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Due to the increasingly heterogeneous trajectories of aging, gerontology requires theoretical models and empirical methods that can meaningfully, reliably, and precisely describe, explain, and predict causes and effects within the aging process, considering particular contexts and situations. Human behavior occurs in contexts; nevertheless, situational changes are often neglected in context-based behavior research. This article follows the tradition of environmental gerontology research based on Lawton’s Person-Environment-Interaction model (P-E model) and the theoretical developments of recent years. The authors discuss that, despite an explicit time component, current P-E models could be strengthened by focusing on detecting P-E interactions in various everyday situations. Enhancing Lawton’s original formula via a situationally based component not only changes the theoretical perspectives on the interplay between person and environment but also demands new data collection approaches in empirical environmental research. Those approaches are discussed through the example of collecting mobile data with smartphones. Future research should include the situational dimension to investigate the complex nature of person environment interactions.
Digital technologies have gained vast relevance in postmodern societies and digital infrastructures are substantially integrated into the everyday lives of older people. This digitization is reframing the norms and practices of later life as well as the social construct of age itself. Despite the increasing amount of studies in the field of aging and technologies, it still lacks theorizing. This paper addresses this deficit, suggesting that the study of aging and technologies could profit from a comprehensive integration of theories from the sociology of aging, critical gerontology, and science-and-technology studies. We aim to make a theoretical contribution to this issue, asking: how is age being done in a digitized world? Applying a praxeological approach to aging and technologies, we firstly examine how theoretical and empirical work has constructed aging with technologies so far and identify its shortcomings. Some of this work so far lacks a proper consideration of social inequalities within these processes, whereas other studies lack a thorough consideration of materialities. Secondly, in an attempt to equally "praxeologize" and "materialize" the study of aging and technologies we develop a theoretical model that aims to overcome these shortcomings. In what we frame as a material praxeology of aging with technology, we are concerned with how age is being done through discursive formations, set into practice through social and material practices and involved in the (re)production of social inequalities. Enriching a Bordieuan terminology of social fields with notions of non-human agency, this praxeology is founded on three assumptions: (1) Social fields constitute the contexts in which age as a social phenomenon is being done with and through technologies (2) Human and non-human agents are equally involved in this process (3) The actions of the involved agents emerge from an agency distributed among them, and are structured through the power relations between them. Thirdly, we exemplify the application of this model by reference to a research project in the field of Active and Assistive Living.
The effects of aging on response time were examined in a paper-based lexical-decision experiment with younger (age 18–36) and older (age 64–75) adults, applying Ratcliff’s diffusion model. Using digital pens allowed the paper-based assessment of response times for single items. Age differences previously reported by Ratcliff and colleagues in computer-based experiments were partly replicated: older adults responded more conservatively than younger adults and showed a slowing of their nondecision components of RT by 53 ms. The rates of evidence accumulation (drift rate) showed no age-related differences. Participants with a higher score in a vocabulary test also had higher drift rates. The experiment demonstrates the possibility to use formal processing models with paper-based tests.