Related Experiment Video
Updated: Jun 4, 2026

Computerized Adaptive Testing System of Functional Assessment of Stroke
Published on: January 7, 2019
Comparison of scoring methods for the participation assessment with recombined tools-objective
Jennifer A Bogner1, Gale G Whiteneck, John D Corrigan
1Department of Physical Medicine and Rehabilitation, Ohio State University, Columbus, USA. bogner.1@osu.edu
Objective:
To develop and compare 2 scoring algorithms for a measure of participation, the Participation Assessment with Recombined Tools-Objective (PART-O) based on the assumption that more participation is better versus an alternative that reflects balance in domains of participation.
Design:
Survey.
Setting:
Community settings.
Participants:
Three groups of participants under the age of 65 years were included: (1) persons with spinal cord injury, traumatic brain injury, stroke, and other disorders who are commonly treated in acute rehabilitation settings (n=220), and (2) participants from the general population who did (n=366) or (3) did not (n=284) self-report limitations indicative of a disability who participated in the 2006 Colorado Behavioral Risk Factor Surveillance System (N=870).
Interventions:
Not applicable.
Main Outcome Measure:
PART-O.
Results:
We developed PART-O subscores using a consensus process and then evaluated them empirically. We combined subscores using 2 contrasting algorithms, one using average scores and the other reflecting the amount of participation and variation in participation across 3 domains. The algorithms for the total scores yielded normal distributions in all 3 samples and were equally sensitive to the impact of disability. While strongly correlated, about 30% of the variance of the 2 total scores was not shared.
Conclusions:
Two scoring algorithms for the PART-O illustrate contrasting perspectives of the construct of participation. The 2 algorithms may be used in future studies to expand our understanding of the construct of participation.
Related Concept Videos
Multiple Comparison Tests
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
Review and Preview
Percentiles are a type of fractile that partition data into...