011). An affordable compact humanoid robot for Autism Spectrum Disorder interventions in children. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2011, 5319–5322. https://doi.org/10.1109/IEMBS.2011.6091316CrossRef

Dickstein-Fischer, L. A., Crone-Todd, D. E., Chapman, I. M., Fathima, A. T., & Fischer, G. S. (2018). Socially assistive robots: current status and future prospects for autism interventions. Innovation and Entrepreneurship in Health, 5, 15–25. https://doi.org/10.2147/IEH.S138753CrossRef

Dickstein-Fischer, L. A., Pereira, R. H., Gandomi, K. Y., Fathima, A. T., & Fischer, G. S. (2017). Interactive tracking for robot-assisted autism therapy. Paper presented at the Proceedings of the Companion of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, Vienna, Austria. https://doi.org/10.1145/3029798.3038390

Diehl, J. J., Schmitt, L. M., Villano, M., & Crowell, C. R. (2012). The clinical use of robots for individuals with autism spectrum disorders: A critical review. Research in Autism Spectrum Disorders, 6(1), 249–262. https://doi.org/10.1016/j.rasd.2011.05.006CrossRefPubMedPubMedCentral

Dietz, P., & Leigh, D. (2001). DiamondTouch: a multi-user touch technology. Paper presented at the Proceedings of the 14th annual ACM symposium on User interface software and technology. https://doi.org/10.1145/502348.502389

Divan, G., Vajaratkar, V., Desai, M. U., Strik-Lievers, L., & Patel, V. (2012). Challenges, coping strategies, and unmet needs of families with a child with autism spectrum disorder in Goa, India. Autism Research, 5(3), 190–200. https://doi.org/10.1002/aur.1225CrossRefPubMedPubMedCentral

Durkin, M. S., Elsabbagh, M., Barbaro, J., Gladstone, M., Happe, F., Hoekstra, R. A., & Shih, A. (2015). Autism screening and diagnosis in low resource settings: Challenges and opportunities to enhance research and services worldwide. Autism Research, 8(5), 473–476. https://doi.org/10.1002/aur.1575CrossRefPubMedPubMedCentral

Dutta, S., Geiger, T., & Lanvin, B. (2015). The Global Information Technology Report. ICTs for Inclusive Growth. Paper presented at the Geneva, World Economic Forum and INSEAD. Retrieved from http://www3.weforum.org/docs/WEF_Global_IT_Report_2015.pdf. (Accessed 21 Nov 2020)

Egger, H. L., Dawson, G., Hashemi, J., Carpenter, K. L., Espinosa, S., Campbell, K., & Tepper, M. (2018). Automatic emotion and attention analysis of young children at home: A ResearchKit autism feasibility study. NPJ Digital Medicine, 1(1), 1–10. https://doi.org/10.1038/s41746-018-0024-6CrossRef

Elsabbagh, M., Divan, G., Koh, Y. J., Kim, Y. S., Kauchali, S., Marcín, C., Montiel-Nava, C., Pate, V., Paula, C. S., Wang, C., Yasamy, M. T., & Fombonne, E. (2012). Global prevalence of autism and other pervasive developmental disorders. Autism Research, 5(3), 160–179. https://doi.org/10.1002/aur.239CrossRefPubMedPubMedCentral

Facebook Technologies. (2021). Compare headsets. Retrieved from https://www.oculus.com/compare/. (Accessed 12 Jan 2021)

Farley, M. A., McMahon, W. M., JensonFombonne, W. R. E., Miller, J., Gardner, M., Block, H., Pingree, C. B., Ritvo, E. R., Ritvo, R. A., & Coon, H. (2009). Twenty-year outcome for individuals with autism and average or near-average cognitive abilities. Autism Research, 2(2), 109–118. https://doi.org/10.1002/aur.69CrossRefPubMed

Fletcher, R. R., Dobson, K., Goodwin, M. S., Eydgahi, H., Wilder-Smith, O., Fernholz, D., & Picard, R. W. (2010). iCalm: Wearable sensor and network architecture for wirelessly communicating and logging autonomic activity. IEEE Transactions on Information Technology in Biomedicine, 14(2), 215–223. https://doi.org/10.1109/titb.2009.2038692CrossRefPubMed

Florida State University. (2021). Baby Navigator. Retrieved from https://babynavigator.com. (Accessed 6 Jan 2021)

