Abstract
BackgroundResponse times to depressive symptom items in a mobile-based depression screening instrument has potential as an implicit self-schema indicator for depression but has yet to be determined; the instrument was designed to readily record depressive symptoms experienced on a daily basis. In this study, the well-validated Korean version of the Center for Epidemiologic Studies Depression Scale-Revised (K-CESD-R) was adopted.ObjectiveThe purpose of this study was to investigate the relationship between depression severity (ie, explicit measure: total K-CESD-R Mobile scores) and the latent trait of interest in schematic self-referent processing of depressive symptom items (ie, implicit measure: response times to items in the K-CESD-R Mobile scale). The purpose was to investigate this relationship among undergraduate students who had never been diagnosed with, but were at risk for, major depressive disorder (MDD) or comorbid MDD with other neurological or psychiatric disorders.MethodsA total of 70 participants—36 males (51%) and 34 females (49%)—aged 19-29 years (mean 22.66, SD 2.11), were asked to complete both mobile and standard K-CESD-R assessments via their own mobile phones. The mobile K-CESD-R sessions (binary scale: yes or no) were administered on a daily basis for 2 weeks. The standard K-CESD-R assessment (5-point scale) was administered on the final day of the 2-week study period; the assessment was delivered via text message, including a link to the survey, directly to participants’ mobile phones.ResultsA total of 5 participants were excluded from data analysis. The result of polynomial regression analysis showed that the relationship between total K-CESD-R Mobile scores and the reaction times to the depressive symptom items was better explained by a quadratic trend—F (2, 62)=21.16, P<.001, R2=.41—than by a linear trend—F (1, 63)=25.43, P<.001, R2=.29. It was further revealed that the K-CESD-R Mobile app had excellent internal consistency (Cronbach alpha=.94); at least moderate concurrent validity with other depression scales, such as the Korean version of the Quick Inventory for Depressive Symptomatology-Self Report (ρ=.38, P=.002) and the Patient Health Questionnaire-9 (ρ=.48, P<.001); a high adherence rate for all participants (65/70, 93%); and a high follow-up rate for 10 participants whose mobile or standard K-CESD-R score was 13 or greater (8/10, 80%).ConclusionsAs hypothesized, based on a self-schema model for depression that represented both item and person characteristics, the inverted U-shaped relationship between the explicit and implicit self-schema measures for depression showed the potential of an organizational breakdown; this also showed the potential for a subsequent return to efficient processing of schema-consistent information along a continuum, ranging from nondepression through mild depression to severe depression. Further, it is expected that the updated K-CESD-R Mobile app can play an important role in encouraging people at risk for depression to seek professional follow-up for mental health care.
Highlights
BackgroundWhy do most psychometric instruments screen for or diagnose mental health problems only based on a summed total score, requiring that the same items be administered to all individuals? On the grounds of classical test theory [1,2,3], traditional psychometric measurements for depressive symptoms, such as the Beck Depression Inventory-II [4], the Patient Health Questionnaire-9 (PHQ-9) [5], the Geriatric Depression Scale [6], and the Center for Epidemiologic Studies Depression Scale-Revised (CESD-R) [7], have assumed that all items are weighted and that the characteristics of items cannot be separated from those of the person
The result of polynomial regression analysis showed that the relationship between total K-CESD-R Mobile scores and the reaction times to the depressive symptom items was better explained by a quadratic trend—F (2, 62)=21.16, P
It was further revealed that the K-CESD-R Mobile app had excellent internal consistency (Cronbach alpha=.94); at least moderate concurrent validity with other depression scales, such as the Korean version of the Quick Inventory for Depressive Symptomatology-Self Report (ρ=.38, P=.002) and the Patient Health Questionnaire-9 (ρ=.48, P
Summary
BackgroundWhy do most psychometric instruments screen for or diagnose mental health problems (eg, depression, anxiety, and stress) only based on a summed total score, requiring that the same items be administered to all individuals? On the grounds of classical test theory [1,2,3], traditional psychometric measurements for depressive symptoms, such as the Beck Depression Inventory-II [4], the Patient Health Questionnaire-9 (PHQ-9) [5], the Geriatric Depression Scale [6], and the Center for Epidemiologic Studies Depression Scale-Revised (CESD-R) [7], have assumed that all items are weighted and that the characteristics of items cannot be separated from those of the person. Item response theory (IRT) [11,12] has not assumed that all people are measured with the same level of certainty, in that individuals with the same total score may display a wide variation in the relative severity and frequency of depressive symptoms. Previous studies on the development of IRT-based computerized adaptive testing for depression [14,15,16,17] have had a greater emphasis on increased efficiency without loss of accuracy in assessing the presence and severity of depressive symptoms What these studies have neglected is that examining the potential existence and function of a self-schema in nondepressed and depressed individuals should come first. The well-validated Korean version of the Center for Epidemiologic Studies Depression Scale-Revised (K-CESD-R) was adopted
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