An item-level response shift study on the change of health state with the rating of asthma-specific quality of life: a report from the PROMIS® Pediatric Asthma Study | mijn-bsl Skip to main content

Mijn bibliotheek

Shop

Nieuws
Boeken
Tijdschriften
E-learning
Web-tv
Video
Audio

Tips voor Mijn BSL

UITGEBREID ZOEKEN
Inloggen
Top
Quality of Life Research

Tip

Swipe om te navigeren naar een ander artikel

Gepubliceerd in: Quality of Life Research 6/2016

01-06-2016 | Special Section: Response Shift Effects at Item Level (by invitation only)

An item-level response shift study on the change of health state with the rating of asthma-specific quality of life: a report from the PROMIS® Pediatric Asthma Study

Auteurs: Pranav K. Gandhi, Carolyn E. Schwartz, Bryce B. Reeve, Darren A. DeWalt, Heather E. Gross, I-Chan Huang

Gepubliceerd in: Quality of Life Research | Uitgave 6/2016

Log in om toegang te krijgen
share
DELEN

Deel dit onderdeel of sectie (kopieer de link)

  • Optie A:
    Klik op de rechtermuisknop op de link en selecteer de optie “linkadres kopiëren”
  • Optie B:
    Deel de link per e-mail
    Link delen
publish
Publiceer nu

Abstract

Purpose

To examine item-level response shift associated with the change in asthma-related health state (i.e., change in asthma control status and global rating of change (GRC) in breathing problems).

Methods

Study sample comprised 238 asthmatic children who were between 8 and 17.9 years and completed the Pediatric Asthma Quality of Life Questionnaire (PAQLQ) symptoms, emotion function, and activity limitation domains at baseline and a follow-up assessment. Structural equation modeling was implemented to assess item-level response shift associated with the change in asthma-related health state with the adjustment for the influence of confounding variables. The magnitude of item-level response shift and its influence on the change of domain scores was estimated using Cohen’s effect sizes.

Results

We found no instances of item-level response shift. However, two items were identified with measurement bias related to GRC due to breathing problems. Specifically, asthmatic children with better/about the same GRC due to breathing problems reported lower scores for one item in the emotional domain at follow-up compared to those with deteriorated GRC due to breathing problems. In addition, asthmatic children with better/about the same GRC due to breathing problems reported better scores for another item in the symptom domain at baseline compared to those with deteriorated GRC due to breathing problems. The impact of measurement bias was small and did not bias the change of domain scores over time.

