Dataset Information

Suicidal ideation and behavior in institutions of higher learning: A latent class analysis.

ABSTRACT: Suicide is the second leading cause of death among undergraduate students, with an annual rate of 7.5 per 100,000. Suicidal behavior (SB) is complex and heterogeneous, which might be explained by there being multiple etiologies of SB. Data-driven identification of distinct at-risk subgroups among undergraduates would bolster this argument. We conducted a latent class analysis (LCA) on survey data from a large convenience sample of undergraduates to identify subgroups, and validated the resulting latent class model on a sample of graduate students. Data were collected through the Interactive Screening Program deployed by the American Foundation for Suicide Prevention. LCA identified 6 subgroups from the undergraduate sample (N = 5654). In the group with the most students reporting current suicidal thoughts (N = 623, 66% suicidal), 22.5% reported a prior suicide attempt, and 97.6% endorsed moderately severe or worse depressive symptoms. Notably, LCA identified a second at-risk group (N = 662, 27% suicidal), in which only 1.5% of respondents noted moderately severe or worse depressive symptoms. When graduate students (N = 1138) were classified using the model, a similar frequency distribution of groups was found. Finding multiple replicable groups at-risk for suicidal behavior, each with a distinct prevalence of risk factors, including a group of students who would not be classified as high risk with depression-based screening, is consistent with previous studies that identified multiple potential etiologies of SB.

SUBMITTER: Bernanke J

PROVIDER: S-EPMC5826724 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Suicidal ideation and behavior in institutions of higher learning: A latent class analysis.

Bernanke Joel J Galfalvy Hanga C HC Mortali Maggie G MG Hoffman Laura A LA Moutier Christine C Nemeroff Charles B CB Stanley Barbara H BH Clayton Paula P Harkavy-Friedman Jill J Oquendo Maria A MA

Journal of psychiatric research 20170909

Suicide is the second leading cause of death among undergraduate students, with an annual rate of 7.5 per 100,000. Suicidal behavior (SB) is complex and heterogeneous, which might be explained by there being multiple etiologies of SB. Data-driven identification of distinct at-risk subgroups among undergraduates would bolster this argument. We conducted a latent class analysis (LCA) on survey data from a large convenience sample of undergraduates to identify subgroups, and validated the resulting ...[more]

PMID: 28923719

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Project description:ImportanceFirearm ownership is associated with increased risk for suicide.ObjectiveTo examine patterns of associations among suicidal thoughts and behaviors among gun owners and non-gun owners in the US.Design, setting, and participantsIn this survey study, cross-sectional online survey data were collected from March to April 2020 from US adults recruited via Qualtrics Panels. Quota sampling was used to approximate US census demographics.Main outcomes and measuresThe primary outcomes were past-year passive suicidal ideation, active suicidal ideation, suicidal planning, suicidal behaviors, and nonsuicidal self-injury as measured by items from the Self-Injurious Thoughts and Behaviors Interview-Revised (SITBI-R). Simple latent class analysis (LCA) was used to assign participants to separate classes based on posterior probabilities, and multigroup LCA was used to assess whether the same construct was measured in specified groups.ResultsOf 65 079 adults invited to participate, 10 625 (16.3%) completed the survey; 9153 responded "yes" or "no" to the firearm ownership item and were included in the analysis. Of these 9153 respondents (4695 [51.3%] male; mean [SD] age, 46.7 [16.8] years), 2773 (30.3%) reported owning a gun and 6380 (69.7%) reported not owning a gun. Compared with non-gun owners, gun owners were more likely to be male (1779 [64.2%] vs 2916 [45.7%]; χ21, 263.3; P < .001) and White (2090 [75.4%] vs 3945 [61.8%]; χ25, 232.9; P < .001) and to have served in the military (772 [27.8%] vs 609 [9.5%]; χ21, 571.4; P < .001). Five distinct patterns of SITBI-R item endorsement were extracted using simple LCA. Multigroup LCA indicated that the probability of SITBI-R item endorsement differed between gun owners and non-gun owners across subgroups. Among gun owners, the probability of past-month nonfatal suicide attempts was highest in class 4 (ranging from 16.8% for reaching out for help to 27.2% for starting, then changing one's mind). Gun owners in class 4 were characterized by high probabilities of endorsing thoughts about specific ways or methods to attempt suicide (100%) and preparatory behavior (100%). Among non-gun owners, the probability of nonfatal suicide attempts was highest in class 5 (ranging from 14.9% for reaching out for help to 29.7% for starting, then changing one's mind). Non-gun owners in class 5 were characterized by high probabilities of endorsing passive suicidal ideation (84.0%-100%), active suicidal ideation (86.7%-95.0%), and thoughts about specific ways or methods to attempt suicide (97.4%) and a specific place (92.1%) to attempt suicide.Conclusions and relevanceIn this study, in subgroups with lower probabilities of suicide attempt, gun owners and non-gun owners showed similar patterns of suicide risk item endorsement, but when the probability of a suicide attempt increased, gun owners were less likely than non-gun owners to endorse passive and active suicidal ideation. These findings suggest that assessing a broader range of suicide risk indicators may improve risk detection.

