Abstract
Purpose
We aimed to develop and calibrate an item bank to measure physical function (PF) in Singapore, a multi-ethnic city in Southeast Asia.
Methods
We recruited participants from community and hospital settings stratified for age and gender, with and without medical conditions to administer candidate pool of 61-items derived from the people’s perspectives. We calibrated their responses using Samejima’s graded response model of item response theory (IRT), including model assumptions, model fit, differential item functioning (DIF), and concurrent and known-groups validity.
Results
496 participants (50% male; 41% above 50 years old; 33.3% Chinese, 32.7% Malay and 34.1% Indian; 35% without chronic illness) were included in the calibration of item bank. 6 items were excluded due to mis-fit and local dependence. Redundancies in the response level was collapsed and re-scoring, while preserving the 5-level response structure. We found the final 55-item PF bank had adequate fit to IRT assumptions of unidimensionality, local independence and monotonicity. Items generally showed discernible ceiling effects with latent scores between − 3.5 to + 1.5. We found no DIF with gender, ethnicity or education. The PF scores correlated in the hypothesized direction with self-reported global health (Spearman’s rho = − 0.35, 95% confidence intervals − 0.43 to − 0.27) and discriminated between groups stratified by age, gender and medical conditions.
Conclusion
The 55-item Singapore PF item bank provides an adequate tool for measuring the lower end of PF, with greatest potential utility in healthcare settings where restoration to normal physical functioning is the goal of intervention.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Report, H. P. F. H. M. (2020). Health-related quality of life and well-being. Retrieved June 1, 2019, from https://www.healthypeople.gov/2020/about/foundation-health-measures/Health-Related-Quality-of-Life-and-Well-Being.
Testa, M. A., & Simonson, D. C. (1996). Assessment of quality-of-life outcomes. The New England Journal of Medicine, 334(13), 835–840. https://doi.org/10.1056/NEJM199603283341306.
Sajid, M. S., Tonsi, A., & Baig, M. K. (2008). Health-related quality of life measurement. International Journal of Health Care Quality Assurance, 21(4), 365–373. https://doi.org/10.1108/09526860810880162.
World Health Organization. (1946). Health related quality of life (HRQOL). Preamble to the constitution of WHO as adopted by the international health conference. Geneva: World Health Organization.
Services UDoHAH. (2009). Guidance for industry. Patient-reported outcome measures: Use in medical product development to support labeling claims. Retrieved June 1, 2019, from https://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM193282.pdf.
European Medicines Agency CfMPfHU. (2005). Reflection paper on the regulatory guidance for the use of health related quality of life (HRQL) measures in the evaluation of medicinal products. Retrieved June 1, 2019, from https://www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2009/09/WC500003637.pdf.
Hilarius, D. L., Kloeg, P. H., Gundy, C. M., & Aaronson, N. K. (2008). Use of health-related quality-of-life assessments in daily clinical oncology nursing practice: A community hospital-based intervention study. Cancer, 113(3), 628–637. https://doi.org/10.1002/cncr.23623.
Detmar, S. B., Muller, M. J., Schornagel, J. H., Wever, L. D., & Aaronson, N. K. (2002). Health-related quality-of-life assessments and patient-physician communication: A randomized controlled trial. JAMA, 288(23), 3027–3034.
Pang, S., Subramaniam, M., Lee, S. P., Lau, Y. W., Abdin, E., Chua, B. Y., et al. (2017). The Singaporean public beliefs about the causes of mental illness: Results from a multi-ethnic population-based study. Epidemiology and Psychiatric Sciences. https://doi.org/10.1017/S2045796017000105.
Nakane, Y., Jorm, A. F., Yoshioka, K., Christensen, H., Nakane, H., & Griffiths, K. M. (2005). Public beliefs about causes and risk factors for mental disorders: A comparison of Japan and Australia. BMC Psychiatry, 5, 33. https://doi.org/10.1186/1471-244X-5-33.
Thumboo, J., Fong, K. Y., Machin, D., Chan, S. P., Leon, K. H., Feng, P. H., et al. (2001). A community-based study of scaling assumptions and construct validity of the English (UK) and Chinese (HK) SF-36 in Singapore. Quality of Life Research, 10(2), 175–188.
Fukuhara, S., Bito, S., Green, J., Hsiao, A., & Kurokawa, K. (1998). Translation, adaptation, and validation of the SF-36 Health Survey for use in Japan. Journal of Clinical Epidemiology, 51(11), 1037–1044.
Thumboo, J., Ow, M. Y. L., Uy, E. J. B., Xin, X., Chan, Z. Y. C., Sung, S. C., et al. (2018). Developing a comprehensive, culturally sensitive conceptual framework of health domains in Singapore. PLoS ONE, 13(6), e0199881. https://doi.org/10.1371/journal.pone.0199881.
Uy, E. J. B., Bautista, D. C., Xin, X., Cheung, Y. B., Thio, S. T., & Thumboo, J. (2018). Using best-worst scaling choice experiments to elicit the most important domains of health for health-related quality of life in Singapore. PLoS ONE, 13(2), e0189687. https://doi.org/10.1371/journal.pone.0189687.
