Development of a Physiotherapy Outcome-Influence Framework for Rehabilitation Planning

Thesis Abstract

This study addresses the persistent gap between physiotherapy interventions and optimal rehabilitation outcomes by developing a structured Outcome-Influence Framework to guide rehabilitation planning. The problem arises from heterogeneous assessment practices, limited integration of patient-reported outcomes with clinician-rated measures, and the absence of a coherent model linking functional outcomes to therapeutic influences across the rehabilitation trajectory. The aim is to establish a theoretically grounded, practically applicable framework that integrally maps determinants of outcome quality to planning processes in physiotherapy. Specific objectives are (1) to identify core outcome domains used in physiotherapy rehabilitation across musculoskeletal, neurological, and post-surgical populations; (2) to delineate patient-, intervention-, and system-level influences on outcomes through a multi-method evidence synthesis; (3) to formulate a conceptual model integrating theoretical constructs from the ICF (International Classification of Functioning, Disability and Health) and Expectancy-Value Theory to explain outcome variability; (4) to validate the framework through expert consensus and empirical testing; and (5) to propose actionable guidelines for rehabilitation planning and evaluation. The methodology adopts a mixed-methods sequential design. In the qualitative phase, semi-structured interviews (n=40) with physiotherapists, patients, and rehabilitation managers across three clinical settings will explore perceived drivers of outcome variation. The quantitative phase employs a prospective cohort (n=320) of adults undergoing physiotherapy for musculoskeletal and neurological conditions, with outcomes assessed at baseline, 6 weeks, and 12 weeks using standardized measures including the Short Form Health Survey (SF-12), the Knee Injury and Osteoarthritis Outcome Score (KOOS) or equivalent condition-specific instruments, and clinician-rated mobility scales. Instrument validity and reliability will be established through pilot testing and calculation of Cronbach’s alpha and intraclass correlation coefficients (ICCs). Data collection will also include patient activation measures and therapy adherence indices to capture modifiable influence factors. Data analysis will utilize exploratory and confirmatory factor analysis to identify latent constructs, followed by hierarchical multiple regression to determine the contributions of patient-, intervention-, and system-level variables to outcome scores, and structural equation modeling (SEM) to test the proposed Outcome-Influence Framework. The qualitative data will be analyzed using thematic analysis, with coding conducted by two independent researchers and triangulated against quantitative findings. A nominal group technique will be used with expert panels (n=15-20 clinicians and researchers) to achieve consensus on the framework components and their operationalization. The theoretical underpinning integrates the ICF framework with Expectancy-Value Theory to elucidate motivation, engagement, and perceived value as mediators of therapeutic outcomes, guiding the specification of influence pathways in the model. Expected findings include identification of a core set of outcome domains common across conditions, quantification of the relative impact of patient-related factors (age, comorbidity, activation), intervention-related factors (therapy dose, modality mix, adherence), and system-related factors (access, continuity of care) on functional and health-related quality-of-life outcomes. The framework is anticipated to demonstrate good fit (CFI > 0.90, RMSEA < 0.08) in SEM analyses, with mediation effects indicating that patient activation and adherence partly transmit the influence of therapeutic variables on outcomes. The study aims to produce a validated, implementable framework that maps precise influence pathways, supports standardized assessment, and informs planning decisions such as treatment sequencing, dosage, and discharge criteria. The contribution to knowledge includes (1) a novel, integrative framework combining ICF-based outcome domains with motivational and expectancy mechanisms to explain rehabilitation outcome variability; (2) empirical evidence delineating the relative weight of modifiable versus non-modifiable influences on physiotherapy outcomes across diverse conditions; (3) a validated measurement and reporting toolkit for routine use in clinical practice; and (4) actionable guidelines for rehabilitation planning that optimize resource use and patient-centered care. The study concludes that a structured Outcome-Influence Framework enhances the predictability and quality of rehabilitation planning by clarifying influence pathways, informing personalized intervention strategies, and enabling standardized outcome monitoring across care settings. Recommendations emphasize early activation and adherence strategies, condition-specific tailoring of intervention intensity within the framework, and integration into electronic health record systems to support ongoing benchmarking and continuous quality improvement.