Fombonne, E. (2009). Epidemiology of pervasive developmental disorders. Pediatric Research, 65(6), 591–598. https://doi.org/10.1203/PDR.0b013e31819e7203CrossRefPubMed

Franz, L., Chambers, N., von Isenburg, M., & de Vries, P. J. (2017). Autism spectrum disorder in sub-saharan africa: A comprehensive scoping review. Autism Research, 10(5), 723–749. https://doi.org/10.1002/aur.1766CrossRefPubMedPubMedCentral

Gal, E., Lamash, L., Bauminger-Zviely, N., Zancanaro, M., & Weiss, P. L. (2016). Using multitouch collaboration technology to enhance social interaction of children with high-functioning autism. Physical & Occupational Therapy in Pediatrics, 36(1), 46–58. https://doi.org/10.3109/01942638.2015.1040572CrossRef

Gartner. (2018). Gartner Says Worldwide Wearable Device Sales to Grow 26 Percent in 2019. https://www.gartner.com/en/newsroom/press-releases/2018-11-29-gartner-says-worldwide-wearable-device-sales-to-grow. (Accessed 22 Nov 2020)

Gentry, T., Wallace, J., Kvarfordt, C., & Lynch, K. B. (2010). Personal digital assistants as cognitive aids for high school students with autism: Results of a community-based trial. Journal of Vocational Rehabilitation, 32(2), 101–107. https://doi.org/10.3233/JVR-2010-0499CrossRef

Gillwald, A. (2013). Towards an understanding of ICT access and use in Africa. Retrieved from https://www.researchictafrica.net/presentations/Presentations/2013%20Gillwald%20-%20Towards%20an%20understanding%20of%20%20ICT%20access%20and%20use%20in%20Africa.pdf. (Accessed 22 Nov 2020)

Gomez, R. (2014). When you do not have a computer: Public-access computing in developing countries. Information Technology for Development, 20(3), 274–291. https://doi.org/10.1080/02681102.2012.751573CrossRef

Goodwin, M. S., Groden, J., Velicer, W. F., Lipsitt, L. P., Baron, M. G., Hofmann, S. G., & Groden, G. (2006). Cardiovascular arousal in individuals with autism. Focus on Autism and Other Developmental Disabilities, 21(2), 100–123. https://doi.org/10.1177/10883576060210020101CrossRef

Goodwin, M. S., Intille, S. S., Albinali, F., & Velicer, W. F. (2011). Automated detection of stereotypical motor movements. Journal of Autism and Developmental Disorders, 41(6), 770–782. https://doi.org/10.1007/s10803-010-1102-zCrossRefPubMed

Grinker, R. R., Chambers, N., Njongwe, N., Lagman, A. E., Guthrie, W., Stronach, S., Richard, B. O., Kauchali, S., Killian, B., Chhagan, M., Yucel, F., Kumudu, M., Baker-Cummings, C., Grether, J., & Wetherby, A. M. (2012). “Communities” in community engagement: lessons learned from autism research in South Korea and South Africa. Autism Research, 5(3), 201–210. https://doi.org/10.1002/aur.1229CrossRefPubMedPubMedCentral

Groupe Spéciale Mobile Association. (2020). The state of mobile internet connectivitiy 2020. Retrieved from https://www.gsma.com/r/wp-content/uploads/2020/09/GSMA-State-of-Mobile-Internet-Connectivity-Report-2020.pdf. (Accessed 23 Nov 2020)

Grynszpan, O., Weiss, P. L., Perez-Diaz, F., & Gal, E. (2014). Innovative technology-based interventions for autism spectrum disorders: A meta-analysis. Autism, 18(4), 346–361. https://doi.org/10.1177/1362361313476767CrossRefPubMed

Harrison, A. J., Bradshaw, L. P., Naqvi, N. C., Paff, M. L., & Campbell, J. M. (2017). Development and psychometric evaluation of the autism stigma and knowledge questionnaire (ASK-Q). Journal of Autism and Developmental Disorders, 47(10), 3281–3295. https://doi.org/10.1007/s10803-017-3242-xCrossRefPubMed

Harrison, A. J., Long, K. A., Tommet, D. C., & Jones, R. N. (2017). Examining the role of race, ethnicity, and gender on social and behavioral ratings within the autism diagnostic observation schedule. Journal of Autism and Developmental Disorders, 47(2), 2770–2782. https://doi.org/10.1007/s10803-017-3176-3CrossRefPubMed

