Original Article

Generating Rasch-based activity of daily living measures from the Spinal Cord Injury Longitudinal Aging Study

Received:
Revised:
Accepted:
Published online:

Abstract

Study design:

Retrospective Longitudinal Study.

Objectives:

(1) To determine whether the Spinal Cord Injury Activities of Daily Living (SCI_ADL) measure shows adequate item-level and precision psychometrics; (2) to investigate whether the SCI_ADL measure effectively detects ADL changes across time; (3) to describe self-care task(s) participants can and cannot do across time.

Setting:

Two Midwestern hospitals and 1 Southeastern specialty hospital in 1993.

Methods:

All participants were adults with traumatic SCI of at least 1-year duration at enrollment. We used 20-year (1993–2013) retrospective longitudinal data and categorized participants into three injury levels: C1–C4 (cervical; n=50), C5–C8 (n=126) and T1–S5 (thoracic, lumbar and sacral; n=168). We first examined psychometrics of the SCI_ADL with factor and Rasch analyses; then we investigated longitudinal change of SCI_ADL scores at three time points over 20 years (1993, 2003 and 2013) using generalized linear mixed modeling and post hoc analyses.

Results:

The SCI_ADL measure demonstrated unidimensionality, person strata of 2.9, high Cronbach’s α (0.93) and fair person reliability (0.76). T1–S5 had the highest measures, following C5–C8 and C1–C4 at three time points (P<0.05). The C1–C4 and T1–S5 groups showed significant decreases from 2003 to 2013; however, none of the three groups showed significant differences from 1993 to 2003 (P<0.05).

Conclusions:

The SCI_ADL measure could detect longitudinal ADL changes of the population with SCI across time. The C1–C4 group decreased the most in ADLs, indicating higher need of long-term services and rehabilitation.

Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.

References

  1. 1.

    , , , , . Advances in functional assessment for medical rehabilitation. Top Geriatr Rehabil 1986; 1: 59–74.

  2. 2.

    , . The Functional Independence Measure: a comparative study of clinician and self-ratings. Paraplegia 1993; 31: 457–461.

  3. 3.

    , , , , . Prediction of rehabilitation outcomes with disability measures. Arch Phys Med Rehabil 1994; 75: 133–143.

  4. 4.

    , , , . Inpatient rehabilitation outcomes in patients with malignant spinal cord compression compared to other non-traumatic spinal cord injury: a population based study. J Spinal Cord Med 2015; 38: 754–764.

  5. 5.

    , , , . Association between time-to-rehabilitation and outcomes following traumatic spinal cord injury. Arch Phys Med Rehabil 2016; 97: 1620–1627.

  6. 6.

    , , , , , . Social support and life satisfaction in spinal cord injury during and up to one year after inpatient rehabilitation. J Rehab Med 2010; 42: 265–271.

  7. 7.

    , , , , , et al. The Catz–Itzkovich SCIM: a revised version of the Spinal Cord Independence Measure. Disabil Rehabil 2001; 23: 263–268.

  8. 8.

    , , , , , et al. The Spinal Cord Independence Measure (SCIM) version III: reliability and validity in a multi-center international study. Disabil Rehabil 2007; 29: 1926–1933.

  9. 9.

    , , , , , et al. Activity and participation after spinal cord injury: state-of-the-art report. J Rehabil Res Dev 2012; 49: 155–174.

  10. 10.

    , , , , , et al. Development and initial evaluation of the Spinal Cord Injury-Functional Index. Arch Phys Med Rehabil 2012; 93: 1733–1750.

  11. 11.

    , , , . The natural course of spinal cord injury: changes over 40 years among those with exceptional survival. Spinal Cord 2017; 55: 502–508.

  12. 12.

    , , . SCI Longitudinal Aging Study: 40 years of research. Top Spinal Cord Inj Rehabil 2015; 21: 189–200.

  13. 13.

    . The classic measure of disability in activities of daily living is biased by age but an expanded IADL/ADL measure is not. J Gerontol B 2010; 65: 720–732.

  14. 14.

    , , , , , et al. A prospective study on physical activity levels after spinal cord injury during inpatient rehabilitation and the year after discharge. Arch Phys Med Rehabil 2008; 89: 2094–2101.

  15. 15.

    , , , , Group S-SR. Increased participation in activities of daily living is associated with lower cholesterol levels in people with spinal cord injury. Arch Phys Med Rehabil 2009; 90: 1755–1759.

  16. 16.

    , . Applying the Rasch Model: Fundamental Measurement in the Human Sciences, 2nd edn.Lawrence Erlbaum Associates: Mahwah, NJ, USA. 2007.

