skip to main content
research-article
Free Access
Just Accepted

Adult Autism Research Priorities and Conceptualization in Computing Research: Invitation to Co-Lead with Autistic Adults

Authors Info & Claims
Online AM:24 January 2024Publication History
Skip Abstract Section

Abstract

Autism research is primarily targeted toward children and at normalizing autistic traits. We conducted a literature review of computing research on adult autism, focusing on identifying research priorities set by autistic adults and their allies, determining participation levels, identifying how autism is conceptualized, and the types of technologies designed and their purposes. We found: 1) that computing research in adult autism is neither representative of older and non-binary adults nor of autistic adults living outside the USA and Europe; 2) a lack of technologies geared towards the priorities set by autistic adults and their allies, and 3) that computing research primarily views adult autism as a medical deficit and builds design solutions and technologies that follow this marginalizing narrative. We discuss the status quo and provide recommendations for computing researchers to encourage research built on user needs and respectful of autistic adults.

References

  1. Bury, S.M., R. Jellett, J.R. Spoor, and D. Hedley, “It Defines Who I Am” or “It's Something I Have”: What Language Do [Autistic] Australian Adults [on the Autism Spectrum] Prefer? Journal of Autism and Developmental Disorders, 2020.Google ScholarGoogle Scholar
  2. Gernsbacher, M.A., Editorial Perspective: The use of person-first language in scholarly writing may accentuate stigma. Journal of Child Psychology and Psychiatry, 2017. 58(7): p. 859-861.Google ScholarGoogle Scholar
  3. Kenny, L., et al., Which terms should be used to describe autism? Perspectives from the UK autism community. Autism, 2016. 20(4): p. 442-462.Google ScholarGoogle Scholar
  4. The Parliamntary Office of Science and Technology UK, Autism, in POSTNOTE, M. Laurie and P. Border, Editors. 2020, UK Parliament.Google ScholarGoogle Scholar
  5. Durkin, M.S., et al., Autism screening and diagnosis in low resource settings: Challenges and opportunities to enhance research and services worldwide. Autism Research, 2015. 8(5): p. 473-476.Google ScholarGoogle Scholar
  6. Laurie, M.H., A. Manches, and S. Fletcher-Watson, Design implications from Cognitive Event Analysis: A case study of digitally mediated interaction in autistic children, in International Conference on Interaction Design and Children. 2019, Association for Computing Machinery: Boise, ID, USA. p. 476–481.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Spiel, K., C. Frauenberger, O. Keyes, and G. Fitzpatrick, Agency of Autistic Children in Technology Research—A Critical Literature Review. ACM Transactions of Computer-Human Interacttion, 2019. 26(6): p. Article 38.Google ScholarGoogle Scholar
  8. Williams, R.M., Metaeugenics and Metaresistance: From Manufacturing the ‘Includeable Body’ to Walking Away from the Broom Closet. The Canadian Journal of Children's Rights, 2019. 6(1).Google ScholarGoogle Scholar
  9. Frymiare, J., M. Gernsbacher, and B. Harp, Infantilizing Autism. Disability Studies Quarterly, 2011. 31: p. 17.Google ScholarGoogle Scholar
  10. Akhtar, N., J. Dinishak, and J.L. Frymiare, Still Infantilizing Autism? An Update and Extension of Stevenson et al. (2011). Autism in Adulthood, 2022. 4(3): p. 224-232.Google ScholarGoogle Scholar
  11. Williams, R.M. and J.E. Gilbert, Perseverations of the academy: A survey of wearable technologies applied to autism intervention. International Journal of Human-Computer Studies, 2020. 143: p. 102485.Google ScholarGoogle ScholarCross RefCross Ref
  12. Singhal, N., et al., An Expert Discussion on Autism in Adulthood in Low- and Middle-Income Countries. Autism in Adulthood, 2019. 1(4): p. 241-247.Google ScholarGoogle Scholar
  13. Warner, G., J.R. Parr, and J. Cusack, Workshop Report: Establishing Priority Research Areas to Improve the Physical Health and Well-Being of Autistic Adults and Older People. Autism in Adulthood, 2018. 1(1): p. 20-26.Google ScholarGoogle Scholar
  14. Campbell, F.K., Precision ableism: a studies in ableism approach to developing histories of disability and abledment. Rethinking History, 2019. 23(2): p. 138-156.Google ScholarGoogle Scholar
  15. Milton, D.E.M., On the ontological status of autism: the ‘double empathy problem’. Disability & Society, 2012. 27(6): p. 883-887.Google ScholarGoogle Scholar
  16. Spiel, K. and K. Gerling, The Purpose of Play: How HCI Games Research Fails Neurodivergent Populations. ACM Trans. Comput.-Hum. Interact., 2021. 28(2): p. Article 11.Google ScholarGoogle Scholar
  17. Farahar, C. UPDATE: Detailed what IS autism? 2022 [cited 2022 23 May]; Available from: https://soyoureautistic.com/update-detailed-what-is-autism/.Google ScholarGoogle Scholar
  18. Botha, M. Dr Monique Botha. 2022 [cited 2022 23 May]; Available from: https://www.moniquebotha.com/.Google ScholarGoogle Scholar
  19. Williams, R. Rua M. Williams. 2022 [cited 2022 23 May]; Available from: http://www.ruamae.com/.Google ScholarGoogle Scholar
  20. Keyes, O., Automating autism: Disability, discourse, and artificial intelligence. The Journal of Sociotechnical Critique, 2020. 1(1): p. 8.Google ScholarGoogle Scholar
  21. Çorlu, D., et al., Involving Autistics in User Experience Studies: A Critical Review, in Conference on Designing Interactive Systems. 2017, Association for Computing Machinery: Edinburgh, United Kingdom. p. 43–55.Google ScholarGoogle Scholar
  22. Linxen, S., et al., How WEIRD is CHI?, in Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 2021, Association for Computing Machinery. p. Article 143.Google ScholarGoogle Scholar
  23. Spiel, K., et al., Nothing About Us Without Us: Investigating the Role of Critical Disability Studies in HCI, in Conference on Human Factors in Computing Systems. 2020, Association for Computing Machinery: Honolulu, HI, USA. p. 1–8.Google ScholarGoogle Scholar
  24. Williams, R. and J. Gilbert, “Nothing About Us Without Us” Transforming Participatory Research and Ethics in Human Systems Engineering. 2019. p. 113-134.Google ScholarGoogle Scholar
  25. World Health Organization. Disability and health. Fact sheets 2021 [cited 2022 13 September]; Available from: https://www.who.int/news-room/fact-sheets/detail/disability-and-health.Google ScholarGoogle Scholar
  26. Global coalition. #WeThe15. 2021 [cited 2021 7 October]; Available from: https://www.wethe15.org/.Google ScholarGoogle Scholar
  27. Fletcher-Watson, S. and F. Happéh, Autism: A new introduction to psychological theory and current debate. 2019: Routledge.Google ScholarGoogle Scholar
  28. Czech, H., Hans Asperger, National Socialism, and “race hygiene” in Nazi-era Vienna. Molecular Autism, 2018. 9(1): p. 29.Google ScholarGoogle Scholar
