Ruttenberg, David Paul; (2025) Towards technologically enhanced mitigation of autistic adults’ sensory sensitivity experiences and attentional, and mental wellbeing disturbances. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

This thesis explores strategies for improving sonic distractibility, performance, and autonomy for a limited autistic adult population, to determine whether or not and what types of technology-supported accommodations might be desired and tolerated by autistic individuals. 90% of autistic adults report that sensory issues cause barriers to their daily functioning at school and at work (Leekam et al., 2007). Differences arise from psychophysiological responses (e.g., anxiety and fatigue) and atypical reactivity to auditory, visual, and other cues (Bemporad, 1979; Grandin & Scariano, 1986; Cesaroni & Garber, 1991; Williams, 1999; Gerland, 2003). Research suggests that technologies might provide tools to help, manage, and/or alleviate distractibility in mainstream environments. For example, prosthetic and extender technologies show promise by supplementing innate autistic abilities with real-time cues that guide sensory sensitivity, attentional focus, and social interactions (e.g., el Kaliouby & Robinson, 2007). The dissertation consolidates engineering, psychological, and ethical perspectives that are pertinent to understanding autistic adults’ lived sensory experiences. A multidisciplinary approach was adopted to investigate what might constitute supportive technology-enhanced accommodations that mitigate distractibility and mental health in daily activities. A set of well-tolerated mediations is identified through participatory research and testing with autistic adults to respond to their sensitivity, attention, anxiety, and fatigue in diverse contexts from higher education institutions to employment, and broader social situations. Technology selection hinges upon appreciating how distraction, mental health, and the environment impact individuals (MacLennan et al., 2022). Despite the documented fragility of autistic populations’ physical and cognitive states (Lai et al., 2019; Leekam et al., 2007), technologists are said routinely to misunderstand neurodiversity by designing for non-disabled people (Shew, 2020). Therefore, a mixed methods approach may help engineers identify what sensor types (e.g., pupillary, auditory, or head sway) and accommodations (e.g., alert, filter, or guidance) might best support autistic individuals’ daily routines (Rad & Furlanello, 2016). This thesis relies on consultations to draw from different epistemic approaches that explore, define, and verify sensory sensitivity. Resulting mediating models (MM): (i) predict how mental health connects sensory cues to distractibility; and (ii) provide design specifications for real-time sensory tools (i.e., alerts, filters, and guidance) to reduce susceptibility to distraction. These were explored during in-field, Sustained Attention to Response Task (SART) experiments using the Wizard of Oz (WOz) methodology, which informed how inclusive and implementable prototypes could be created using participants’ recommendations. With respect to ethics of technology, this thesis underscores the importance of engineers and academics critically evaluating the impacts of extensive data collection, processing, and sharing on vulnerable users, including autistic people. Their foremost objective should be to mitigate the risk of unintended data exposure and protect against potential exploitation or harm (Simm et al., 2014; Edelson, 2010; Harrison, 2018; Sala et al., 2020; Warrier & Baron-Cohen, 2021), rather than solely focusing on deploying software and hardware solutions (Shew, 2017). Outcomes of the research presented include: (i) confirmation of autistic adults’ lived experience of sensory sensitivity, distractibility, and mental health concerns in academic, employment, and social contexts; (ii) affirmation of autistic adults’ desire for assistive technologies that may provide accommodation, comfort, and support autistic in confounding and highly distracting environments; (iii) extension of existing, non- autistic sensory-mental and health-distraction models’ directionality, validity, and mediating abilities to novel, autistic models; (iii) improvements of clinical performance, self-reported mental health, and tolerance of prototype mediations that help autistic adults overcome hyper, hypo-reactivity, or sensory seeking inputs; and (iv) recommendations for how technologists might design, collect, and deploy data in ways that ethically support and treat fairly populations that are at-risk and highly vulnerable.

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