Hedges, S. H., Odom, S. L., Hume, K., & Sam, A. (2018). Technology use as a support tool by secondary students with autism. Autism, 22(1), 70–79. https://doi.org/10.1177/1362361317717976CrossRefPubMed

International Data Corporation (IDC). (2019). Worldwide Wearables Market to Top 300 Million Units in 2019 and Nearly 500 Million Units in 2023, Says IDC. Retrieved from https://www.idc.com/getdoc.jsp?containerId=prUS45737919. (Accessed 23 Nov 2020)

International Data Corporation (IDC). (2020). Low- to Mid-Range Smartphones Dominate Worldwide Smartphone Forecast with the Fastest Growth Expected in $400–600 Price Band, According to IDC. Retrieved from https://www.idc.com/getdoc.jsp?containerId=prUS46865120. (Accessed 23 Nov 2020)

International Telecommunication Union (ITU). (2010). ICT Facts and Figures 2010. Retrieved from https://www.itu.int/ITU-D/ict/material/FactsFigures2010.pdf. (Accessed 23 Nov 2020)

International Telecommunication Union (ITU). (2016). ICT Facts and Figures 2016. Retrieved from https://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFactsFigures2016.pdf. (Accessed 23 Nov 2020)

International Telecommunication Union (ITU). (2019). Statistics. Global and Regional ICT Data (2005–2019). Retrieved fromhttps://www.itu.int/en/ITU-D/Statistics/Pages/stat/default.aspx. (Accessed 23 Nov 2020)

Kandalaft, M. R., Didehbani, N., Krawczyk, D. C., Allen, T. T., & Chapman, S. B. (2013). Virtual reality social cognition training for young adults with high-functioning autism. Journal of Autism and Developmental Disorders, 43(1), 34–44. https://doi.org/10.1007/s10803-012-1544-6CrossRefPubMed

Kanne, S. M., Carpenter, L. A., & Warren, Z. (2018). Screening in toddlers and preschoolers at risk for autism spectrum disorder: Evaluating a novel mobile-health screening tool. Autism Research, 11(7), 1038–1049. https://doi.org/10.1002/aur.1959CrossRefPubMed

Kaplan, W. A. (2006). Can the ubiquitous power of mobile phones be used to improve health outcomes in developing countries? Globalization and Health, 2(1), 9. https://doi.org/10.1186/1744-8603-2-9CrossRefPubMedPubMedCentral

Karsh, B. T. (2004). Beyond usability: Designing effective technology implementation systems to promote patient safety. Quality and Safety in Health Care, 13, 388–394. https://doi.org/10.1136/qhc.13.5.388CrossRefPubMedPubMedCentral

Kazdin, A. E., & Rabbitt, S. M. (2013). Novel models for delivering mental health services and reducing the burdens of mental illness. Clinical Psychological Science, 1(2), 170–191. https://doi.org/10.1177/2167702612463566CrossRef

Keusch, G. T., Wilentz, J., & Kleinman, A. (2006). Stigma and global health: developing a research agenda. Lancet, 367(9509), 525–527. https://doi.org/10.1016/S0140-6736(06)68183-XCrossRefPubMed

Kientz, J. A., Goodwin, M. S., Hayes, G. R., & Abowd, G. D. (2014). Interactive technologies for autism. Synthesis Lectures on Assistive, Rehabilitative, and Health-Preserving Technologies, 2(2), 1–177. https://doi.org/10.2200/S00533ED1V01Y201309ARH004CrossRef

Kim, E. S., Berkovits, L. D., Bernier, E. P., Leyzberg, D., Shic, F., Paul, R., & Scassellati, B. (2012). Social robots as embedded reinforcers of social behavior in children with autism. Journal of Autism and Developmental Disorders, 43(5), 1038–1049. https://doi.org/10.1007/s10803-012-1645-2CrossRef

Koumpouros, Y., & Kafazis, T. (2019). Wearables and mobile technologies in autism spectrum disorder interventions: A systematic literature review. Research in Autism Spectrum Disorders, 66, 1–25.CrossRef

Kumar, P., Paton, C., & Kirigia, D. (2016). I’ve got 99 problems but a phone ain’t one: Electronic and mobile health in low and middle income countries. Archives of Diseases in Childhood, 101(10), 974–979. https://doi.org/10.1136/archdischild-2015-308556CrossRef

