When Patient Reports and Sensors Disagree in Parkinson's Disease: Construct Overlap, Personal Priorities, and the Value of Assessment

Abstract Patient reports and digital sensors describe different aspects of living with Parkinson's disease. Treating disagreement as evidence that one source is unreliable can obscure clinically useful information, especially when movement changes and personal burden follow different trajectories. This methodological analysis asks how construct overlap and patient priorities influence the interpretation and practical value of combined assessment. A targeted narrative selection of primary measurement, qualitative, digital-health, and access studies informs two reproducible hypothetical calculations. The first defines a motor sensor and a reported-burden measure through shared motor variation, distinct nonmotor variation, and independent measurement error. With identical error variances of 0.25, increasing the nonmotor loading from zero to one and two reduces their expected correlation from 0.800 to 0.596 and 0.390 without introducing systematic bias. The second compares two fictional assessment bundles through declared information coverage, personal priority weights, and assessment burden. Their preferred ordering reverses when the motor-priority weight crosses 0.556, although neither bundle changes technically. These calculations are not observations, estimates of Parkinson symptom relationships, or evaluations of a deployed platform. They show why a single correlation coefficient cannot establish patient relevance, why symptom-specific agreement requires aligned time windows and constructs, and why lower assessment burden can matter independently of predictive accuracy. A practical interpretation framework distinguishes technical error, expected construct divergence, changing activity opportunities, and changes in personal priorities. Future validation should report these pathways separately and evaluate whether the resulting assessment improves decisions that people value. 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