  29. Lord, C., et al., Austism diagnostic observation schedule: A standardized observation of communicative and social behavior. Journal of Autism and Developmental Disorders, 1989. 19(2): p. 185-212.Google ScholarGoogle Scholar
  30. Lord, C., R. Luyster, K. Gotham, and W. Guthrie, ADOS-2. Autism Diagnostic Observation Schedule. 2nd ed. 2012, Torrance, CA: Western Psychological Services.Google ScholarGoogle Scholar
  31. Mitra, S. and T. Shakespeare, Remodeling the ICF. Disability and Health Journal, 2019. 12(3): p. 337-339.Google ScholarGoogle Scholar
  32. United Nations. Convention on the Rights of Persons with Disabilities. 2006 3 May 2008 [cited 2022 13 September]; Available from: https://www.ohchr.org/en/instruments-mechanisms/instruments/convention-rights-persons-disabilities.Google ScholarGoogle Scholar
  33. Singer, J., NeuroDiversity The birth of an idea. 2017: Kindle.Google ScholarGoogle Scholar
  34. Singer, J., Reflections on Neurodiversity, in What is ND? 2022, Blogger.Google ScholarGoogle Scholar
  35. Bottema-Beutel, K., et al., Avoiding Ableist Language: Suggestions for Autism Researchers. Autism in Adulthood, 2020.Google ScholarGoogle Scholar
  36. Ballou, E.P., What the Neurodiversity Movement Does—And Doesn't—Offer, in THINKING PERSON'S GUIDE TO AUTISM. 2018, Blogger.Google ScholarGoogle Scholar
  37. Taylor, H., B. Fernandes, and S. Wraight, The Evolution of Complementary Cognition: Humans Cooperatively Adapt and Evolve through a System of Collective Cognitive Search. Cambridge Archaeological Journal, 2021: p. 1-17.Google ScholarGoogle Scholar
  38. Taylor, H. and M.D. Vestergaard, Developmental dyslexia: neurodevelopmental disorder or specialisation in Exploration? Frontiers in Psychology, 2022. 13(889245): p. 1-19.Google ScholarGoogle Scholar
  39. Hearst, C. Constellation model. 2006 [cited 2022 23 May]; Available from: https://www.autangel.org.uk/resources/#constellationmodel.Google ScholarGoogle Scholar
  40. Cuve, H.C., et al., Are Autistic and Alexithymic Traits Distinct? A Factor-Analytic and Network Approach. Journal of Autism and Developmental Disorders, 2022. 52(5): p. 2019-2034.Google ScholarGoogle Scholar
  41. Crane, L., L. Goddard, and L. Pring, Sensory processing in adults with autism spectrum disorders. Autism, 2009. 13(3): p. 215-228.Google ScholarGoogle Scholar
  42. MacLennan, K., S. O'Brien, and T. Tavassoli, In Our Own Words: The Complex Sensory Experiences of Autistic Adults. Journal of Autism and Developmental Disorders, 2022. 52(7): p. 3061-3075.Google ScholarGoogle Scholar
  43. Robertson, A.E. and R.S.R. David, The sensory experiences of adults with autism spectrum disorder: A qualitative analysis. Perception, 2015. 44(5): p. 569-86.Google ScholarGoogle Scholar
  44. Cope, R. and A. Remington, The Strengths and Abilities of Autistic People in the Workplace. Autism in Adulthood, 2022. 4(1): p. 22-31.Google ScholarGoogle Scholar
  45. Russell, G., et al., Mapping the Autistic Advantage from the Accounts of Adults Diagnosed with Autism: A Qualitative Study. Autism in Adulthood, 2019. 1(2): p. 124-133.Google ScholarGoogle Scholar
  46. Bonnel, A., et al., Enhanced Pitch Sensitivity in Individuals with Autism: A Signal Detection Analysis. J. Cognitive Neuroscience, 2003. 15(2): p. 226–235.Google ScholarGoogle Scholar
  47. Remington, A. and J. Fairnie, A sound advantage: Increased auditory capacity in autism. Cognition, 2017. 166: p. 459-465.Google ScholarGoogle Scholar
  48. Kirchner, J., W. Ruch, and I. Dziobek, Brief Report: Character Strengths in Adults with Autism Spectrum Disorder Without Intellectual Impairment. Journal of Autism and Developmental Disorders, 2016. 46(10): p. 3330-3337.Google ScholarGoogle Scholar
  49. Crompton, C.J., et al., Autistic peer-to-peer information transfer is highly effective. Autism, 2020. 24(7): p. 1704-1712.Google ScholarGoogle Scholar
  50. Robinson, A., I. Galbraith, and L. Carrick, Practitioner experience of the impact of humanistic methods on autism practice: a preliminary study. Advances in Autism, 2021. 7(2): p. 114-128.Google ScholarGoogle Scholar
  51. Hollomotz, A., Disability, Oppression and Violence: Towards a Sociological Explanation. Sociology, 2012. 47(3): p. 477-493.Google ScholarGoogle Scholar
  52. Kirby, A.V. and K.E. McDonald, The State of the Science on Autism in Adulthood: Building an Evidence Base for Change. Autism in Adulthood, 2021. 3(1): p. 2-4.Google ScholarGoogle Scholar
  53. Geurts, H.M., et al., Ageing and heterogeneity regarding autism spectrum conditions: A protocol paper of an accelerated longitudinal study. BMJ Open, 2021. 11(3).Google ScholarGoogle ScholarCross RefCross Ref
  54. Howlin, P. and I. Magiati, Autism spectrum disorder: outcomes in adulthood. Current Opinion in Psychiatry, 2017. 30(2): p. 69-76.Google ScholarGoogle Scholar
  55. Bennett, M. and E. Goodall, Exploring the Needs of Autistic Seniors, in Addressing Underserved Populations in Autism Spectrum Research. 2022, Emerald Publishing Limited: Bingley, UK. p. 11-25.Google ScholarGoogle ScholarCross RefCross Ref
  56. den Houting, J. and E. Pellicano, A Portfolio Analysis of Autism Research Funding in Australia, 2008–2017. Journal of Autism and Developmental Disorders, 2019. 49(11): p. 4400-4408.Google ScholarGoogle Scholar
  57. Hoekstra, R.A., F. Girma, B. Tekola, and Z. Yenus, Nothing about us without us: the importance of local collaboration and engagement in the global study of autism. BJPsych International, 2018. 15(2): p. 40-43.Google ScholarGoogle Scholar
  58. Jones, D.R., et al., An Expert Discussion on Structural Racism in Autism Research and Practice. Autism in Adulthood, 2020. 2(4): p. 273-281.Google ScholarGoogle Scholar
  59. Bennett, M. and E. Goodall, Researching African American Autistics, in Addressing Underserved Populations in Autism Spectrum Research. 2022, Emerald Publishing Limited: Bingley, UK. p. 75-97.Google ScholarGoogle ScholarCross RefCross Ref
  60. Ames, J.L., et al., Racial/Ethnic Differences in Psychiatric and Medical Diagnoses Among Autistic Adults. Autism in Adulthood, 2022.Google ScholarGoogle Scholar
  61. Giwa Onaiwu, M., “They Don't Know, Don't Show, or Don't Care”: Autism's White Privilege Problem. Autism in Adulthood, 2020. 2(4): p. 270-272.Google ScholarGoogle Scholar
  62. Huang, Y., S.R.C. Arnold, K.-R. Foley, and J.N. Trollor, Diagnosis of autism in adulthood: A scoping review. Autism, 2020. 24(6): p. 1311-1327.Google ScholarGoogle Scholar
  63. Murphy, S., R.L. Flower, and R. Jellett, Women seeking an autism diagnosis in Australia: A qualitative exploration of factors that help and hinder. Autism, 2022.Google ScholarGoogle Scholar
  64. Harmens, M., F. Sedgewick, and H. Hobson, The Quest for Acceptance: A Blog-Based Study of Autistic Women's Experiences and Well-Being during Autism Identification and Diagnosis. Autism in Adulthood, 2022. 4(1): p. 42-51.Google ScholarGoogle Scholar