Kumazaki, H., Yoshikawa, Y., Yoshimura, Y., Ikeda, T., Hasegawa, C., Saito, D. N., & Ishiguro, H. (2018). The impact of robotic intervention on joint attention in children with autism spectrum disorders. Molecular Autism, 9(1), 1–10. https://doi.org/10.1186/s13229-018-0230-8CrossRef

Lagunju, I. A., Bella-Awusah, T. T., & Omigbodun, O. O. (2014). Autistic disorder in Nigeria: Profile and challenges to management. Epilepsy & Behavior, 39, 126–129. https://doi.org/10.1016/j.yebeh.2014.08.020CrossRef

Law, G. C., Neihart, M., & Dutt, A. (2018). The use of behavior modeling training in a mobile app parent training program to improve functional communication of young children with autism spectrum disorder. Autism, 22(4), 424–439. https://doi.org/10.1177/1362361316683887CrossRefPubMed

Mahapatra, P., Pati, S., Sinha, R., Chauhan, A. S., Nanda, R. R., & Nallala, S. (2019). Parental care-seeking pathway and challenges for autistic spectrum disorders children: A mixed method study from Bhubaneswar, Odisha. Indian Journal of Psychiatry, 61(1), 37–44. https://doi.org/10.4103/psychiatry.IndianJPsychiatry_257_18CrossRefPubMedPubMedCentral

Michels, K. M., Hofman, K. J., Keusch, G. T., & Hrynkow, S. H. (2006). Stigma and global health: Looking forward. Lancet, 367(9509), 538–539. https://doi.org/10.1016/S0140-6736(06)68190-7CrossRefPubMed

Min, C. H., & Tewfik, A. H. (2010). Automatic characterization and detection of behavioral patterns using linear predictive coding of accelerometer sensor data. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2010: 220–223. https://doi.org/10.1109/IEMBS.2010.5627850

Naslund, J. A., Aschbrenner, K. A., Araya, R., Marsch, L. A., Unutzer, J., Patel, V., & Bartels, S. J. (2017). Digital technology for treating and preventing mental disorders in low-income and middle-income countries: A narrative review of the literature. Lancet Psychiatry, 4(6), 486–500. https://doi.org/10.1016/S2215-0366(17)30096-2CrossRefPubMedPubMedCentral

Odom, S. L., Thompson, J. L., Hedges, S., Boyd, B. A., Dykstra, J. R., Duda, M. A., & Bord, A. (2015). Technology-aided interventions and instruction for adolescents with autism spectrum disorder. Journal of Autism and Developmental Disorders, 45(12), 3805–3819. https://doi.org/10.1007/s10803-014-2320-6CrossRefPubMed

Olusanya, B. O., Davis, A. C., Wertlieb, D., Boo, N. Y., Nair, M., Halpern, R., Kuper, H., Breinbauer, C., de Vries, P. J., Gladstone, M., Halfon, N., Kancherla, V., Mulaudzi, M. C., Kakooza-Mwesige, A., Ogbo, F. A., Olusanya, J. O., WrightWilliams, S. M. A. N., Manguerra, H.,… Kassebaum, N. J. (2018). Developmental disabilities among children younger than 5 years in 195 countries and territories, 1990–2016: A systematic analysis for the Global Burden of Disease Study 2016. The Lancet Global Health, 6(10), e1100–e1121. https://doi.org/10.1016/S2214-109X(18)30309-7CrossRef

Olusanya, B. O., Wright, S. M., Nair, M. K. C., Boo, N.-Y., Halpern, R., Kuper, H., & Kassebaum, N. J. (2020). Global burden of childhood epilepsy, intellectual disability, and sensory impairments. Pediatrics. https://doi.org/10.1542/peds.2019-2623CrossRefPubMed

Parsons, D., Wilson, N. J., Vaz, S., Lee, H., & Cordier, R. (2019). Appropriateness of the TOBY application, an iPad intervention for children with autism spectrum disorder: A thematic approach. Journal of Autism and Developmental Disorders, 49(10), 4053–4066. https://doi.org/10.1007/s10803-019-04115-9CrossRefPubMed

Parsons, S., Leonard, A., & Mitchell, P. (2006). Virtual environments for social skills training: Comments from two adolescents with autistic spectrum disorder. Computers & Education, 47(2), 186–206. https://doi.org/10.1016/j.compedu.2004.10.003CrossRef

