Swipe om te navigeren naar een ander artikel
The online version of this article (doi:10.1007/s11136-014-0825-2) contains supplementary material, which is available to authorized users.
To develop and validate a new disease-specific quality of life measure in hyperhidrosis for use in both routine clinical practice and clinical research.
Interviews and focus group discussions with hyperhidrosis patients, reported elsewhere, provided the content for the measure validated in this study (n = 71). A panel of dermatologists (n = 5) and patients (n = 7) carried out content validation. Further, item reduction and the initial construct validation were carried out in a cross-sectional study (n = 595), using the unidimensional Rasch analysis and exploratory factor analysis. Subsequently, the construct validity, reliability and responsiveness of the revised measure were assessed in a longitudinal study (n = 260). Data collection for the item reduction and the final validation phases was entirely carried out online.
The expert panels judged the HidroQoL as content valid. Rasch analysis supported the revision of response options from five to three. Following removal of misfitting items, a set of 15 items showed optimal fit to the model (chi-squared statistic = 159.64, p = 0.07). Three additional items were retained on consideration of their importance to patients, resulting in an 18-item instrument. The items were grouped into two subscales, daily life activities and psychosocial life domains, based on results of the factor analysis. In subsequent construct validation, the HidroQoL correlated with the DLQI (r s = 0.6, p < 0.01). Reliability was high (internal consistency, Cronbach’s alpha: overall scale = 0.9; test–retest reliability, Intra-class correlation = 0.9). The HidroQoL scores were sensitive to change in patients’ disease severity (score change from baseline to follow-up after 15–35 days, Cohen’s ES = 0.47).
This study has provided the initial evidence supporting measurement properties and the use of the HidroQoL instrument in both routine clinical practice and in research, for assessing quality of life impacts in hyperhidrosis.
Scree plot showing optimal number of factors for the 21 items of the HidroQoL following item reduction using exploratory factor analysis. The optimal number of factors for extraction is identified by counting the factors lying to the left of the curve’s elbow. Factors to the right represent random rather than meaningful co-variation among the items (TIFF 17 kb)11136_2014_825_MOESM1_ESM.tif
Test characteristic curves of the HidroQoL total score and the latent QoL variable, by age groups. The relationship between the HidroQoL total raw score and the latent QoL variable was similar for the different age groups, indicating absence of bias for the total score in spite of DIF observed in some items (JPEG 28 kb)11136_2014_825_MOESM2_ESM.jpg
Test characteristic curves of the HidroQoL total score and the latent QoL variable, by body area affected. The relationship between the HidroQoL total raw score and the latent QoL variable was similar for patients with different sites of hyperhidrosis (JPEG 39 kb)11136_2014_825_MOESM3_ESM.jpg
Test characteristic curves of the HidroQoL total score and the latent QoL variable, by HDSS score (disease severity). The relationship between the HidroQoL total raw score and the latent QoL variable was similar for patients with different levels of disease severity (JPEG 31 kb)11136_2014_825_MOESM4_ESM.jpg
Test characteristic curves of the HidroQoL total score and the latent QoL variable, by comorbidity. The relationship between the HidroQoL total raw score and the latent QoL variable was similar for patients with different levels of disease severity (JPEG 22 kb)11136_2014_825_MOESM5_ESM.jpg
Supplementary material 6 (DOCX 19 kb)11136_2014_825_MOESM6_ESM.docx
Solish, N. (2006). Assessing hyperhidrosis disease severity and impact on quality of life. Cutis, 77(Suppl. 5), 17–27.
Strutton, D. R., Kowalski, J. W., Glaser, D. A., & Stang, P. E. (2004). US prevalence of hyperhidrosis and impact on individuals with axillary hyperhidrosis: Results from a national survey. Journal of the American Academy of Dermatology, 51(2), 241–248. doi: 10.1016/j.jaad.2003.12.040. CrossRefPubMed
Solish, N., Bertucci, V., Dansereau, A., Hong, H. C., Lynde, C., Lupin, M., et al. (2007). A comprehensive approach to the recognition, diagnosis, and severity-based treatment of focal hyperhidrosis: Recommendations of the Canadian Hyperhidrosis Advisory Committee. Dermatologic Surgery, 33(8), 908–923. doi: 10.1111/j.1524-4725.2007.33192.x. PubMed
Fayers, P., & Machin, D. (2007). Quality of life: The assessment, analysis and interpretation of patient-reported outcomes (2nd ed.). West Sussex: Wiley. CrossRef
Guyatt, G. H., Osoba, D., Wu, A. W., Wyrwich, K. W., & Norman, G. R. (2002). Methods to explain the clinical significance of health status measures. Mayo Clinical Proceedings, 77(4), 371–383. CrossRef
Kamudoni, P., Salek, S., Mueller, B., & Mueller, C. (2012). Hyperhidrosis Quality of Life Index (Hidroqol (c)): A novel patient reported outcome measure in hyperhidrosis. Journal of Investigative Dermatology, 132(S2), S73–S73.
