Health and Quality of Life Outcomes | |
Measurement of change in health status with Rasch models | |
Giorgio Bertolotti2  Ornella Bettinardi4  Giulio Vidotto3  Pasquale Anselmi1  | |
[1] Department FISPPA, University of Padova, Via Venezia 8, Padova, 35131, Italy;Psychology Unit, Maugeri Foundation, Via Roncaccio 16, Tradate, 21029, VA, Italy;Department of General Psychology, University of Padova, Via Venezia 8, Padova, 35131, Italy;Department of Mental Health and Pathological Addiction, Via delle Valli 5, Piacenza, 29121, Italy | |
关键词: Item response theory; Rasch; Rehabilitation; Health status; Measurement of change; | |
Others : 1133870 DOI : 10.1186/s12955-014-0197-x |
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received in 2014-04-11, accepted in 2014-12-18, 发布年份 2015 | |
【 摘 要 】
Background
The traditional approach to the measurement of change presents important drawbacks (no information at individual level, ordinal scores, variance of the measurement instrument across time points), which Rasch models overcome. The article aims to illustrate the features of the measurement of change with Rasch models.
Methods
To illustrate the measurement of change using Rasch models, the quantitative data of a longitudinal study of heart-surgery patients (N = 98) were used. The scale “Perception of Positive Change” was used as an example of measurement instrument. All patients underwent cardiac rehabilitation, individual psychological intervention, and educational intervention. Nineteen patients also attended progressive muscle relaxation group trainings. The scale was administered before and after the interventions. Three Rasch approaches were used. Two separate analyses were run on the data from the two time points to test the invariance of the instrument. An analysis was run on the stacked data from both time points to measure change in a common frame of reference. Results of the latter analysis were compared with those of an analysis that removed the influence of local dependency on patient measures. Statistics t, χ2 and F were used for comparing the patient and item measures estimated in the Rasch analyses (a-priori α = .05). Infit, Outfit, R and item Strata were used for investigating Rasch model fit, reliability, and validity of the instrument.
Results
Data of all 98 patients were included in the analyses. The instrument was reliable, valid, and substantively unidimensional (Infit, Outfit < 2 for all items, R = .84, item Strata range = 3.93-6.07). Changes in the functioning of the instrument occurred across the two time, which prevented the use of the two separate analyses to unambiguously measure change. Local dependency had a negligible effect on patient measures (p ≥ .8674). Thirteen patients improved, whereas 3 worsened. The patients who attended the relaxation group trainings did not report greater improvement than those who did not (p = .1007).
Conclusions
Rasch models represent a valid framework for the measurement of change and a useful complement to traditional approaches.
【 授权许可】
2015 Anselmi et al.; licensee BioMed Central.
【 预 览 】
Files | Size | Format | View |
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20150304195048786.pdf | 452KB | download | |
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Figure 1. | 43KB | Image | download |
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【 参考文献 】
- [1]Husted JA, Cook RJ, Farewell VT, Gladman DD: Methods for assessing responsiveness: a critical review and recommendations. J Clin Epidemiol. 2000, 53:459-68.
- [2]Beaton DE, Hogg-Johnson S, Bombardier C: Evaluating changes in health status: reliability and responsiveness of five generic health status measures in workers with musculoskeletal disorders. J Clin Epidemiol. 1997, 50:79-93.
- [3]Cohen J: Statistical power analysis for the behavioral sciences. 2nd edition. Erlbaum, New Jersey; 1988.
- [4]Fischer GH: The precision of gain scores under an item response theory perspective: a comparison of asymptotic and exact conditional inference about change. Appl Psych Meas. 2003, 27:3-26.
- [5]Kahler E, Rogausch A, Brunner E, Himmel W: A parametric analysis of ordinal quality-of-life data can lead to erroneous results. J Clin Epidemiol. 2008, 61:475-80.
- [6]Wright BD: Comparisons require stability. Rasch Meas Trans. 1996, 10:506.
- [7]Rasch G: Probabilistic models for some intelligence and attainment test. Copenhagen: Danish Institute for Educational Research; 1960. Reprinted. The University of Chicago Press, Chicago; 1980.
- [8]Andrich D: Rasch models for measurement. Sage, Beverly Hills; 1988.
- [9]Bond TG, Fox CM: Applying the Rasch model: fundamental measurement in the human sciences. Lawrence Erlbaum, Mahwah; 2001.
- [10]Anselmi P, Vianello M, Voci A, Robusto E: Implicit sexual attitude of heterosexual, gay and bisexual individuals: disentangling the contribution of specific associations to the overall measure. Plos One. 2013, 8:e78990.
- [11]Anselmi P, Vianello M, Robusto E: Preferring thin people does not imply derogating fat people. A Rasch analysis of the implicit weight attitude. Obesity. 2013, 21:261-5.
- [12]Fisher AG: The assessment of IADL motor skills: an application of many-facet Rasch analysis. Am J Occup Ther. 1993, 47:319-29.
- [13]Haley SM, McHorney CA, Ware JE Jr: Evaluation of the MOS SF-36 physical functioning scale (PF-10): I. unidimensionality and reproducibility of the Rasch item scale. J Clin Epidemiol 1994, 47:671-84.