Parsons, S., Mitchell, P., & Leonard, A. (2004). The use and understanding of virtual environments by adolescents with autistic spectrum disorders. Journal of Autism and Developmental Disorders, 34(4), 449–466. https://doi.org/10.1023/b:jadd.0000037421.98517.8dCrossRefPubMed

Patel, V., Flisher, A. J., Nikapota, A., & Malhotra, S. (2008). Promoting child and adolescent mental health in low and middle income countries. Journal of Child Psychology and Psychiatry, 49(3), 313–334. https://doi.org/10.1111/j.1469-7610.2007.01824.xCrossRefPubMed

Paul, R., Augustyn, A., Klin, A., & Volkmar, F. R. (2005). Perception and production of prosody by speakers with autism spectrum disorders. Journal of Autism and Developmental Disorders, 35(2), 205–220. https://doi.org/10.1007/s10803-004-1999-1CrossRefPubMed

Pickard, K. E., Wainer, A. L., Bailey, K. M., & Ingersoll, B. R. (2016). A mixed-method evaluation of the feasibility and acceptability of a telehealth-based parent-mediated intervention for children with autism spectrum disorder. Autism, 20(7), 845–855. https://doi.org/10.1177/1362361315614496CrossRefPubMed

Pillay, S., Duncan, E. M., & de Vries, P. J. (2021). Autism in the Western Cape province of South Africa: Rates, socio-demographics, disability and educational characteristics in one million school children. Autism, 25(4), 1076–1089. https://doi.org/10.1177/1362361320978042CrossRefPubMed

Ploog, B. O., Scharf, A., Nelson, D., & Brooks, P. J. (2013). Use of computer-assisted technologies (CAT) to enhance social, communicative, and language development in children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 43(2), 301–322. https://doi.org/10.1007/s10803-012-1571-3CrossRefPubMed

POP Communications. (2020). How much should an interactive touchscreen solution cost?. https://www.popcomms.com/blog/much-interactive-touchscreen-solution-cost/ (Accessed 23 Nov 2020)

Proctor, E., Silmere, H., Raghavan, R., Hovmand, P., Aarons, G., Bunger, A., & Hensley, M. (2011). Outcomes for implementation research: Conceptual distinctions, measurement challenges, and research agenda. Administration and Policy in Mental Health, 38(2), 65–76. https://doi.org/10.1007/s10488-010-0319-7CrossRefPubMed

Rogers, S. J., & Dawson, G. (2010). Early start Denver model for young children with autism: Promoting language, learning, and engagement. Guilford Press.

Rogerson, J., Falkmer, M., Cuomo, B., Falkmer, T., Whitehouse, A. J. O., Granich, J., & Vaz, S. (2019). Parental experiences using the therapy outcomes by you (TOBY) application to deliver early intervention to their child with autism. Developmental Neurorehabilitation, 22(4), 219–227. https://doi.org/10.1080/17518423.2018.1440259CrossRefPubMed

Rojas-Méndez, J. I., Parasuraman, A., & Papadopoulos, N. (2017). Demographics, attitudes, and technology readiness. Marketing Intelligence & Planning, 35(1), 18–39. https://doi.org/10.1108/mip-08-2015-0163CrossRef

Ruparelia, K., Abubakar, A., Badoe, E., Bakare, M., Visser, K., Chugani, D. C., Chugani, H. T., Donald, K. A., Wilmshurst, J. M., Shih, A., Skuse, D., & Newton, C. R. (2014). Autism spectrum disorders in Africa: Current challenges in identification, assessment, and treatment a report on the international child neurology association meeting on ASD in Africa, Ghana, April 3–5. Journal of Child Neurology, 31(8), 1018–1026. https://doi.org/10.1177/0883073816635748CrossRef

Saiano, M., Pellegrino, L., Casadio, M., Summa, S., Garbarino, E., Rossi, V., & Sanguineti, V. (2015). Natural interfaces and virtual environments for the acquisition of street crossing and path following skills in adults with autism spectrum disorders: A feasibility study. Journal of Neuroengineering and Rehabilitation, 12(1), 17. https://doi.org/10.1186/s12984-015-0010-zCrossRefPubMedPubMedCentral

Sarker, H., Tam, A., Foreman, M., Fay, N., Dhuliawala, M., & Das, A. (2018). Detection of stereotypical motor movements in autism using a smartwatch-based system. Annual Symposium Proceedings. AMIA Symposium, 2018, 952–960.

