期刊论文详细信息
BMC Medical Research Methodology
Re-evaluating a vision-related quality of life questionnaire with item response theory (IRT) and differential item functioning (DIF) analyses
Ger HMB van Rens4  Maaike Langelaan1  Dirk L Knol2  Ruth MA van Nispen3 
[1] Netherlands Institute for Health Services Research (NIVEL), Utrecht, the Netherlands;Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, the Netherlands;EMGO+ Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands;Department of Ophthalmology, Elkerliek Hospital, Helmond, the Netherlands
关键词: Differential item functioning;    Graded response model;    Item response theory;    Vision-related quality of life;    Visual impairment;   
Others  :  1139993
DOI  :  10.1186/1471-2288-11-125
 received in 2010-09-16, accepted in 2011-09-02,  发布年份 2011
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【 摘 要 】

Background

For the Low Vision Quality Of Life questionnaire (LVQOL) it is unknown whether the psychometric properties are satisfactory when an item response theory (IRT) perspective is considered. This study evaluates some essential psychometric properties of the LVQOL questionnaire in an IRT model, and investigates differential item functioning (DIF).

Methods

Cross-sectional data were used from an observational study among visually-impaired patients (n = 296). Calibration was performed for every dimension of the LVQOL in the graded response model. Item goodness-of-fit was assessed with the S-X2-test. DIF was assessed on relevant background variables (i.e. age, gender, visual acuity, eye condition, rehabilitation type and administration type) with likelihood-ratio tests for DIF. The magnitude of DIF was interpreted by assessing the largest difference in expected scores between subgroups. Measurement precision was assessed by presenting test information curves; reliability with the index of subject separation.

Results

All items of the LVQOL dimensions fitted the model. There was significant DIF on several items. For two items the maximum difference between expected scores exceeded one point, and DIF was found on multiple relevant background variables. Item 1 'Vision in general' from the "Adjustment" dimension and item 24 'Using tools' from the "Reading and fine work" dimension were removed. Test information was highest for the "Reading and fine work" dimension. Indices for subject separation ranged from 0.83 to 0.94.

Conclusions

The items of the LVQOL showed satisfactory item fit to the graded response model; however, two items were removed because of DIF. The adapted LVQOL with 21 items is DIF-free and therefore seems highly appropriate for use in heterogeneous populations of visually impaired patients.

【 授权许可】

   
2011 van Nispen et al; licensee BioMed Central Ltd.

