The objective of this doctoral thesis was to inform the development of future prediction models of functioning in spinal cord injury (SCI) by examining the complexity of functioning and its predictors in persons with SCI attending first rehabilitation in Switzerland as well as the current state of prediction research in the field of SCI rehabilitation. To achieve this objective, three related research studies were conducted. Study 1 used the International Classification of Functioning, Disability and Health (ICF) as a conceptual framework and structural equation modelling (SEM) as methodology to investigate associations between body structures and functions, and activities as well as their relationship with contextual factors and characteristics of the health condition in persons with SCI in Switzerland at discharge from first rehabilitation. Findings revealed potential important direct and indirect effects within the tested association structures. Study 2 used latent process mixed models (LPMMs) and multinomial logistic regression as methodologies to identify classes of functioning trajectories and corresponding predictors of class membership in persons with SCI undergoing first rehabilitation in Switzerland. Results showed four distinct classes of functioning trajectories and revealed robust predictors for distinguishing between identified classes. Lastly, study 3 summarized current literature on prediction models of functioning in the field of SCI rehabilitation in the form of a scoping review. Results showed that the potential of functioning-based prediction models for use in clinical practice remains to be explored. Altogether, the findings of this doctoral thesis will pave the way for discussions and future research on prediction models of functioning in SCI with the ultimate goal of enhancing clinical practice.

+ ID der Publikation: unilu_57702 + Sprache: Englisch + Letzte Aktualisierung: 2022-03-09 15:28:24