Words of Suicide: Identifying Suicidal Risk in Written Communications

Author(s):  
Amendra Shrestha ◽  
Nazar Akrami ◽  
Lisa Kaati ◽  
Julia Kupper ◽  
Matthew R. Schumacher
Keyword(s):  
Crisis ◽  
2012 ◽  
Vol 33 (2) ◽  
pp. 80-86 ◽  
Author(s):  
Sami Hamdan ◽  
Nadine Melhem ◽  
Israel Orbach ◽  
Ilana Farbstein ◽  
Mohammad El-Haib ◽  
...  

Background: Relatively little is known about the role of protective factors in an Arab population in the presence of suicidal risk factors. Aims: To examine the role of protective factors in a subsample of in large Arab Kindred participants in the presence of suicidal risk factors. Methods: We assessed protective and risk factors in a sample of 64 participants (16 suicidal and 48 nonsuicidal) between 15 and 55 years of age, using a comprehensive structured psychiatric interview, the Composite International Diagnostic Interview (CIDI), self-reported depression, anxiety, hopelessness, impulsivity, hostility, and suicidal behavior in first-degree and second-relatives. We also used the Religiosity Questionnaire and suicide attitude (SUIATT) and multidimensional perceived support scale. Results: Suicidal as opposed to nonsuicidal participants were more likely to have a lifetime history of major depressive disorder (MDD) (68.8% vs. 22.9% χ2 = 11.17, p = .001), an anxiety disorder (87.5% vs. 22.9, χ2 = 21.02, p < .001), or posttraumatic stress disorder (PTSD) (25% vs. 0.0%, Fisher’s, p = .003). Individuals who are otherwise at high risk for suicidality have a much lower risk when they experience higher perceived social support (3.31 ± 1.36 vs. 4.96 ± 1.40, t = 4.10, df = 62, p < .001), and they have the view that suicide is somehow unacceptable (1.83 ± .10 vs. 1.89 ± .07, t = 2.76, df = 60, p = .008). Conclusions: Taken together with other studies, these data suggest that the augmentation of protective factors could play a very important role in the prevention of incidental and recurrent suicidal behavior in Arab populations, where suicidal behavior in increasing rapidly.


2015 ◽  
Author(s):  
Tina Yu ◽  
Zunaira Jilani ◽  
Edward C. Chang ◽  
Erin E. Fowler ◽  
Jiachen Lin ◽  
...  

2019 ◽  
Vol 43 (1) ◽  
pp. 3-16 ◽  
Author(s):  
R. Elizabeth Capps ◽  
Kurt D. Michael ◽  
J. P. Jameson
Keyword(s):  

Author(s):  
Michael Joshua Landau

Acoustical properties of speech have been shown to be related to mental states such as remission and depression. The objective of this project was to relate the energy in frequency bands with the severity of the mental state using the Beck Depression Inventory (BDI). Recorded speech was obtained from male and female subjects with mental states of remission, depression, and suicidal risk. These subjects had recorded automated and spontaneous speech samples. Multiple regression analysis was used to relate the independent energy band ratio variables with the dependent BDI scores, and thus allow the determination of equitable BDI scores for future patients. For the male group, the square of the 3rd energy band and the cross-product of the 2nd and 3rd energy band were prominent in both the reading and interviewed groups. Therefore the equation with the 2nd lowest Akaike Information Criterion (AIC) score was chosen for the reading male group, and the 1st lowest AIC score was chosen for the interviewed male group. For the female group, the square and cross-product of the 1st and 2nd energy bands were prominent in both the reading and interviewed groups. Therefore the 2nd lowest AIC score was chosen for the reading female group, and the 1st lowest AIC score was chosen for the interviewed female group. The clinician could thus determine the patient’s mood or state of mind by comparing the estimated BDI score with the ranges of total BDI scores: remitted 0 – 20, depressed 15 – 38, suicidal 38 – 46. Keywords: speech, mental states, power spectra, multiple regression, information theoretic criterion


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sunhae Kim ◽  
Hye-Kyung Lee ◽  
Kounseok Lee

AbstractMinnesota 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-Resturcutred 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 scale scores as predictors. On applying the random forest method to suicidal ideation and suicidal attempts, the 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.


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