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Background: People from lower socioeconomic groups are more likely to smoke and less likely to succeed in achieving abstinence, making tobacco smoking a leading driver of health inequalities. Contextual factors affecting subpopulations may moderate the efficacy of individual-level smoking cessation interventions. It is not known whether any intervention performs differently across socioeconomically-diverse populations and contexts.

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As global populations age, ensuring the mobility safety of elderly individuals has become a prominent concern, highlighting the need for innovative designs in assistive products for seniors. This study aims to offer a scientific and practical design methodology for mobility aid designers, validated through the design of a walker for elderly users. To begin, potential user needs for walkers were identified using User Journey Mapping, with these needs categorized through the Kano model to establish a structured hierarchy of design requirements.

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Importance: A wide range of medications, noncombustible nicotine products, behavioral support, and alternative treatments are available in England to help people stop smoking. Understanding their effectiveness outside of clinical trial settings can support informed decision-making.

Objectives: To provide up-to-date estimates of the prevalence of different smoking cessation aids and associations with quit success and to explore moderation by socioeconomic position.

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Purpose: An assistive technology ecosystem requires co-ordinated collaboration between policy, products, provision processes, and personnel. A needs assessment was conducted of the assistive technology sector in Queensland to examine these components from the perspective of all key stakeholders. This paper reports the findings of the expressed needs of the assistive technology sector as experienced by the AT advisors and suppliers.

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Empowering People with Disabilities in Smart Homes Using Predictive Informing.

Sensors (Basel)

January 2025

University of Zagreb, Faculty of Transport and Traffic Sciences, Vukelićeva 4, 10000 Zagreb, Croatia.

The possibilities of the Ambient Assisted Living (AAL)/Enhanced Living Environments (ELE) concept in the environment of a smart home were investigated to improve accessibility and improve the quality of life of a person with disabilities. This paper focuses on the concept of predictive information for a person with disabilities in a smart home environment concept where artificial intelligence (AI) and machine learning (ML) systems use data on the user's preferences, habits, and possible incident situations. A conceptual mathematical model is proposed, the purpose of which is to provide predictive user information from defined data sets.

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