title: Efficiency of diagnostic model to predict recurrent suicidal incidents in diverse world communities.
abstract: Suicidal attempts have a very significant effect on the society, and they also reflect on the efforts of the supporting health care and counseling facilities; and the mental health professionals involved. The impact of suicide is further magnified by the needs of persons who attempt suicide multiple times, requiring emergency health care and rehabilitation. Preventing such activities becomes a major task for the support providing agencies as soon as patient with such tendencies are identified. There are repetitive traits that can be observed during the entire therapeutic program among the high-risk group individuals, who are susceptible to this kind of activity and such traits indicate for specific profiling. The aim of the instrument is to prevent the occurrence of the repetitive suicidal attempts of the patients in various world regions, which may have significantly higher and concerning suicide rates. This profile has been constructed on the various parameters recognized in the statistical analysis of the patient population, which have been identified or can be under treatment for their suicidal behavior. This instrument is developed to predict the probability of population segments who may attempt suicide and repetitively, by matching the parameters of the profile with that of the patient pool. Building a profile for the purpose of predicting behavior of this kind can strengthen the intervention strategies more comprehensively and reduce such incidents and health care requirements and expenses.
authors.affiliation: Health Promotion Management American University, Washington D.C., USA.
authors.forename: Vatsalya
authors.initials: V
authors.lastname: Vatsalya
authors.affiliation: Behavioral Sciences, Fort Valley State University, Fort valley GA, USA.
authors.forename: Kan
authors.initials: K
authors.lastname: Chandras
authors.affiliation: Department of Biology, Georgetown University, Washington D.C., USA.
authors.forename: Shweta
authors.initials: S
authors.lastname: Srivastava
authors.affiliation: Health Promotion Management American University, Washington D.C., USA.
authors.forename: Robert
authors.initials: R
authors.lastname: Karch
keywords: Instrument; Parameters; Predictor; Risk Category; Suicidse