Conclusions

No item-level response shift, but two instances of measurement bias, appears in asthmatic children. However, the impact of these measurement issues is negligible.
vorige artikel On the validity of measuring change over time in routine clinical assessment: a close examination of item-level response shifts in psychosomatic inpatients
volgende artikel Using structural equation modeling to detect response shifts and true change in discrete variables: an application to the items of the SF-36
Literatuur
1.
Sprangers, M. A., & Schwartz, C. E. (1999). Integrating response shift into health-related quality of life research: A theoretical model. Social Science and Medicine, 48, 1507–1515. CrossRefPubMed
2.
Schwartz, C. E., & Sprangers, M. A. (1999). Methodological approaches for assessing response shift in longitudinal health-related quality of life research. Social Science and Medicine, 48, 1531–1548. CrossRefPubMed
3.
Hamidou, Z., Dabakuyo, T. S., & Bonnetain, F. (2011). Impact of response shift on longitudinal quality-of-life assessment in cancer clinical trials. Expert Review of Pharmacoeconomics & Outcomes Research, 11(5), 549–559. CrossRef
4.
Gillison, F., Skevington, S., & Standage, M. (2008). Exploring response shift in the quality of life of healthy adolescents over 1 year. Quality of Life Research, 17, 997–1008. CrossRefPubMed
5.
De Civita, M., Regier, D., Alamgir, A. H., Anis, A. H., FitzGerald, M. J., et al. (2005). Evaluating health-related quality of life studies pediatric populations. Pharmacoeconomics, 23(7), 659–685. CrossRefPubMed
6.
Schwartz, C. E., Feinberg, R. G., Jilinskaia, E., & Applegate, J. C. (1999). An evaluation of psychosocial intervention for survivors of childhood cancer: Paradoxical effects of response shift over time. Pysho-Oncology, 8, 344–354. CrossRef
7.
Rapkin, B. D., & Schwartz, C. E. (2004). Toward a theoretical of quality-of-life appraisal: Implications of findings from studies of response shift. Health and Quality of Life Outcomes, 2, 14. CrossRefPubMedPubMedCentral
8.
Ahmed, S., Sawatzky, R., Levesque, J.-F., Ehrmann-Feldman, D., & Schwartz, C. E. (2014). Minimal evidence of response shift in the absence of a catalyst. Quality of Life Research, 23(9), 2421–2430. CrossRefPubMed
9.
Oort, F. J., Visser, M. R. M., & Sprangers, M. A. G. (2009). Formal definitions of measurement bias and explanation bias clarify measurement and conceptual perspectives on response shift. Journal of Clinical Epidemiology, 62, 1126–1137. CrossRefPubMed
10.
Gandhi, P. K., Ried, L. D., Kimberlin, C., Kauf, T. K., & Huang, I.-C. (2013). Influence of explanatory and confounding variables on HRQoL after controlling for measurement bias and response shift in measurement. Expert Reviews of Pharmacoeconomics & Outcomes Research, 13(6), 841–851. CrossRef
11.
Schwartz, C. E., Sprangers, M. A. G., Carey, A., & Reed, G. (2004). Exploring response shift in longitudinal data. Psychology and Health, 19(1), 51–69. CrossRef
12.
Schwartz, C. E., & Rapkin, B. D. (2012). Understanding appraisal processes underlying the then test: A mixed methods investigation. Quality of Life Research, 21(3), 381–388. CrossRefPubMed
13.
Ahmed, S., Mayo, N. E., Corbiere, M., Wood-Dauphinee, S., Hanley, J., & Cohen, R. (2005). Change in quality of life in people with stroke over time: true change or response shift? Quality of Life Research, 14, 611–627. CrossRefPubMed
14.
Schwartz, C. E., & Sprangers, M. A. G. (2010). Guidelines for improving the stringency of response shift research using the then-test. Quality of Life Research, 19, 455–464. CrossRefPubMed
15.
Schwartz, C. E., Sprangers, M. A. G., Ahmed, S., Bode, R., Li, Y., Oort, F. J., et al. (2011). Response shift in patients with multiple sclerosis: An application of three statistical techniques. Quality of Life Research, 20(10), 1561–1572. CrossRefPubMed
16.
Schwartz, C. E., Ahmed, S., Sawatsky, R., Sajobi, T., Mayo, N., Finkelstein, J. A., et al. (2013). Guidelines for secondary analysis in search of response shift. Quality of Life Research, 22(22), 2663–2673. CrossRefPubMed
17.
King-Kallimanis, B. L., Oort, F. J., Visser, M. R. M., & Sprangers, M. A. G. (2009). Structural equation modeling of health-related quality-of-life data illustrates the measurement and conceptual perspectives on response shift. Journal of Clinical Epidemiology, 62, 1157–1164. CrossRefPubMed
