• 제목/요약/키워드: Suicide prediction

검색결과 18건 처리시간 0.021초

Use of a Machine Learning Algorithm to Predict Individuals with Suicide Ideation in the General Population

  • Ryu, Seunghyong;Lee, Hyeongrae;Lee, Dong-Kyun;Park, Kyeongwoo
    • Psychiatry investigation
    • /
    • 제15권11호
    • /
    • pp.1030-1036
    • /
    • 2018
  • Objective In this study, we aimed to develop a model predicting individuals with suicide ideation within a general population using a machine learning algorithm. Methods Among 35,116 individuals aged over 19 years from the Korea National Health & Nutrition Examination Survey, we selected 11,628 individuals via random down-sampling. This included 5,814 suicide ideators and the same number of non-suicide ideators. We randomly assigned the subjects to a training set (n=10,466) and a test set (n=1,162). In the training set, a random forest model was trained with 15 features selected with recursive feature elimination via 10-fold cross validation. Subsequently, the fitted model was used to predict suicide ideators in the test set and among the total of 35,116 subjects. All analyses were conducted in R. Results The prediction model achieved a good performance [area under receiver operating characteristic curve (AUC)=0.85] in the test set and predicted suicide ideators among the total samples with an accuracy of 0.821, sensitivity of 0.836, and specificity of 0.807. Conclusion This study shows the possibility that a machine learning approach can enable screening for suicide risk in the general population. Further work is warranted to increase the accuracy of prediction.

자살 행동과 연관된 생물학적, 유전적 예측인자 (Biological and Genetic Prediction Factors Associated with Suicidal Behavior)

  • 김용구
    • 생물정신의학
    • /
    • 제12권1호
    • /
    • pp.3-12
    • /
    • 2005
  • Most suicides(about 90%) occur in the context of psychiatric disorders. Prediction of suicide risk in patients with mental illness is very important in preventing suicide attempts. However, current approaches to predict suicidality are based on clinical history and have low specificity and biological markers are not yet included. Many studies have explored the association between different biological parameters and suicidality. Studies of cerebro-spinal fluid(CSF) demonstrated that 5-HIAA and HVA levels were lower in patients with a history of suicide. Platelet serotonin transporter and the 5-HT2 serotonin receptor have also been studied in relation to violence and suicide. Depressive patients with greater suicidal tendency had significantly lower cholesterol concentrations but some researchers failed to find the correlation. DST non-supression is reported to predict suicidality in major depression. Several studies demonstrated a relationship between intron 7 polymorphism of tryptophan hydroxylase and suicidal behavior. Since suicide is not occurred in a single disease, the systematic and comprehensive study in large samples with various diagnoses is necessary to find the biological and genetic predictors of suicidal behavior.

  • PDF

소셜 빅 데이터를 활용한 자살검색 요인 다변량 분석 (Multivariate Analysis of Factors for Search on Suicide Using Social Big Data)

  • 송태민;송주영;안지영;진달래
    • 보건교육건강증진학회지
    • /
    • 제30권3호
    • /
    • pp.59-73
    • /
    • 2013
  • Objectives: The study is aimed at examining the individual reasons and regional/environmental factors of online search on suicide using social big data to predict practical behaviors related to suicide and to develop an online suicide prevention system on the governmental level. Methods: The study was conducted using suicide-related social big data collected from online news sites, blogs, caf$\acute{e}$s, social network services and message boards between January 1 and December 31, 2011 (321,506 buzzes from users assumed as adults and 67,742 buzzes from those assumed as teenagers). Technical analysis and development of the suicide search prediction model were done using SPSS 20.0, and the structural model, nd multi-group analysis was made using AMOS 20.0. Also, HLM 7.0 was applied for the multilevel model analysis of the determinants of search on suicide by teenagers. Results: A summary of the results of multivariate analysis is as follows. First, search on suicide by adults appeared to increase on days when there were higher number of suicide incidents, higher number of search on drinking, higher divorce rate, lower birth rate and higher average humidity. Second, search on suicide by teenagers rose on days when there were higher number of teenage suicide incidents, higher number of search on stress or drinking and less fine dust particles. Third, the comparison of the results of the structural equation model analysis of search on suicide by adults and teenagers showed that teenagers were more likely to proceed from search on stress to search on sports, drinking and suicide, while adults significantly tended to move from search on drinking to search on suicide. Fourth, the result of the multilevel model analysis of determinants of search on suicide by teenagers showed that monthly teenagers suicide rate and average humidity had positive effect on the amount of search on suicide. Conclusions: The study shows that both adults and teenagers are influenced by various reasons to experience stress and search on suicide on the Internet. Therefore, we need to develop diverse school-level programs that can help relieve teenagers of stress and workplace-level programs to get rid of the work-related stress of adults.