  65. Davis, A., M. Solomon, and H. Belcher, Examination of Race and Autism Intersectionality Among African American/Black Young Adults. Autism in Adulthood, 2022.Google ScholarGoogle Scholar
  66. McDonald, T.A.M., Autism Identity and the “Lost Generation”: Structural Validation of the Autism Spectrum Identity Scale and Comparison of Diagnosed and Self-Diagnosed Adults on the Autism Spectrum. Autism in Adulthood, 2020. 2(1): p. 13-23.Google ScholarGoogle Scholar
  67. Cage, E. and Z. Troxell-Whitman, Understanding the Relationships Between Autistic Identity, Disclosure, and Camouflaging. Autism in Adulthood, 2020. 2(4): p. 334-338.Google ScholarGoogle Scholar
  68. Leedham, A., A.R. Thompson, R. Smith, and M. Freeth, ‘I was exhausted trying to figure it out’: The experiences of females receiving an autism diagnosis in middle to late adulthood. Autism, 2020. 24(1): p. 135-146.Google ScholarGoogle Scholar
  69. Lilley, R., et al., ‘A way to be me’: Autobiographical reflections of autistic adults diagnosed in mid-to-late adulthood. Autism, 2022. 26(6): p. 1395-1408.Google ScholarGoogle Scholar
  70. De Broize, M., et al., Exploring the Experience of Seeking an Autism Diagnosis as an Adult. Autism in Adulthood, 2022. 4(2): p. 130-140.Google ScholarGoogle Scholar
  71. Evans, K., et al., A Survey of Autistic Adults from New Zealand on the Autism Diagnostic Process During Adolescence and Adulthood. Journal of Autism and Developmental Disorders, 2022. 52(2): p. 771-781.Google ScholarGoogle Scholar
  72. Wigham, S., et al., Consensus statements on optimal adult post-autism diagnosis support and services: Delphi process following a UK survey of autistic adults, relatives and clinicians. Autism. 0(0): p. 13623613221097502.Google ScholarGoogle Scholar
  73. Kapp, S.K., K. Gillespie-Lynch, L.E. Sherman, and T. Hutman, Deficit, difference, or both? Autism and neurodiversity. Developmental Psychology, 2013. 49(1): p. 59-71.Google ScholarGoogle Scholar
  74. Botha, M., B. Dibb, and D.M. Frost, "Autism is me": an investigation of how autistic individuals make sense of autism and stigma. Disability & Society, 2022. 37(3): p. 427-453.Google ScholarGoogle ScholarCross RefCross Ref
  75. Flett, G.L., et al., The destructiveness and public health significance of socially prescribed perfectionism: A review, analysis, and conceptual extension. Clinical Psychology Review, 2022. 93: p. 102130.Google ScholarGoogle Scholar
  76. Gibbs, V., J. Hudson, and E. Pellicano, The Extent and Nature of Autistic People's Violence Experiences During Adulthood: A Cross-sectional Study of Victimisation. Journal of Autism and Developmental Disorders, 2022.Google ScholarGoogle Scholar
  77. Perry, E., W. Mandy, L. Hull, and E. Cage, Understanding Camouflaging as a Response to Autism-Related Stigma: A Social Identity Theory Approach. Journal of Autism and Developmental Disorders, 2021.Google ScholarGoogle Scholar
  78. Tang, L. and B. Bie, The stigma of autism in china: an analysis of newspaper portrayals of autism between 2003 and 2012. Health Communication, 2016. 31(4): p. 445-452.Google ScholarGoogle Scholar
  79. Someki, F., et al., Stigma associated with autism among college students in Japan and the United States: An online training study. Research in Developmental Disabilities, 2018. 76: p. 88-98.Google ScholarGoogle Scholar
  80. Han, E., K. Scior, K. Avramides, and L. Crane, A systematic review on autistic people's experiences of stigma and coping strategies. Autism Research, 2022. 15(1): p. 12-26.Google ScholarGoogle Scholar
  81. Pearson, A., K. Rose, and J. Rees, ‘I felt like I deserved it because I was autistic’: Understanding the impact of interpersonal victimisation in the lives of autistic people. Autism, 2022.Google ScholarGoogle Scholar
  82. Trundle, G., K.A. Jones, D. Ropar, and V. Egan, Prevalence of Victimisation in Autistic Individuals: A Systematic Review and Meta-Analysis. Trauma, Violence, and Abuse, 2022.Google ScholarGoogle Scholar
  83. Raymaker, D.M., et al., “Having All of Your Internal Resources Exhausted Beyond Measure and Being Left with No Clean-Up Crew”: Defining Autistic Burnout. Autism in Adulthood, 2020. 2(2): p. 132-143.Google ScholarGoogle Scholar
  84. Crane, L., et al., ‘Something needs to change’: Mental health experiences of young autistic adults in England. Autism, 2019. 23(2): p. 477-493.Google ScholarGoogle Scholar
  85. Zheng, S., et al., Depression in independent young adults on the autism spectrum: Demographic characteristics, service use, and barriers. Autism, 2021: p. 13623613211008276.Google ScholarGoogle Scholar
  86. Hossain, M.M., et al., Prevalence of comorbid psychiatric disorders among people with autism spectrum disorder: An umbrella review of systematic reviews and meta-analyses. Psychiatry Research, 2020. 287: p. 112922.Google ScholarGoogle ScholarCross RefCross Ref
  87. Smith DaWalt, L., J. Hong, J.S. Greenberg, and M.R. Mailick, Mortality in individuals with autism spectrum disorder: Predictors over a 20-year period. Autism: the international journal of research and practice, 2019. 23(7): p. 1732-1739.Google ScholarGoogle Scholar
  88. Cai, R.Y., et al., “Self-compassion changed my life”: The self-compassion experiences of autistic and non-autistic adults and its relationship with mental health and psychological wellbeing. Journal of Autism and Developmental Disorders, 2022.Google ScholarGoogle Scholar
  89. Chaplin, E., et al., Self-harm and Mental Health Characteristics of Prisoners with elevated rates of autistic traits. Research in Developmental Disabilities, 2021. 114: p. 103987.Google ScholarGoogle Scholar
  90. Cassidy, S. and J. Rodgers, Understanding and prevention of suicide in autism. The Lancet Psychiatry, 2017. 4(6): p. e11.Google ScholarGoogle ScholarCross RefCross Ref
  91. Hedley, D. and M. Uljarević, Systematic Review of Suicide in Autism Spectrum Disorder: Current Trends and Implications. Current Developmental Disorders Reports, 2018. 5(1): p. 65-76.Google ScholarGoogle Scholar
  92. Lever, A.G. and H.M. Geurts, Psychiatric Co-occurring Symptoms and Disorders in Young, Middle-Aged, and Older Adults with Autism Spectrum Disorder. Journal of Autism and Developmental Disorders, 2016. 46(6): p. 1916-1930.Google ScholarGoogle Scholar
  93. Brede, J., et al., “We Have to Try to Find a Way, a Clinical Bridge” - autistic adults' experience of accessing and receiving support for mental health difficulties: A systematic review and thematic meta-synthesis. Clinical Psychology Review, 2022. 93: p. 102131.Google ScholarGoogle Scholar
  94. Strömberg, M., L. Liman, P. Bang, and K. Igelström, Experiences of Sensory Overload and Communication Barriers by Autistic Adults in Health Care Settings. Autism in Adulthood, 2021. 4(1): p. 66-75.Google ScholarGoogle Scholar
  95. Belcher, H.L., On Being Autistic and in Mental Health Crisis Care. Autism in Adulthood, 2022. 4(3): p. 179-182.Google ScholarGoogle Scholar
