Rasch analysis of the forgotten joint score in patients with total hip arthroplasty

Authors

  • Flavia Stano Department of Medicine and Health Science “Vincenzo Tiberio”, University of Molise, Campobasso, Italy
  • Leonardo Pellicciari IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
  • Fabio La Porta IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
  • Daniele Piscitelli Department of Kinesiology, University of Connecticut, Storrs, CT, US
  • Domenico Angilecchia Department of Medicine and Health Science “Vincenzo Tiberio”, University of Molise, Campobasso, Italy; Rehabilitation service - ASL, Bari, Italy
  • Maria Signorelli Rehabilitation Service "San Giovanni di Dio", Adelfia, Italy
  • Giuseppe Giovannico Department of Medicine and Health Scienze "Vincenzo Tiberio", University of Molise, Campobasso, Italy
  • Sanaz Pournajaf Neurorehabilitation Research Lab, Department of Neurological and Rehabilitation Sciences, IRCCS San Raffaele, Rome, Italy
  • Serena Caselli Unità Operativa Complessa di Medicina Riabilitativa, Azienda Ospedaliero-Universitaria di Modena, Modena, Italy

DOI:

https://doi.org/10.2340/jrm.v56.15774

Keywords:

Arthroplasty, Replacement, Hip, Patient Reported Outcome Measures, Psychometrics, Outcome Assessment, Health Care

Abstract

Objective: To assess the internal construct validity, including local independence, unidimensionality, monotonicity, and invariance, reliability, and targeting of the Forgotten Joint Score within the Rasch Measurement Theory framework.

Design: Cross-sectional study.

Patients: A total of 111 patients with total hip arthroplasty at least 3 months after surgery.

Methods: The Forgotten Joint Score was submitted to each subject during their rehabilitative treatment in an Italian centre and then to Rasch analysis.

Results: The base Rasch analysis showed a satisfactory fit to the model with strict unidimensionality and no differential item functioning. However, monotonicity (11 out of 12 items showed disordered thresholds) and local independence were  violated. After rescoring 10 items and creating 5 subtests to account for local dependence, the scale satisfied all the other Rasch model requirements (i.e. invariance, local independence, monotonicity, unidimensionality, and multi-group invariance), with reliability indexes (> 0.850) for measurement at the individual level and proper targeting. A raw-score-to-measure conversion table was provided.

Conclusion: After structural (i.e. collapsing items categories) and non-structural (i.e. creating subtests) strategies, the Forgotten Joint Score satisfied the measurement requirements of the Rasch model, and it can be used in patients with total hip arthroplasty in clinical and research settings.

Downloads

Download data is not yet available.

References

Charnley J. Arthroplasty of the hip. a new operation. Lancet 1961; 1: 1129-1132.

https://doi.org/10.1016/S0140-6736(61)92063-3 DOI: https://doi.org/10.1016/S0140-6736(61)92063-3

Hussein IH, Zalikha AK, Tuluca A, Crespi Z, El-Othmani MM. Epidemiology of obese patients undergoing revision total knee arthro-plasty: understanding demographics, comorbidities, and propensity weighted analysis of inpatient outcomes. J Am Acad Orthop Surg Glob Res Rev 2022; 6: e21.00263.

https://doi.org/10.5435/JAAOSGlobal-D-21-00263 DOI: https://doi.org/10.5435/JAAOSGlobal-D-21-00263

Ethgen O, Bruyere O, Richy F, Dardennes C, Reginster JY. Health-related quality of life in total hip and total knee arthroplasty. A qualitative and systematic review of the literature. J Bone Joint Surg Am 2004; 86: 963-974.

https://doi.org/10.2106/00004623-200405000-00012 DOI: https://doi.org/10.2106/00004623-200405000-00012

Torre M, Ceccarelli S, Biondi A, Carrani E, Cornacchia A, Mari V, et al. Registro Italiano ArtroProtesi. Report Annuale 2021. Roma; 2022.