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【 参考文献 】
  • [1]Stelmack J: Quality of life of low-vision patients and outcomes of low-vision rehabilitation. Optom Vis Sci 2001, 78:335-342.
  • [2]Klaver CC, Wolfs RC, Vingerling JR, Hofman A, de Jong PT: Age-specific prevalence and causes of blindness and visual impairment in an older population: the Rotterdam Study. Arch Ophthalmol 1998, 116:653-658.
  • [3]McCabe P, Nason F, Demers TP, Friedman D, Seddon JM: Evaluating the effectiveness of a vision rehabilitation intervention using an objective and subjective measure of functional performance. Ophthalmic Epidemiol 2000, 7:259-270.
  • [4]de Boer MR, Twisk J, Moll AC, Volker-Dieben HJM, de Vet HCW, van Rens GHMB: Outcomes of low vision services using optometric and multidisciplinary approaches: a non-randomized comparison. Ophthalmic Physiol Opt 2006, 26:535-544.
  • [5]van Nispen RMA, Knol DL, Langelaan M, de Boer MR, Terwee CB, van Rens GHMB: Applying multilevel item response theory to vision-related quality of life in Dutch visually impaired elderly. Optom Vis Sci 2007, 84:710-720.
  • [6]Birk T, Hickl S, Wahl HW, Miller D, Kämmerer A, Holz F, Becker S, Völcker HE: Development and pilot evaluation of a psychosocial intervention program for patients with age-related macular degeneration. Gerontologist 2004, 44:836-843.
  • [7]Reeves BC, Harper RA, Russell WB: Enhanced low vision rehabilitation for people with age related macular degeneration: a randomised controlled trial. Br J Ophthalmol 2004, 88:1443-1449.
  • [8]Hinds A, Sinclair A, Park J, Suttie A, Paterson H, Macdonald M: Impact of an interdisciplinary low vision service on the quality of life of low vision patients. Br J Ophthalmol 2003, 87:1391-1396.
  • [9]Finger R, Fleckenstein M, Holz F, Scholl H: Quality of life in age-related macular degeneration: a review of available vision-specific psychometric tools. Qual Life Res 2008, 17:559-574.
  • [10]van Nispen RMA, de Boer MR, van Rens GHMB: Additional psychometric information and vision-specific questionnaires are available for age-related macular degeneration. Qual Life Res 2009, 18:65-69.
  • [11]de Boer MR, Moll AC, de Vet HCW, Terwee CB, Volker-Dieben HJM, van Rens GHMB: Psychometric properties of vision-related quality of life questionnaires: a systematic review. Ophthalmic Physiol Opt 2004, 24:257-273.
  • [12]Wolffsohn JS, Cochrane AL: Design of the low vision quality-of-life questionnaire (LVQOL) and measuring the outcome of low-vision rehabilitation. Am J Ophthalmol 2000, 130:793-802.
  • [13]de Boer MR, de Vet HCW, Terwee CB, Moll AC, Volker-Dieben HJM, van Rens GHMB: Changes to the subscales of two vision-related quality of life questionnaires are proposed. J Clin Epidemiol 2005, 58:1260-1268.
  • [14]de Boer MR, Terwee CB, de Vet HCW, Moll AC, Volker-Dieben HJM, van Rens GHMB: Evaluation of cross-sectional and longitudinal construct validity of two vision-related quality of life questionnaires: the LVQOL and VCM1. Qual Life Res 2006, 15:233-248.
  • [15]van Nispen RMA, Knol DL, Neve JJ, van Rens GHMB: A multilevel item response theory model was investigated for longitudinal vision-related quality of life data. J Clin Epidemiol 2010, 63:321-330.
  • [16]Reeve BB, Hays RD, Chang C-H, Perfetto EM: Applying item response theory to enhance health outcomes assessment. Qual Life Res 2007, 16:1-3.
  • [17]Massof RW: An interval-scaled scoring algorithm for visual function questionnaires. Optom Vis Sci 2007, 84:689-704.
  • [18]Langelaan M, van Nispen RMA, Knol DL, Moll AC, de Boer MR, Wouters B, van Rens GHMB: Visual Functioning Questionnaire: reevaluation of psychometric properties for a group of working-age adults. Optom Vis Sci 2007, 84:775-784.
  • [19]Lamoureux E, Pesudovs K, Pallant J, Rees G, Hassell JB, Caudle LE, Keeffe JE: An evaluation of the 10-item Vision Core Measure 1 (VCM1) scale (the Core Module of the Vision-related Quality of Life scale) using Rasch analysis. Ophthalmic Epidemiol 2008, 15:224-233.
  • [20]Embretson S, Reise S: Item response theory for psychologists. Mahwah, NJ: Erlbaum; 2000.
  • [21]Tutz G: Sequential item response models with an ordered response. Brit J Math Stat Psychol 1990, 43:39-55.
  • [22]van Engelenburg G: On psychometric models for polytomous items with ordered categories within the framework of item response theory. University of Amsterdam, the Netherlands; 1997.