  96. Camm-Crosbie, L., et al., ‘People like me don't get support’: Autistic adults’ experiences of support and treatment for mental health difficulties, self-injury and suicidality. Autism, 2018. 23(6): p. 1431-1441.Google ScholarGoogle Scholar
  97. Lipinski, S., et al., A blind spot in mental healthcare? Psychotherapists lack education and expertise for the support of adults on the autism spectrum. Autism, 2022. 26(6): p. 1509-1521.Google ScholarGoogle Scholar
  98. Adams, D. and K. Young, A Systematic Review of the Perceived Barriers and Facilitators to Accessing Psychological Treatment for Mental Health Problems in Individuals on the Autism Spectrum. Review Journal of Autism and Developmental Disorders, 2021. 8(4): p. 436-453.Google ScholarGoogle Scholar
  99. Baron-Cohen, S., Chapter 11 - Empathizing, systemizing, and the extreme male brain theory of autism, in Progress in Brain Research, I. Savic, Editor. 2010, Elsevier. p. 167-175.Google ScholarGoogle Scholar
  100. Haney, J.L., Autism, females, and the DSM-5: Gender bias in autism diagnosis. Social Work in Mental Health, 2016. 14(4): p. 396-407.Google ScholarGoogle Scholar
  101. Adamou, M., M. Johnson, and B. Alty, Autism Diagnostic Observation Schedule (ADOS) scores in males and females diagnosed with autism: a naturalistic study. Advances in Autism, 2018. 4(2): p. 49-55.Google ScholarGoogle Scholar
  102. Hillier, A., et al., LGBTQ + and autism spectrum disorder: Experiences and challenges. International Journal of Transgender Health, 2020. 21(1): p. 98-110.Google ScholarGoogle ScholarCross RefCross Ref
  103. Kourti, M. and A. MacLeod, “I Don't Feel Like a Gender, I Feel Like Myself”: Autistic Individuals Raised as Girls Exploring Gender Identity. Autism in Adulthood, 2019. 1(1): p. 52-59.Google ScholarGoogle Scholar
  104. Cooper, K., W. Mandy, C. Butler, and A. Russell, The lived experience of gender dysphoria in autistic adults: An interpretative phenomenological analysis. Autism, 2022. 26(4): p. 963-974.Google ScholarGoogle Scholar
  105. Steinberg, H., T. Garfield, A. Becker, and L. Shea, What Category Best Fits: Understanding Transgender Identity in a Survey of Autistic Individuals. Autism in Adulthood, 2022.Google ScholarGoogle Scholar
  106. Pecora, L.A., et al., Gender identity, sexual orientation and adverse sexual experiences in autistic females. Molecular Autism, 2020. 11(1).Google ScholarGoogle Scholar
  107. McAuliffe, C., R.J. Walsh, and E. Cage, “My whole life has been a process of finding labels that fit”: A Thematic Analysis of Autistic LGBTQIA+ Identity and Inclusion in the LGBTQIA+ Community. Autism in Adulthood, 2022.Google ScholarGoogle Scholar
  108. Gibbs, V., et al., Experiences of physical and sexual violence as reported by autistic adults without intellectual disability: Rate, gender patterns and clinical correlates. Research in Autism Spectrum Disorders, 2021. 89.Google ScholarGoogle ScholarCross RefCross Ref
  109. Dike, J.E., et al., A Systematic Review of Sexual Violence Among Autistic Individuals. Review Journal of Autism and Developmental Disorders, 2022.Google ScholarGoogle Scholar
  110. Murphy, J., et al., Autism and transgender identity: Implications for depression and anxiety. Research in Autism Spectrum Disorders, 2020. 69.Google ScholarGoogle ScholarCross RefCross Ref
  111. Barrington, D.J., H.J. Robinson, E. Wilson, and J. Hennegan, Experiences of menstruation in high income countries: A systematic review, qualitative evidence synthesis and comparison to low- and middle-income countries. PLOS ONE, 2021. 16(7): p. e0255001.Google ScholarGoogle ScholarCross RefCross Ref
  112. Hennegan, J., et al., Women's and girls’ experiences of menstruation in low- and middle-income countries: A systematic review and qualitative metasynthesis. PLOS Medicine, 2019. 16(5): p. e1002803.Google ScholarGoogle Scholar
  113. Moseley, R.L., T. Druce, and J.M. Turner-Cobb, ‘When my autism broke’: A qualitative study spotlighting autistic voices on menopause. Autism, 2020. 24(6): p. 1423-1437.Google ScholarGoogle Scholar
  114. Groenman, A.P., et al., Menstruation and menopause in autistic adults: Periods of importance? Autism, 2022. 26(6): p. 1563-1572.Google ScholarGoogle Scholar
  115. Karavidas, M. and R.O. de Visser, “It's Not Just in My Head, and It's Not Just Irrelevant”: Autistic Negotiations of Menopausal Transitions. Journal of Autism and Developmental Disorders, 2022. 52(3): p. 1143-1155.Google ScholarGoogle Scholar
  116. Samuel, P., et al., Sensory challenges experienced by autistic women during pregnancy and childbirth: a systematic review. Archives of Gynecology and Obstetrics, 2022. 305(2): p. 299-311.Google ScholarGoogle Scholar
  117. Steward, R., et al., “Life is Much More Difficult to Manage During Periods”: Autistic Experiences of Menstruation. Journal of Autism and Developmental Disorders, 2018. 48(12): p. 4287-4292.Google ScholarGoogle Scholar
  118. Sonido, M., S. Arnold, J. Higgins, and Y.I.J. Hwang, Autism in Later Life: What Is Known and What Is Needed? Current Developmental Disorders Reports, 2020. 7(2): p. 69-77.Google ScholarGoogle Scholar
  119. Mason, D., G.R. Stewart, S.J. Capp, and F. Happé, Older Age Autism Research: A Rapidly Growing Field, but Still a Long Way to Go. Autism in Adulthood, 2022. 4(2): p. 164-172.Google ScholarGoogle Scholar
  120. Edelson, S.M., et al., Strategies for Research, Practice, and Policy for Autism in Later Life: A Report from a Think Tank on Aging and Autism. Journal of Autism and Developmental Disorders, 2021. 51(1): p. 382-390.Google ScholarGoogle Scholar
  121. Miller, D., J. Rees, and A. Pearson, “Masking Is Life”: Experiences of Masking in Autistic and Nonautistic Adults. Autism in Adulthood, 2021. 3(4): p. 330-338.Google ScholarGoogle Scholar
  122. Pearson, A. and K. Rose, A Conceptual Analysis of Autistic Masking: Understanding the Narrative of Stigma and the Illusion of Choice. Autism in Adulthood, 2021. 3(1): p. 52-60.Google ScholarGoogle Scholar
  123. Mantzalas, J., et al., What Is Autistic Burnout? A Thematic Analysis of Posts on Two Online Platforms. Autism in Adulthood, 2021. 4(1): p. 52-65.Google ScholarGoogle Scholar
  124. Hayward, S.M., K.R. McVilly, and M.A. Stokes, “I Would Love to Just Be Myself”: What Autistic Women Want at Work. Autism in Adulthood, 2019. 1(4): p. 297-305.Google ScholarGoogle Scholar
  125. Nicholas, D.B., et al., An Expert Discussion on Employment in Autism. Autism in Adulthood, 2019. 1(3): p. 162-169.Google ScholarGoogle Scholar
  126. Ee, D., et al., Loneliness in Adults on the Autism Spectrum. Autism in Adulthood, 2019. 1(3): p. 182-193.Google ScholarGoogle Scholar
  127. Stewart, G.R., et al., Self-harm and Suicidality Experiences of Middle-Age and Older Adults With vs. Without High Autistic Traits. Journal of Autism and Developmental Disorders, 2022.Google ScholarGoogle Scholar
  128. Brosnan, M. and S. Adams, The Expectancies and Motivations for Heavy Episodic Drinking of Alcohol in Autistic Adults. Autism in Adulthood, 2020. 2(4): p. 317-324.Google ScholarGoogle Scholar