Pennington MW, Grieve R, van der Meulen JH. Lifetime cost effectiveness of different brands of prosthesis used for total hip arthro-plasty: a study using the NJR dataset. Bone Joint J 2015; 97-B: 762-770.

https://doi.org/10.1302/0301-620X.97B6.34806 DOI: https://doi.org/10.1302/0301-620X.97B6.34806

Basch E, Barbera L, Kerrigan CL, Velikova G. Implementation of patient-reported outcomes in routine medical care. Am Soc Clin Oncol Educ Book 2018; 38: 122-134.

https://doi.org/10.1200/EDBK_200383 DOI: https://doi.org/10.1200/EDBK_200383

Staniszewska S, Haywood KL, Brett J, Tutton L. Patient and public involvement in patient-reported outcome measures: evolution not revolution. Patient 2012; 5: 79-87.

https://doi.org/10.2165/11597150-000000000-00000 DOI: https://doi.org/10.2165/11597150-000000000-00000

Behrend H, Giesinger K, Giesinger JM, Kuster MS. The "forgotten joint" as the ultimate goal in joint arthroplasty: validation of a new patient-reported outcome measure. J Arthroplasty 2012; 27: 430-436.e431.

https://doi.org/10.1016/j.arth.2011.06.035 DOI: https://doi.org/10.1016/j.arth.2011.06.035

Longo UG, De Salvatore S, Piergentili I, Indiveri A, Di Naro C, Santamaria G, et al. Total hip arthroplasty: minimal clinically im-portant difference and patient acceptable symptom state for the forgotten joint score 12. Int J Environ Res Public Health2021; 18: 2267.

https://doi.org/10.3390/ijerph18052267 DOI: https://doi.org/10.3390/ijerph18052267

Angilecchia D, Stano F, Signorelli M, Giovannico G, Pournajaf S, Pellicciari L. Psychometric properties of the Italian version of the Forgotten Joint Score in patients with total hip arthroplasty. Int J Rehabil Res 2022; 45: 343-349.

https://doi.org/10.1097/MRR.0000000000000549 DOI: https://doi.org/10.1097/MRR.0000000000000549

Hu L-t, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equat Model 2009; Volume 6.

https://doi.org/10.1080/10705519909540118 DOI: https://doi.org/10.1080/10705519909540118

Andrich D. Rasch models for measurement. London: Sage Publications; 1988.

https://doi.org/10.4135/9781412985598 DOI: https://doi.org/10.4135/9781412985598

La Porta F, Franceschini M, Caselli S, Cavallini P, Susassi S, Tennant A. Unified Balance Scale: an activity-based, bed to communi-ty, and aetiology-independent measure of balance calibrated with rasch analysis. J Rehabil Med 2011; 43: 435-444.

https://doi.org/10.2340/16501977-0797 DOI: https://doi.org/10.2340/16501977-0797

Tennant A, Conaghan PG. The Rasch measurement model in rheumatology: what is it and why use it? When should it be applied, and what should one look for in a Rasch paper? Arthritis Rheum 2007; 57: 1358-1362.

https://doi.org/10.1002/art.23108 DOI: https://doi.org/10.1002/art.23108

Hobart J, Cano S. Improving the evaluation of therapeutic interventions in multiple sclerosis: the role of new psychometric methods. Health Technol Assess 2009; 13: iii, ix-x, 1-177.

https://doi.org/10.3310/hta13120 DOI: https://doi.org/10.3310/hta13120

Niama Natta DD, Thienpont E, Bredin A, Salaun G, Detrembleur C. Rasch analysis of the Forgotten Joint Score in patients undergoing knee arthroplasty. Knee Surg Sports Traumatol Arthrosc 2019; 27: 1984-1991.

https://doi.org/10.1007/s00167-018-5109-x DOI: https://doi.org/10.1007/s00167-018-5109-x

