期刊论文详细信息
Health and Quality of Life Outcomes
Development and calibration of an item bank for the assessment of activities of daily living in cardiovascular patients using Rasch analysis
Markus Wirtz4  Juergen Bengel1  Maren Boecker3  Anne Haschke1  Birgit Abberger1  Harald Baumeister2 
[1] Department of Rehabilitation Psychology and Psychotherapy, Institute of Psychology, University of Freiburg, Engelbergerstraße 41, Freiburg D-79085, Germany;Medical Psychology and Medical Sociology, Medical Faculty, University of Freiburg, Freiburg, Germany;Institute of Medical Psychology and Medical Sociology, University Hospital of RWTH Aachen, Aachen, Germany;Department of Research Methods, Institute of Psychology, University of Education Freiburg, Freiburg, Germany
关键词: Rasch model;    Item response theory;    Item bank;    Computerized adaptive test;    Cardiovascular disease;    Activities of daily living;   
Others  :  823379
DOI  :  10.1186/1477-7525-11-133
 received in 2012-12-05, accepted in 2013-08-01,  发布年份 2013
PDF
【 摘 要 】

Background

To develop and calibrate the activities of daily living item bank (ADLib-cardio) as a prerequisite for a Computer-adaptive test (CAT) for the assessment of ADL in patients with cardiovascular diseases (CVD).

Methods

After pre-testing for relevance and comprehension a pool of 181 ADL items were answered on a five-point Likert scale by 720 CVD patients, who were recruited in fourteen German cardiac rehabilitation centers. To verify that the relationship between the items is due to one factor, a confirmatory factor analysis (CFA) was conducted. A Mokken analysis was computed to examine the double monotonicity (i.e. every item generates an equivalent order of person traits, and every person generates an equivalent order of item difficulties). Finally, a Rasch analysis based on the partial credit model was conducted to test for unidimensionality and to calibrate the item bank.

Results

Results of CFA and Mokken analysis confirmed a one factor structure and double monotonicity. In Rasch analysis, merging response categories and removing items with misfit, differential item functioning or local response dependency reduced the ADLib-cardio to 33 items. The ADLib-cardio fitted to the Rasch model with a nonsignificant item-trait interaction (chi-square=105.42, df=99; p=0.31). Person-separation reliability was 0.81 and unidimensionality could be verified.

Conclusions

The ADLib-cardio is the first calibrated, unidimensional item bank that allows for the assessment of ADL in rehabilitation patients with CVD. As such, it provides the basis for the development of a CAT for the assessment of ADL in patients with cardiovascular diseases. Calibrating the ADLib-cardio in other than rehabilitation cardiovascular patient settings would further increase its generalizability.

【 授权许可】

   
2013 Baumeister et al.; licensee BioMed Central Ltd.

【 预 览 】
附件列表
Files Size Format View
20140713003317802.pdf 677KB PDF download
Figure 1. 71KB Image download
【 图 表 】

Figure 1.

