Neurodiversity and Technostress: Towards a Multimodal Research Design for Evaluating Subjective, Physiological, and Behavioral Responses

2026-04-23

AI Summary

This study addresses a critical gap in technostress research by incorporating neurodiversity, an aspect largely overlooked in existing literature that predominantly focuses on neurotypical populations. It presents the first systematic investigation comparing multidimensional stress responses between neurodivergent and neurotypical individuals during structured and unstructured digital tasks, employing a standardized experimental paradigm. The research adopts a multimodal measurement approach, integrating subjective self-reports, physiological signals, and behavioral interaction data to comprehensively assess differences in stress mechanisms across groups. By elucidating how neurocognitive diversity modulates technostress experiences, this work provides empirical foundations for rethinking human–computer interaction paradigms and informs the design of more inclusive digital work environments that accommodate diverse cognitive profiles.

Technology Category

Humans and AI: Interaction Techniques and DevicesCognitive Modeling & Cognitive Systems: Affective ComputingApplication Domains: Humanities & Computational Social Science

Application Category

Economics, Online Markets and Human Computation: Research challenges in human and human-AI computationResponsible Web: Machine-in-the-loop, human agency and autonomyWeb Mining and Content Analysis: Bridging structured and unstructured data

Abstract

Digitalization has transformed modern work by increasing efficiency while also introducing new forms of strain. Technostress (TS) describes subjective, physiological, and behavioral stress responses related to digital technology use. Existing TS research has predominantly focused on neurotypical populations and rarely integrates multiple stress dimensions within a single design. This paper addresses these gaps by proposing a controlled experimental research design that systematically compares neurodivergent and neurotypical individuals under standardized digital stress conditions. The proposed design combines structured and unstructured digital tasks with a multimodal measurement approach covering subjective perceptions, physiological activation, and observable interaction behavior. By integrating neurodiversity into TS research, the paper contributes to a more differentiated understanding of digital stress and provides a methodological approach for more inclusive digital work design.

Problem

• neurodiversity
• technostress
• multimodal measurement
• digital stress
• inclusive design

Innovation

• neurodiversity
• technostress
• multimodal measurement
• digital stress
• inclusive design