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Health and Quality of Life Outcomes
Published in: Health and Quality of Life Outcomes 1/2020

Open Access 01-12-2020 | Research

Functioning of young patients with cerebral palsy: Rasch analysis of the pediatric evaluation of disability inventory computer adaptive test daily activity and mobility

Authors: Maíra Ferreira Amaral, Rosana Ferreira Sampaio, Wendy Jane Coster, Mariana Peixoto Souza, Marisa Cotta Mancini

Published in: Health and Quality of Life Outcomes | Issue 1/2020

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Abstract

Background

People with cerebral palsy experience limitations in performing activities of daily living. Rehabilitation practitioners seek valid instruments to measure changes in the performance of those activities. The Pediatric Evaluation of Disability Inventory Computer Adaptive Test (PEDI-CAT) is a new tool to assess functioning in children and youth with various health conditions. Its validity needs to be evaluated in a way that is consistent with the theoretical model on which it was based. We aimed to evaluate the fit of daily activity and mobility items and children with CP to the Rasch model and to compare the performance in daily activities and mobility of older children, adolescents, and young adults with CP based on manual function and gross motor function limitations.

Methods

Eighty-three parents of children and youth of 8–20 years old (mean age: 11.6) with different severity levels of cerebral palsy participated in this study. Ninety-one items of the PEDI-CAT Daily Activities and Mobility domains were analyzed through Rasch analysis to evaluate relative item difficulty and participant ability. Participants were described according to the Manual Ability (MACS) (level I: 21.7%; II: 32.5%; III: 24.1%; IV: 7.2% and V: 3.6%) and the Gross Motor Function (GMFCS) (level I: 37.3%; II: 26.5%; III: 6%; IV: 18.1%; and V: 7.2%) classification systems levels.

Results

Our data fit the Rasch Model. Parents had difficulty distinguishing some PEDI-CAT response categories. Participants from MACS and GMFCS levels IV and V showed lower ability to perform relatively more difficult items. There was a floor effect in both domains. Only 7.7% of the items presented differential item functioning when individuals with mild MACS and GMFCS levels (I, II) and moderate level (III) and individuals with moderate (III) and severe levels (IV, V) were compared.

