Measuring Hypochondria with Short Health Anxiety Inventory: Psychometric Properties in Colombian University Students

Medición de la hipocondría con el Short Health Anxiety Inventory: propiedades psicométricas en estudiantes universitarios colombianos

Published 2024-02-15

Open | Download
HTML Icon XML Icon PDF Icon Flip Icon
Issue
Vol. 6 No. 2 (2024)
Section
Research Article
How to Cite
1.
Measuring Hypochondria with Short Health Anxiety Inventory: Psychometric Properties in Colombian University Students. Rev. Investig. Innov. Cienc. Salud [Internet]. 2024 Feb. 15 [cited 2024 Nov. 21];6(2):128-3. Available from: https://riics.info/index.php/RCMC/article/view/266
DOI

https://doi.org/10.46634/riics.266
Dimensions
PlumX
license
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Renato Zambrano-Cruz
School of Psychology; Universidad Cooperativa de Colombia; Medellín; Colombia.
    Perfil Google Scholar
    https://orcid.org/0000-0003-2155-0039
    Jorge Restrepo-Carvajal
    School of Education and Social Sciences; Tecnológico de Antioquia – Institución Universitaria; Medellín; Colombia.
      https://orcid.org/0000-0001-8790-7454
      Tatiana Castañeda-Quirama
      School of Psychology; Politécnico Grancolombiano; Medellín; Colombia.
        https://orcid.org/0000-0002-1132-4241
        Show authors biography

        Introduction. The Short Health Anxiety Inventory is a commonly used tool for assessing health anxiety, but its psychometric properties and internal structure have not been examined in a Latin American Spanish-speaking population. This study aimed to establish the psychometric properties among Colombian university students.

        Method. The goodness of fit of four latent structure models of the Short Health Anxiety Inventory was tested using confirmatory factor analysis in a sample of 1004 Colombian university students.

        Results. The results show that the original model's structure does not fit well (CFI = .808; RMSEA = .074), and the reliability was .796 and .703 for the original two variables.

        Conclusions. The findings do not support the utilization of the Colombian version of the Short Health Anxiety Inventory by researchers and clinicians among Colombian university students.

