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21-11-2022

Using Rasch measurement theory to explore the fitness for purpose of the genetic counseling outcome scale: a tale of two scales

Auteurs: Kennedy Borle, Jehannine Austin, Skye Barbic

Gepubliceerd in: Quality of Life Research | Uitgave 3/2023

Abstract

Background

The genetic counseling outcome scale (GCOS-24) is commonly used in clinical genetics to measure patient empowerment; however, there is inconclusive psychometric evidence about this scale.

Methods

Using data from an urban Canadian clinic where the GCOS-24 is routinely administered before (T1) and 1 month after (T2) genetic counseling, we used Rasch measurement theory (RMT) to test the ordering of response option thresholds, fit, spread of item locations, residual correlations, person separation index (PSI), and stability across time.

Results

Data from 379 participants showed that the original GCOS-24 items had poor fit to the Rasch model (χ² = 367.8, p < 0.001). Two models emerged that demonstrated excellent fit to the Rasch model. In Model 1, the response scale options were collapsed and 8 items were removed, leading to an excellent fit to the Rasch model (χ² = 112.4, df = 144, p = 0.975), good reliability (rp = 0.82), and responsiveness to change (mean = 0.75 logits, F = 125.68, p < 0.001). In Model 2, the response scale options were collapsed, 3 items were removed, and the scale divided into two sets (GCOS-Pos, GCOS-Neg). The GCOS-Pos set showed excellent overall fit to the Rasch model (χ² = 92.5, df = 90, p = 0.407), good reliability (rp = 0.73), and responsiveness to change (mean = 0.74 logits, F = 80.12, p < 0.001). The GCOS-Neg set showed excellent overall fit to the Rasch model (χ² = 84.55, df = 97, p = 0.81), but poor reliability (rp = 0.19) and small, but significant responsiveness to change (mean = 0.19 logits, F = 28.73, p < 0.001).

Conclusion

These models show that there are psychometric issues with the GCOS-24 scale, and our study provides options for how to measure empowerment more robustly.

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Resta, R., Biesecker, B. B., Bennett, R. L., Blum, S., Hahn, S. E., Strecker, M. N., & Williams, J. L. (2006). A new definition of genetic counseling: National society of genetic counselors’ task force report. Journal of Genetic Counseling, 15(2), 77–83. https://doi.org/10.1007/s10897-005-9014-3CrossRefPubMed

Madlensky, L., Trepanier, A. M., Cragun, D., Lerner, B., Shannon, K. M., & Zierhut, H. (2017). A rapid systematic review of outcomes studies in genetic counseling. Journal of Genetic Counseling, 26(3), 361–378. https://doi.org/10.1007/s10897-017-0067-xCrossRefPubMed

Mcallister, M., Payne, K., Macleod, R., Nicholls, S., Donnai, D., & Davies, L. (2008). Patient empowerment in clinical genetics services. Journal of Health Psychology, 13(7), 895–905. https://doi.org/10.1177/1359105308095063CrossRefPubMed

Barr, P. J., Scholl, I., Bravo, P., Faber, M. J., Elwyn, G., & McAllister, M. (2015). Assessment of patient empowerment–—A systematic review of measures. PLoS ONE, 10(5), 1–24. https://doi.org/10.1371/journal.pone.0126553CrossRef

Mcallister, M., Wood, A., Dunn, G., Shiloh, S., & Todd, C. (2011). The genetic counseling outcome scale: A new patient-reported outcome measure for clinical genetics services. Clinical Genetics, 79(5), 413–424. https://doi.org/10.1111/j.1399-0004.2011.01636.xCrossRefPubMed

McAllister, M., & Dearing, A. (2015). Patient reported outcomes and patient empowerment in clinical genetics services. Clinical Genetics, 88(2), 114–121. https://doi.org/10.1111/cge.12520CrossRefPubMed

Davison, N., Payne, K., Eden, M., McAllister, M., Roberts, S. A., Ingram, S., Black, G. C. M., & Hall, G. (2017). Exploring the feasibility of delivering standardized genomic care using ophthalmology as an example. Genetics in Medicine, 19(9), 1032–1039. https://doi.org/10.1038/gim.2017.9CrossRefPubMed

Borle, K., Morris, E., Inglis, A., & Austin, J. (2018). Risk communication in genetic counseling: Exploring uptake and perception of recurrence numbers, and their impact on patient outcomes. Clinical Genetics, 94(2), 239–245. https://doi.org/10.1111/cge.13379CrossRefPubMed

Palmer, C. G. S., McConkie-Rosell, A., Holm, I. A., LeBlanc, K., Sinsheimer, J. S., Briere, L. C., Dorrani, N., Herzog, M. R., Lincoln, S., Schoch, K., Spillmann, R. C., & Brokamp, E. (2018). Understanding adult participant and parent empowerment prior to evaluation in the undiagnosed diseases network. Journal of Genetic Counseling, 27(5), 1087–1101. https://doi.org/10.1007/s10897-018-0228-6CrossRefPubMedPubMedCentral

10.

Slomp, C., Morris, E., Inglis, A., Lehman, A., & Austin, J. (2018). Patient outcomes of genetic counseling: Assessing the impact of different approaches to family history collection. Clinical Genetics, 93(4), 830–836. https://doi.org/10.1111/cge.13176CrossRefPubMed

11.

Costal Tirado, A., McDermott, A. M., Thomas, C., Ferrick, D., Harris, J., Edwards, A., & McAllister, M. (2017). Using patient-reported outcome measures for quality improvement in clinical genetics: An exploratory study. Journal of Genetic Counseling, 26(5), 1017–1028. https://doi.org/10.1007/s10897-017-0079-6CrossRefPubMedPubMedCentral

12.

