Skip to main content

Advertisement

Log in

Reducing respondent burden: validation of the Brief Impact of Vision Impairment questionnaire

  • Published:
Quality of Life Research Aims and scope Submit manuscript

Abstract

Purpose

To develop a psychometrically sound and valid Brief Impact of Vision Impairment (IVI) questionnaire.

Methods

Cross-sectional data from four prospective studies (2001–2008) were pooled and randomly divided into development/validation sets (n = 416) each. Items with suboptimal psychometric properties were iteratively removed in the development set to form the Brief IVI. Psychometric properties of the Brief IVI were independently tested in the validation sample. Correlation between person measures from the original and Brief IVI was assessed [Pearson r and intraclass correlation coefficient (ICC)]. Criterion validity was determined by testing the Brief IVI’s ability to discriminate levels of vision impairment (analysis of variance, ANOVA). Responsiveness was tested by comparing the ICC of the original and Brief IVI data obtained pre-/post-intervention.

Results

The 15-item Brief IVI, and its 9-item Visual Functioning and 6-item Emotional Well-being subscales had ordered thresholds, good precision and targeting, unidimensionality, and minimal item misfit (replicated in the validation sample). Brief and original IVI person measures were highly correlated (r = 0.97 and ICC = 0.98, p < 0.001), indicating the Brief IVI provides statistically similar measurement of vision-related quality of life (VRQoL). Brief IVI mean logit scores declined as vision impairment worsened (p = 0.001) demonstrating criterion validity. ICC of the original versus Brief IVI pre-/post-intervention was excellent (0.98), establishing that the Brief IVI was as responsive to changes in VRQoL as the original.

Conclusions

The Brief 15-item IVI can obtain valid and responsive measurement of VRQoL with half the items in the original and has potential to reduce respondent burden in QoL studies.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Lamoureux, E. L., Hassell, J. B., & Keeffe, J. E. (2004). The determinants of participation in activities of daily living in people with impaired vision. American Journal of Ophthalmology, 137(2), 265–270.

    Article  PubMed  Google Scholar 

  2. Lamoureux, E. L., Pallant, J. F., Pesudovs, K., et al. (2007). The effectiveness of low-vision rehabilitation on participation in daily living and quality of life. Investigative Ophthalmology & Visual Science, 48(4), 1476–1482.

    Article  Google Scholar 

  3. West, S. K., Munoz, B., Rubin, G. S., et al. (1997). Function and visual impairment in a population-based study of older adults. The SEE project. Salisbury Eye Evaluation. Investigative Ophthalmology & Visual Science, 38(1), 72–82.

    CAS  Google Scholar 

  4. Rees, G., Tee, H. W., Marella, M., et al. (2010). Vision-specific distress and depressive symptoms in people with vision impairment. Investigative Ophthalmology & Visual Science, 51(6), 2891–2896.

    Article  Google Scholar 

  5. Rovner, B., & Ganguli, M. (1998). Depression and disability associated with impaired vision: The MoVies Project. Journal of the American Geriatrics Society, 46(5), 617–619.

    Article  CAS  PubMed  Google Scholar 

  6. Evans, J. R., Fletcher, A. E., & Wormald, R. P. (2007). Depression and anxiety in visually impaired older people. Ophthalmology, 114(2), 283–288.

    Article  PubMed  Google Scholar 

  7. Snyder, C. F., Aaronson, N. K., Choucair, A. K., et al. (2012). Implementing patient-reported outcomes assessment in clinical practice: A review of the options and considerations. Quality of Life Research, 21(8), 1305–1314.

    Article  PubMed  Google Scholar 

  8. U.S. Department of Health and Human Services FDA Center for Drug Evaluation and Research, U.S. Department of Health and Human Services FDA Center for Biologics Evaluation and Research, U.S. Department of Health and Human Services FDA Center for Devices and Radiological Health. (2006). Guidance for industry: Patient-reported outcome measures: Use in medical product development to support labeling claims: Draft guidance. Health and quality of life outcomes, p. 479.

  9. Weih, L. M., Hassell, J. B., & Keeffe, J. (2002). Assessment of the impact of vision impairment. Investigative Ophthalmology & Visual Science, 43(4), 927–935.

    Google Scholar 

  10. Lamoureux, E. L., Pallant, J. F., Pesudovs, K., et al. (2006). The impact of vision impairment questionnaire: An evaluation of its measurement properties using Rasch analysis. Investigative Ophthalmology & Visual Science, 47(11), 4732–4741.

