Normative Data on the Beck Depression Inventory - Second Edition (BDI-II) in College Students

• Published in: Journal of clinical psychology Vol. 71; no. 9; pp. 898 - 907
• Main Authors: Whisman, Mark A., Richardson, Emily D.
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01.09.2015; Wiley Periodicals Inc
• Subjects: Adolescent; Adult; BDI-II; Beck Depression Inventory - Second Edition; College students; Depressive Disorder - diagnosis; Depressive Disorder - epidemiology; Ethnicity; Female; Humans; Male; Mental depression; normative data; norms; Psychiatric Status Rating Scales - standards; Psychiatric Status Rating Scales - statistics & numerical data; Psychometrics; Quantitative psychology; Ratings & rankings; Reliable Change Index; Reproducibility of Results; Student behavior; Students; United States - epidemiology; Universities; Young Adult; United States; United States > US; Reliable Change Index; BDI-II; Beck Depression Inventory - Second Edition; normative data; norms
• ISSN: 0021-9762; 1097-4679
• DOI: 10.1002/jclp.22188

Objective This study was conducted to provide normative data on the Beck Depression Inventory – Second Edition (BDI‐II) in college students. Method Data were obtained from 15,233 college students drawn from 17 universities in the United States, weighted to match the gender and race/ethnicity of enrollment in degree‐granting institutions. Results Descriptive statistics, point prevalence of individuals exceeding cutoff scores, and mean differences by gender and race/ethnicity were provided. Because the distribution of BDI‐II scores was not normal, percentile ranks for raw scores were provided for the total sample and separately by gender and race/ethnicity for the total sample and by race/ethnicity for men and women. Normative data were used to calculate the Reliable Change Index on the BDI‐II for college students. Conclusion Because the distribution of BDI‐II scores demonstrated significant skewness and non‐normal kurtosis, percentile ranks are important to consider in interpreting scores on the measure, in addition to descriptive statistics.