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.

Grant Number: 1R21DC022357-01
NIH Institute/Center: NIH
Principal Investigator: Sameer Ashaie