  129. Brosnan, M. and S. Adams, Adapting Drug and Alcohol Therapies for Autistic Adults. Autism in Adulthood, 2022. 4(3): p. 214-223.Google ScholarGoogle Scholar
  130. Adams, D., M. Stainsby, and J. Paynter, Autistic Mothers of Autistic Children: A Preliminary Study in an Under-Researched Area. Autism in Adulthood, 2021. 3(4): p. 339-346.Google ScholarGoogle Scholar
  131. McDonnell, C.G. and E.A. DeLucia, Pregnancy and Parenthood Among Autistic Adults: Implications for Advancing Maternal Health and Parental Well-Being. Autism in Adulthood, 2021. 3(1): p. 100-115.Google ScholarGoogle Scholar
  132. Geurts, H.M., R. Charlton, and L. Bishop, Ageing when Being Autistic, in Handbook on Ageing with Disability. 2021. p. 148-157.Google ScholarGoogle Scholar
  133. Crompton, C.J., C. Michael, M. Dawson, and S. Fletcher-Watson, Residential Care for Older Autistic Adults: Insights from Three Multiexpert Summits. Autism in Adulthood, 2020. 2(2): p. 121-127.Google ScholarGoogle Scholar
  134. Desideri, L., et al., Assistive Technology for Cognition to Support Executive Functions in Autism: a Scoping Review. Advances in Neurodevelopmental Disorders, 2020. 4(4): p. 330-343.Google ScholarGoogle Scholar
  135. Pennington, R.C., Computer-Assisted Instruction for Teaching Academic Skills to Students With Autism Spectrum Disorders: A Review of Literature. Focus on Autism and Other Developmental Disabilities, 2010. 25(4): p. 239-248.Google ScholarGoogle Scholar
  136. Wainer, A.L. and B.R. Ingersoll, The use of innovative computer technology for teaching social communication to individuals with autism spectrum disorders. Research in Autism Spectrum Disorders, 2011. 5(1): p. 96-107.Google ScholarGoogle Scholar
  137. Wilkenfeld, D.A. and A.M. McCarthy, Ethical Concerns with Applied Behavior Analysis for Autism Spectrum “Disorder”. Kennedy Institute of Ethics Journal, 2020. 30(1).Google ScholarGoogle Scholar
  138. Lo, J. Why A European Autism Research Program Has Sparked Fears Of Eugenics. 2018 6 December 2018 [cited 2021 6 August]; Available from: https://theestablishment.co/why-a-european-autism-research-program-has-sparked-fears-of-eugenics/index.html.Google ScholarGoogle Scholar
  139. Sandoval-Norton, A.H., G. Shkedy, and D. Shkedy, Long-term ABA Therapy Is Abusive: A Response to Gorycki, Ruppel, and Zane. Advances in Neurodevelopmental Disorders, 2021. 5(2): p. 126-134.Google ScholarGoogle Scholar
  140. Leaf, J.B., et al., Concerns About ABA-Based Intervention: An Evaluation and Recommendations. Journal of Autism and Developmental Disorders, 2022. 52(6): p. 2838-2853.Google ScholarGoogle Scholar
  141. Begum, M., R.W. Serna, and H.A. Yanco, Are Robots Ready to Deliver Autism Interventions? A Comprehensive Review. International Journal of Social Robotics, 2016. 8(2): p. 157-181.Google ScholarGoogle Scholar
  142. Boisvert, M., R. Lang, M. Andrianopoulos, and M.L. Boscardin, Telepractice in the assessment and treatment of individuals with autism spectrum disorders: A systematic review. Developmental Neurorehabilitation, 2010. 13(6): p. 423-432.Google ScholarGoogle Scholar
  143. Chia, G.L.C., A. Anderson, and L.A. McLean, Use of Technology to Support Self-Management in Individuals with Autism: Systematic Review. Review Journal of Autism and Developmental Disorders, 2018. 5(2): p. 142-155.Google ScholarGoogle Scholar
  144. Ferguson, J., E.A. Craig, and K. Dounavi, Telehealth as a Model for Providing Behaviour Analytic Interventions to Individuals with Autism Spectrum Disorder: A Systematic Review. Journal of Autism and Developmental Disorders, 2019. 49(2): p. 582-616.Google ScholarGoogle Scholar
  145. Fletcher-Watson, S., A Targeted Review of Computer-Assisted Learning for People with Autism Spectrum Disorder: Towards a Consistent Methodology. Review Journal of Autism and Developmental Disorders, 2014. 1(2): p. 87-100.Google ScholarGoogle Scholar
  146. Sutherland, R., D. Trembath, and J. Roberts, Telehealth and autism: A systematic search and review of the literature. International Journal of Speech-Language Pathology, 2018. 20(3): p. 324-336.Google ScholarGoogle Scholar
  147. Valencia, K., C. Rusu, D. Quiñones, and E. Jamet, The Impact of Technology on People with Autism Spectrum Disorder: A Systematic Literature Review. Sensors (Basel, Switzerland), 2019. 19(20): p. 4485.Google ScholarGoogle ScholarCross RefCross Ref
  148. Walsh, E., J. Holloway, A. McCoy, and H. Lydon, Technology-Aided Interventions for Employment Skills in Adults with Autism Spectrum Disorder: A Systematic Review. Review Journal of Autism and Developmental Disorders, 2017. 4(1): p. 12-25.Google ScholarGoogle Scholar
  149. Chen, W., Multitouch Tabletop Technology for People with Autism Spectrum Disorder: A Review of the Literature. Procedia Computer Science, 2012. 14: p. 198-207.Google ScholarGoogle Scholar
  150. McGhee Hassrick, E., et al., Benefits and Risks: A Systematic Review of Information and Communication Technology Use by Autistic People. Autism in Adulthood, 2021. 3(1): p. 72-84.Google ScholarGoogle Scholar
  151. Michael, C., Is Being Othered a Co-Occurring Condition of Autism? Autism in Adulthood, 2021. 3(2): p. 118-119.Google ScholarGoogle Scholar
  152. Page, M.J., et al., The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 2021. 372: p. n71.Google ScholarGoogle Scholar
  153. Ouzzani, M., H. Hammady, Z. Fedorowicz, and A. Elmagarmid, Rayyan—a web and mobile app for systematic reviews. Systematic Reviews, 2016. 5(1): p. 210.Google ScholarGoogle Scholar
  154. World Health Organization. Adolescent health. 2022 [cited 2022 22 December]; Available from: https://www.who.int/health-topics/adolescent-health#tab=tab_1.Google ScholarGoogle Scholar
  155. Arnstein, S.R., A Ladder Of Citizen Participation. Journal of the American Institute of Planners, 1969. 35(4): p. 216-224.Google ScholarGoogle Scholar
  156. Roche, L., D. Adams, and M. Clark, Research priorities of the autism community: A systematic review of key stakeholder perspectives. Autism, 2021. 25(2): p. 336-348.Google ScholarGoogle Scholar
  157. Elo, S. and H. Kyngäs, The qualitative content analysis process. J Adv Nurs, 2008. 62(1): p. 107-15.Google ScholarGoogle Scholar
  158. Banskota, A. and Y.-K. Ng, Recommending Video Games to Adults with Autism Spectrum Disorder for Social-Skill Enhancement, in Conference on User Modeling, Adaptation and Personalization. 2020, Association for Computing Machinery: Genoa, Italy. p. 14–22.Google ScholarGoogle Scholar
  159. Begel, A., et al., How a Remote Video Game Coding Camp Improved Autistic College Students' Self-Efficacy in Communication. Sigcse '21, 2021: p. 142–148.Google ScholarGoogle Scholar
  160. Boyd, L.E., et al., SayWAT: Augmenting Face-to-Face Conversations for Adults with Autism, in Conference on Human Factors in Computing Systems. 2016, Association for Computing Machinery: San Jose, California, USA. p. 4872–4883.Google ScholarGoogle Scholar
