Identify if the article addresses reliability or validity
Explain how the article addresses sources of error variance, reliability estimates, evidence of validity, or bias and fairness.
Identify the specific type of reliability or validity for example, test-retest reliability, predictive validity, et cetera).
Identify the overall results of the research including any psychometric or statistical outcome.
Minnesota Multiphasic Personality Inventory-2 (MMPI-2) is a widely used tool for early detection of psychological maladjustment and assessing the level of adaptation for a large group in clinical settings, schools, and corporations. This study aims to evaluate the utility of MMPI-2 in assessing suicidal risk using the results of MMPI-2 and suicidal risk evaluation. A total of 7,824 datasets collected from college students were analyzed. The MMPI-2-Restructured Clinical Scales (MMPI-2-RF) and the response results for each question of the Mini International Neuropsychiatric Interview (MINI) suicidality module were used. For statistical analysis, random forest and K-Nearest Neighbors (KNN) techniques were used with suicidal ideation and suicide attempt as dependent variables and 50 MMPI-2 accuracy was 92.9% and 95%, respectively, and the Area Under the Curves (AUCs) were 0.844 and 0.851, respectively. When the KNN method was applied, the accuracy was 91.6% and 94.7%, respectively, and the AUCs were 0.722 and 0.639, respectively. The study confirmed that machine learning using MMPI-2 for a large group provides reliable accuracy in classifying and predicting the subject's suicidal ideation and past suicidal attempts. Among the 7824 participants, 3685 (47.1%) were male, a total of 6738.6% participants classified as a suicidal ideation group, and 404 (5.4%) were classified as a suicidal attempt group. Of the total datasets, 5008 were used as train data, 1252 as validation data, and 1564 as test data. Prediction accuracy of the random forest method was 92.9% for suicidal ideation and 95% for suicidal attempts; k-Nearest Neighbors (KNN) accurately predicted 91.6% of suicidal ideation and 94.7% of suicidal attempts. Table shows all parameters for suicidal ideation and suicidal attempts. When using the Suicidal/Death Ideation (SUI) scale t score to predict suicidal ideation and suicidal attempts, the area under the curve (AUCs) were 0.769 and 0.815. And using the random forest method to predict Suicidal ideation and suicidal attempts, the AUCs were 0.844 and 0.851, which were more accurate than 0.722 and 0.639 when KNN was applied. The F1 score was highest when using the random forest method of suicide attempt 92.6%) and lowest when applying KNN for suicide ideation (88.4%).