Project description:BackgroundGiven the relatively high rates of suicidal ideation and attempt among people with chronic pain, there is a need to understand the underlying factors to target suicide prevention efforts. To date, no study has examined the association between pain phenotypes and suicide related behaviors among those with mild traumatic brain injuries.ObjectiveTo determine if pain phenotypes were independently associated with suicidal ideation / attempt or if comorbidities within the pain phenotypes account for the association between pain phenotypes and suicide related behaviors.MethodsThis is a longitudinal retrospective cohort study of suicide ideation/attempts among pain phenotypes previously derived using general mixture latent variable models of the joint distribution of repeated measures of pain scores and pain medications/treatment. We used national VA inpatient, outpatient, and pharmacy data files for Post-9/11 Veterans with mild traumatic injury who entered VA care between fiscal years (FY) 2007 and 2009. We considered a counterfactual causal modeling framework to assess the extent that the pain phenotypes during years 1-5 of VA care were predictive of suicide ideation/attempt during years 6-8 of VA care conditioned on covariates being balanced between pain phenotypes.ResultsWithout adjustment, pain phenotypes were significant predictors of suicide related behaviors. When we used propensity scores to balance the comorbidities present in the pain phenotypes, the pain phenotypes were no longer significantly associated with suicide related behaviors.ConclusionThese findings suggest that suicide ideation/attempt is associated with pain trajectories primarily through latent multimorbidity. Therefore, it is critical to identify and manage comorbidities (e.g., depression, post-traumatic stress disorder) to prevent tragic outcomes associated with suicide related behaviors throughout the course of chronic pain and mild traumatic brain injury management.

Project description:Depression is one of the most common mental illnesses but remains underdiagnosed. Suicide, as a core symptom of depression, urgently needs to be monitored at an early stage, i.e., the suicidal ideation (SI) stage. Depression and subsequent suicidal ideation should be supervised on social media. In this research, we investigated depression and concomitant suicidal ideation by identifying individuals' linguistic characteristics through machine learning approaches. On Weibo, we sampled 487,251 posts from 3196 users from the depression super topic community (DSTC) as the depression group and 357,939 posts from 5167 active users on Weibo as the control group. The results of the logistic regression model showed that the SCLIWC (simplified Chinese version of LIWC) features such as affection, positive emotion, negative emotion, sadness, health, and death significantly predicted depression (Nagelkerke's R2 = 0.64). For model performance: F-measure = 0.78, area under the curve (AUC) = 0.82. The independent samples' t-test showed that SI was significantly different between the depression (0.28 ± 0.5) and control groups (-0.29 ± 0.72) (t = 24.71, p < 0.001). The results of the linear regression model showed that the SCLIWC features, such as social, family, affection, positive emotion, negative emotion, sadness, health, work, achieve, and death, significantly predicted suicidal ideation. The adjusted R2 was 0.42. For model performance, the correlation between the actual SI and predicted SI on the test set was significant (r = 0.65, p < 0.001). The topic modeling results were in accordance with the machine learning results. This study systematically investigated depression and subsequent SI-related linguistic characteristics based on a large-scale Weibo dataset. The findings suggest that analyzing the linguistic characteristics on online depression communities serves as an efficient approach to identify depression and subsequent suicidal ideation, assisting further prevention and intervention.

