Abstract
(1) Background: The Patient Health Questionnaire-9 (PHQ-9) is a tool that screens patients for depression in primary care settings. In this study, we evaluated the efficacy of PHQ-9 in evaluating suicidal ideation (2) Methods: A total of 8760 completed questionnaires collected from college students were analyzed. The PHQ-9 was scored in combination with and evaluated against four categories (PHQ-2, PHQ-8, PHQ-9, and PHQ-10). Suicidal ideations were evaluated using the Mini-International Neuropsychiatric Interview suicidality module. Analyses used suicide ideation as the dependent variable, and machine learning (ML) algorithms, k-nearest neighbors, linear discriminant analysis (LDA), and random forest. (3) Results: Random forest application using the nine items of the PHQ-9 revealed an excellent area under the curve with a value of 0.841, with 94.3% accuracy. The positive and negative predictive values were 84.95% (95% CI = 76.03–91.52) and 95.54% (95% CI = 94.42–96.48), respectively. (4) Conclusion: This study confirmed that ML algorithms using PHQ-9 in the primary care field are reliably accurate in screening individuals with suicidal ideation.
Highlights
The age difference between groups was not significant; the total score for each Patient Health Questionnaire-9 (PHQ-9) item and the sum of each scoring method was significantly higher in the suicidal ideation group (Table 1)
We found differences between machine learning (ML) techniques; we confirmed that k-nearest neighbors classification (KNN), linear discriminant analysis (LDA), and random forest all predicted suicidal ideations at an excellent level
Because the Patient Health Questionnaire (PHQ)-9 was originally developed to screen for depression and not for suicide, these results indicate that PHQ-9 and PHQ-10 would be very useful for screening suicide risk in a primary care situation
Summary
The Patient Health Questionnaire (PHQ-9) is an effective screening tool for major depressive disorders and is a reliable and useful evaluation tool for moderate symptoms of depression in various clinical environments [8,9,10]. This tool has been verified for screening for depression in the general population and various groups outside the primary care environment [11,12]
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