From Impairment to Participation: A Systems Approach to Understanding the Complexity of Aphasia

Project Summary Language is vital to much, if not all, aspects of a person’s life. For those persons with aphasia (PWA), a language disorder, the impact of aphasia extends beyond the language impairment to cognition, participation, and psychosocial aspects. To address the needs of PWA, historically two conceptualizations of aphasia and

approaches to rehabilitation have emerged in the field: impairment-focused and life participation. The impairment-focused approach puts prominence on language impairment, and more recently also underlying cognitive impairments that impact language processing. The life participation approach puts prominence on

participation goals, and the environment and psychosocial needs of the person to reach their goals. The field of clinical aphasiology has long recognized the importance of both approaches; however, there remains no quantitative model to determine the degree of interactivity and relative impact of impairment and life

participation variables in PWA at assessment. This lack of model limits the ability to make informed decisions about what to target in aphasia rehabilitation. The long-term goal of this proposal is to develop a complexity model of aphasia to transform conceptualization and rehabilitation of aphasia that maximally improves both the

aphasia (impairment) and its impact (participation) in a parsimonious and efficient way. The central hypothesis of this project is that impairment variables (e.g., comprehension and naming ability) and life participation variables (e.g., mental health, social roles and activities) influence each other in complex ways.

The use of cutting-edge, data-driven techniques from complex systems science will provide a way to model the constellation of relationships between impairment and life participation variables, with the ability to identify central variables and clusters of variables that are tightly connected (Aim 1). Furthermore, these techniques

will provide a method to detect putative causal relationships between variables (e.g., naming impairment causes lower communication confidence), which is a critical need in clinical aphasiology research where sample sizes are relatively small, and large randomized controlled trials are not always feasible (Aim 2). Lastly,

the prognostic value of the complexity model of aphasia will be investigated by testing whether the most central and causal variables from the model predict post-treatment outcomes (Aim 3). This project benefits from leveraging a large existing dataset of PWA (n = 61) who participated in Intensive Comprehensive Aphasia

Programs (ICAPs) between the years 2016-2024. The use of the ICAPs data is critical for capturing measures of both aphasia approaches at assessment. By the accomplishing the Aims of this project, a foundational model will be established from which future work will a) expand the complexity aphasia model to include brain

structure and function data – a critical set of variables given the leading cause of aphasia is stroke – and b) develop idiographic (i.e., individual-level) complexity models of aphasia for precision medicine.