Yuen, J., Lee, S. Y., Courtney, E., Lim, J., Soh, H., Li, S. T., Chen, Y., McAllister, M., Fenwick, E. K., & Ngeow, J. (2020). Evaluating empowerment in genetic counseling using patient-reported outcomes. Clinical Genetics, 97(2), 246–256. https://doi.org/10.1111/cge.13646CrossRefPubMed

13.

Segundo-Ribeiro, M., Bacalá, B. T., & de Andrade AlvarengaNascimento McAllisterFlória-Santos, W. L. C. M. M. (2020). Adaptation and preliminary validation of the genetic counseling outcome scale (GCOS-24) in a Brazilian genetic counseling setting. European Journal of Medical Genetics. https://doi.org/10.1016/j.ejmg.2020.104018CrossRefPubMed

14.

Muñoz-Cabello, P., García-Miñaúr, S., Espinel-Vallejo, M. E., Fernández-Franco, L., Stephens, A., Santos-Simarro, F., Lapunzina-Badía, P., & McAllister, M. (2018). Translation and cross-cultural adaptation with preliminary validation of GCOS-24 for use in Spain. Journal of Genetic Counseling, 27(3), 732–743. https://doi.org/10.1007/s10897-017-0154-zCrossRefPubMed

15.

Voorwinden, J. S., Plantinga, M., Krijnen, W., Ausems, M., Knoers, N., Velthuizen, M., Birnie, E., Lucassen, A. M., & van LangenRanchor, I. M. A. V. (2019). A validated PROM in genetic counselling: The psychometric properties of the Dutch version of the genetic counselling outcome scale. European Journal of Human Genetics, 27(5), 681–690. https://doi.org/10.1038/s41431-018-0318-9CrossRefPubMedPubMedCentral

16.

Yusuf, A., Peltekova, I., Savion‐Lemieux, T., Frei, J., Joober, R., Howe, J., Scherer, S. W., & Elsabbagh, M. (2021). Adaptation and validation of the genetic counseling outcome scale for autism spectrum disorders and related conditions. Journal of Genetic Counseling, 30(1), 305–318. https://doi.org/10.1002/jgc4.1323CrossRefPubMed

17.

Thomas, C., & McAllister, M. (2019). Establishing the minimum clinically important difference for the genetic counseling outcome scale (GCOS-24). Journal of Genetic Counseling, 28(5), 1003–1010. https://doi.org/10.1002/jgc4.1152CrossRefPubMed

18.

Grant, P. E., Pampaka, M., Payne, K., Clarke, A., & McAllister, M. (2019). Developing a short-form of the genetic counselling outcome scale: The genomics outcome scale. European Journal of Medical Genetics, 62(5), 324–334. https://doi.org/10.1016/j.ejmg.2018.11.015CrossRefPubMed

19.

Cano, S. J., Pendrill, L. R., Barbic, S. P., & Fisher, W. P. (2018). Patient-centred outcome metrology for healthcare decision-making. Journal of Physics: Conference Series. https://doi.org/10.1088/1742-6596/1044/1/012057CrossRef

20.

Barbic, S. P., Cano, S. J., & Mathias, S. (2018). The problem of patient-centred outcome measurement in psychiatry: Why metrology hasn’t mattered and why it should. Journal of Physics: Conference Series. https://doi.org/10.1088/1742-6596/1044/1/012069CrossRef

21.

Cabitza, F., & Dui, L. G. (2018). Collecting patient reported outcomes in the wild: Opportunities and challenges. Studies in Health Technology and Informatics, 247, 36–40. https://doi.org/10.3233/978-1-61499-852-5-36CrossRefPubMed

22.

Oehrlein, E. M., Perfetto, E. M., Love, T. R., Chung, Y., & Ghafoori, P. (2018). Patient-reported outcome measures in the food and drug administration pilot compendium: Meeting today’s standards for patient engagement in development? Value in Health, 21(8), 967–972. https://doi.org/10.1016/j.jval.2018.01.004CrossRefPubMed

23.

Inglis, A., Koehn, D., Mcgillivray, B., Stewart, S. E., & Austin, J. (2015). Evaluating a unique, specialist psychiatric genetic counseling clinic: Uptake and impact. Clinical Genetics, 87(3), 218–224. https://doi.org/10.1111/cge.12415CrossRefPubMed

24.

Tatum, D. (2000). Rasch analysis: An introduction to objective measurement. Laboratory Medicine, 31(5), 272–274.CrossRef

25.

Cano, S. J., Barrett, L. E., Zajicek, J. P., & Hobart, J. C. (2011). Beyond the reach of traditional analyses: Using Rasch to evaluate the DASH in people with multiple sclerosis. Multiple Sclerosis Journal, 17(2), 214–222. https://doi.org/10.1177/1352458510385269CrossRefPubMed

26.

Andrich, D., Sheridan, B., & Luo, G. (2010). RUMM 2030. 4.0 for windows (upgrade 4600.0109). RUMM laboratory Pty Ltd.

Titel: Using Rasch measurement theory to explore the fitness for purpose of the genetic counseling outcome scale: a tale of two scales
Auteurs: Kennedy Borle
Jehannine Austin
Skye Barbic
Publicatiedatum: 21-11-2022
Uitgeverij: Springer International Publishing
Gepubliceerd in: Quality of Life Research / Uitgave 3/2023
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI: https://doi.org/10.1007/s11136-022-03289-7

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Abstract

Background

Methods

Results

Conclusion

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