【 参考文献 】
  • [1]Federman AD, Penrod JD, Livote E, Hebert P, Keyhani S, Doucette J, Siu AL: Development of and recovery from difficulty with activities of daily living: an analysis of national data. J Aging Health 2010, 22:1081-1098.
  • [2]von Groote PM, Bickenbach JE, Gutenbrunner C: The world report on disability - implications, perspectives and opportunities for physical and rehabilitation medicine (PRM). J Rehabil Med 2011, 43:869-875.
  • [3]Fieo RA, Austin EJ, Starr JM, Deary IJ: Calibrating ADL-IADL scales to improve measurement accuracy and to extend the disability construct into the preclinical range: a systematic review. BMC Geriatr 2011, 11:42. BioMed Central Full Text
  • [4]Elliott D, Denehy L, Berney S, Alison JA: Assessing physical function and activity for survivors of a critical illness: a review of instruments. Aust Crit Care 2011, 24:155-166.
  • [5]Kucukdeveci AA, Tennant A, Grimby G, Franchignoni F: Strategies for assessment and outcome measurement in physical and rehabilitation medicine: an educational review. J Rehabil Med 2011, 43:661-672.
  • [6]Buurman BM, van Munster BC, Korevaar JC, de Haan RJ, de Rooij SE: Variability in measuring (instrumental) activities of daily living functioning and functional decline in hospitalized older medical patients: a systematic review. J Clin Epidemiol 2011, 64:619-627.
  • [7]Fries JF, Bruce B, Bjorner J, Rose M: More relevant, precise, and efficient items for assessment of physical function and disability: moving beyond the classic instruments. Ann Rheum Dis 2006, 65(Suppl 3):iii16-21.
  • [8]Thomas VS, Rockwood K, McDowell I: Multidimensionality in instrumental and basic activities of daily living. J Clin Epidemiol 1998, 51:315-321.
  • [9]das Nair R, Moreton BJ, Lincoln NB: Rasch analysis of the Nottingham extended activities of daily living scale. J Rehabil Med 2011, 43:944-950.
  • [10]LaPlante MP: The classic measure of disability in activities of daily living is biased by age but an expanded IADL/ADL measure is not. J Gerontol B Psychol Sci Soc Sci 2010, 65:720-732.
  • [11]Hambleton RK: Emergence of item response modeling in instrument development and data analysis. Medical Care 2000, 38:II60-II65.
  • [12]Lundgren NA, Tennant A: Past and present issues in Rasch analysis: the functional independence measure (FIM) revisited. J Rehabil Med 2011, 43:884-891.
  • [13]Heinemann AW, Deutsch A: Commentary on "past and present issues in Rasch analysis: the fim revisited". J Rehabil Med 2011, 43:958-960.
  • [14]Embretson SE, Reise SP: (Eds): Item response theory for psychologists. Mahwah: Lawrence Erlbaum Associates; 2000.
  • [15]van der Linden WJ, Glas CAW: (Eds): Computerized adaptive testing: Theory and practice. Boston, MA: Kluwer Academic; 2000.
  • [16]Gibbons RD, Weiss DJ, Kupfer DJ, Frank E, Fagiolini A, Grochocinski VJ, Bhaumik DK, Stover A, Bock RD, Immekus JC: Using computerized adaptive testing to reduce the burden of mental health assessment. Psychiatr Serv 2008, 59:361-368.
  • [17]Forkmann T, Boecker M, Norra C, Eberle N, Kircher T, Schauerte P, Mischke K, Westhofen M, Gauggel S, Wirtz M: Development of an item bank for the assessment of depression in persons with mental illnesses and physical diseases using Rasch analysis. Rehabil Psychol 2009, 54:186-197.
  • [18]Weisscher N, Glas CA, Vermeulen M, de Haan RJ: The use of an item response theory-based disability item bank across diseases: accounting for differential item functioning. J Clin Epidemiol 2010, 63:543-549.
  • [19]Rose M, Bjorner JB, Becker J, Fries JF, Ware JE: Evaluation of a preliminary physical function item bank supported the expected advantages of the Patient-Reported Outcomes Measurement Information System (PROMIS). J Clin Epidemiol 2008, 61:17-33.
  • [20]Ware JE, Gandek B, Sinclair SJ, Bjorner JB: Item response theory and computerized adaptive testing: implications for outcomes measurement in rehabilitation. Rehabil Psychol 2005, 50:71-78.
  • [21]Haley SM, Ni P, Hambleton RK, Slavin MD, Jette AM: Computer adaptive testing improved accuracy and precision of scores over random item selection in a physical functioning item bank. J Clin Epidemiol 2006, 59:1174-1182.
  • [22]Bode RK, Lai J, Dineen K, Heinemann AW, Shevrin D, von Roenn J, Cella D: Expansion of a physical function item bank and development of an abbreviated form for clinical research. J Appl Meas 2006, 7:1-15.
  • [23]Abberger B, Haschke S, Krense C, Wirtz M, Bengel W, Baumeister H: Development and calibration of an item bank for the assessment of anxiety in cardiovascular patients using Rasch analysis. J Clin Epidemiol 2013, 66:919-928.
  • [24]Haschke A, Abberger B, Muller E, Wirtz M, Bengel J, Baumeister H: Calibration of an item bank for work capacity in cardiological rehabilitation patients. Eur J Prev Cardiolin press
  • [25]Haschke A, Abberger B, Schröder K, Wirtz M, Bengel J, Baumeister H: Überprüfung kalibrierter Itembanken zur Erfassung beruflicher Funktionsfähigkeit an einer Stichprobe ambulanter kardiologischer Rehabilitanden. Rehabilitation, e-first