Patrick, D. L., Burke, L. B., Gwaltney, C. J., Leidy, N. K., Martin, M. L., Molsen, E., et al. (2011). Content validity—Establishing and reporting the evidence in newly developed patient-reported outcomes (PRO) instruments for medical product evaluation: ISPOR PRO good research practices task force report: Part 2—Assessing respondent understanding. Value in Health, 14(8), 978–988. CrossRefPubMed
Kowalski, J. W., Eadie, N., Dagget, S., & Lai, P. N. (2004). Validity and reliability of the hyperhidrosis disease severity scale ( HDSS). In: Paper presented at the 62nd annual meeting of the American Academy of Dermatology Washington, DC, 6–10 February.
Kowalski, J. (2007). Minimal important difference (MID) of the Dermatology Life Quality Index in patients with axillary and palmar hyperhidrosis. Journal of the American Academy of Dermatology, 56(2), 52.
Sampogna, F., Spagnoli, A., Di Pietro, C., Pagliarello, C., Paradisi, A., Tabolli, S., et al. (2013). Field performance of the skindex-17 Quality of Life Questionnaire: A comparison with the skindex-29 in a large sample of dermatological outpatients. Journal of Investigative Dermatology, 133(1), 104–109. CrossRefPubMed
Nijsten, T. E. C., Sampogna, F., Chren, M.-M., & Abeni, D. D. (2006). Testing and reducing skindex-29 using Rasch analysis: Skindex-17. Journal of Investigative Dermatology, 126(6), 1244–1250. http://www.nature.com/jid/journal/v126/n6/suppinfo/5700212s1.html.
Aawar, N. (2011). Evaluation of patient compliance with renal replacement therapy and its impact on patient reported outcomes. Cardiff: Cardiff University.
Jemec, G. B., Esmann, S., Holm, E. A., Tycho, A., & Jorgensen, T. M. (2006). Time spent on treatment (TSOT). An independent assessment of disease severity in atopic dermatitis. Acta Dermatovenerologica Alpina Panonica Et Adriatica, 15(3), 119–124.
Muthén, L. K., & Muthén, B. O. (1998–2010). Mplus User’s Guide (6th edn.). Los Angeles, CA: Muthén & Muthén.
Costello, A., & Osborne, J. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research & Evaluation, 10, 173–178.
Lackey, N. R., Sullivan, J. J., & Pett, M. A. (2003). Making sense of factor analysis: The use of factor analysis for instrument development in health care research. London: SAGE.
Tennant, A., & Conaghan, P. G. (2007). 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 Care & Research, 57(8), 1358–1362. CrossRef
Smith, E. (2002). Detecting and evaluating the impact of multidimensionality using item fit statistics and principal component analysis of residuals. Journal of Applied Measurement, 3(2), 205–231. PubMed
Andrich, D., Sheridan, B., & Luo, G. (2012). Interpreting RUMM 2030 analysis: Part I dichotomous data. Perth: RUMM Laboratory.
Teale, C., Roberts, G., Hamm, H., & Naumann, M. (2002). Development, validity, and reliability of the Hyperhidrosis Impact Questionnaire (HHIQ) (abstract). Quality of Life Research, 11(7), 702.
Bond, T. G., & Fox, C. M. (2007). Applying the Rasch model: Fundamental measurement in the human sciences. Mahwah, NJ: Lawrence Erlbaum Associates Publishers.
Salek, S. (1998). Compendium of quality of life instruments (Vol. Bd. 4). Haslemere: Euromed Communications.
Streiner, D. L., & Norman, G. R. (2008). Health measurement scales: A practical guide to their development and use. Oxford: Oxford University Press. CrossRef
Coons, S. J., Gwaltney, C. J., Hays, R. D., Lundy, J. J., Sloan, J. A., Revicki, D. A., et al. (2009). Recommendations on evidence needed to support measurement equivalence between electronic and paper-based patient-reported outcome (PRO) measures: ISPOR ePRO good research practices task force report. Value in Health, 12(4), 419–429. CrossRefPubMed
Internet Users (per 100 people). (2013). http://data.worldbank.org/indicator/IT.NET.USER.P2. Accessed June 14, 2013.
- The development and validation of a disease-specific quality of life measure in hyperhidrosis: the Hyperhidrosis Quality of Life Index (HidroQOL©)
M. S. Salek
- Springer International Publishing