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
Gepubliceerd in: Quality of Life Research 9/2021

13-05-2021

Psychometric properties of the Dutch-Flemish PROMIS® pediatric item banks Anxiety and Depressive Symptoms in a general population

Auteurs: L. H. Klaufus, M. A. J. Luijten, E. Verlinden, M. F. van der Wal, L. Haverman, P. Cuijpers, M. J. M. Chinapaw, C. B. Terwee

Gepubliceerd in: Quality of Life Research | Uitgave 9/2021

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

This study aims to validate the Dutch-Flemish PROMIS pediatric item banks v2.0 Anxiety and Depressive Symptoms, the short forms 8a, and computerized adaptive tests (CATs) in a general Dutch population and to provide reference data.

Methods

Participants (N = 2,893, aged 8–18), recruited by two internet survey providers, completed both item banks. These item banks were assessed on unidimensionality, local independence, monotonicity, Graded Response Model (GRM) item fit, and differential item functioning (DIF) for gender, age group, region, ethnicity, and language. The short forms and CATs were assessed on reliability and construct validity compared to the Revised Child Anxiety and Depression Scale short version (RCADS-22) subscales. Reference scores were calculated.

Results

Both item banks showed sufficient unidimensionality, local independence, monotonicity, and GRM item fit, except for three Depressive Symptoms items that showed insufficient GRM item fit. No DIF was found when using ordinal regression analyses, except for two Depressive Symptoms items that showed DIF for language; all items showed DIF for language when using IRT PRO, except for one Anxiety item. Both short forms and CATs revealed sufficient reliability for moderate and severe levels of anxiety and depression, as well as high positive correlations with corresponding RCADS-22 subscales and slightly lower correlations with non-corresponding RCADS-22 subscales.

Conclusion

The Dutch-Flemish PROMIS pediatric item banks v2.0 Anxiety and Depressive Symptoms, the short forms 8a and CATs are useful to assess and monitor anxiety and depression in a general population. Reference data are presented.
vorige artikel The development and initial validation of the Breast Cancer Recurrence instrument (BreastCaRe)—a patient-reported outcome measure for detecting symptoms of recurrence after breast cancer
volgende artikel Measurement properties of the Boston Carpal Tunnel Questionnaire in subjects with neurophysiological confirmation of carpal tunnel syndrome: a Rasch analysis perspective
Voetnoten
1
For brevity, children and adolescents are referred to as “children” in this paper.
 