메타분석에 기반한 자살 예측 연구에서 전통적 통계 기법과 머신러닝 기반 접근법의 예측력 비교 (Comparison between Machine Learning and Traditional Tecnique for Suicide Prediction based on Meta-analysis)

  • 권혁준;서종한
    • 한국심리학회지 : 문화 및 사회문제
    • /
    • 제30권3호
    • /
    • pp.239-265
    • /
    • 2024
  • 본 연구는 자살 관련 행동에 대해 전통적인 예측 모형(기법)과 머신러닝 알고리즘을 활용한 연구의 예측력을 비교하기 위한 목적에서 수행되었다. 따라서 체계적 리뷰 수준에서 벗어나 메타분석을 통해 과학적으로 두 가지 기법의 예측력에 대해 살펴보고, 지역적인 수준에서 특히 국내 연구를 통해 알 수 있는 변인들을 분석하여 추후 자살 관련 행동 예측 연구에 도움을 주고자 하였다. 이를 위해 머신러닝을 사용한 연구 50개와 전통적 기법을 활용한 연구 74개로 총 124개의 문헌이 메타분석에 포함되었다. 연구 결과 전통적 기법을 활용한 연구들의 통합 AUC는 .770으로 머신러닝을 활용한 연구들의 통합 AUC값인 .853보다 낮은 것으로 나타났다. 특히 아시아권의 연구(AUC = .944)가 서양(AUC = .820)과 한국(AUC = .864)의 연구에 비해 높은 정확도를 나타내었다. 국내 연구에서의 조절효과를 추가적으로 분석한 결과 남성의 비율이 많을수록, 예측 대상이 자살 시도일수록 예측 정확도가 높았으며, 예측 대상이 자살 사망일수록, 그리고 신경망분석(Neural Network)을 활용한 연구일수록 예측 정확도가 낮았다. 본 연구는 자살 관련 행동의 예측에 대한 다양한 연구결과를 종합하고, 머신러닝을 활용한 예측의 효과성을 검증하는 한편, 국내에서 활용가능한 변인을 탐색하는 데 그 의의가 있다.

로지스틱 회귀모형과 의사결정 나무모형을 활용한 청소년 자살 시도 예측모형 비교: 2019 청소년 건강행태 온라인조사를 이용한 2차 자료분석 (Comparison of the Prediction Model of Adolescents' Suicide Attempt Using Logistic Regression and Decision Tree: Secondary Data Analysis of the 2019 Youth Health Risk Behavior Web-Based Survey)

  • 이윤주;김희진;이예슬;정혜선
    • 대한간호학회지
    • /
    • 제51권1호
    • /
    • pp.40-53
    • /
    • 2021
  • Purpose: The purpose of this study was to develop and compare the prediction model for suicide attempts by Korean adolescents using logistic regression and decision tree analysis. Methods: This study utilized secondary data drawn from the 2019 Youth Health Risk Behavior web-based survey. A total of 20 items were selected as the explanatory variables (5 of sociodemographic characteristics, 10 of health-related behaviors, and 5 of psychosocial characteristics). For data analysis, descriptive statistics and logistic regression with complex samples and decision tree analysis were performed using IBM SPSS ver. 25.0 and Stata ver. 16.0. Results: A total of 1,731 participants (3.0%) out of 57,303 responded that they had attempted suicide. The most significant predictors of suicide attempts as determined using the logistic regression model were experience of sadness and hopelessness, substance abuse, and violent victimization. Girls who have experience of sadness and hopelessness, and experience of substance abuse have been identified as the most vulnerable group in suicide attempts in the decision tree model. Conclusion: Experiences of sadness and hopelessness, experiences of substance abuse, and experiences of violent victimization are the common major predictors of suicide attempts in both logistic regression and decision tree models, and the predict rates of both models were similar. We suggest to provide programs considering combination of high-risk predictors for adolescents to prevent suicide attempt.

Characteristics of Women Who Have Had Cosmetic Breast Implants That Could Be Associated with Increased Suicide Risk: A Systematic Review, Proposing a Suicide Prevention Model

  • Manoloudakis, Nikolaos;Labiris, Georgios;Karakitsou, Nefeli;Kim, Jong B.;Sheena, Yezen;Niakas, Dimitrios
    • Archives of Plastic Surgery
    • /
    • 제42권2호
    • /
    • pp.131-142
    • /
    • 2015
  • Literature indicates an increased risk of suicide among women who have had cosmetic breast implants. An explanatory model for this association has not been established. Some studies conclude that women with cosmetic breast implants demonstrate some characteristics that are associated with increased suicide risk while others support that the breast augmentation protects from suicide. A systematic review including data collection from January 1961 up to February 2014 was conducted. The results were incorporated to pre-existing suicide risk models of the general population. A modified suicide risk model was created for the female cosmetic augmentation mammaplasty candidate. A 2-3 times increased suicide risk among women that undergo cosmetic breast augmentation has been identified. Breast augmentation patients show some characteristics that are associated with increased suicide risk. The majority of women reported high postoperative satisfaction. Recent research indicates that the Autoimmune syndrome induced by adjuvants and fibromyalgia syndrome are associated with silicone implantation. A thorough surgical, medical and psycho-social (psychiatric, family, reproductive, and occupational) history should be included in the preoperative assessment of women seeking to undergo cosmetic breast augmentation. Breast augmentation surgery can stimulate a systematic stress response and increase the risk of suicide. Each risk factor of suicide has poor predictive value when considered independently and can result in prediction errors. A clinical management model has been proposed considering the overlapping risk factors of women that undergo cosmetic breast augmentation with suicide.