18.
Gandhi, P. K., Ried, L. D., Huang, I. C., Kimberlin, C. L., & Kauf, T. L. (2012). Assessment of response shift using two structural equation modeling techniques. Quality of Life Research, 22(3), 461–471. CrossRefPubMedPubMedCentral
19.
Oort, F. J., Visser, M. R. M., & Sprangers, M. A. G. (2005). An application of structural equation modeling to detect response shifts and true change in quality of life data from cancer patients undergoing invasive surgery. Quality of Life Research, 14, 599–609. CrossRefPubMed
20.
Visser, M., Oort, F., & Sprangers, M. (2005). Methods to detect response shift in quality of life data: A convergent validity study. Quality of Life Research, 14, 629–639. CrossRefPubMed
21.
Ahmed, S., Mayo, N. E., Wood-Dauphinee, S., Hanley, J. A., & Cohen, S. R. (2005). The structural equation modeling technique did not show a response shift, contrary to the results of the then test and the individualized approaches. Journal of Clinical Epidemiology, 58(11), 1125–1133. CrossRefPubMed
22.
Gandhi, P. K., Kenzik, K. M., Thompson, L. A., DeWalt, D., Revicki, D. A., Shenkman, E. A., et al. (2013). Exploring factors influencing asthma control and asthma-specific health-related quality of life among children. Respiratory Research, 14(1), 26. CrossRefPubMedPubMedCentral
23.
Smith, L. A., Bokhour, B., Hohman, K. H., Miroshnik, I., Kleinman, K. P., Cohn, E., et al. (2008). Modifiable risk factors for suboptimal control and controller medication underuse among children with asthma. Pediatrics, 122(4), 760–769. CrossRefPubMed
24.
Lozano, P., Finkelstein, J. A., Hecht, J., Shulruff, R., & Weiss, K. B. (2003). Asthma medication use and disease burden in children in a primary care population. Archives of Pediatrics and Adolescent Medicine, 157(1), 81–88. CrossRefPubMed
25.
Koster, E. S., Raaijmakers, J. A., Vijverberg, S. J., Koenderman, L., Postma, D. S., Koppelman, G. H., et al. (2011). Limited agreement between current and long-term asthma control in children: The PACMAN cohort study. Pediatric Allergy and Immunology, 22(8), 776–783. CrossRefPubMed
26.
Chen, H., Gould, M. K., Blanc, P. D., Miller, D. P., Kamath, T. V., Lee, J. H., et al. (2007). Asthma control, severity, and quality of life: Quantifying the effect of uncontrolled disease. Journal of Allergy and Clinical Immunology, 120, 396–402. CrossRefPubMed
27.
Zheng, Li, Huang, I.-C., Thompson, L., Tuli, S., Huang, S.-W., DeWalt, D., et al. (2013). The relationships between asthma control, daytime sleepiness, and quality of life among children with asthma: A path analysis. Sleep Medicine, 14(7), 641–647. CrossRef
28.
Dean, B. B., Calimlim, B. M., Kindermann, S. L., Khandker, R. K., & Tinkelman, D. (2009). The impact of uncontrolled asthma on absenteeism and health-related quality of life. The Journal of Asthma, 46, 861–866. CrossRefPubMed
29.
Pont, L. G., Van der Molen, T., Denig, P., Van der Werf, G. T., & Haaijer-Ruskamp, F. M. (2004). Relationship between guideline treatment and health-related quality of life in asthma. European Respiratory Journal, 23(5), 718–722. CrossRefPubMed
30.
Guilbert, T. W., Garris, C., Jhingran, P., Bonafede, M., Tomaszewski, K. J., Bonus, T., et al. (2011). Asthma that is not well-controlled is associated with increased healthcare utilization and decreased quality of life. The Journal of Asthma, 48(2), 126–132. CrossRefPubMed
31.
Juniper, E. F., Guyatt, G. H., Feeny, D. H., Ferrie, P. J., Griffin, L. E., & Townsend, M. (1996). Measuring quality of life in children with asthma. Quality of Life Research, 5, 35–46. CrossRefPubMed
32.
Raat, H., Bueving, H. J., de Jongste, J. C., Grol, M. H., Juniper, E. F., & van der Wouden, J. C. (2005). Responsiveness, longitudinal- and cross-sectional construct validity of the Pediatric Asthma Quality of Life Questionnaire (PAQLQ) in Dutch children with asthma. Quality of Life Research, 14(1), 265–272. CrossRefPubMed
33.
Patino, C. M., Okelo, S. O., Rand, C. S., Riekert, K. A., Krishnan, J. A., Thompson, K., et al. (2008). The asthma control and communication instrument: A clinical tool developed for ethnically diverse populations. The Journal of Allergy and Clinical Immunology, 122(5), 936.e6–943.e6. CrossRef
34.
