About: Suicidal ideation is a research topic. Over the lifetime, 15272 publications have been published within this topic receiving 517077 citations. The topic is also known as: suicide ideation & suicidal thoughts.
TL;DR: The theory is proposed that the most dangerous form of suicidal desire is caused by the simultaneous presence of two interpersonal constructs-thwarted belongingness and perceived burdensomeness (and hopelessness about these states)-and further that the capability to engage in suicidal behavior is separate from the desire to engageIn suicidal behavior.
Abstract: Suicidal behavior is a major problem worldwide and, at the same time, has received relatively little empirical attention. This relative lack of empirical attention may be due in part to a relative absence of theory development regarding suicidal behavior. The current article presents the interpersonal theory of suicidal behavior. We propose that the most dangerous form of suicidal desire is caused by the simultaneous presence of two interpersonal constructs—thwarted belongingness and perceived burdensomeness (and hopelessness about these states)—and further that the capability to engage in suicidal behavior is separate from the desire to engage in suicidal behavior. According to the theory, the capability for suicidal behavior emerges, via habituation and opponent processes, in response to repeated exposure to physically painful and/or fear-inducing experiences. In the current article, the theory’s hypotheses are more precisely delineated than in previous presentations (Joiner, 2005), with the aim of inviting scientific inquiry and potential falsification of the theory’s hypotheses.
TL;DR: Findings suggest that the Columbia-Suicide Severity Rating Scale is suitable for assessment of suicidal ideation and behavior in clinical and research settings.
Abstract: The Columbia–Suicide Severity Rating Scale was initially designed to assess suicidal ideation and behavior in clinical trials. Psychometric analysis of data on adolescents indicated that a lifetime history of worst-point suicidal ideation including either suicidal intent or intent with a plan predicts a future risk of an actual attempt that is four times as great as the risk associated with a history of current suicidal ideation—including a desire to be dead—or increased general ratings of depression.
TL;DR: A meta-analysis of studies that have attempted to longitudinally predict a specific STB-related outcome suggests the need for a shift in focus from risk factors to machine learning-based risk algorithms.
Abstract: Suicidal thoughts and behaviors (STBs) are major public health problems that have not declined appreciably in several decades. One of the first steps to improving the prevention and treatment of STBs is to establish risk factors (i.e., longitudinal predictors). To provide a summary of current knowledge about risk factors, we conducted a meta-analysis of studies that have attempted to longitudinally predict a specific STB-related outcome. This included 365 studies (3,428 total risk factor effect sizes) from the past 50 years. The present random-effects meta-analysis produced several unexpected findings: across odds ratio, hazard ratio, and diagnostic accuracy analyses, prediction was only slightly better than chance for all outcomes; no broad category or subcategory accurately predicted far above chance levels; predictive ability has not improved across 50 years of research; studies rarely examined the combined effect of multiple risk factors; risk factors have been homogenous over time, with 5 broad categories accounting for nearly 80% of all risk factor tests; and the average study was nearly 10 years long, but longer studies did not produce better prediction. The homogeneity of existing research means that the present meta-analysis could only speak to STB risk factor associations within very narrow methodological limits-limits that have not allowed for tests that approximate most STB theories. The present meta-analysis accordingly highlights several fundamental changes needed in future studies. In particular, these findings suggest the need for a shift in focus from risk factors to machine learning-based risk algorithms. (PsycINFO Database Record
TL;DR: The SSI scale was found to have high internal consistency and moderately high correlations with clinical ratings of suicidal risk and self-administered measures of self-harm, and it was sensitive to changes in levels of depression and hopelessness over time.
Abstract: This article describes the rationale, development, and validation of the Scale for Suicide Ideation (SSI), a 19-item clinical research instrument designed to quantify and assess suicidal intention. The scale was found to have high internal consistency and moderately high correlations with clinical ratings of suicidal risk and self-administered measures of self-harm. Furthermore, it was sensitive to changes in levels of depression and hopelessness over time. Its construct validity was supported by two studies by different investigators testing the relationship between hopelessness, depression, and suicidal ideation and by a study demonstrating a significant relationship between high level of suicidal ideation and "dichotomous" attitudes about life and related concepts on a semantic differential test. Factor analysis yielded three meaningful factors: active suicidal desire, specific plans for suicide, and passive suicidal desire.
TL;DR: Physician education in depression recognition and treatment and restricting access to lethal methods reduce suicide rates, and other interventions need more evidence of efficacy.
Abstract: ContextIn 2002, an estimated 877 000 lives were lost worldwide through
suicide. Some developed nations have implemented national suicide prevention
plans. Although these plans generally propose multiple interventions, their
effectiveness is rarely evaluated.ObjectivesTo examine evidence for the effectiveness of specific suicide-preventive
interventions and to make recommendations for future prevention programs and
research.Data Sources and Study SelectionRelevant publications were identified via electronic searches of MEDLINE,
the Cochrane Library, and PsychINFO databases using multiple search terms
related to suicide prevention. Studies, published between 1966 and June 2005,
included those that evaluated preventative interventions in major domains;
education and awareness for the general public and for professionals; screening
tools for at-risk individuals; treatment of psychiatric disorders; restricting
access to lethal means; and responsible media reporting of suicide.Data ExtractionData were extracted on primary outcomes of interest: suicidal behavior
(completion, attempt, ideation), intermediary or secondary outcomes (treatment
seeking, identification of at-risk individuals, antidepressant prescription/use
rates, referrals), or both. Experts from 15 countries reviewed all studies.
Included articles were those that reported on completed and attempted suicide
and suicidal ideation; or, where applicable, intermediate outcomes, including
help-seeking behavior, identification of at-risk individuals, entry into treatment,
and antidepressant prescription rates. We included 3 major types of studies
for which the research question was clearly defined: systematic reviews and
meta-analyses (n = 10); quantitative studies, either randomized
controlled trials (n = 18) or cohort studies (n = 24);
and ecological, or population- based studies (n = 41). Heterogeneity
of study populations and methodology did not permit formal meta-analysis;
thus, a narrative synthesis is presented.Data SynthesisEducation of physicians and restricting access to lethal means were
found to prevent suicide. Other methods including public education, screening
programs, and media education need more testing.ConclusionsPhysician education in depression recognition and treatment and restricting
access to lethal methods reduce suicide rates. Other interventions need more
evidence of efficacy. Ascertaining which components of suicide prevention
programs are effective in reducing rates of suicide and suicide attempt is
essential in order to optimize use of limited resources.