ArticleJMIR human factors2026
User Acceptance of Smart Home Emergency Response Systems: Mixed Methods Study.
Article in JMIR human factors, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
Background: Smart home emergency response systems (SHERS) leverage existing smart home infrastructure to detect critical events and alert emergency services without manual activation. Unlike personal emergency response systems, which require users to trigger alarms, SHERS initiate alerts autonomously. Although technically feasible, user acceptance has received limited empirical attention. Objective: This study examined factors influencing the intention to adopt SHERS in private households, identifying key facilitators and barriers to acceptance. Methods: A mixed methods study followed the Double Diamond framework. In the discover/define phases, expert interviews (n=3) and secondary data analysis informed persona and scenario development. In the "develop" phase, brainwriting workshops (6-3-5 method, n=12) generated design requirements translated into a low-fidelity prototype. In the "deliver" phase, an online survey (n=85) assessed acceptance using the Technology Usage Inventory. Structural equation modeling tested hypothesized relationships, and methodological triangulation integrated qualitative and quantitative findings. Results: Perceived accessibility was the strongest positive predictor of intention to use (β=0.33, P=.02), while skepticism showed a marginally negative effect (β=-0.34, P=.06). The model explained 66% of variance in behavioral intention (R²=0.66). Triangulation confirmed that concerns about complexity, false alarms, and data privacy underlie these effects. Experts emphasized that technology should support rather than replace human decision-making; workshop participants stressed intuitive setup and user control over alarm cancellation. Conclusions: SHERS acceptance is primarily associated with perceived accessibility, while skepticism may act as a barrier. Developers should prioritize seamless integration with existing ecosystems, clear feedback mechanisms to prevent false alarms, and strong data protection.
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