  161. Bozgeyikli, L., et al., Vocational Rehabilitation of Individuals with Autism Spectrum Disorder with Virtual Reality. ACM Trans. Access. Comput., 2017. 10(2): p. Article 5.Google ScholarGoogle Scholar
  162. Burke, M., R. Kraut, and D. Williams, Social use of computer-mediated communication by adults on the autism spectrum, in Conference on Computer supported cooperative work. 2010, Association for Computing Machinery: Savannah, Georgia, USA. p. 425–434.Google ScholarGoogle ScholarDigital LibraryDigital Library
  163. Engelhardt, C.R., et al., Effects of Violent-Video-Game Exposure on Aggressive Behavior, Aggressive-Thought Accessibility, and Aggressive Affect Among Adults With and Without Autism Spectrum Disorder. Psychological Science, 2015. 26(8): p. 1187-1200.Google ScholarGoogle Scholar
  164. Hong, H., E. Gilbert, G.D. Abowd, and R.I. Arriaga, In-group Questions and Out-group Answers: Crowdsourcing Daily Living Advice for Individuals with Autism, in Conference on Human Factors in Computing Systems. 2015, Association for Computing Machinery: Seoul, Republic of Korea. p. 777–786.Google ScholarGoogle ScholarDigital LibraryDigital Library
  165. Hong, H., J.G. Kim, G.D. Abowd, and R.I. Arriaga, Designing a social network to support the independence of young adults with autism. 2012, Association for Computing Machinery: Seattle, Washington, USA. p. 627–636.Google ScholarGoogle ScholarDigital LibraryDigital Library
  166. Hong, H., et al., Investigating the use of circles in social networks to support independence of individuals with autism, in Conference on Human Factors in Computing Systems. 2013, Association for Computing Machinery: Paris, France. p. 3207–3216.Google ScholarGoogle ScholarDigital LibraryDigital Library
  167. Kaliouby, R.e. and A. Teeters, Eliciting, capturing and tagging spontaneous facialaffect in autism spectrum disorder, in international Conference on Multimodal Interfaces. 2007, Association for Computing Machinery: Nagoya, Aichi, Japan. p. 46–53.Google ScholarGoogle Scholar
  168. Lin, T., et al., Empathics system: application of emotion analysis AI through smart glasses, in International Conference on PErvasive Technologies Related to Assistive Environments. 2020, Association for Computing Machinery: Corfu, Greece. p. Article 34.Google ScholarGoogle Scholar
  169. Mazurek, M.O., Social media use among adults with autism spectrum disorders. Comput. Hum. Behav., 2013. 29(4): p. 1709–1714.Google ScholarGoogle Scholar
  170. Mazurek, M.O., C.R. Engelhardt, and K.E. Clark, Video games from the perspective of adults with autism spectrum disorder. Comput. Hum. Behav., 2015. 51(PA): p. 122–130.Google ScholarGoogle Scholar
  171. Morales-Villaverde, L.M., K. Caro, T. Gotfrid, and S. Kurniawan, Online Learning System to Help People with Developmental Disabilities Reinforce Basic Skills, in International ACM SIGACCESS Conference on Computers and Accessibility. 2016, Association for Computing Machinery: Reno, Nevada, USA. p. 43–51.Google ScholarGoogle ScholarDigital LibraryDigital Library
  172. Morris, M.R., A. Begel, and B. Wiedermann, Understanding the Challenges Faced by Neurodiverse Software Engineering Employees: Towards a More Inclusive and Productive Technical Workforce, in International ACM SIGACCESS Conference on Computers & Accessibility. 2015, Association for Computing Machinery: Lisbon, Portugal. p. 173–184.Google ScholarGoogle ScholarDigital LibraryDigital Library
  173. Neupane, A., et al., Do Social Disorders Facilitate Social Engineering? A Case Study of Autism and Phishing Attacks, in Computer Security Applications Conference. 2018, Association for Computing Machinery: San Juan, PR, USA. p. 467–477.Google ScholarGoogle Scholar
  174. Ramnauth, R., et al., A Social Robot for Improving Interruptions Tolerance and Employability in Adults with ASD. Hri '22, 2022: p. 4–13.Google ScholarGoogle Scholar
  175. Salekin, A. and N. Russo, Understanding Autism: The Power of EEG Harnessed by Prototypical Learning. Mcps '21, 2021: p. 12–16.Google ScholarGoogle ScholarDigital LibraryDigital Library
  176. Zolyomi, A., et al., Managing Stress: The Needs of Autistic Adults in Video Calling. Proc. ACM Hum.-Comput. Interact., 2019. 3(CSCW): p. Article 134.Google ScholarGoogle ScholarDigital LibraryDigital Library
  177. Zolyomi, A., T. Gotfrid, and K. Shinohara, Socializing via a Scarf: Individuals with Intellectual and Developmental Disabilities Explore Smart Textiles, in Conference on Human Factors in Computing Systems. 2019, Association for Computing Machinery: Glasgow, Scotland Uk. p. Paper LBW0217.Google ScholarGoogle ScholarDigital LibraryDigital Library
  178. Barbu, E., M.T. Martín-Valdivia, E. Martínez-Cámara, and L.A. Ureña-López, Language technologies applied to document simplification for helping autistic people. Expert Syst. Appl., 2015. 42(12): p. 5076–5086.Google ScholarGoogle Scholar
  179. Cassidy, S.A., et al., Expressive visual text-to-speech as an assistive technology for individuals with autism spectrum conditions. Comput. Vis. Image Underst., 2016. 148(C): p. 193–200.Google ScholarGoogle Scholar
  180. Eraslan, S., V. Yaneva, Y. Yesilada, and S. Harper, Do Web Users with Autism Experience Barriers When Searching for Information Within Web Pages?, in Conference on The Future of Accessible Work. 2017, Association for Computing Machinery: Perth, Western Australia, Australia. p. Article 20.Google ScholarGoogle ScholarDigital LibraryDigital Library
  181. Eraslan, S., Y. Yesilada, V. Yaneva, and S. Harper, Autism Detection Based on Eye Movement Sequences on the Web: A Scanpath Trend Analysis Approach. W4a '20, 2020.Google ScholarGoogle ScholarDigital LibraryDigital Library
  182. Ferrario, M.A., et al., Computing and mental health: intentionality and reflection at the click of a button, in Conference on Pervasive Computing Technologies for Healthcare. 2017, Association for Computing Machinery: Barcelona, Spain. p. 1–10.Google ScholarGoogle ScholarDigital LibraryDigital Library
  183. Matthews, O., et al., Combining Trending Scan Paths with Arousal to Model Visual Behaviour on the Web: A Case Study of Neurotypical People vs People with Autism, in Conference on User Modeling, Adaptation and Personalization. 2019, Association for Computing Machinery: Larnaca, Cyprus. p. 86–94.Google ScholarGoogle Scholar
  184. McGowan, J., G. Leplâtre, and I. McGregor, CymaSense: A Novel Audio-Visual Therapeutic Tool for People on the Autism Spectrum, in International ACM SIGACCESS Conference on Computers and Accessibility. 2017, Association for Computing Machinery: Baltimore, Maryland, USA. p. 62–71.Google ScholarGoogle ScholarDigital LibraryDigital Library
  185. Shim, L., et al., Evaluating multimodal driver displays of varying urgency for drivers on the autistic spectrum, in International Conference on Automotive User Interfaces and Interactive Vehicular Applications. 2015, Association for Computing Machinery: Nottingham, United Kingdom. p. 133–140.Google ScholarGoogle ScholarDigital LibraryDigital Library