National Asthma Education and Prevention Program. (2007). Expert panel report 3 (EPR-3): Guidelines for the diagnosis and management of asthma-summary report 2007. Journal of Allergy and Clinical Immunology, 120(5 Suppl), S94–S138.
35.
Juniper, E. F., Guyatt, G. H., Feeny, D. H., Griffith, L. E., & Ferrie, P. J. (1997). Minimum skills required by children to complete health-related quality of life instruments for asthma: comparison of measurement properties. European Respiratory Journal, 10(10), 2285–2294. CrossRefPubMed
36.
Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York, London: Guilford Press.
37.
Barclay-Goddard, R., Lix, L. M., Tate, R., Weinberg, L., & Mayo, N. E. (2009). Response shift was identified over multiple occasions with a structural equation modeling framework. Journal of Clinical Epidemiology, 62, 1181–1188. CrossRefPubMed
38.
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1(2), 130–149. CrossRef
39.
Hochberg, Y., & Benjamini, Y. (1990). More powerful procedures for multiple significance testing. Statistics in Medicine, 9, 811–818. CrossRefPubMed
40.
Jöreskog, K., & Sörbom, D. (1993). LISREL 8. Lincolnwood, Il: Scientific Software Internatonal Inc.
41.
SAS Institute. (2004). SAS users guide, version 9.1. Cary, NC: SAS Institute, Inc.
42.
Brinksma, A., Tissing, W. J., Sulkers, E., Kamps, W. A., Roodbol, P. F., & Sanderman, R. (2014). Exploring the response shift phenomenon in childhood patients with cancer and its effect on health-related quality of life. Oncology Nursing Forum, 41(1), 48–56. CrossRefPubMed
43.
44.
Timmerman, A. A., Anteunis, L. J., & Meesters, C. M. (2003). Response-shift bias and parent-reported quality of life in children with otitis media. Archives of Otolaryngology - Head and Neck Surgery, 129(9), 987–991. CrossRefPubMed
45.
Verdam, M. G. E., Oort, F. J., Visser, M. R. M., & Sprangers, M. A. G. (2012). Response shift detection through then-test and structural equation modeling: Decomposing observed change and testing tacit assumptions. Netherlands Journal of Psychology, 67(3), 58–67.
46.
Brossart, D. F., Clay, D. L., & Willson, V. L. (2002). Methodological and statistical considerations for threats to internal validity in pediatric outcome data: Response shift in self-report outcomes. Journal of Pediatric Psychology, 27(1), 97–107. CrossRefPubMed
47.
Verdam, M. G. E., Oort, F. J, & Sprangers, M. A. G. (2015). Using structural equation modeling to detect response shifts and true change in discrete variables: An application to the items of the SF-36. Quality of Life Research. doi: 10.​1007/​s11136-015-1195-0
48.
Guilleux, A., Blanchin, M., Vanier, A., Guillemin, F., Falissard, B., Schwartz, C. E., et al. (2015). Response shift algorithm in item response theory (ROSALI) for response shift detection with missing data in longitudinal patient-reported outcome studies. Quality of Life Research, 24, 553–564. CrossRefPubMed
Metagegevens
Titel
An item-level response shift study on the change of health state with the rating of asthma-specific quality of life: a report from the PROMIS® Pediatric Asthma Study
Auteurs
Pranav K. Gandhi
Carolyn E. Schwartz
Bryce B. Reeve
Darren A. DeWalt
Heather E. Gross
I-Chan Huang
Publicatiedatum
01-06-2016
Uitgeverij
Springer International Publishing
Gepubliceerd in
Quality of Life Research / Uitgave 6/2016
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-016-1290-x

Andere artikelen Uitgave 6/2016

Quality of Life Research 6/2016 Naar de uitgave

Review

Quality of life among patients after bilateral prophylactic mastectomy: a systematic review of patient-reported outcomes

OriginalPaper

Validation of the EORTC QLQ-INFO 25 questionnaire in Lebanese cancer patients: Is ignorance a Bliss?

Special Section: Response Shift Effects at Item Level (by invitation only)

The Guttman errors as a tool for response shift detection at subgroup and item levels

OriginalPaper

Relationship between depression and health-related quality of life in patients undergoing coronary artery bypass grafting: a MOTIV-CABG substudy

OriginalPaper

Cardiff cardiac ablation patient-reported outcome measure (C-CAP): validation of a new questionnaire set for patients undergoing catheter ablation for cardiac arrhythmias in the UK

OriginalPaper

Validity, responsiveness, and minimal clinically important difference of EQ-5D-5L in stroke patients undergoing rehabilitation