    Article  Google Scholar 

  11. Lamoureux, E. L., Pallant, J. F., Pesudovs, K., et al. (2007). The Impact of Vision Impairment questionnaire: An assessment of its domain structure using confirmatory factor analysis and Rasch analysis. Investigative Ophthalmology & Visual Science, 48(3), 1001–1006.

    Article  Google Scholar 

  12. Finger, R. P., Fenwick, E., Marella, M., et al. (2011). The relative impact of vision impairment and cardiovascular disease on quality of life: The example of pseudoxanthoma elasticum. Health Qual Life Outcomes, 9, 113.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Finger, R. P., Fenwick, E., Marella, M., et al. (2011). The impact of vision impairment on vision-specific quality of life in Germany. Investigative Ophthalmology & Visual Science, 52(6), 3613–3619.

    Article  Google Scholar 

  14. Rees, G., Xie, J., Chiang, P. P., et al. (2015). A randomised controlled trial of a self-management programme for low vision implemented in low vision rehabilitation services. Patient Education and Counseling, 98(2), 174–181.

    Article  PubMed  Google Scholar 

  15. Fenwick, E., Ong, P., Sabanayagam, C., et al. (2015). Assessment of the psychometric properties of the Chinese Impact of Vision Impairment questionnaire in a population-based study: Findings from the Singapore Chinese Eye Study. Quality of Life Research, 25(4), 871–880.

    Article  PubMed  Google Scholar 

  16. Lamoureux, E. L., Pallant, J. F., Pesudovs, K., et al. (2008). Assessing participation in daily living and the effectiveness of rehabiliation in age related macular degeneration patients using the impact of vision impairment scale. Ophthalmic Epidemiology, 15(2), 105–113.

    Article  PubMed  Google Scholar 

  17. O’Connor, P. M., Scarr, B. C., Lamoureux, E. L., et al. (2010). Validation of a quality of life questionnaire in the Pacific Island. Ophthalmic Epidemiology, 17(6), 378–386.

    Article  PubMed  Google Scholar 

  18. Gothwal, V. K., Reddy, S. P., Fathima, A., et al. (2013). Assessment of the impact of keratoconus on vision-related quality of life. Investigative Ophthalmology & Visual Science, 54(4), 2902–2910.

    Article  Google Scholar 

  19. Ratanasukon, M., Tongsomboon, J., Bhurayanontachai, P., & Jirarattanasopa, P. (2016). The Impact of Vision Impairment (IVI) Questionnaire; Validation of the Thai-Version and the Implementaion on Vision-Related Quality of Life in Thai Rural Community. PLoS One, 11(5), e0155509.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Aaronson, N., Alonso, J., Burnam, A., et al. (2002). Assessing health status and quality-of-life instruments: Attributes and review criteria. Quality of Life Research, 11(3), 193–205.

    Article  PubMed  Google Scholar 

  21. Turner, R. R., Quittner, A. L., Parasuraman, B. M., et al. (2007). Patient-reported outcomes: Instrument development and selection issues. Value in Health: The Journal of the International Society for Pharmacoeconomics and Outcomes Research, 10(Suppl 2), S86–S93.

    Article  Google Scholar 

  22. Rees, G., Xie, J., Holloway, E. E., et al. (2013). Identifying distinct risk factors for vision-specific distress and depressive symptoms in people with vision impairment. Investigative Ophthalmology & Visual Science, 54(12), 7431–7438.

    Article  Google Scholar 

  23. Linacre, J. M. (2005). A user’s guide to Winsteps/Ministeps Rasch-model programs. Chicago, IL: MESA Press.

    Google Scholar 

  24. Andrich, D. (1978). Rating formulation for ordered response categories. Psychometrica, 43, 561–573.

    Article  Google Scholar 

  25. Prieto, L., Alonso, J., & Lamarca, R. (2003). Classical test theory versus Rasch analysis for quality of life questionnaire reduction. Health Qual Life Outcomes, 1, 27.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Massof, R. W. (2004). Likert and Guttman scaling of visual function rating scale questionnaires. Ophthalmic Epidemiology, 11(5), 381–399.

    Article  PubMed  Google Scholar 

  27. Lamoureux, E., & Pesudovs, K. (2011). Vision-specific quality-of-life research: A need to improve the quality. American Journal of Ophthalmology, 151(2), 195-7 e2.