Saxena, S., Thornicroft, G., Knapp, M., & Whiteford, H. (2007). Resources for mental health: scarcity, inequity, and inefficiency. Lancet, 370(9590), 878–889. https://doi.org/10.1016/S0140-6736(07)61239-2CrossRefPubMed

Scassellati, B. (2007). How social robots will help us to diagnose, treat, and understand autism. In S. Thrun, R. Brooks, & H. Durrant-Whyte (Eds.), Robotics research. Springer tracts in advanced robotic (pp. 552–563). Berlin: Springer.

Scassellati, B., Admoni, H., & Matarić, M. (2012). Robots for use in autism research. Annual Review of Biomedical Engineering, 14, 275–294. https://doi.org/10.1146/annurev-bioeng-071811-150036CrossRefPubMed

Silver, L. (2019). Smartphone ownership is growing rapidly around the world, but not always equally. Pew Research Center. https://www.pewresearch.org/global/2019/02/05/smartphone-ownership-is-growing-rapidly-around-the-world-but-not-always-equally/. (Accessed 30 Apr 2020)

Standen, P. J., & Brown, D. J. (2005). Virtual reality in the rehabilitation of people with intellectual disabilities: Review. Cyberpsychology, Behavavior, and Social Networking, 8(3), 272–288. https://doi.org/10.1089/cpb.2005.8.272CrossRef

Statista. (2020a). Average selling price of personal computers (PCs) worldwide from 2015 to 2019, in actual and constant currency. Retrieved from https://www.statista.com/statistics/722992/worldwide-personal-computers-average-selling-price/. (Accessed 22 Nov 2020)

Statista. (2020b). Smartphone ownership rate by country 2018. https://www.statista.com/statistics/539395/smartphone-penetration-worldwide-by-country/. (Accessed 22 Nov 2020)

Statista. (2021). Number of mHealth apps available in the Apple App Store from 1st quarter 2015 to 4th quarter 2020. Retrieved from https://www.statista.com/statistics/779910/health-apps-available-ios-worldwide/https://www.statista.com/statistics/779919/health-apps-available-google-play-worldwide/. (Accessed 22 Nov 2020)

Stichter, J. P., Laffey, J., Galyen, K., & Herzog, M. (2014). iSocial: Delivering the social competence intervention for adolescents (SCI-A) in a 3D virtual learning environment for youth with high functioning autism. Journal of Autism and Developmental Disorders, 44(2), 417–430. https://doi.org/10.1007/s10803-013-1881-0CrossRefPubMed

Travers, J. C., & Fefer, S. A. (2016). Effects of shared active surface technology on the communication and speech of two preschool children with disabilities. Focus on Autism and Other Developmental Disabilities, 32(1), 44–54. https://doi.org/10.1177/1088357615611390CrossRef

van Schalkwyk, G. I., Marin, C. E., Ortiz, M., Rolison, M., Qayyum, Z., McPartland, J. C., & Silverman, W. K. (2017). Social media use, friendship quality, and the moderating role of anxiety in adolescents with autism spectrum disorder. Journal of Autism and Developmental Disorders, 47(9), 2805–2813. https://doi.org/10.1007/s10803-017-3201-6CrossRefPubMedPubMedCentral

Vidal, M., Turner, J., Bulling, A., & Gellersen, H. (2012). Wearable eye tracking for mental health monitoring. Computer Communications, 35(11), 1306–1311. https://doi.org/10.1016/j.comcom.2011.11.002CrossRef

Vismara, L. A., Young, G. S., Stahmer, A. C., Griffith, E. M., & Rogers, S. J. (2009). Dissemination of evidence-based practice: Can we train therapists from a distance? Journal of Autism and Developmental Disorders, 39(12), 1636–1651. https://doi.org/10.1007/s10803-009-0796-2CrossRefPubMedPubMedCentral

Warren, S. F., Gilkerson, J., Richards, J. A., Oller, D. K., Xu, D., Yapanel, U., & Gray, S. (2010). What automated vocal analysis reveals about the vocal production and language learning environment of young children with autism. Journal of Autism and Developmental Disorders, 40(5), 555–569. https://doi.org/10.1007/s10803-009-0902-5CrossRefPubMed