Wright BD. Model selection: Rating Scale Model (RSM) or Partial Credit Model (PCM)? Rasch Measure Trans 1998; 12: 641-642

Pellicciari L, Piscitelli D, Basagni B, De Tanti A, Algeri L, Caselli S, et al. 'Less is more': validation with Rasch analysis of five short-forms for the Brain Injury Rehabilitation Trust Personality Questionnaires (BIRT-PQs). Brain Inj 2020; 34: 1741-1755.

https://doi.org/10.1080/02699052.2020.1836402 DOI: https://doi.org/10.1080/02699052.2020.1836402

Caselli S, Kreiner S, Ianes AB, Piperno R, F LAP. The Early Functional Abilities-revised may bridge the gap between the disorder of consciousness and the functional independence scales: evidence from Rasch analysis. Eur J Phys Rehabil Med 2022; 58: 805-817.

https://doi.org/10.23736/S1973-9087.22.07522-0 DOI: https://doi.org/10.23736/S1973-9087.22.07522-0

Pellicciari L, Piscitelli D, Caselli S, La Porta F. A Rasch analysis of the Conley Scale in patients admitted to a general hospital. Disabil Rehabil 2019; 41: 2807-2816.

https://doi.org/10.1080/09638288.2018.1478000 DOI: https://doi.org/10.1080/09638288.2018.1478000

La Porta F, Caselli S, Susassi S, Cavallini P, Tennant A, Franceschini M. Is the Berg Balance Scale an internally valid and reliable measure of balance across different etiologies in neurorehabilitation? a revisited Rasch analysis study. Arch Phys Med Rehabil 2012; 93: 1209-1216.

https://doi.org/10.1016/j.apmr.2012.02.020 DOI: https://doi.org/10.1016/j.apmr.2012.02.020

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

La Porta F, Giordano A, Caselli S, Foti C, Franchignoni F. Is the Berg Balance Scale an effective tool for the measurement of early postural control impairments in patients with Parkinson's disease? Evidence from Rasch analysis. Eur J Phys Rehabil Med 2015; 51: 705-716.

Kreiner S. The Rasch model for dichotomous items. In: Christensen KB, Kreiner S, Mesbah M, editors. in Rasch Models in Health. London UK, Hoboken NJ: ISTE Ltd and John Wiley & Sons, Inc; 2013

https://doi.org/10.1002/9781118574454.ch1 DOI: https://doi.org/10.1002/9781118574454.ch1

Christensen KB, Makransky G, Horton M. Critical Values for Yen's Q3: Identification of Local Dependence in the Rasch Model Using Residual Correlations. Appl Psychol Meas 2017; 41: 178-194.

https://doi.org/10.1177/0146621616677520 DOI: https://doi.org/10.1177/0146621616677520

Fisher WPj. Rating scale instrument quality criteria. Rasch Measurement Transactions 2007; 21:1: 1095.

Kreiner S, Christensen KB. Person parameter estimation and measurement in Rasch Models. In: Christensen KB, Kreiner S, Mesbah M, editors. In: Rasch Models in Health. London UK, Hoboken NJ: ISTE Ltd and John Wiley & Sons, Inc; 2013.

https://doi.org/10.1002/9781118574454 DOI: https://doi.org/10.1002/9781118574454

Wright BD. Separation, reliability and skewed distributions: statistically different levels of performance. Rasch Measure Trans 2001; 14.

Reeve BB, Hays RD, Bjorner JB, Cook KF, Crane PK, Teresi JA, 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: S22-31.

https://doi.org/10.1097/01.mlr.0000250483.85507.04 DOI: https://doi.org/10.1097/01.mlr.0000250483.85507.04

Revicki DA, Chen W, Tucker CA. Developing item banks for patient-reported health outcomes. In: Reise PS, Revicki DA, editors. Handbook of Item Response Theory Modeling: applications to typical performance assessments. New York; 2014.

