IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-03649277.html
   My bibliography  Save this paper

Development and Calibration of the PREMIUM Item Bank for Measuring Respect and Dignity for Patients with Severe Mental Illness

Author

Listed:
  • Sara Fernandes

    (CEReSS - Centre d'études et de recherche sur les services de santé et la qualité de vie - AMU - Aix Marseille Université)

  • Guillaume Fond

    (Fondation FondaMental [Créteil], CEReSS - Centre d'études et de recherche sur les services de santé et la qualité de vie - AMU - Aix Marseille Université)

  • Xavier Zendjidjian

    (CEReSS - Centre d'études et de recherche sur les services de santé et la qualité de vie - AMU - Aix Marseille Université)

  • Pierre Michel

    (AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Karine Baumstarck

    (CEReSS - Centre d'études et de recherche sur les services de santé et la qualité de vie - AMU - Aix Marseille Université)

  • Christophe Lançon

    (CEReSS - Centre d'études et de recherche sur les services de santé et la qualité de vie - AMU - Aix Marseille Université)

  • Ludovic Samalin

    (Fondation FondaMental [Créteil])

  • Pierre-Michel Llorca

    (Fondation FondaMental [Créteil])

  • Magali Coldefy

    (IRDES - Institut de Recherche et Documentation en Economie de la Santé - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres)

  • Pascal Auquier

    (CEReSS - Centre d'études et de recherche sur les services de santé et la qualité de vie - AMU - Aix Marseille Université)

  • Laurent Boyer

    (CEReSS - Centre d'études et de recherche sur les services de santé et la qualité de vie - AMU - Aix Marseille Université)

  • Group Collaborators of The French Premium

Abstract

Most patient-reported experience measures (PREMs) are paper-based, leading to a high burden for patients and care providers. The aim of this study was to (1) calibrate an item bank to measure patients' experience of respect and dignity for adult patients with serious mental illnesses and (2) develop computerized adaptive testing (CAT) to improve the use of this PREM in routine practice. Patients with schizophrenia, bipolar disorder, and major depressive disorder were enrolled in this multicenter and cross-sectional study. Psychometric analyses were based on classical test and item response theories and included evaluations of unidimensionality, local independence, and monotonicity; calibration and evaluation of model fit; analyses of differential item functioning (DIF); testing of external validity; and finally, CAT development. A total of 458 patients participated in the study. Of the 24 items, 2 highly inter-correlated items were deleted. Factor analysis showed that the remaining items met the unidimensional assumption (RMSEA = 0.054, CFI = 0.988, TLI = 0.986). DIF analyses revealed no biases by sex, age, care setting, or diagnosis. External validity testing has generally supported our assumptions. CAT showed satisfactory accuracy and precision. This work provides a more accurate and flexible measure of patients' experience of respect and dignity than that obtained from standard questionnaires.

Suggested Citation

  • Sara Fernandes & Guillaume Fond & Xavier Zendjidjian & Pierre Michel & Karine Baumstarck & Christophe Lançon & Ludovic Samalin & Pierre-Michel Llorca & Magali Coldefy & Pascal Auquier & Laurent Boyer , 2022. "Development and Calibration of the PREMIUM Item Bank for Measuring Respect and Dignity for Patients with Severe Mental Illness," Post-Print hal-03649277, HAL.
    • Handle: RePEc:hal:journl:hal-03649277
    DOI: 10.3390/jcm11061644
    Note: View the original document on HAL open archive server: https://amu.hal.science/hal-03649277v1
    as