Literatuur
1.
Polanczyk, G. V., Salum, G. A., Sugaya, L. S., Caye, A., & Rohde, L. A. (2015). Annual research review: A meta-analysis of the worldwide prevalence of mental disorders in children and adolescents. Journal of Child Psychology and Psychiatry, 56(3), 345–365PubMedCrossRef
2.
Erskine, H. E., Moffitt, T. E., Copeland, W. E., Costello, E. J., Ferrari, A. J., Patton, G., et al. (2015). A heavy burden on young minds: The global burden of mental and substance use disorders in children and youth. Psychological Medicine, 45(7), 1551–1563PubMedCrossRef
3.
Patton, G. C., Coffey, C., Romaniuk, H., Mackinnon, A., Carlin, J. B., Degenhardt, L., et al. (2014). The prognosis of common mental disorders in adolescents: A 14-year prospective cohort study. The Lancet, 383(9926), 1404–1411CrossRef
4.
Clayborne, Z. M., Varin, M., & Colman, I. (2019). Systematic review and meta-analysis: Adolescent depression and long-term psychosocial outcomes. Journal of the American Academy of Child & Adolescent Psychiatry, 58(1), 72–79CrossRef
5.
Doering, S., Lichtenstein, P., Gillberg, C., Middeldorp, C. M., Bartels, M., et al. (2019). Anxiety at age 15 predicts psychiatric diagnoses and suicidal ideation in late adolescence and young adulthood: Results from two longitudinal studies. BMC Psychiatry, 19, 363PubMedPubMedCentralCrossRef
6.
Johnson, D., Dupuis, G., Piche, J., Clayborne, Z., & Colman, I. (2017). Adult mental health outcomes of adolescent depression: A systematic review. Depression and Anxiety, 35(8), 700–716CrossRef
7.
Siu, A. L. (2016). Screening for depression in children and adolescents: U.S. Preventive Services Task Force recommendation statement. Annals of Internal Medicine, 164(5), 360–366PubMedCrossRef
8.
Stockings, E. A., Degenhardt, L., Dobbins, T., & Lee, Y. Y. (2016). Preventing depression and anxiety in young people: A review of the joint efficacy of universal, selective and indicated prevention. Psychological Medicine, 46(1), 11–26PubMedCrossRef
9.
Beidas, R. S., Stewart, R. E., Walsh, L., Lucas, S., Downey, M. M., Jackson, K., et al. (2015). Free, brief, and validated: Standardized instruments for low-resource mental health settings. Cognitive and Behavioral Practice, 22(1), 5–19PubMedPubMedCentralCrossRef
10.
Cohen, J. R., So, F. K., Hankin, B. L., & Lee, B. A. (2019). Youth depression screening with parent and self-reports: Assessing current and prospective depression risk. Child Psychiatry & Human Development, 50(4), 647–660CrossRef
11.
Chorpita, B. F., Yim, L., Moffitt, C., Umemoto, L. A., & Francis, S. E. (2000). Assessment of symptoms of DSM-IV anxiety and depression in children: A revised child anxiety and depression scale. Behaviour Research and Therapy, 38(8), 835–855PubMedCrossRef
12.
Ebesutani, C., Reise, S. P., Chorpita, B. F., Ale, C., Regan, J., Young, J., et al. (2012). The Revised Child Anxiety and Depression Scale-short version: Scale reduction via exploratory bifactor modeling of the broad anxiety factor. Psychological Assessment, 24(4), 833–845PubMedCrossRef
13.
Fried, E. I., & Nesse, R. M. (2015). Depression sum-scores don’t add up: Why analyzing specific depression symptoms is essential. BMC Medicine, 13, 72PubMedPubMedCentralCrossRef
14.
McElroy, E., Fearon, P., Belsky, J., Fonagy, P., & Patalay, P. (2018). Networks of depression and anxiety symptoms across development. Journal of the American Academy of Child & Adolescent Psychiatry, 57(12), 964–973CrossRef
15.
De Vet, H. C., Terwee, C. B., Mokkink, L. B., & Knol, D. L. (2011). Measurement in medicine: A practical guide. Cambridge: Cambridge University Press.CrossRef
16.
Cella, D., Yount, S., Rothrock, N., Gershon, R., Cook, K., Reeve, B., et al. (2007). The Patient-Reported Outcomes Measurement Information System (PROMIS): Progress of an NIH roadmap cooperative group during its first two years. Medical Care, 45(5 Suppl 1), S3–S11PubMedPubMedCentralCrossRef
17.
Cella, D., Riley, W., Stone, A., Rothrock, N., Reeve, B., Yount, S., et al. (2010). Initial adult health item banks and first wave testing of the Patient-Reported Outcomes Measurement Information System (PROMISTM) network: 2005–2008. Journal of Clinical Epidemiology, 63(11), 1179–1194PubMedPubMedCentralCrossRef
18.
DeWalt, D. A., Rothrock, N., Yount, S., Stone, A. A., & PROMIS Cooperative Group. (2007). Evaluation of item candidates: The PROMIS qualitative item review. Medical Care, 45(5 Suppl 1), S12–S21PubMedPubMedCentralCrossRef
19.
Irwin, D. E., Varni, J. W., Yeatts, K., & DeWalt, D. A. (2009). Cognitive interviewing methodology in the development of a pediatric item bank: A patient reported outcomes measurement information system (PROMIS) study. Health and Quality of Life Outcomes, 7, 3PubMedPubMedCentralCrossRef
20.
Walsh, T. R., Irwin, D. E., Meier, A., Varni, J. W., & DeWalt, D. A. (2008). The use of focus groups in the development of the PROMIS pediatrics item bank. Quality of Life Research, 17(5), 725–735PubMedPubMedCentralCrossRef
21.
Cella, D., Gershon, R., Lai, J., & Choi, S. (2007). The future of outcomes measurement: Item banking, tailored short-forms, and computerized adaptive assessment. Quality of Life Research, 16(Suppl 1), 133–141PubMedCrossRef
22.
Irwin, D. E., Stucky, B., Langer, M. M., Thissen, D., Morgan DeWitt, E., Lai, J., et al. (2010). An item response analysis of the pediatric PROMIS anxiety and depressive symptoms scales. Quality of Life Research, 19(4), 595–607PubMedPubMedCentralCrossRef
23.
Irwin, D. E., Stucky, B. D., Thissen, D., Morgan DeWitt, E., Lai, J., Yeatts, K., et al. (2010). Sampling plan and patient characteristics of the PROMIS pediatrics large-scale survey. Quality of Life Research, 19(4), 585–594PubMedPubMedCentralCrossRef