  • [23]Akkermans LMW: Studies on statistical models for polytomously scored test items. University of Twente, the Netherlands; 1998.
  • [24]Skrondal A, Rabe-Hesketh S: Generalized latent variable modeling: multilevel, longitudinal, and structural equation models. London, UK: Chapman & Hall; 2004:113.
  • [25]Sass DA, Schmitt TA, Walker CM: Estimating non-normal latent trait distributions within item response theory using true and estimated item parameters. Appl Meas Educat 2008, 21:65-88.
  • [26]Orlando Edelen M, Reeve BB: Applying item response theory (IRT) modeling to questionnaire development, evaluation, and refinement. Qual Life Res 2007, 16:5-18.
  • [27]Crane P, van Belle G, Larson E: Test bias in a cognitive test: differential item functioning in the CASI. Stat Med 2004, 23:241-256.
  • [28]Teresi J, Fleishman J: Differential item functioning and health assessment. Qual Life Res 2007, 16:33-42.
  • [29]Reeve BB, Hays RD, Bjorner JB, Cook KF, Crane PK, Teresi JA, Thissen D, Revicki DA, Weiss DJ, Hambleton RK, Liu H, Gershon R, Reise SP, Lai J, Cella D: 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-S31.
  • [30]Samejima F: Estimation of latent ability using response pattern of graded scores. Psychometric Monograph Supplement No 17: Richmond, VA: William Byrd Press; 1969.
  • [31]Thissen D: MULTILOG™ User's guide. Multiple, categorical item analysis and test scoring using item response theory. Chicago: Scientific Software Inc.; 1991.
  • [32]Bjorner J, Christensen K, Orlando M, Thissen D: [http://www.isoqol.org/2005ConfAbstracts.pdf] webciteTesting the fit of item response theory models for patient reported outcomes. 2005. International Society for Quality of Life Research meeting abstracts. webciteThe QLR journal, P-151, Abstract #1676
  • [33]Orlando M, Thissen D: Likelihood-based item-fit indices for dichotomous item response theory models. Appl Psychol Meas 2000, 24:50-64.
  • [34]Orlando M, Thissen D: Further examination of the performance of S-X2, an item fit index for dichotomous item response theory models. Appl Psychol Meas 2003, 27:289-298.
  • [35]Teresi J, Ocepek-Welikson K, Kleinman M, Cook KF, Crane PK, Gibbons LE, Morales LS, Orlando-Edelen M, Cella D: Evaluating measurement equivalence using item response theory log-likelihood ratio (IRTLR) method to assess differential item functioning (DIF): applications (with illustrations) to measures of physical functioning ability and general distress. Qual Life Res 2007, 16:43-68.
  • [36]Thissen D: IRTLRDIF v.2.0b: Software for the computation of the statistics involved in item response theory likelihood-ratio tests for differential item functioning. Chapel Hill, NC: L.L. Thurstone Psychometric Laboratory, University of North Carolina at Chapel Hill; 2001.
  • [37]Thissen D: IRTLRDIF software. [http://www.unc.edu/~dthissen/dl.html] webcite Accessed at 14 Sep 2010
  • [38]Langer M, Hill C, Thissen D, Burwinkle T, Varni J, DeWalt D: Item response theory detected differential item functioning between healthy and ill children in quality-of-life measures. J Clin Epidemiol 2008, 61:268-276.
  • [39]Gustafsson J: The Rasch model for dichotomous items: Theory, applications and a computer program. (Internal Rep No. 63) Institute of Education, University of Goteborg; 1977.
  • [40]Wolffsohn JS, Cochrane AL, Watt NA: Implementation methods for vision related quality of life questionnaires. Br J Ophthalmol 2000, 84:1035-1040.
  • [41]van Nispen RMA, Knol DL, Mokkink LB, Comijs HC, Deeg DJH, van Rens GHMB: Vision-related quality of life Core Measure (VCM1) showed low-impact differential item functioning between groups with different administration modes. J Clin Epidemiol 2010, 63:1232-1241.
  • [42]Schwartz N, Strack F, Hippler H, Bishop G: The impact of administration mode on response effects in survey measurement. Appl Cognitive Psychol 1991, 5:193-212.
  • [43]Raju NS, Oshima TC: Two prophecy formulas for assessing the reliability of item response theory-based ability estimates. Educat Psychol Meas 2005, 65:361.
  • [44]Samejima F: Estimation of reliability coefficients using the test information function and its modifications. Appl Psychol Meas 1994, 18:229.
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