CRITERION-BASED VALIDITY OF THE DEPRESSION SCALE OF LATVIAN CLINICAL PERSONALITY INVENTORY
DOI:
https://doi.org/10.17770/sie2017vol1.2351Keywords:
depression, criterion validity, reliability, screening, sensitivity, specificityAbstract
The main aim of this study was to evaluate the criterion validity and to estimate the cut-off score of the Depression scale (DS) and short Depression scale (DSs) for a new self-report measure – Latvian Clinical Personality Inventory (LCPI). Usefulness of DS and DSs for identifying patients with major depression were analysed based on psychometric analysis of data acquired from psychiatric inpatient sample with depressive disorder (n = 37) in comparison to randomised stratified community subsample (n = 176) selected from the overall test development sample (N = 888). The present study was carried within the framework of the National Research Program (BIOMEDICINE) 2014 – 2017 (sub-project Nr.5.8.2.). It was shown that all 24 item of DS show good to excellent discrimination power. Cronbach’s alpha was 0.97 for DS and 0.95 for DSs in test development sample. For DS, the optimal cut-off score was 26 points (sensitivity 95%, specificity 91%, and positive predicted value of 69%). For DSs, the optimal cut-off was 12 points (sensitivity 92%, specificity 89%, and positive predicted value 63%). DS and DSs of LCPI is proved to have good criterion validity in detecting depression and to be a reliable and valid instrument for assessment of depression symptoms in patients with depression and in general population. Subjects scoring at least 26 on DS or 12 points on DSs constitute a target group for further diagnostic assessment in order to determine appropriate treatment.Downloads
References
American Psychiatric Association (2013). Diagnostic and Statistical Manual of Mental
Disorders (5rd edition). Washington, DC.
Ayuso-Mateos, J. L., Vázquez-Barquero, J. L., Dowrick, C., Lehtinen, V., Dalgard, O. S., Casey, P., & ... Wilkinson, G. (2001). Depressive disorders in Europe: prevalence figures from the ODIN study. The British Journal of Psychiatry, 179, 308-316.
Gilbody, S., Richards, D., Brealey, S., & Hewitt, C. (2007). Screening for depression in medical settings with the Patient Health Questionnaire (PHQ): a diagnostic meta-analysis. Journal of General Internal Medicine, 22(11), 1596-1602.
Grissom. R. J.. & Kim. J. J. (2005). Effect sizes for research: A broad practical approach. Mahwah. NJ: Erlbaum.
Haringsma, R., Engels, G. I., Beekman, A. F., & Spinhoven, P. (2004). The criterion validity of the Center for Epidemiological Studies Depression Scale (CES-D) in a sample of self-referred elders with depressive symptomatology. International Journal of Geriatric Psychiatry, 19(6), 558-563.
Hedges. L. V. (1981). Distribution theory for Glass' estimator of effect size and related estimators. Journal of Educational Statistics. 6(2), 107–128. doi:10.3102/10769986006002107.
Marcus, S. M., Young, E. A., Kerber, K. B., Kornstein, S., Farabaugh, A. H., Mitchell, J., & ... Rush, A. J. (2005). Gender differences in depression: Findings from the STAR*D study. Journal of Affective Disorders, 87(2/3), 141-150. doi:10.1016/j.jad.2004.09.008
Mathers, C. D., & Loncar, D. (2006). Projections of global mortality and burden of disease from 2002 to 2030. Plos Medicine, 3(11), e442.
Meehl, P. E., & Rosen, A. (1955). Antecedent probability and the efficiency of psychometric signs, patterns, or cutting scores. Psychological Bulletin, 52(3), 194-216.