약물중독 자살환자에서 사망군과 생존군의 비교 (A Study on the Patients Who Attempted Suicide with Drug Intoxication)

  • 한종수;윤성우;최성수
    • 한국산학기술학회논문지
    • /
    • 제14권4호
    • /
    • pp.1863-1870
    • /
    • 2013
  • 본 연구는 응급의료센터에 약물중독으로 자살을 시도한 환자 중 생존군과 사망군을 분류하여 대상자의 내원 시 상태와 내원후 치료결과를 파악함으로써 향후 환자 발생시 임상적인 중증도 예측과 자살예방 연구에 기초자료로 활용하기 위함이다. 2009년 6월부터 2011년 5월까지 최근 2년간 광주광역시 C 대학병원 응급의료센터에 약물 중독으로 내원한 환자 중 비의도적인 사고 환자를 제외한 자살 환자만을 대상으로 하여, 의무기록으로 자료를 수집하였다. 연구결과 약물중독 자살환자에서 연령이 높고, 교육수준이 낮으며, 독거인 경우사망률이 높았고, 농약을 음독한 경우 예후가 좋지 않았다. 자살원인이 경제적문제와 우울증인 경우에 사망률이 높았고, 내원시 의식이 혼미, 반혼수/혼수인 경우 예후가 좋지 않았다. 약물중독 자살환자의 위험군을 파악하여 임상적인 중증도 예측에 도움이되고, 이들에 대한 적절한 약물교육과 더불어 정신적인 지지가 중요하다는 사실을 인지 시키고자 한다.

의사결정나무 기법을 이용한 노인들의 자살생각 예측모형 및 의사결정 규칙 개발 (A Development of Suicidal Ideation Prediction Model and Decision Rules for the Elderly: Decision Tree Approach)

  • 김덕현;유동희;정대율
    • 한국정보시스템학회지:정보시스템연구
    • /
    • 제28권3호
    • /
    • pp.249-276
    • /
    • 2019
  • Purpose The purpose of this study is to develop a prediction model and decision rules for the elderly's suicidal ideation based on the Korean Welfare Panel survey data. By utilizing this data, we obtained many decision rules to predict the elderly's suicide ideation. Design/methodology/approach This study used classification analysis to derive decision rules to predict on the basis of decision tree technique. Weka 3.8 is used as the data mining tool in this study. The decision tree algorithm uses J48, also known as C4.5. In addition, 66.6% of the total data was divided into learning data and verification data. We considered all possible variables based on previous studies in predicting suicidal ideation of the elderly. Finally, 99 variables including the target variable were used. Classification analysis was performed by introducing sampling technique through backward elimination and data balancing. Findings As a result, there were significant differences between the data sets. The selected data sets have different, various decision tree and several rules. Based on the decision tree method, we derived the rules for suicide prevention. The decision tree derives not only the rules for the suicidal ideation of the depressed group, but also the rules for the suicidal ideation of the non-depressed group. In addition, in developing the predictive model, the problem of over-fitting due to the data imbalance phenomenon was directly identified through the application of data balancing. We could conclude that it is necessary to balance the data on the target variables in order to perform the correct classification analysis without over-fitting. In addition, although data balancing is applied, it is shown that performance is not inferior in prediction rate when compared with a biased prediction model.

Psychological Risk and Protective Factors for Suicidal Ideation: A Study in an Adolescent Sample in an Insular Context

  • Ana Margarida Cunha;Claudia Carmo;Marta Bras
    • Journal of the Korean Academy of Child and Adolescent Psychiatry
    • /
    • 제34권4호
    • /
    • pp.250-257
    • /
    • 2023
  • Objectives: Adolescents are at risk of suicide. As suicide is a multifactorial process, risk and protective factors are relevant constructs for suicide prediction. This study explored the effects of risk and protective factors on suicidal ideation in adolescents on the island of São Miguel (Azores). Methods: A sample of 750 adolescents (male: n=358; 47.7%; mean age=14.67 years; standard deviation=1.85 years) from the island of São Miguel (Azores) completed several measures related to suicidal ideation and associated factors. Using a cross-sectional design, this study conducted descriptive, correlational, predictive, mediation, and moderation analyses. Results: Adolescents generally displayed high levels of risk and protective factors; an indicative proportion exhibited significant suicidal ideation with females presenting the greatest vulnerability. Furthermore, the results highlight that depression is the best predictor of suicidal ideation, however, the association between these variables is mediated. Conclusion: The data corroborate that the suicidal reality of adolescents in the Autonomous Region of the Azores is worrisome. Having substantiated the complexity of the suicidal context in young people in the present research, the need to continue studying risk/protective factors in this area is supported.