  17. 17.

    . Dimensions of subjective well-being after spinal cord injury: an empirical analysis by gender and race/ethnicity. Arch Phys Med Rehabil 1998; 79: 900–909.

  18. 18.

    , . Mplus User's Guide7th edn.Muthen & Muthen: Los Angeles, CA, USA. 2015.

  19. 19.

    . A User's Guide to Winsteps Ministeps 3.70.0: Rasch Model Computer Programs. Winsteps: Chicago, IL, USA,. 2012.

  20. 20.

    , , . An empirical bayes approach to mantel–haenszel DIF analysis. J Ed Meas 1999; 36: 1–28.

  21. 21.

    . Rasch analysis of repeated measures. Rasch Meas Trans 2011; 25: 1317.

  22. 22.

    SAS Institute IncSAS for Windows, 9.4 edn.SAS Institute: Cary, NC, USA,. 2015.

  23. 23.

    , , , , , . Exploratory and confirmatory factor analysis of the PROMIS pain quality item bank. Qual Life Res 2014; 23: 245–255.

  24. 24.

    , . A Beginner's Guide to Structural Equation Modeling, 2nd edn.Lawrence Erlbaum Associates: Mahwah, NJ, USA,. 2004.

  25. 25.

    , , , , , et al. Psychometric evaluation and calibration of health-related quality of life item banks: plans for the Patient-Reported Outcomes Measurement Information System (PROMIS). Med Care 2007; 45 (Suppl 1): S22–S31.

  26. 26.

    . Rasch model estimation: further topics. J Appl Meas 2004; 5: 95–110.

  27. 27.

    . Predicting responses from Rasch measures. J Appl Meas 2010; 11: 1–10.

  28. 28.

    . Detecting and evaluating the impact of multidimensionality using item fit statistics and principal component analysis of residuals. J Appl Meas 2002; 3: 205–231.

  29. 29.

    , , . Using item mean squares to evaluate fit to the Rasch model. J Outcome Meas 1998; 2: 66–78.

  30. 30.

    . Optimizing rating scale category effectiveness. J Appl Meas 2002; 3: 85–106.

  31. 31.

    , . Number of person or item strata. Rasch Meas Trans 2002; 16: 888.

  32. 32.

    , . Individual-patient monitoring in clinical practice: are available health status surveys adequate? Qual Life Res 1995; 4: 293–307.

  33. 33.

    . Statisical Power Analysis for the Behavioral Sciences2nd edn.Erlbaum: Hillsdale, NJ, USA,. 1988.

  34. 34.

    . Use of item response theory to link 3 modules of functional status items from the Asset and Health Dynamics Among the Oldest Old study. Arch Phys Med Rehabil 2002; 83: 383–394.

  35. 35.

    , , , . Self-scoring templates for motor and cognitive subscales of the FIM instrument for persons with spinal cord injury. Arch Phys Med Rehabil 2014; 95: 676–9 e5.

  36. 36.

    , , , , . Metric properties of the Spinal Cord Independence Measure-Self Report in a community survey. J Rehabil Med 2016; 48: 149–164.

  37. 37.

    , , , . A prospective study of health and risk of mortality after spinal cord injury. Arch Phys Med Rehabil 2008; 89: 1482–1491.

Download references

Acknowledgements

The contents of this publication were developed under a grant from the National Institute on Disability, Independent Living and Rehabilitation Research (NIDILRR; grant number 90IF0015). NIDILRR is a Center within the Administration for Community Living (ACL), Department of Health and Human Services (HHS). The contents of this publication do not necessarily represent the policy of NIDILRR, ACL, HHS, and you should not assume endorsement by the Federal Government.

Author information

Affiliations

  1. Division of Rehabilitation Sciences, School of Health Professions, University of Texas Medical Branch, Galveston, TX, USA

    • C-Y Li
    •  & I Hong
  2. Division of Occupational Therapy, College of Health Professions, Medical University of South Carolina, Charleston, SC, USA

    • C A Velozo
  3. Department of Health Sciences and Research, College of Health Professions, Medical University of South Carolina, Charleston, SC, USA

    • C Li
    •  & J S Krause
  4. Department of Medicine, Medical University of South Carolina, Charleston, SC, USA

    • J C Newman

Authors

  1. Search for C-Y Li in:

  2. Search for C A Velozo in:

  3. Search for I Hong in:

  4. Search for C Li in:

  5. Search for J C Newman in:

  6. Search for J S Krause in:

Competing interests

The authors declare no conflict of interest.

Corresponding author

Correspondence to J S Krause.

Supplementary information