- [14]Heinemann AW, Linacre JM, Wright BD, Hamilton BB, Granger C: Relationships between impairment and physical disability as measured by the functional independence measure. Arch Phys Med Rehab. 1993, 74:566-73.
- [15]Heinemann AW, Linacre JM, Wright BD, Hamilton BB, Granger C: Prediction of rehabilitation outcomes with disability measures. Arch Phys Med Rehab. 1994, 75:133-43.
- [16]Ludlow LH, Haley SM, Gans BM: A hierarchical model of functional performance in rehabilitation medicine: the Tufts assessment of motor performance. Eval Health Prof. 1992, 15:59-74.
- [17]Michielin P, Vidotto G, Altoè G, Colombari M, Sartori L, Bertolotti G, et al.: Proposta di un nuovo strumento per la verifica dell'efficacia nella pratica dei trattamenti psicologici e psicoterapeutici. G Ital Med Lav Ergon 2008, 30(Suppl 1A):98-104.
- [18]Bettinardi O, Vidotto G, Moroni L, Pedretti RFE, Maini M, Rosi A, et al.: Measuring change in rehabilitative cardiology: reliability of a short questionnaire to assess an outcome. Monaldi Arch Chest Dis. 2012, 78:97-104.
- [19]Giannuzzi P: National guideline in rehabilitation cardiology and secondary prevention in cardiovascular diseases. Monaldi Arch Chest Dis. 2006, 66:81-116.
- [20]Graham I, Atar D, Borch-Johnsen K, Boysen G, Burell G, Cifkova R, et al.: European guidelines on cardiovascular disease preventionion clinical practice: full text. Fourth Joint Task Force of the European Society of Cardiology and other societies on cardiovascular disease prevention in clinical practice (constituted by representatives of nine societies and by invited experts). Eur J Cardiovasc Prev Rehabil 2007, 14 Suppl 2:1-113.
- [21]Jacobson E: Progressive relaxation. University of Chicago Press, Chicago; 1938.
- [22]Fair PL: Biofeedback-assisted relaxation strategies in psychotherapy. In Biofeedback: principles and practice for clinicians. Edited by Basmajian JV. Williams and Wilkins, Baltimore; 1983.
- [23]Andrich D: A rating scale formulation for ordered response categories. Psychometrika. 1978, 43:561-73.
- [24]Masters GN: A Rasch model for partial credit scoring. Psychometrika. 1982, 47:149-74.
- [25]Mallinson T: Rasch analysis of repeated measures. Rasch Meas Trans. 2011, 251:1317.
- [26]Wright BD: Rack and stack: time 1 vs. time 2 or pre-test vs. post-test. Rasch Meas Trans 2003, 17:905-6.
- [27]Chien TW: Repeated measure designs (time series) and Rasch. Rasch Meas Trans. 2008, 22:1171.
- [28]Linacre JM: Facets Rasch measurement computer program [computer program]. Version 3.66.0. Winsteps.com, Chicago; 2009.
- [29]Fisher RA: Statistical methods for research workers. 5th edition. Oliver & Boyd, Edinburgh; 1932.
- [30]Linacre JM: What do Infit and Outfit, mean-square and standardized mean? Rasch Meas Trans. 2002, 16:878.
- [31]Smith EV Jr: Evidence for the reliability of measures and validity of measure interpretation:a Rasch measurement perspective. J Appl Meas. 2001, 2:281-311.
- [32]Messick S: Validity. In Educational measurement. 3rd edition. Edited by Linn RL. Macmillan, New York; 1989:13-103.
- [33]Fisher W Jr: Reliability, separation, strata statistics. Rasch Meas Trans. 1992, 6:238.
- [34]Linacre JM: Optimizing rating scale category effectiveness. J Appl Meas. 2002, 3:85-106.
- [35]Andrich D: Controversy and the Rasch model: a characteristic of incompatible paradigms? Med Care. 2004, 42(Suppl 1):7-16.
- [36]Tuley MR, Mulrow CD, McMahan CA: Estimating and testing an index of responsiveness and the relationship of the index to power. J Clin Epidemiol. 1991, 44:417-21.
- [37]Wright JG, Young NL: A comparison of different indices of responsiveness. J Clin Epidemiol. 1997, 50:239-46.
- [38]Cristante F, Robusto E: Assessing change with the extended logistic model. Brit J Math Stat Psychol. 2007, 60:367-75.
- [39]Fischer GH, Parzer P: An extension of the rating scale model with an application to the measurement of change. Psychometrika. 1991, 56:637-51.
- [40]Fischer GH, Ponocny I: An extension of the partial credit model with an application to the measurement of change. Psychometrika. 1994, 59:177-92.
- [41]Miceli R, Settanni M, Vidotto G: Measuring change in training programs: an empirical illustration. Psychol Sci Quart. 2008, 50:433-47.
- [42]Robusto E, Cristante F, Vianello M: Assessing the impact of replication on implicit association test effect by means of the extended logistic model for the assessment of change. Behav Res Methods. 2008, 40:954-60.