24.
Alonso, J., Bartlett, S. J., Rose, M., Aaronson, N. K., Chaplin, J. E., Efficace, F., et al. (2013). The case for an international patient-reported outcomes measurement information system (PROMIS®) initiative. Health and Quality of Life Outcomes, 11(1), 1–5CrossRef
25.
Haverman, L., Grootenhuis, M. A., Raat, H., van Rossum, M. A. J., van Dulmen-den Broeder, E., Hoppenbrouwers, K., et al. (2016). Dutch-Flemish translation of nine pediatric item banks from the Patient-Reported Outcomes Measurement Information System (PROMIS)®. Quality of Life Research, 25(3), 761–765PubMedCrossRef
26.
27.
Klaufus, L., Verlinden, E., van der Wal, M., Kösters, M., Cuijpers, P., & Chinapaw, M. (2020). Psychometric evaluation of two short versions of the Revised Child Anxiety and Depression Scale. BMC Psychiatry, 20, 47PubMedPubMedCentralCrossRef
28.
Reeve, B. B., Hays, R. D., Bjorner, J. B., Cook, K. F., Crane, P. K., Teresi, J. A., et al. (2007). Psychometric evaluation and calibration of health-related quality of life item banks: Plans for the Patient-Reported Outcomes Measurement Information System (PROMIS). Medical Care, 45(5 Suppl 1), S22–S31PubMedCrossRef
29.
Rosseel, Y. (2012). Lavaan: An R package for structural equation modeling and more. Journal of Statistical Software, 48(2), 1–36CrossRef
30.
Satorra, A., & Bentler, P. M. (2001). A scaled difference chi-square test statistic for moment structure analysis. Psychometrika, 66(4), 507–514CrossRef
31.
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling, 6(1), 1–55CrossRef
32.
33.
34.
Rodriguez, A., Reise, S. P., & Haviland, M. G. (2016). Applying bifactor statistical indices in the evaluation of psychological measures. Journal of Personality Assessment, 98(3), 223–237PubMedCrossRef
35.
Reise, S. P., Scheines, R., Widaman, K. F., & Haviland, M. G. (2013). Multidimensionality and structural coefficient bias in structural equation modeling: A bifactor perspective. Educational and Psychological Measurement, 73(1), 5–26CrossRef
36.
Chen, F. F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling, 14(3), 464–504CrossRef
37.
38.
Mokken, R. J. (2011). A theory and procedure of scale analysis. Amsterdam: De Gruyter.
39.
Chalmers, R. P. (2012). Mirt: A multidimensional item response theory package for the R environment. Journal of Statistical Software, 48(6), 1–29CrossRef
40.
Kang, T., & Chen, T. T. (2008). Performance of the generalized S-X2 item fit index for polytomous IRT models. Journal of Educational Measurement, 45(4), 391–406CrossRef
41.
Revicki, D. A., Chen, W., Harnam, N., Cook, K. F., Amtmann, D., Callahan, L. F., et al. (2009). Development and psychometric analysis of the PROMIS pain behavior item bank. Pain, 146(1–2), 158–169PubMedPubMedCentralCrossRef
42.
Choi, S. W., Gibbons, L. E., & Crane, P. K. (2011). Lordif: an R package for detecting differential item functioning using iterative hybrid ordinal logistic regression/item response theory and Monte Carlo simulations. Journal of Statistical Software, 39(8), 1–30PubMedPubMedCentralCrossRef
43.
44.
Magis, D., & Raîche, G. (2012). Random generation of response patterns under computerized adaptive testing with the R package catR. Journal of Statistical Software, 48(8), 1–31CrossRef
45.
Mokkink, L. B., Terwee, C. B., Patrick, D. L., Alonso, J., Stratford, P. W., Knol, D. L., et al. (2010). The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: An international Delphi study. Quality of Life Research, 19(4), 539–549PubMedPubMedCentralCrossRef
46.
Carle, A. C., Bevans, K. B., Tucker, C. A., & Forrest, C. B. (2020). Using nationally representative percentiles to interpret PROMIS pediatric measures. Quality of Life Research, 29(11), 1–8
47.
Kaat, A.J., & Schalet, B.D. (2018). P040 A simulation study of DIF detection procedures, in Proceedings of the 4th Annual PROMIS® Health Organization Conference: Global advances in methodology and clinical science. Journal of Patient-Reported Outcomes, 2(Suppl 1): 53.
48.
Kösters, M. P., Chinapaw, M. J., Zwaanswijk, M., van der Wal, M. F., & Koot, H. M. (2015). Structure, reliability, and validity of the revised child anxiety and depression scale (RCADS) in a multi-ethnic urban sample of Dutch children. BMC Psychiatry, 15, 132PubMedPubMedCentralCrossRef
Metagegevens
Titel
Psychometric properties of the Dutch-Flemish PROMIS® pediatric item banks Anxiety and Depressive Symptoms in a general population
Auteurs
L. H. Klaufus
M. A. J. Luijten
E. Verlinden
M. F. van der Wal
L. Haverman
P. Cuijpers
M. J. M. Chinapaw
C. B. Terwee
Publicatiedatum
13-05-2021
Uitgeverij
Springer International Publishing
Gepubliceerd in
Quality of Life Research / Uitgave 9/2021
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649
DOI
https://doi.org/10.1007/s11136-021-02852-y

Andere artikelen Uitgave 9/2021

Quality of Life Research 9/2021 Naar de uitgave

OriginalPaper

Measurement properties of the Boston Carpal Tunnel Questionnaire in subjects with neurophysiological confirmation of carpal tunnel syndrome: a Rasch analysis perspective

OriginalPaper

The impact of idiopathic pulmonary fibrosis on health state utility values: evidence from Australia

OriginalPaper

Psychometric assessment of EQ-5D-5L and ReQoL measures in patients with anxiety and depression: construct validity and responsiveness

OriginalPaper

Diabetes and health-related quality of life among American Indians: the role of psychosocial factors

OriginalPaper

PROMIS Global Health: Feasibility in home health

OriginalPaper

Enabling cross-cultural data pooling in trials: linguistic validation of head and neck cancer measures for Indian patients