Conclusions

PEDI-CAT daily activities and mobility domains are valid to evaluate children, adolescents and youth with CP of different severities, but the addition of items to these domains is recommended in order to address their floor effect.
Appendix
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Literature
1.
Mutlu A, Büğüsan S, Kara ÖK. Impairments, activity limitations, and participation restrictions of the international classification of functioning, disability, and health model in children with ambulatory cerebral palsy. Saudi Med J. 2017;38(2):176–85.PubMedPubMedCentralCrossRef
2.
World Health Organization. International classification of functioning, disability and health: ICF. Geneva: World Health Organization; 2001.
3.
Law M, Darrah J. Emerging therapy approaches: an emphasis on function. J Child Neurol. 2014;29(8):1101–7.PubMedCrossRef
4.
Vos R, Becher J, Ketelaar M, Smits D, Voorman J, Tan SS, et al. Developmental trajectories of daily activities in children and adolescents with cerebral palsy. Pediatrics. 2013;132(4):e915–23.PubMedCrossRef
5.
Cusick A, Mcintyre S, Novak I, Lannin N, Lowe K. A comparison of goal attainment scaling and the Canadian occupational performance measure for pediatric rehabilitation research. PediatrRehabil. 2006;9(2):149–57.
6.
James S, Ziviani J, Boyd R. A systematic review of activities of daily living measures for children and adolescents with cerebral palsy. Dev Med Child Neurol. 2014;56:233–44.PubMedCrossRef
7.
Hilton CL, Goloff SE, Altaras O, Josman N. Centennial vision—review of instrument development and testing studies for children and youth. Am J OccupTher. 2013;67:e30-54.CrossRef
8.
Wright FV, Majnemer A. The concept of a toolbox of outcome measures for children with cerebral palsy: why, what, and how to use? J Child Neurol. 2014;29(8):1055–65.PubMedCrossRef
9.
Himuro N, Abe H, Nishibu H, Seino T, Mori M. Easy-to-use clinical measures of walking ability in children and adolescents with cerebral palsy: a systematic review. DisabilRehabil. 2016;39(10):957–68.
10.
Haley SM, Coster WJ, Dumas HM, Fragala-Pinkham MA, Moed R. PEDI-CAT development, standardization and administration manual. Boston: CREcare; 2012.
11.
Debuse D, Brace H. Outcome measures of activity for children with cerebral palsy: a systematic review. PediatrPhysTher. 2011;23:221–31.
12.
Smits D, Gorter JW, Van-Schie PE, Dallmeijer AJ, Ketelaar M. How do changes in motor capacity, motor capability, and motor performance relate in children and adolescents with cerebral palsy? Arch Phys Med Rehabil. 2014;95:1577–84.PubMedCrossRef
13.
Ohrvall AM, Eliasson AC, Lowing K, Odman P, Krumlinde-Sundholm L. Self-care and mobility skills in children with cerebral palsy, related to their manual ability and gross motor function classifications. Dev Med Child Neurol. 2010;52(11):1048–55.PubMedCrossRef
14.
Haley SM, Coster WJ, Kao YC, Dumas HM, Fragala-Pinkham MA, Kramer J, et al. Lessons from use of the Pediatric Evaluation of Disability Inventory: where do we go from here? PediatrPhysTher. 2010;22(1):69–75.
15.
Haley SM, Coster WJ, Dumas HM, Fragala-Pinkham MA, Kramer J, Ni P, et al. Accuracy and precision of the Pediatric Evaluation of Disability Inventory computer-adaptive tests (PEDI-CAT). Dev Med Child Neurol. 2011;53(12):1100–6.PubMedPubMedCentralCrossRef
16.
Dumas HM, Fragala-Pinkham MA. Concurrent validity and reliability of the pediatric evaluation of disability inventory-computer. PediatrPhysTher. 2012;24:171–6.
17.
Fragala-Pinkham MA, Dumas HM, Lombard KA, O’Brien JE. Responsiveness of the Pediatric Evaluation of Disability Inventory-Computer Adaptive Test in measuring functional outcomes for inpatient pediatric rehabilitation. J PediatrRehabil Med. 2016;9(3):215–22.
18.
Kramer J, Coster W, Kao YC, Snow A, Orsmond G. A new approach to the measurement of adaptive behavior: development of the PEDI-CAT for children and youth with autism spectrum disorders. PhysOccupTherPediatr. 2012;32:34–47.
19.
Dumas HM, Fragala-Pinkham MA, Rosen EL, O’Brien JE. Construct validity of the pediatric evaluation of disability inventory computer adaptive test (PEDI-CAT) in children with medical complexity. DisabilRehabil. 2017;39(23):2446–51.
20.
Mann TN, Donald KA, Laughton B, Lamberts RP, Langerak NG. HIV encephalopathy with bilateral lower limb spasticity: upper limb motor function and level of activity and participation. Dev Med Child Neurol. 2017;59:412–9.PubMedCrossRef
21.
Pasternak A, Sideridis G, Fragala-Pinkham MA, Glanzman AM, Montes J, Dunaway S, et al. Raschanalyzes of the pediatric evaluation of disability inventory-computer adaptive test (PEDI-CAT) item bank for children and young adults with spinal muscular atrophy. Muscle Nerve. 2016;54(6):1097–107.PubMedCrossRef
22.
Frazier K, Lynch M, Sump C, Conaway M, Stevenson R. Validation and feasibility of the Pediatric Evaluation of Disability Inventory-Computer Adapted Test (PEDI-CAT) in a cerebral palsy clinic. Dev Med Child Neurol. 2016;58(S5):90–90.