Mitchell, A. J., Vaze, A., & Rao, S. (2009). Clinical diagnosis of depression in primary care: A meta-analysis. The Lancet, 374(9690), 609-619. Retrieved from https://search.proquest.com/docview/199048061?accountid=32994
Perepjolkina, V., Koļesņikova, J., Mārtinsone, K., Stepens, A. (in press). Latvijas Klīniskais personības tests (LKPT). Tehniskā rokasgrāma. Rīga: RSU
Perepjolkina, V., Kolesnikova, J., Mārtinsone, K., & Stepens, A. (2016). Latvijas Klīniskā personības testa otrās sākotnējo apgalvojumu kopas izstrāde: integratīvās pieejas pielietošana [Development of the Second Preliminary Item Pool of the Latvian Clinical Personality Inventory: an Integrative Approach]. Society, integration, education. Proceedings of the International Scientifical Conference, Volume I, May 27th-28th, pp. 469–483. Rēzeknes Tehnoloģiju akadēmija, 2016. http://journals.ru.lv/index.php/SIE/article/view/1521/1673 (In Latvian)
Pulmanis, T., Japeniņa, S., Taube, M. (2016). Psihiskā veselība Latvijā 2015. gadā. Tematiskais ziņojums, 16. izdevums [Mental Health in Latvia in 2015: A Thematic Report] (in Latvian). Rīga: Slimību profilakses un kontroles cents. Accessed: https://www.spkc.gov.lv/upload/Psihiska_veseliba_faili/851438_tz_pvl_2015_final_vietnem.pdf
Rancans, E., Vrublevska, J., Kivite, A., Ivanovs, R., Logins, R., & Berze, L. (2016). P.2.h.008 - Prevalence of depression in primary care settings in Latvia – the results of the National Research Program BIOMEDICINE. European Neuropsychopharmacology, 26, S478-S479. doi:10.1016/S0924-977X(16)31483-3
Rancans, E., Vrublevska, J., Snikere, S., Koroleva, I., & Trapencieris, M. (2014). The point prevalence of depression and associated sociodemographic correlates in the general population of Latvia. Journal of Affective Disorders, 156, 104-110. doi:10.1016/j.jad.2013.11.022
Rancans, E., Vrublevska, J., Trapencieris, M., Snikere, S., Ivanovs, R., Logins, R., & Berze, L. (2016). P.2.h.016 - Validity of patient health questionnaire (PHQ-9) in detecting depression in primary care settings in Latvia – the results of the National Research Project BIOMEDICINE. European Neuropsychopharmacology, 26, S481. doi:10.1016/S0924-977X(16)31487-0
Rihmer, Z. (2007). Suicide risk in mood disorders. Current Opinion In Psychiatry, 20(1), 17-22.
Sawilowsky, S. S. (2009). New effect size rules of thumb. Journal of Modern Applied Statistical Methods, 8(2), 597 – 599.
Stangroom. J. (2017). Effect Size Calculator for T-Test. Social Science Statistics. http://www.socscistatistics.com/effectsize/Default3.aspx [Accessed: 6 February 2017].
Streiner, D. L. (2003). Diagnosing tests: using and misusing diagnostic and screening tests. Journal of Personality Assessment, 81(3), 209-219.
Vrublevska, J., Trapencieris, M., Snikere, S., Grinberga, D., Velika, B., Pudule, I., & Rancans, E. (2017). The 12-month prevalence of depression and health care utilization in the general population of Latvia. Journal of Affective Disorders, 210, 204-210. doi:10.1016/j.jad.2016.12.031
Williams, J. J., Pignone, M., Ramirez, G., & Perez Stellato, C. (2002). Identifying depression in primary care: a literature synthesis of case-finding instruments. General Hospital Psychiatry, 24(4), 225-237.
World Health Organisation. (1992). International Statistical Classification of Diseases and Related Health Problems, 10th Revision (ICD-10). Geneva: WHO.
Zlotnick, C., Kohn, R., Keitner, G., & Della Grotta, S. A. (2000). The relationship between quality of interpersonal relationships and major depressive disorder: findings from the National Comorbidity Survey. Journal of Affective Disorders, 59(3), 205-215.
