Free
Poster Session
Issue Date: August 2016
Published Online: August 01, 2016
Updated: January 01, 2021
Let's Get Functional: Can Muscle Groups Account for ADL Challenges?
Author Affiliations
  • Medical University of South Carolina
  • Medical University of South Carolina
  • Medical University of South Carolina
  • Medical University of South Carolina
  • Medical University of South Carolina
  • Medical University of South Carolina
  • Medical University of South Carolina
  • Medical University of South Carolina
Article Information
Health and Wellness / Education of OTs and OTAs / Neurologic Conditions / Rehabilitation, Participation, and Disability / Stroke / Assessment/Measurement
Poster Session   |   August 01, 2016
Let's Get Functional: Can Muscle Groups Account for ADL Challenges?
American Journal of Occupational Therapy, August 2016, Vol. 70, 7011500032. https://doi.org/10.5014/ajot.2016.70S1-PO3113
American Journal of Occupational Therapy, August 2016, Vol. 70, 7011500032. https://doi.org/10.5014/ajot.2016.70S1-PO3113
Abstract

Date Presented 4/8/2016

We investigated the application of the previously identified common component of activities of daily living, number of muscle groups, for two measures. The component demonstrated a moderate correlation with item difficulty on the Stoke Impact Scale (r = .62) and a correlation with the FIM™ (r = .17).

Primary Author and Speaker: Clare Fitzmaurice

Additional Authors and Speakers: Christine Harris, Ickpyo Hong, Matthew Husband, Craig Velozo, Emily Schoen, Erica Ingram, Danielle Kapustka

PURPOSE: The purpose of this study was to determine whether the number of essential muscle groups recruited during different activities of daily living (ADLs) correlates with item difficulty on two similar ADL measurement tools. We hypothesized that the number of muscle groups recruited would account for the similar amount of variance in item difficulty across two similar ADL instruments.
RATIONALE: Previous research demonstrated a significant correlation between item difficulty and number of muscles recruited on the Stroke Impact Scale (SIS)–ADL instrument, but not on the International Classification of Functioning, Disability and Health–Activity Measure (Velozo et al., 2015). By choosing similar instruments, the FIM™ and the SIS–Physical Activity, we assumed that the number of muscle groups would be well correlated with the item difficulty hierarchy of the both instruments.
DESIGN: Cross-sectional design
PARTICIPANTS: Raters were 6 second-yr occupational therapy students, 5 women and 1 man, ranging in age from 23 to 25 yr.
METHOD: Item hierarchy of the two instruments was retrieved from the published papers. Raters were trained on the scoring criteria of the number of muscle groups on test items and individually rated the number of muscle groups perceived to be recruited during each activity on items from the FIM and SIS.
ANALYSIS: The criterion of the number of muscle groups was the three essential muscle groups that act when moving body parts, including shoulder and arm, wrist and hand, and lower extremity. Intraclass correlation coefficients (ICCs) were used to investigate the reliability of raters’ ratings on the number of muscle groups for the FIM and SIS items. The correlation between the item difficulty for the FIM and SIS and the number of muscle groups was calculated, and its significance was tested. The amount of variance explained by the independent variable was estimated for each instrument. All analyses were conducted using SPSS Version 23 software.
RESULTS: The 6 raters demonstrated reliable ratings on the number of muscle groups for the test items of the FIM, ICC(2, 6) = .95 and the SIS, ICC(2, 6) = .97. For the FIM, the correlation between the item difficulty and the number of muscle groups demonstrated a weak association (r = .174, p = .57), with only 3% of the variance explained by the number of muscle groups. In contrast to the FIM, the correlation between the item difficulty of the SIS and the number of muscle groups demonstrated a moderated association (r =.617, p = .011), and 38% of the variance explained by the number of muscle groups. Although two similar ADL instruments were used, the previously identified common component, the number of muscle groups, was not a common factor in explaining item difficulties for the FIM and SIS.
DISCUSSION: Although number of muscle groups was highly reliable across raters when rating ADLs, number of muscle groups accounted for a significant amount of variance for the SIS but not the FIM. Two factors may contribute to the discrepancy in the findings: (1) The FIM includes ADLs that involve only upper extremities (UEs) and ADLs that involve only lower extremities (LEs), and the SIS primarily involves ADLs that involve only LEs and (2) number of muscles appears to account for variance of LE items, not UE combined with LE items.
Future studies are needed to discover independent variables that account for UE variance and studies that compare across instruments that only have UE or LE ADL items.
References:
Velozo, A. C., Li, C., Stewart, L., Coats, E., McArdle, C., Tomsic, P., . . . Simon, L. (2015, April). Cracking the code to ADL scales: Determining if a single measurement model underlies different ADL scales. Poster presented at the 2015 AOTA Conference & Expo, Nashville, TN.