Wei, C., & Kolko, B. E. (2005). Studying mobile phone use in context: Cultural, political, and economic dimensions of mobile phone use. Paper Presented at the Professional Communication Conference. https://doi.org/10.1109/IPCC.2005.1494179CrossRef

Weiss, P., Cobb, S., & Zancanaro, M. (2014). Challenges in developing new technologies for special needs education: A force-field analysis. Paper presented at the 10th International Conference on Disability, Virtual Reality and Associated Technologies, Sweden. Retrieved from https://pdfs.semanticscholar.org/46f3/083aa3ebfd6842503c443956c2488f49426a.pdf. (Accessed 30 Apr 2020)

Wesolowski, A., Eagle, N., Noor, A. M., Snow, R. W., & Buckee, C. O. (2012). Heterogeneous mobile phone ownership and usage patterns in Kenya. PLoS ONE. https://doi.org/10.1371/journal.pone.0035319CrossRefPubMedPubMedCentral

Wesolowski, A., O’Meara, W. P., Tatem, A. J., Ndege, S., Eagle, N., & Buckee, C. O. (2015). Quantifying the impact of accessibility on preventive healthcare in sub-Saharan Africa using mobile phone data. Epidemiology, 26(2), 223–228. https://doi.org/10.1097/EDE.0000000000000239CrossRefPubMedPubMedCentral

Wetherby, A. M., Woods, J. J., Morgan, L., Holland, R. D., & Wiseman, N. D. R. (n.d.). Autism Navigator. Retrieved from http://www.autismnavigator.com. (Accessed 29 Apr 2020)

Williams, L. W., Matson, J. L., Beighley, J. S., & Konst, M. (2014). Ethnic disparities in early autism assessment: A large scale screening study of infants and toddlers. Journal of Developmental and Physical Disabilities, 27(2), 141–148. https://doi.org/10.1007/s10882-014-9406-0CrossRef

World Bank. (2016). World Development Report 2016—Digital Dividends. Retrieved from http://documents.worldbank.org/curated/en/896971468194972881/pdf/102725-PUB-Replacement-PUBLIC.pdf. (Accessed 22 Nov 2020)

World Bank. (2020). Development Data Group. Income level/low- and middle-income countries. Retrieved from https://data.worldbank.org/income-level/low-and-middle-income. (Accessed 22 Nov 2020)

World Health Organization. (2013). Meeting report: Autism spectrum disorders and other developmental disorders: From raising awareness to building capacity: World Health Organization, Geneva, Switzerland. Retrieved from https://apps.who.int/iris/handle/10665/103312. (Accessed 22 Nov 2020)

Ye, Q., Deng, Z., Chen, Y., Liao, J., Li, G., & Lu, Y. (2019). How resource scarcity and accessibility affect patients’ usage of mobile health in China: Resource competition perspective. JMIR mHealth and uHealth. https://doi.org/10.2196/13491CrossRefPubMedPubMedCentral

Ye, Z., Li, Y., Fathi, A., Han, Y., Rozga, A., Abowd, G. D., & Rehg, J. M. (2012). Detecting eye contact using wearable eye-tracking glasses. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing (UbiComp ’12). Association for Computing Machinery, New York, NY, USA, 699–704. https://doi.org/10.1145/2370216.2370368

Zurovac, D., Sudoi, R. K., Akhwale, W. S., Ndiritu, M., Hamer, D. H., Rowe, A. K., & Snow, R. W. (2011). The effect of mobile phone text-message reminders on Kenyan health workers’ adherence to malaria treatment guidelines: A cluster randomised trial. Lancet, 378(9793), 795–803. https://doi.org/10.1016/S0140-6736(11)60783-6CrossRefPubMedPubMedCentral

Zurovac, D., Talisuna, A. O., & Snow, R. W. (2012). Mobile phone text messaging: tool for malaria control in Africa. PLoS Medicine. https://doi.org/10.1371/journal.pmed.1001176CrossRefPubMedPubMedCentral

Titel: The Digital Divide in Technologies for Autism: Feasibility Considerations for Low- and Middle-Income Countries
Auteurs: Aubrey J. Kumm
Marisa Viljoen
Petrus J. de Vries
Publicatiedatum: 13-06-2021
Uitgeverij: Springer US
Gepubliceerd in: Journal of Autism and Developmental Disorders / Uitgave 5/2022
Print ISSN: 0162-3257
Elektronisch ISSN: 1573-3432
DOI: https://doi.org/10.1007/s10803-021-05084-8

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