  • [26]Boecker M, Wirtz M, Eberle N, Gauggel S: On the way to the Neuro-CAT: develoment and initial evaluation of the Aachen ADL-item bank. In In robabilistic models for measurement in education, psychology, social science and health. Edited by Brodersen J, Nielsen T, Kreiner S. Copenhagen, Denmark: University of Copenhagen; 2010.
  • [27]WHO: International Classification of Functioning, Disability and Health (ICF). Geneva: WHO; 2001.
  • [28]Kolen MJ, Brennan RL: Test equating, scaling, and linking: Methods and practices. 2nd edition. New York, NY: Springer; 2004.
  • [29]Muthén L, Muthén B: Mplus: statistical analysis with latent variables: user's guide. Los Angeles: Muthén&Muthén; 2004.
  • [30]Browne MW, Cudeck R: Alternative ways of assessing model fit. Sociological Methods & Research 1992, 21:230-258.
  • [31]Haley SM, Coster WJ, Andres PL, Ludlow LH, Ni P, Bond TLY, Sinclair SJ, Jette AM: Activity outcome measurement for postacute care. Med Care 2004, 42:I49-61.
  • [32]StataCorp: Stata Statistical Software, release 9.0. College Station. TX: Stata Corporation; 2005.
  • [33]Mokken RJ: Nonparametric models for dichotomous responses. In Handbook of modern item response theory. Edited by van der Linden WJ, Hambleton RK. New York: Springer; 1997:350-367.
  • [34]Masters GN: A Rasch model for partial credit scoring. Psychometrika 1982, 47:149-174.
  • [35]Andrich D, Lyne A, Sheridan B, Luo G: Rumm 2030. Perth: RUMM Laboratory; 2009.
  • [36]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.
  • [37]Pallant JF, Tennant A: An introduction to the Rasch measurement model: an example using the Hospital Anxiety and Depression Scale (HADS). Br J Clin Psychol 2007, 46:1-18.
  • [38]Smith EV: Detecting and evaluating the impact of mulitdimensionality using item fit statistics and principal component analysis of residuals. J Appl Meas 2002, 205-231.
  • [39]Reeve BB: Special issues for building computerized adaptive tests for measuring patient-reported outcomes: the National Institute of Health's investment in new technology. Medical Care 2006, 44:198-204.
  • [40]Lai J, Cella D, Dineen K, Bode R: Roenn J von, Gershon RC, Shevrin D: an item bank was created to improve the measurement of cancer-related fatigue. J Clin Epidemiol 2005, 58:190-197.
  • [41]Forkmann T, Boecker M, Wirtz M, Eberle N, Westhofen M, Schauerte P, Mischke K, Kircher T, Gauggel S, Norra C: Development and validation of the Rasch-based depression screening (DESC) using Rasch analysis and structural equation modelling. J Behav Ther Exp Psychiatry 2009, 40:468-478.
  • [42]Newson RS, Witteman JCM, Franco OH, Stricker BHC, Breteler MMB, Hofman A, Tiemeier H: Predicting survival and morbidity-free survival to very old age. AGE 2010, 32:521-534.
  • [43]McKenzie LH, Simpson J, Stewart M: The impact of depression on activities of daily living skills in individuals who have undergone coronary artery bypass graft surgery. Psychol Health Med 2009, 14:641-653.
  • [44]Cameron ID, Schaafsma FG, Wilson S, Baker W, Buckley S: Outcomes of rehabilitation in older people - functioning and cognition are the most important predictors: An inception cohort study. J Rehabil Med 2012, 44:24-30.
  • [45]Baumeister H, Kriston L, Bengel J, Härter M: High agreement of self-report and physician-diagnosed somatic conditions yields limited bias in examining mental-physical comorbidity. J Clin Epidemiol 2010, 63:558-565.
  • [46]Härter M, Baumeister H, Reuter K, Jacobi F, Hofler M, Bengel J, Wittchen HU: Increased 12-month prevalence rates of mental disorders in patients with chronic somatic diseases. Psychother Psychosom 2007, 76:354-360.
  • [47]Baumeister H, Hutter N, Bengel J: Psychological and pharmacological interventions for depression in patients with coronary artery disease. Cochrane Database Syst Rev 2011., (9) Art.No.:CD008012
  • [48]Baumeister H, Hutter N, Bengel J, Härter M: Quality of life in medically ill persons with comorbid mental disorders: a systematic review and meta-analysis. Psychother Psychosom 2011, 80:275-286.
  • [49]Baumeister H, Balke K, Härter M: Psychiatric and somatic comorbidities are negatively associated with quality of life in physically ill patients. J Clin Epidemiol 2005, 58:1090-1100.
  • [50]Haschke A, Hutter N, Baumeister H: Indirect costs in patients with coronary artery disease and mental disorders: a systematic review and meta-analysis. Int J Occup Med Environ Health 2012, 25:319-329.
  • [51]Thissen D, Reeve BB, Bjorner JB, Chang CH: Methodological issues for building item banks and computerized adaptive scales. Qual Life Res 2007, 16:109-119.
  • [52]Abberger B, Haschke A, Wirtz M, Kroehne U, Bengel J, Baumeister B: Development and evaluation of a computer-adaptive test to assess anxiety in cardiovascular rehabilitation patients – ACAT-cardio. Arch Phys Med Rehabil 2013. in press
  • [53]Choi SW: Firestar: Computerized Adaptive Testing (CAT) Simulation Program for Polytomous IRT Models. Appl Psychol Meas 2009, 33:644-645.
  文献评价指标  
  下载次数:7次 浏览次数:10次