  186. Simm, W., et al., Anxiety and Autism: Towards Personalized Digital Health, in Conference on Human Factors in Computing Systems. 2016, Association for Computing Machinery: San Jose, California, USA. p. 1270–1281.Google ScholarGoogle Scholar
  187. Simm, W., M.A. Ferrario, A. Gradinar, and J. Whittle, Prototyping “clasp”: implications for designing digital technology for and with adults with autism, in Conference on Designing Interactive Systems. 2014, Association for Computing Machinery: Vancouver, BC, Canada. p. 345–354.Google ScholarGoogle Scholar
  188. Yaneva, V., L.A. Ha, S. Eraslan, and Y. Yesilada, Adults with High-functioning Autism Process Web Pages With Similar Accuracy but Higher Cognitive Effort Compared to Controls, in Web For All Conference. 2019, Association for Computing Machinery: San Francisco, CA, USA. p. Article 34.Google ScholarGoogle ScholarDigital LibraryDigital Library
  189. Yaneva, V., et al., Detecting Autism Based on Eye-Tracking Data from Web Searching Tasks, in Internet of Accessible Things. 2018, Association for Computing Machinery: Lyon, France. p. Article 16.Google ScholarGoogle ScholarDigital LibraryDigital Library
  190. Yaneva, V., I. Temnikova, and R. Mitkov, Accessible Texts for Autism: An Eye-Tracking Study, in International ACM SIGACCESS Conference on Computers & Accessibility. 2015, Association for Computing Machinery: Lisbon, Portugal. p. 49–57.Google ScholarGoogle ScholarDigital LibraryDigital Library
  191. Rapp, A., et al., Designing an Urban Support for Autism, in International Conference on Human-Computer Interaction with Mobile Devices and Services. 2019, Association for Computing Machinery: Taipei, Taiwan. p. Article 43.Google ScholarGoogle Scholar
  192. Tarantino, L., G.D. Gasperis, T.D. Mascio, and M.C. Pino, Immersive applications: what if users are in the autism spectrum?, in Conference on Virtual-Reality Continuum and its Applications in Industry. 2019, Association for Computing Machinery: Brisbane, QLD, Australia. p. Article 32.Google ScholarGoogle ScholarDigital LibraryDigital Library
  193. Rapp, A., et al., Holistic User Models for Cognitive Disabilities: Personalized Tools for Supporting People with Autism in the City, in Conference on User Modeling, Adaptation and Personalization. 2018, Association for Computing Machinery: Singapore, Singapore. p. 109–113.Google ScholarGoogle Scholar
  194. Mauro, N., L. Ardissono, and F. Cena, Personalized Recommendation of PoIs to People with Autism. 2020: p. 163–172.Google ScholarGoogle Scholar
  195. Sundberg, M., Online gaming, loneliness and friendships among adolescents and adults with ASD. Comput. Hum. Behav., 2018. 79(C): p. 105–110.Google ScholarGoogle Scholar
  196. Shahid, S., J.t. Voort, M. Somers, and I. Mansour, Skeuomorphic, flat or material design: requirements for designing mobile planning applications for students with autism spectrum disorder, in International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct. 2016, Association for Computing Machinery: Florence, Italy. p. 738–745.Google ScholarGoogle ScholarDigital LibraryDigital Library
  197. Gentile, V., et al., Touch or touchless? evaluating usability of interactive displays for persons with autistic spectrum disorders, in International Symposium on Pervasive Displays. 2019, Association for Computing Machinery: Palermo, Italy. p. Article 10.Google ScholarGoogle ScholarDigital LibraryDigital Library
  198. Passerino, L.M. and L.M.C. Santarosa, Autism and digital learning environments: Processes of interaction and mediation. Comput. Educ., 2008. 51(1): p. 385–402.Google ScholarGoogle Scholar
  199. Downing, J., Applied or Denied? The eLearning Experience of an Autistic, Mature-Aged University Student. Int. J. Cyber Ethics Educ., 2014. 3(2): p. 1–15.Google ScholarGoogle Scholar
  200. Newton, A.T., A.D.I. Kramer, and D.N. McIntosh, Autism online: a comparison of word usage in bloggers with and without autism spectrum disorders, in Conference on Human Factors in Computing Systems. 2009, Association for Computing Machinery: Boston, MA, USA. p. 463–466.Google ScholarGoogle ScholarDigital LibraryDigital Library
  201. Hong, H., G.D. Abowd, and R.I. Arriaga, Towards designing social question-and-answer systems for behavioral support of individuals with autism, in International Conference on Pervasive Computing Technologies for Healthcare. 2015, ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering): Istanbul, Turkey. p. 17–24.Google ScholarGoogle ScholarCross RefCross Ref
  202. Ferrario, M.A., et al., Values-first SE: research principles in practice, in Conference on Software Engineering Companion. 2016, Association for Computing Machinery: Austin, Texas. p. 553–562.Google ScholarGoogle Scholar
  203. Dewinter, J., A.I.R. van der Miesen, and L.G. Holmes, INSAR Special Interest Group Report: Stakeholder Perspectives on Priorities for Future Research on Autism, Sexuality, and Intimate Relationships. Autism Research, 2020. 13(8): p. 1248-1257.Google ScholarGoogle Scholar
  204. Pellicano, L., A. Dinsmore, and T. Charman, What should autism research focus upon? Community views and priorities from the UK. Autism, 2014. 18(7): p. 756-770.Google ScholarGoogle Scholar
  205. Gotham, K., et al., Characterizing the daily life, needs, and priorities of adults with autism spectrum disorder from Interactive Autism Network data. Autism, 2015. 19(7): p. 794-804.Google ScholarGoogle Scholar
  206. James Lind Alliance. Autism PSP final report. 2015 [cited 2021 26 July]; Available from: https://www.jla.nihr.ac.uk/priority-setting-partnerships/autism/.Google ScholarGoogle Scholar
  207. Benevides, T.W., et al., Listening to the autistic voice: Mental health priorities to guide research and practice in autism from a stakeholder-driven project. Autism, 2020. 24(4): p. 822-833.Google ScholarGoogle Scholar
  208. Amaral, D.G., et al., Gaps in Current Autism Research: The Thoughts of the Autism Research Editorial Board and Associate Editors. Autism Research, 2019. 12(5): p. 700-714.Google ScholarGoogle Scholar
  209. Caldwell-Harris, C.L. and C.J. Jordan, Systemizing and special interests: Characterizing the continuum from neurotypical to autism spectrum disorder. Learning and Individual Differences, 2014. 29: p. 98-105.Google ScholarGoogle Scholar
  210. Sasson, N.J., G.S. Dichter, and J.W. Bodfish, Affective Responses by Adults with Autism Are Reduced to Social Images but Elevated to Images Related to Circumscribed Interests. PLOS ONE, 2012. 7(8): p. e42457.Google ScholarGoogle ScholarCross RefCross Ref
  211. Hobson, R.P., El autismo y el desarrollo de la mente. 1995, Madrid: Alianza Editorial.Google ScholarGoogle Scholar
  212. Attwood, T., The Complete Guide to Asperger's Syndrome. 2007: Jessica Kingsley Publishers.Google ScholarGoogle Scholar