23.
Shore BJ, Allar BG, Miller PE, Matheney TH, Snyder BD, Fragala-Pinkham MA. Evaluating the discriminant validity of the Pediatric Evaluation of Disability Inventory: Computer Adaptive Test in children with cerebral palsy. PhysTher. 2017;97(6):669–76.
24.
Burgess A, Boyd R, Chatfield MD, Ziviani J, Sakzewski L. Self-care and manual ability in children with cerebral palsy: a longitudinal study. Dev Med Child Neurol. 2020;62(9):1061–7.PubMedCrossRef
25.
Tesio L. Measuring behaviors and perceptions: Raschanalyzes as a tool for rehabilitation research. J Rehabil Med. 2003;35:105–15.PubMedCrossRef
26.
Franchignoni F, Giordano A, Ferriero G. Considerations about the use and misuse of Rasch analysis in rehabilitation outcome studies. Eur J PhysRehabil Med. 2009;45(2):289–91.
27.
Mancini MC, Coster WJ, Amaral MF, Avelar BS, Freitas R, Sampaio RF. New version of the Pediatric Evaluation of Disability Inventory (PEDI-CAT): translation, cultural adaptation to Brazil and analyses of psychometric properties. Braz J PhysTher. 2016;20(6):561–70.CrossRef
28.
Linacre JM. Sample size and item calibration stability. RaschMeas Trans. 1994;7:328.
29.
Palisano R, Rosenbaum P, Walter S, Russell D, Wood E, Galuppi B. Developmental and reliability of a system to classify gross motor function in children with cerebral palsy. Dev Med Child Neurol. 1997;39(4):214–23.PubMedCrossRef
30.
Eliasson AC, Krumlinde-Sundholm L, Rösblad B, Beckung E, Arner M, Öhrvall AM, Rosenbaum P. The Manual Ability Classification System (MACS) for children with cerebral palsy: scale development and evidence of validity and reliability. Dev Med Child Neurol. 2006;48:549–54.PubMedCrossRef
31.
Linacre JM. Winsteps® Rasch measurement computer program user’s guide. Beaverton, Oregon: Winsteps.com; 2017.
32.
Linacre JM. When to stop removing items and persons in Rasch misfit analyzes? RaschMeas Trans. 2010;23:1241.
33.
Fisher W Jr. Reliability, separation, strata statistics. RaschMeas Trans. 1992;6:238.
34.
Ludlow LH, Rollison J, Cronin J, Wallingford T. Development of the teaching economic literacy: confidence and anxiety (TELCA) instrument. Int J EducPsychol Assess. 2012;9(2):82–103.
35.
Coster WJ, Kramer JMF, Dooley M, Liljenquist K, Kao YC, Ni P. Evaluating the appropriateness of a new computer-administered measure of adaptive function for children and youth with autism spectrum disorders. Autism. 2016;20(1):14–25.PubMedCrossRef
36.
Andrade PM, Haase VG, Oliveira-Ferreira F. An ICF-based approach for cerebral palsy from a biopsychosocial perspective. Dev Neurorehabil. 2012;15(6):391–400.PubMedCrossRef
37.
38.
Ohrvall AM, Krumlinde-Sundholm L, Eliasson AC. The stability of the manual ability classification system over time. Dev Med Child Neurol. 2014;56(2):185–9.PubMedCrossRef
39.
Scott NW, Fayers PM, Aaronson NK, Battomley A, Graeff A, Groenvold M, et al. Differential item functioning (DIF) analyses of health-related quality of life instruments using logistic regression. Health Qual Life Outcomes. 2010;8:81.PubMedPubMedCentralCrossRef
40.
Souza MAP, Coster WJ, Mancini MC, Dutra FCMS, Kramer J, Sampaio RF. Rasch analysis of the participation scale (P-scale): usefulness of the P-scale to a rehabilitation services network. BMC Public Health. 2017;17:934.PubMedPubMedCentralCrossRef
41.
Prodinger B, Tennant A, Stucki G. Standardized reporting of functioning information on ICF-based common metrics. Eur J PhysRehabil Med. 2018;54(1):110–7.
42.
Jette AM, Haley SM. Contemporary measurement techniques for rehabilitation outcomes assessment. J Rehabil Med. 2005;37:339–45.PubMedCrossRef
43.
Chantry J, Dunford C. How do computer assistive technologies enhance participation in childhood occupations for children with multiple and complex disabilities? A review of the current literature. Br J OccupTher. 2010;73(8):351–65.CrossRef
44.
McCarty E, Morress C. Establishing access to technology: an evaluation and intervention model to increase the participation of children with cerebral palsy. Phys Med RehabilClin N Am. 2009;20:523–34.CrossRef
45.
Davies C, Mudge S, Ameratunga S, Stotti NS. Enabling self-directed computer use for individuals with cerebral palsy: a systematic review of assistive devices and technologies. Dev Med Child Neurol. 2010;52(6):510–6.PubMedCrossRef
46.
Pakula AT, Braun KVN, Yeargin-Allsopp M. Cerebral palsy: classification and epidemiology. Phys Med RehabilClin N Am. 2009;20:425–52.CrossRef
Metadata
Title
Functioning of young patients with cerebral palsy: Rasch analysis of the pediatric evaluation of disability inventory computer adaptive test daily activity and mobility
Authors
Maíra Ferreira Amaral
Rosana Ferreira Sampaio
Wendy Jane Coster
Mariana Peixoto Souza
Marisa Cotta Mancini
Publication date
01-12-2020
Publisher
BioMed Central
Published in
Health and Quality of Life Outcomes / Issue 1/2020
Electronic ISSN: 1477-7525
DOI
https://doi.org/10.1186/s12955-020-01624-5

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