    Article  PubMed  Google Scholar 

  28. Bond, T. G., & Fox, C. M. (2001). Applying the Rasch model: Fundamental measurement in the human sciences. London: Lawrence Erlbaum Associates.

    Google Scholar 

  29. Pesudovs, K., Burr, J. M., Harley, C., et al. (2007). The development, assessment, and selection of questionnaires. Optometry and Vision Science, 84(8), 663–674.

    Article  PubMed  Google Scholar 

  30. Linacre, J. (2002). A user’s guide to Winsteps: Rasch-model computer program. Chicago: Mesa Press.

    Google Scholar 

  31. Baghaei, P. (2008). Local dependency and rasch measures. Rasch Measurement Transactions, 21(3), 1105–1106.

    Google Scholar 

  32. Wright, B. (2003). Rack and stack: Time 1 vs time 2. Rasch Measurement Transactions, 17(1), 905–906.

    Google Scholar 

  33. Chien, T. (2008). Repeated measure designs and rasch. Rasch Measurement Transactions, 22(3), 1171.

    Google Scholar 

  34. Lamoureux, E. L., Pesudovs, K., Thumboo, J., et al. (2009). An evaluation of the reliability and validity of the visual functioning questionnaire (VF-11) using Rasch analysis in an Asian population. Investigative Ophthalmology & Visual Science, 50(6), 2607–2613.

    Article  Google Scholar 

  35. Khadka, J., Pesudovs, K., McAlinden, C., et al. (2011). Reengineering the glaucoma quality of life-15 questionnaire with rasch analysis. Investigative Ophthalmology & Visual Science, 52(9), 6971–6977.

    Article  Google Scholar 

  36. Gothwal, V. K., Wright, T. A., Lamoureux, E. L., et al. (2010). Activities of Daily Vision Scale: What do the subscales measure? Investigative Ophthalmology & Visual Science, 51(2), 694–700.

    Article  Google Scholar 

  37. Coste, J., Guillemin, F., Pouchot, J., et al. (1997). Methodological approaches to shortening composite measurement scales. Journal of Clinical Epidemiology, 50(3), 247–252.

    Article  CAS  PubMed  Google Scholar 

  38. Swartz, R. J., Baum, G. P., Askew, R. L., et al. (2012). Reducing patient burden to the FACT-Melanoma quality-of-life questionnaire. Melanoma Research, 22(2), 158–163.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Petrillo, J., Cano, S. J., McLeod, L. D., et al. (2015). Using classical test theory, item response theory, and Rasch measurement theory to evaluate patient-reported outcome measures: A comparison of worked examples. Value in Health: The Journal of the International Society for Pharmacoeconomics and Outcomes Research, 18(1), 25–34.

    Article  Google Scholar 

  40. Cappelleri, J. C., Jason Lundy, J., & Hays, R. D. (2014). Overview of classical test theory and item response theory for the quantitative assessment of items in developing patient-reported outcomes measures. Clinical Therapeutics, 36(5), 648–662.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Hays, R. D., Brown, J., Brown, L. U., et al. (2006). Classical test theory and item response theory analyses of multi-item scales assessing parents’ perceptions of their children’s dental care. Medical Care, 44(11 Suppl 3), S60–S68.

    Article  PubMed  Google Scholar 

  42. Meads, D. M., & Bentall, R. P. (2008). Rasch analysis and item reduction of the hypomanic personality scale. Personality and Individual Differences, 44(8), 1772–1783.

    Article  Google Scholar 

Download references

Funding

Prof. Ecosse Lamoureux was supported by an Australian National Health and Medical Research Council (NHMRC) Senior Research Fellowship (#1045280). Dr. Eva Fenwick is currently funded by a NHMRC Early Career Fellowship (#1072987), and Dr. Gwyn Rees is funded by an NHMRC Career Development Fellowship (#1061801). The funding organizations had no role in the design or conduct of this research or preparation of this manuscript. The Centre for Eye Research Australia receives Operational Infrastructure Support from the Victorian Government.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ecosse L. Lamoureux.

Ethics declarations

Conflict of interest

The authors declare they have no conflicts of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Fenwick, E.K., Man, R.E.K., Rees, G. et al. Reducing respondent burden: validation of the Brief Impact of Vision Impairment questionnaire. Qual Life Res 26, 479–488 (2017). https://doi.org/10.1007/s11136-016-1395-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11136-016-1395-2

Keywords

Navigation