Lundgren Nilsson A, Tennant A. Past and present issues in Rasch analysis: the functional independence measure (FIM) revisited. J Rehabil Med 2011; 43: 884-891.

https://doi.org/10.2340/16501977-0871 DOI: https://doi.org/10.2340/16501977-0871

Maritz R, Tennant A, Fellinghauer C, Stucki G, Prodinger B. The Functional Independence Measure 18-item version can be reported as a unidimensional interval-scaled metric: Internal construct validity revisited. J Rehabil Med 2019; 51: 193-200.

https://doi.org/10.2340/16501977-2525 DOI: https://doi.org/10.2340/16501977-2525

Franchignoni F, Horak F, Godi M, Nardone A, Giordano A. Using psychometric techniques to improve the Balance Evaluation Systems Test: the mini-BESTest. J Rehabil Med 2010; 42: 323-331.

https://doi.org/10.2340/16501977-0537 DOI: https://doi.org/10.2340/16501977-0537

Linacre JM. Optimizing rating scale category effectiveness. J Appl Meas 2002; 3: 85-106.

Bland J, Altman D. Multiple significance tests: the Bonferroni method. Br Med J 1995; 310: 170.

https://doi.org/10.1136/bmj.310.6973.170 DOI: https://doi.org/10.1136/bmj.310.6973.170

Linacre JM. Sample size and item calibration stability. Rasch Meas Trans 1994;7:328.; 7: 328.

Marais I. Local dependence. In: Christensen KB, Kreiner S, Mesbah M, editors. in Rasch models in health. London UK, Hoboken NJ: ISTE Ltd and John Wiley & Sons, Inc; 2013.

Caselli S, Sabattini L, Cattaneo D, Jonsdottir J, Brichetto G, Pozzi S, et al. When 'good' is not good enough: a retrospective Rasch analysis study of the Berg Balance Scale for persons with multiple sclerosis. Front Neurol 2023; 14: 1171163.

https://doi.org/10.3389/fneur.2023.1171163 DOI: https://doi.org/10.3389/fneur.2023.1171163

Giesinger JM, Kuster MS, Holzner B, Giesinger K. Development of a computer-adaptive version of the forgotten joint score. J Arthro-plasty 2013; 28: 418-422.

https://doi.org/10.1016/j.arth.2012.08.026 DOI: https://doi.org/10.1016/j.arth.2012.08.026

Aman JE, Elangovan N, Yeh IL, Konczak J. The effectiveness of proprioceptive training for improving motor function: a systematic review. Front Hum Neurosci 2014; 8: 1075.

https://doi.org/10.3389/fnhum.2014.01075 DOI: https://doi.org/10.3389/fnhum.2014.01075

Di Laura Frattura G, Bordoni V, Feltri P, Fusco A, Candrian C, Filardo G. Balance remains impaired after hip arthroplasty: a systema-tic review and best evidence synthesis. Diagnostics (Basel) 2022; 12: 684.

https://doi.org/10.3390/diagnostics12030684 DOI: https://doi.org/10.3390/diagnostics12030684

Moutzouri M, Gleeson N, Billis E, Tsepis E, Panoutsopoulou I, Gliatis J. The effect of total knee arthroplasty on patients' balance and incidence of falls: a systematic review. Knee Surg Sports Traumatol Arthrosc 2017; 25: 3439-3451.

https://doi.org/10.1007/s00167-016-4355-z DOI: https://doi.org/10.1007/s00167-016-4355-z

Published

2024-01-10

How to Cite

Stano, F., Pellicciari, L., La Porta, F., Piscitelli, D., Angilecchia, D., Signorelli, M., … Caselli, S. (2024). Rasch analysis of the forgotten joint score in patients with total hip arthroplasty. Journal of Rehabilitation Medicine, 56, jrm15774. https://doi.org/10.2340/jrm.v56.15774

Issue

Section

Original Report

Categories