J Hand Microsurg 2017; 09(02): 084-091
DOI: 10.1055/s-0037-1604060
Original Article
Thieme Medical and Scientific Publishers Private Ltd.

Using the Rasch Model to Develop a Measure of Participation Capturing the Full Range of Participation Characteristics for the Patients with Hand Injuries

Maryam Farzad
1   Department of Occupational therapy, The University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
,
Fereydoun Layeghi
2   Department of Clinical Science, The University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
,
Ali Hosseini
1   Department of Occupational therapy, The University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
,
Gale Whiteneck
3   Department of Research, Craig Hospital, Englewood, Colorado, United States
,
Ali Asgari
4   The University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
› Author Affiliations
Further Information

Publication History

05 February 2017

26 May 2017

Publication Date:
03 July 2017 (online)

Abstract

Objective The purpose of this paper was to report on the first step in the development of a new instrument to measure participation including the full range of its characteristics.

Methods The 30-item participation behavior questionnaire (PBQ) was developed from four main sources (a literature review of the theatrical basis of participation, available participation measures, and interviews with patients and experts about participation). Item selection and the reliability and validity of the measure were explored using Rasch measurement modeling for analysis.

Participants A total of 404 individuals referred to rehabilitation after hand, wrist, or upper extremity surgery to reduce impairment from trauma, at least 2 months post-injury.

Results An initial pool of 100 items; reflecting 14 characteristics of participation was initially reduced to 91 items after review by 15 participation experts and then further reduced to 30 items by three rounds of Rasch analysis removing misfitting items. The final PBQ has a person reliability of 0.91 with separation of 3.22, indicating it can reliably differentiate four levels of participation. There are no misfitting items and the instrument is unidimensional. All 14 characteristics of participation were retained in the PBQ, and none of the 30 items refer specifically to upper extremity issues.

Conclusion The 30 participation behavior items of the PBQ show promise of being a psychometrically sound measure of participation. Further research is needed to validate the PBQ in samples of people with a range of other disabilities.

Note

Ethic committee of University of Social Welfare and Rehabilitation Sciences, Tehran, Iran, approved this work, using the Rasch model to develop a measure of participation for patients with hand injuries.


 
  • References

  • 1 Organization WH. . International Classification of Functioning, Disability and Health: ICF: World Health Organization; 2001
  • 2 Dijkers MP. Issues in the conceptualization and measurement of participation: an overview. Arch Phys Med Rehabil 2010; 91 (9, Suppl): S5-S16
  • 3 Whiteneck G, Dijkers MP. Difficult to measure constructs: conceptual and methodological issues concerning participation and environmental factors. Arch Phys Med Rehabil 2009; 90 (11, Suppl): S22-S35
  • 4 Nordenfelt L. Action theory, disability and ICF. Disabil Rehabil 2003; 25 (18) 1075-1079
  • 5 Post MW, de Witte LP, Reichrath E, Verdonschot MM, Wijlhuizen GJ, Perenboom RJ. Development and validation of IMPACT-S, an ICF-based questionnaire to measure activities and participation. J Rehabil Med 2008; 40 (08) 620-627
  • 6 Brown M, Dijkers MP, Gordon WA, Ashman T, Charatz H, Cheng Z. Participation objective, participation subjective: a measure of participation combining outsider and insider perspectives. J Head Trauma Rehabil 2004; 19 (06) 459-481
  • 7 Brown M. Participation Objective, Participation Subjective. The Center for Outcome Measurement in Brain Injury; 2006
  • 8 Brown M. Participation Objective–Participation Subjective. Encyclopedia of Clinical Neuropsychology: Springer; 2011: 1875-1877
  • 9 Walker N, Mellick D, Brooks CA, Whiteneck GG. Measuring participation across impairment groups using the Craig Handicap Assessment Reporting Technique. Am J Phys Med Rehabil 2003; 82 (12) 936-941
  • 10 Farzad M, Layeghi F, Asgari A, Hosseini SA, Rassafiani M. Evaluation of non diseased specified outcome measures in hand injuries to assess activity and participation based on ICF content. J Hand Microsurg 2014; 6 (01) 27-34
  • 11 Chen W-H, Lenderking W, Jin Y, Wyrwich KW, Gelhorn H, Revicki DA. Is Rasch model analysis applicable in small sample size pilot studies for assessing item characteristics? An example using PROMIS pain behavior item bank data. Qual Life Res 2014; 23 (02) 485-493
  • 12 Wright BD. Sample-Free Test Calibration and Person Measurement. Paper Presented at the National Seminar on Adult Education Research (Chicago, February 11–13, 1968)
  • 13 Andrich D. Application of a psychometric rating model to ordered categories which are scored with successive integers. Appl Psychol Meas 1978; 2 (04) 581-594
  • 14 Wright BD, Masters GN. Rating Scale Analysis. Rasch Measurement. ERIC; 1982
  • 15 Rasch G. Probabilistic Models for Some Intelligence and Attainment Tests. ERIC; 1993
  • 16 Rasch G. Probabilistic Models for Some Intelligence and Achievement Tests. Copenhagen, Denmark: Danish Institute for Educational Research; 1960
  • 17 Smith Jr EV, Conrad KM, Chang K, Piazza J. An introduction to Rasch measurement for scale development and person assessment. J Nurs Meas 2002; 10 (03) 189-206
  • 18 Wright BD, Linacre JM. Observations are always ordinal; measurements, however, must be interval. Arch Phys Med Rehabil 1989; 70 (12) 857-860
  • 19 Wright BD, Stone MH. . Best Test Design. Rasch Measurement; 1979
  • 20 Bond TG, Fox CM. Applying the Rasch Model: Fundamental Measurement in the Human Sciences. 3rd ed. AE Enschede, The Netherlands: University of Twente; 2001
  • 21 Linacre JM. Detecting multidimensionality: which residual data-type works best?. J Outcome Meas 1998; 2 (03) 266-283
  • 22 Smith Jr EV. Understanding Rasch measurement: detecting and evaluating the impact of multidimenstionality using item fit statistics and principal component analysis of residuals. J Appl Meas 2002; 3 (02) 205-231
  • 23 Linacre JM, Wright B. . Winsteps. Available at http://www.winsteps.com/index.htm . Accessed June 27, 2013
  • 24 Linacre JM, Wright BD. A User's Guide to WINSTEP. Chicago, IL: MESA Press; 2009
  • 25 Shrout PE, Fleiss JL. Intraclass correlations: uses in assessing rater reliability. Psychol Bull 1979; 86 (02) 420-428