Project description:INTRODUCTION:The AARR task force on suicidal ideation and behavior (SI/SB) in dementia conducted an online survey on the extent of SI/SB in individuals diagnosed with mild cognitive impairment (MCI) or dementia who were participating in clinical trials. METHODS:Investigators with experience in conducting SI/SB assessments in clinical trial subjects with MCI or dementia were invited to complete a global 19-item online survey. RESULTS:A total of 204 evaluable responses were collected with the majority from North America and Europe (83.4%) and the remainder from Asia, Latin America, and Mideast/Africa. The mean (SD) number of subjects personally assessed by the respondents in the past year with MCI, mild-moderate dementia, or severe dementia was 12.8 (26.2), 31.2 (39.6), and 10.1 (34.7), respectively. The mean number of subjects in each diagnostic group with suicidal ideation (SI), suicidal behavior (SB), or completed suicide (CS) was on average quite low (0.3 to 1.1 for SI, 0.1 to 0.2 for SB, and 0.0 to 0.2 for CS). Confidence in subject self-reports of SI/SB over different time periods declined with increasing severity of cognitive impairment and with increasing duration of the recall time period assessed. Of respondents, 56% and 75% had low confidence in self-ratings of SI/SB from subjects with severe dementia over the past 24 hours and the past week to 1 month, respectively. Ratings of the reliability of information collected on SI/SB also decreased with increasing severity of cognitive impairment. Approximately 70% of respondents rated the reliability of the information they obtained from all sources (patient, caregiver, and others) for subjects with MCI as high, but only about half (42.0% to 55.3%) and less than a quarter (17.4% to 24.3%) rated the reliability of information obtained for subjects with mild to moderate dementia or severe dementia as high, respectively. DISCUSSION:These results support the usefulness of prospective SI/SB assessments in MCI and mild dementia, raise questions about the reliability of assessments in moderate dementia, and confirm their lack of clinical utility in severe dementia. The results highlight the need for development of validated assessment instruments adapted to the stage of cognitive decline of the patients under study and may be the most effective in the earliest stages of the disease.

Project description:IntroductionNonsuicidal self-injurious behavior (NSSI) is an important risk factor for future suicide attempts. Previous research has identified a number of motivations for engaging in NSSI. The aim of the present study was to translate the Inventory of Statements About Self-Injury (ISAS) into Russian and then to evaluate its psychometric properties in a sample of patients with non-psychotic mental disorders and suicidal ideation (SI). Other aims were to determine the prevalence of specific NSSI functions in this population and to assess the relationship between different NSSI functions and clinical and psychological parameters.Participants and methodsThe study was conducted at the largest center for non-psychotic mental disorders in Moscow. All admitted patients with both NSSI and SI completed the Russian version of the ISAS-II, underwent the Self-Injurious Thoughts and Behaviors Interview, and completed the Personality Inventory for DSM-5 and ICD-11 Brief Form Plus-Modified, the Beck Depression Inventory, and the State-Trait Anxiety Inventory.ResultsA total of 614 patients were included in the study. 543 (88.4%) patients were assigned female at birth with a mean age of 24.86 (7.86) years. Factor analysis supported a two-factor structure (Intrapersonal and Interpersonal) of the Russian version of the ISAS-II, but in contrast to the original study, the "Marking distress" function loaded more strongly on the Interpersonal factor. In people with non-psychotic mental disorders and SI, Interpersonal functions of NSSI are associated with more severe depressive symptoms (r = 0.34), 12 months history of NSSI (r = 0.30), higher number of NSSI methods (r = 0.41), likelihood of future NSSI (r = 0.35) and psychoticism (r = 0.32).ConclusionThe Russian version of the ISAS-II is a valid and reliable instrument for assessing NSSI functions in a population at high risk for suicide attempts. Interpersonal functions are associated with a number of unpleasant clinical and psychological features.

Dataset Information

Suicidal ideation and behavior in institutions of higher learning: A latent class analysis.

Publications

Suicidal ideation and behavior in institutions of higher learning: A latent class analysis.

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