Uy, E. J. B., Xiao, L. Y. S., Xin, X., Yeo, J. P. T., Pua, Y. H., Lee, G. L., et al. (2020). Developing item banks to measure three important domains of health-related quality of life (HRQOL) in Singapore. Health and Quality of Life Outcomes, 18(1), 2. https://doi.org/10.1186/s12955-019-1255-1.
Health, S. M. O. (2014). Singapore Burden of disease study 2010. Retrieved June 1, 2019, from https://www.moh.gov.sg/resources-statistics/singapore-health-facts/disease-burden.
Census of Population 2010. (2010). Retrieved June 1, 2019, from https://www.singstat.gov.sg/publications/cop2010/census10_stat_release3.
Health, S. M. O. (2005). National Health Survey 2004. Retrieved June 1, 2019, from https://www.moh.gov.sg/resources-statistics/reports/national-health-survey-2004.
Health, S. M. O. (2009). National Health Survey 2007. Retrieved June 1, 2019, from https://www.moh.gov.sg/resources-statistics/reports/national-healthsurveillancesurvey-2007.
CASRO, COASRO. (1982). On the definition of response rates. Retrieved June 1, 2019, from https://www.insightsassociation.org/issues-policies/best-practice/casro-definition-response-rates.
Kwan, Y. H., Uy, E. J., Bautista, D. C., Xin, X., Xiao, Y., Lee, G. L., et al. (2019). Development and calibration of a novel social relationship item bank to measure health-related quality of life (HRQoL) in Singapore. Health and Quality of Life Outcomes., 17(1), 82.
Beaton, D. E., Bombardier, C., Guillemin, F., & Ferraz, M. B. (2000). Guidelines for the process of cross-cultural adaptation of self-report measures. Spine, 25(24), 3186–3191.
PROMIS Instrument Development and Validation Scientific Standards Version 2.0 (2013).
Amtmann, D., Cook, K. F., Jensen, M. P., Chen, W. H., Choi, S., Revicki, D., et al. (2010). Development of a PROMIS item bank to measure pain interference. Pain, 150(1), 173–182. https://doi.org/10.1016/j.pain.2010.04.025.
Muthén, L. K., & Muthén, B. O. (1998–2015). Mplus user’s guide: Statistical analysis with latent variables (7th ed.). Los Angeles, CA: Muthén & Muthén.
IBM Support. (2017). Obtaining likelihood-ratio tests for differential item functioning (DIF) in IBM SPSS Statistics. Retrieved April 7, 2020, from https://www.ibm.com/support/pages/obtaining-likelihood-ratio-tests-differential-item-functioning-dif-ibm-spss-statistics.
Norman, G. R., Sloan, J. A., & Wyrwich, K. W. (2003). Interpretation of changes in health-related quality of life: The remarkable universality of half a standard deviation. Medical Care, 41(5), 582–592. https://doi.org/10.1097/01.MLR.0000062554.74615.4C.
Fries, J. F., Spitz, P., Kraines, R. G., & Holman, H. R. (1980). Measurement of patient outcome in arthritis. Arthritis & Rheumatology, 23(2), 137–145.
Rose, M., Bjorner, J. B., Gandek, B., Bruce, B., Fries, J. F., & Ware, J. E., Jr. (2014). The PROMIS Physical Function item bank was calibrated to a standardized metric and shown to improve measurement efficiency. Journal of Clinical Epidemiology, 67(5), 516–526. https://doi.org/10.1016/j.jclinepi.2013.10.024.
Leung, Y. Y., Bin-Abd-Razak, H. R., Talaei, M., Ang, L. W., Yuan, J. M., & Koh, W. P. (2018). Duration of physical activity, sitting, sleep and the risk of total knee replacement among Chinese in Singapore, the Singapore Chinese Health Study. PLoS ONE, 13(9), e0202554. https://doi.org/10.1371/journal.pone.0202554.
Hallal, P. C., Andersen, L. B., Bull, F. C., Guthold, R., Haskell, W., Ekelund, U., et al. (2012). Global physical activity levels: surveillance progress, pitfalls, and prospects. The Lancet, 380(9838), 247–257. https://doi.org/10.1016/S0140-6736(12)60646-1.
Acknowledgements
We are grateful to all participants who gave valuable inputs to the item pool, and those who administered the item bank.
Funding
This study was supported by the National Medical Research Council Health Services Research grant (HSRG/0034/2013).
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
JT has received support from the National Medical Research Council (HSRG/0034/2013). YYL has received salary support from the Singapore National Medical Research Council (NMRC/CSA-INV/0022/2012). All authors have declared no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Leung, Y.Y., Uy, E.J.B., Bautista, D.C. et al. Calibration of a physical functioning item bank for measurement of health-related quality of life in Singapore. Qual Life Res 29, 2823–2833 (2020). https://doi.org/10.1007/s11136-020-02535-0
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11136-020-02535-0