    Download full text from publisher

    File URL: https://amu.hal.science/hal-03649277v1/document
    Download Restriction: no
    File URL: https://libkey.io/10.3390/jcm11061644?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Geoff Masters, 1982. "A rasch model for partial credit scoring," Psychometrika, Springer;The Psychometric Society, vol. 47(2), pages 149-174, June.
    2. R. Bock & Murray Aitkin, 1981. "Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm," Psychometrika, Springer;The Psychometric Society, vol. 46(4), pages 443-459, December.
    3. Chalmers, R. Philip, 2016. "Generating Adaptive and Non-Adaptive Test Interfaces for Multidimensional Item Response Theory Applications," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 71(i05).
    4. Chalmers, R. Philip, 2012. "mirt: A Multidimensional Item Response Theory Package for the R Environment," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i06).
    5. Tam Nguyen & Hae-Ra Han & Miyong Kim & Kitty Chan, 2014. "An Introduction to Item Response Theory for Patient-Reported Outcome Measurement," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 7(1), pages 23-35, March.
    6. Lee Cronbach, 1951. "Coefficient alpha and the internal structure of tests," Psychometrika, Springer;The Psychometric Society, vol. 16(3), pages 297-334, September.
    7. L. Boyer & G. Fond & B. Devictor & J. -C. Samuelian & C. Lançon & F. Rouillon & R. Gaillard & X. Zendjidjian & P. -M. Llorca, 2016. "Reflection on the psychiatric financial allocation in France," Post-Print hal-01482653, HAL.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Felix Zimmer & Clemens Draxler & Rudolf Debelak, 2023. "Power Analysis for the Wald, LR, Score, and Gradient Tests in a Marginal Maximum Likelihood Framework: Applications in IRT," Psychometrika, Springer;The Psychometric Society, vol. 88(4), pages 1249-1298, December.
    2. Chengyu Cui & Chun Wang & Gongjun Xu, 2024. "Variational Estimation for Multidimensional Generalized Partial Credit Model," Psychometrika, Springer;The Psychometric Society, vol. 89(3), pages 929-957, September.
    3. Luo, Nanyu & Ji, Feng & Han, Yuting & He, Jinbo & Zhang, Xiaoya, 2024. "Fitting item response theory models using deep learning computational frameworks," OSF Preprints tjxab, Center for Open Science.
    4. Melissa Gladstone & Gillian Lancaster & Gareth McCray & Vanessa Cavallera & Claudia R. L. Alves & Limbika Maliwichi & Muneera A. Rasheed & Tarun Dua & Magdalena Janus & Patricia Kariger, 2021. "Validation of the Infant and Young Child Development (IYCD) Indicators in Three Countries: Brazil, Malawi and Pakistan," IJERPH, MDPI, vol. 18(11), pages 1-19, June.
    5. Björn Andersson & Tao Xin, 2021. "Estimation of Latent Regression Item Response Theory Models Using a Second-Order Laplace Approximation," Journal of Educational and Behavioral Statistics, , vol. 46(2), pages 244-265, April.
    6. Klaas Sijtsma & Jules L. Ellis & Denny Borsboom, 2024. "Recognize the Value of the Sum Score, Psychometrics’ Greatest Accomplishment," Psychometrika, Springer;The Psychometric Society, vol. 89(1), pages 84-117, March.
    7. Tim Kaiser & Luis Oberrauch & Günther Seeber, 2020. "Measuring economic competence of secondary school students in Germany," The Journal of Economic Education, Taylor & Francis Journals, vol. 51(3-4), pages 227-242, August.
    8. C. Glas & Anna Dagohoy, 2007. "A Person Fit Test For Irt Models For Polytomous Items," Psychometrika, Springer;The Psychometric Society, vol. 72(2), pages 159-180, June.
    9. Joakim Wallmark & James O. Ramsay & Juan Li & Marie Wiberg, 2024. "Analyzing Polytomous Test Data: A Comparison Between an Information-Based IRT Model and the Generalized Partial Credit Model," Journal of Educational and Behavioral Statistics, , vol. 49(5), pages 753-779, October.
    10. Alexander Robitzsch, 2021. "A Comprehensive Simulation Study of Estimation Methods for the Rasch Model," Stats, MDPI, vol. 4(4), pages 1-23, October.
    11. P. Bentler, 1986. "Structural modeling and psychometrika: An historical perspective on growth and achievements," Psychometrika, Springer;The Psychometric Society, vol. 51(1), pages 35-51, March.
    12. Robert Zwitser & Gunter Maris, 2015. "Conditional Statistical Inference with Multistage Testing Designs," Psychometrika, Springer;The Psychometric Society, vol. 80(1), pages 65-84, March.
    13. Anthony C Waddimba & David C Mohr & Howard B Beckman & Mark M Meterko, 2020. "Physicians’ perceptions of autonomy support during transition to value-based reimbursement: A multi-center psychometric evaluation of six-item and three-item measures," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-29, April.
    14. Dylan Molenaar, 2015. "Heteroscedastic Latent Trait Models for Dichotomous Data," Psychometrika, Springer;The Psychometric Society, vol. 80(3), pages 625-644, September.
    15. Christopher J. Urban & Daniel J. Bauer, 2021. "A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 86(1), pages 1-29, March.
    16. Bacci, Silvia & Fabbricatore, Rosa & Iannario, Maria, 2023. "Multilevel IRT models for the analysis of satisfaction for distance learning during the Covid-19 pandemic," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    17. Thiel, Hendrik & Thomsen, Stephan L., 2013. "Noncognitive skills in economics: Models, measurement, and empirical evidence," Research in Economics, Elsevier, vol. 67(2), pages 189-214.
    18. Laura Maldonado-Murciano & Halley M. Pontes & Mark D. Griffiths & Maite Barrios & Juana Gómez-Benito & Georgina Guilera, 2020. "The Spanish Version of the Internet Gaming Disorder Scale-Short Form (IGDS9-SF): Further Examination Using Item Response Theory," IJERPH, MDPI, vol. 17(19), pages 1-14, September.
    19. repec:osf:osfxxx:tjxab_v1 is not listed on IDEAS
    20. Maud Dampérat & Ping Lei & Florence Jeannot, 2019. "IRT Approach for rating scales: applications for normal and non-normal distributions," Post-Print hal-04325043, HAL.
    21. Zhehan Jiang & Jonathan Templin, 2019. "Gibbs Samplers for Logistic Item Response Models via the Pólya–Gamma Distribution: A Computationally Efficient Data-Augmentation Strategy," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 358-374, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hal:journl:hal-03649277. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.