자살예방 프로그램이 초등학교 충동심리에 미치는 영향 (Effect of the Suicide Prevention Program to the Impulsive Psychology of the Elementary School Student)

  • 강수진;강호정;조원철;이태식
    • 한국방재안전학회논문집
    • /
    • 제6권1호
    • /
    • pp.65-72
    • /
    • 2013
  • 본 연구에서는 청소년 자살 문제를 조기 자살 예방 프로그램을 통해 초등학생에 적용하고 프로그램 전과 후의 효과를 비교 분석하여 학생들의 감정 상태와 자살에 대한 충동 등, 심리상태 변화를 확인하였고, 자살예방 프로그램으로서 활용 가능성을 제시하였다. 청소년기는 인지적으로 미성숙하며 정서적으로 충동적인 시기이므로 발달 과정상 매우 불안한 시기이다. 사소한 자극이나 갈등상황에 대해 자살이라는 극단적 현실 도피, 충동적 문제해결 등의 방법으로 자살을 선택할 만큼 정서적으로 불안정하고 예측하기 어려운 시기이다. 최근 핵가족화와 부모들의 자식에 대한 기대감과 교육문제, 사회 환경적요인, 개인 심리적 요인 등의 많은 스트레스는 학생들을 자살이라는 극단적 행동까지 이르게 하고 있다. 이에 본 연구는 자살예방 프로그램을 초등학생 때부터 경험하는 스트레스의 영역과 자살생각과 충동의 정도를 파악하고, 명상교육, 호흡법 등의 예방 프로그램을 통해 분노조절, 감정정화, 자기극복 체험을 통해 긍정적인 자아정체성 확립과 자기조절 능력, 자존감과 생명의 소중함을 깨닫게 함으로 자살예방에 미치는 영향과 효과를 분석하였다. 연구 대상자는 고양시 관내 초등학교 6학년 2개 반 51명을 한 달 동안 매일 아침 30분씩 뇌과학 교육의 원리와 방법을 체험 및 활동 중심으로 진행 하였고, 수업활동지 및 생활 실천교육으로 내면화하여 학습효과를 높이도록 하였다. 자료 수집은 4주간 20회 차 아침수업 실시 전과 후에 자살 가능성을 효과적으로 예측할 수 있도록 개발한 Suicide Probability Scale(이하 SPS-A), 자살위험성 예측척도를 활용하여, 긍정적 전망, 가족 내 친밀감, 충동성, 대인 적대감, 절망감 징후, 절망감 증후군, 자살사고 등 7가지 영역으로 조사 실시 하였다. 분석 방법 및 검증은 SPSS 프로그램을 이용한 Wilcoxon's signed rank test를 이용하였다. 짧은 기간 동안의 프로그램 진행이었지만 평균 비교 분석 시 7가지 영역에서 효과적이고 긍정적인 결과가 나왔다. 그러나 t-test 결과에서는 또 다른 결과가 나왔다. SPS-A 31개 문항 중 3개 문항(7번, 14번, 19번)에서만 변화가 있고, 나머지 문항에서는 변화가 없는 것으로 나타났다. 또한 B반 학생들에 비해 A반 학생들이 변화가 큰 것으로 나타났다. 그리고 A반 학생들의 경우 7가지 영역 중 자살과 가장 밀접한 관계가 있는 절망감증후군과 자살사고 영역에서 프로그램 진행 후 심리적 변화가 있는 것으로 검증 됐다. 학생의 성향에 따라 또는, 프로그램을 진행하는 전문가(담임교사, 진행강사)에 따라 다른 결과가 도출된다는 것도 본 연구를 통해서 알 수 있었다. 본 논문에서 제시한 자살예방 프로그램은 지속적인 프로그램으로 제도화, 활성화 하여 정서적인 스트레스 해소 및 긍정적인 자아정체성 회복, 뇌파 안정을 통한 감정 및 충동 조절을 함으로 학습효과와 자살예방에 도움이 될 것이며, 짧은 시간의 교육 프로그램으로 사장되지 않고, 아동기 부터 청소년기까지 연계하여 정신적, 육체적으로 건강하게 성장할 수 있는 주변 환경을 조성함으로 사회적 문제인 자살 예방에 효과적인 프로그램이 될 것이라 판단된다.