        Article visits 360 | PDF visits 72

        1. American Psychiatric Association. Diagnostic and statistical manual of mental disorders: DSM-5-TR 5th ed. Washington D.C.: The Association; 2022. 1142 p.
        2. Salkovskis PM, Rimes KA, Warwick HMC, Clark DM. The Health Anxiety Inventory: development and validation of scales for the measurement of health anxiety and hypochondriasis. Psychol Med [Internet]. 2002;32(5): 843-53. doi: https://doi.org/10.1017/S0033291702005822
        3. Arnáez S, García-Soriano G, López-Santiago J, Belloch A. The Spanish validation of the Short Health Anxiety Inventory: Psychometric properties and clinical utility. Int J Clin Health Psychol [Internet]. 2019; 19(3): 251-60. doi: https://doi.org/10.1016/j.ijchp.2019.05.003
        4. Alberts NM, Hadjistavropoulos HD, Jones SL, Sharpe D. The Short Health Anxiety Inventory: A systematic review and meta-analysis. J Anxiety Disord [Internet]. 2013;27(1):68-78. doi: https://doi.org/10.1016/j.janxdis.2012.10.009
        5. Morales A, Reis S, Espada JP, Orgilés M. Portuguese validation of the Short Health Anxiety Inventory: Factor structure, reliability, and factor invariance. J Health Psychol [Internet]. 2018;23(14):1872-83. doi: https://doi.org/10.1177/1359105316669859
        6. Wheaton MG, Berman NC, Franklin JC, Abramowitz JS. Health Anxiety: Latent Structure and Associations with Anxiety-related Psychological Processes in a Student Sample. J Psychopathol Behav Assess [Internet]. 2010;32:565-74. doi: https://doi.org/10.1007/s10862-010-9179-4
        7. Alberts NM, Sharpe D, Kehler MD, Hadjistavropoulos HD. Health anxiety: Comparison of the latent structure in medical and non-medical samples. J Anxiety Disord [Internet]. 2011;25(4):612-4. doi: https://doi.org/10.1016/j.janxdis.2011.01.011
        8. Spielberger CD, Reheiser EC. Measuring anxiety, anger, depression, and curiosity as emotional states and personality traits with the STAI, STAXI and STPI. In: Hilsenroth MJ, Segal DL, editors. Comprehensive handbook of psychological assessment, Vol. 2: Personality assessment. Hoboken: John Wiley & Sons, Inc.; 2004. p. 70-86.
        9. Montero I, Leon O. A guide for naming research studies in Psychology. Int J Clin Health Psychol [Internet]. 2007;7(3): 847-62. Available from: http://www.aepc.es/ijchp/articulos.php?coid=Espa%EF%BF%BDol&id=256
        10. Abramowitz JS, Deacon BJ, Valentiner DP. The Short Health Anxiety Inventory: Psychometric Properties and Construct Validity in a Non-clinical Sample. Cognit Ther Res [Internet]. 2007;31(6):871-83. doi: https://doi.org/10.1007/s10608-006-9058-1
        11. Forero CG, Maydeu-Olivares A, Gallardo-Pujol D. Factor Analysis with Ordinal Indicators: A Monte Carlo Study Comparing DWLS and ULS Estimation. Struct Equ Modeling [Internet]. 2009;16(4):625-41. doi: https://doi.org/10.1080/10705510903203573
        12. Mîndrilă D. Maximum Likelihood (ML) and Diagonally Weighted Least Squares (DWLS) Estimation Procedures: A Comparison of Estimation Bias with Ordinal and Multivariate Non-Normal Data. International Journal for Digital Society [Internet]. 2010;1(1):60-66. doi: https://doi.org/10.20533/ijds.2040.2570.2010.0010
        13. Schubert A-L, Hagemann D, Voss A, Bergmann K. Evaluating the model fit of diffusion models with the root mean square error of approximation. J Math Psychol [Internet]. 2017;77:29-45. doi: https://doi.org/10.1016/j.jmp.2016.08.004
        14. Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct Equ Modeling [Internet]. 1999;6(1):1-55. doi: https://doi.org/10.1080/10705519909540118
        15. Gadernmann AM, Guhn M, Zumbo BD. Estimating ordinal reliability for Likert-type and ordinal item response data: A conceptual, empirical, and practical guide. Pract Assess Res Evaluation [Internet]. 2012;17:1-13. doi: https://doi.org/10.7275/n560-j767
        16. Zumbo BD, Gadermann AM, Zeisser C. Ordinal Versions of Coefficients Alpha and Theta for Likert Rating Scales. J Mod Appl Stat Methods [Internet]. 2007;6(1):21-9. doi: https://doi.org/10.22237/jmasm/1177992180
        17. Koo TK, Li MY. A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. J Chiropr Med [Internet]. 2016;15(2):155-63. doi: https://doi.org/10.1016/j.jcm.2016.02.012
        18. Taber KS. The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education. Res Sci Educ [Internet]. 2018;48:1273-96. doi: https://doi.org/10.1007/s11165-016-9602-2
        19. Alshayea AK. Latent structure, measurement invariance, and reliability of an Arabic version of the Short Health Anxiety Inventory. J Exp Psychopathol [Internet]. 2020;11(2). doi: https://doi.org/10.1177/2043808720912629
        20. Kelley K, Lai K. Accuracy in Parameter Estimation for the Root Mean Square Error of Approximation: Sample Size Planning for Narrow Confidence Intervals. Multivariate Behav Res [Internet]. 2011;46(1):1-32. doi: https://doi.org/10.1080/00273171.2011.543027
        21. Sauer KS, Jungmann SM, Witthöft M. Emotional and Behavioral Consequences of the COVID-19 Pandemic: The Role of Health Anxiety, Intolerance of Uncertainty, and Distress (In)Tolerance. Int J Environ Res Public Health [Internet]. 2020;17(19):1-18. doi: https://doi.org/10.3390/ijerph17197241
        Publish with RIICS

        Scimago

        Most read in the last 30 days

        Sistema OJS 3.4.0.7 - Metabiblioteca |