  213. Powell, A., Taking Responsibility: Good Practice Guidelines for Services for Adults with Asperger Syndrome. 2002: National Autistic Society.Google ScholarGoogle Scholar
  214. Cena, F., et al., Personalized Tourist Guide for People with Autism. UMAP '20 Adjunct, 2020: p. 347–351.Google ScholarGoogle Scholar
  215. Strang, J.F., et al., Both sex- and gender-related factors should be considered in autism research and clinical practice. Autism, 2020. 24(3): p. 539-543.Google ScholarGoogle Scholar
  216. Malone, K.M., et al., The Scholarly Neglect of Black Autistic Adults in Autism Research. Autism in Adulthood, 2022.Google ScholarGoogle Scholar
  217. Cummins, C., E. Pellicano, and L. Crane, Autistic adults’ views of their communication skills and needs. International Journal of Language and Communication Disorders, 2020. 55(5): p. 678-689.Google ScholarGoogle Scholar
  218. Pellicano, E., et al., "i Knew She'd Get It, and Get Me": Participants' Perspectives of a Participatory Autism Research Project. Autism in Adulthood, 2022. 4(2): p. 120-129.Google ScholarGoogle Scholar
  219. Gillespie-Lynch, K., et al., Whose Expertise Is It? Evidence for Autistic Adults as Critical Autism Experts. Frontiers in Psychology, 2017. 8(438).Google ScholarGoogle Scholar
  220. Nicolaidis, C., et al., The AASPIRE practice-based guidelines for the inclusion of autistic adults in research as co-researchers and study participants. Autism, 2019. 23(8): p. 2007-2019.Google ScholarGoogle Scholar
  221. Ashworth, M., et al., Toward Empathetic Autism Research: Developing an Autism-Specific Research Passport. Autism in Adulthood, 2021. 3(3): p. 280-288.Google ScholarGoogle Scholar
  222. Cascio, M.A., J.A. Weiss, and E. Racine, Person-oriented ethics for autism research: Creating best practices through engagement with autism and autistic communities. Autism, 2020. 24(7): p. 1676-1690.Google ScholarGoogle Scholar
  223. Rosqvist, H.B., et al., Being, Knowing, and Doing: Importing Theoretical Toolboxes for Autism Studies. Autism in Adulthood, 2022.Google ScholarGoogle Scholar
  224. MacLennan, K., et al., “It Is a Big Spider Web of Things”: Sensory Experiences of Autistic Adults in Public Spaces. Autism in Adulthood, 2022.Google ScholarGoogle Scholar
  225. Zheng, L., et al., The use of everyday and assistive technology in the lives of older autistic adults. Autism, 2021. 26(6): p. 1550-1562.Google ScholarGoogle Scholar
  226. Jones, S.C., Measuring the Wrong Thing the Right Way? Time to Rethink Autism Research Tools. Autism in Adulthood, 2022. 4(2): p. 104-109.Google ScholarGoogle Scholar
  227. Poulsen, R., C. Brownlow, W. Lawson, and E. Pellicano, Meaningful research for autistic people? Ask autistics! Autism, 2022. 26(1): p. 3-5.Google ScholarGoogle Scholar
  228. Pukki, H., et al., Autistic Perspectives on the Future of Clinical Autism Research. Autism in Adulthood, 2022. 4(2): p. 93-101.Google ScholarGoogle Scholar
  229. Botha, M. and E. Cage, "Autism Research is in Crisis": A mixed method study of researcher's constructions of autistic people and autism research. 2022.Google ScholarGoogle Scholar
  230. World Health Organization, International Classification of Functioning, Disability and Health (ICF). 2001, World Health Organization.Google ScholarGoogle Scholar
  231. Bölte, S., W.B. Lawson, P.B. Marschik, and S. Girdler, Reconciling the seemingly irreconcilable: The WHO's ICF system integrates biological and psychosocial environmental determinants of autism and ADHD: The International Classification of Functioning (ICF) allows to model opposed biomedical and neurodiverse views of autism and ADHD within one framework. BioEssays, 2021. 43(9).Google ScholarGoogle Scholar
  232. Happé, F. and U. Frith, Annual Research Review: Looking back to look forward – changes in the concept of autism and implications for future research. Journal of Child Psychology and Psychiatry and Allied Disciplines, 2020. 61(3): p. 218-232.Google ScholarGoogle Scholar
  233. Pellicano, E. and J. den Houting, Annual Research Review: Shifting from ‘normal science’ to neurodiversity in autism science. Journal of Child Psychology and Psychiatry and Allied Disciplines, 2022. 63(4): p. 381-396.Google ScholarGoogle Scholar
  234. Wright, B., P. Spikins, and H. Pearson, Should autism spectrum conditions be characterised in a more positiveway in our modern world? Medicina (Lithuania), 2020. 56(5).Google ScholarGoogle Scholar
  235. Fletcher-Watson, S., et al., Diversity computing. interactions, 2018. 25(5): p. 28–33.Google ScholarGoogle Scholar
  236. Dwyer, P., The Neurodiversity Approach(es): What Are They and What Do They Mean for Researchers? Human Development, 2022. 66(2): p. 73-92.Google ScholarGoogle Scholar
  237. Richards, Z. and M. Hewstone, Subtyping and Subgrouping: Processes for the Prevention and Promotion of Stereotype Change. Personality and Social Psychology Review, 2001. 5(1): p. 52-73.Google ScholarGoogle Scholar
  238. Ferris, L.J., J. Jetten, M.J. Hornsey, and B. Bastian, Feeling Hurt: Revisiting the Relationship Between Social and Physical Pain. Review of General Psychology, 2019. 23(3): p. 320-335.Google ScholarGoogle Scholar
  239. Bertilsdotter Rosqvist, H., et al., Cutting our own keys: New possibilities of neurodivergent storying in research. Autism, 2022. 0(0).Google ScholarGoogle Scholar
  240. Hofmann, M., D. Kasnitz, J. Mankoff, and C.L. Bennett, Living Disability Theory: Reflections on Access, Research, and Design, in Conference on Computers and Accessibility. 2020, Association for Computing Machinery. p. 1-13.Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Adult Autism Research Priorities and Conceptualization in Computing Research: Invitation to Co-Lead with Autistic Adults
          Index terms have been assigned to the content through auto-classification.

          Recommendations

          Comments

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in

          Full Access

          • Published in

            cover image ACM Transactions on Computer-Human Interaction
            ACM Transactions on Computer-Human Interaction Just Accepted
            ISSN:1073-0516
            EISSN:1557-7325
            Table of Contents

            Copyright © 2024 Copyright held by the owner/author(s).

            Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

            Publisher

            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Online AM: 24 January 2024
            • Accepted: 29 September 2023
            • Revised: 2 September 2023
            • Received: 23 December 2022
            Published in tochi Just Accepted

            Check for updates

            Qualifiers

            • research-article
          • Article Metrics

            • Downloads (Last 12 months)231
            • Downloads (Last 6 weeks)60

            Other Metrics

          PDF Format

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader