Open AccessThe Impact of Education on Depression Assessment: Differential Item Functioning Analysis
Author(s) -
Bayley J. Taple,
Robert S. Chapman,
Benjamin D. Schalet,
Rylee Brower,
James W. Griffith
Publication year - 2020
Publication title -
assessment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.59
H-Index - 87
eISSN - 1552-3489
pISSN - 1073-1911
DOI - 10.1177/1073191120971357
Subject(s) - differential item functioning , psychology , respondent , clinical psychology , mental health , depression (economics) , beck depression inventory , dysphoria , affect (linguistics) , health care , psychometrics , psychiatry , item response theory , anxiety , communication , political science , law , economics , macroeconomics , economic growth
A person's level of education can affect their access to health care, and their health outcomes. Increasing rates of depression are another looming public health concern. Therefore, vulnerability is compounded for individuals who have a lower level of education and depression. Assessment of depressive symptoms is integral to many domains of health care including primary care and mental health specialty care. This investigation examined the degree to which education influences the psychometric properties of self-report items that measure depressive symptoms. This study was a secondary data analysis derived from three large internet panel studies. Together, the studies included the Beck Depression Inventory-II, the Center for Epidemiologic Studies Depression Scale, the Patient Health Questionnaire, and the Patient Reported Outcomes Measurement Information System measures of depression. Using a differential item functioning (DIF) approach, we found evidence of DIF such that some items on each of the questionnaires were flagged for DIF with effect sizes ranging from McFadden's Pseudo R 2 = .005 to .022. For example, results included several double-barreled questions flagged for DIF. Overall, questionnaires assessing depression vary in level of complexity, which interacts with the respondent's level of education. Measurement of depression should include consideration of possible educational disparities, to identify people who may struggle with a written questionnaire, or may be subject to subtle psychometric biases associated with education.