Dataset Information

Beyond Depression: Estimating 12-Months Prevalence of Passive Suicidal Ideation in Mid- and Late-Life in the Health and Retirement Study.

ABSTRACT: Objectives:To provide valid estimates of the 12-month prevalence of passive suicidal ideation among older adults, without conditioning on depression status, using the Health and Retirement Study (HRS).

Methods:Data come from the 2012 HRS (n?=?17,434) and 2004/5 Baltimore Epidemiologic Catchment Area (ECA) Study (n?=?755). In the HRS, passive suicidal ideation (i.e., thought a lot about death-your own, someone else's, or death in general) is only assessed on respondents who reported dysphoria/anhedonia; in the ECA, ideation is assessed on all respondents, regardless of depression. We compare two approaches to estimating the 12-month prevalence of passive suicidal ideation in the HRS without conditioning on depression symptoms: 1) a probit selection model within the HRS, and 2) a prediction model developed using appended ECA data applied to the HRS.

Results:Using observed data alone on those who screened positive for depression, 6% of older adults reported passive suicidal ideation in the past year. Depending on the approach used, between 5.4% and 9.2% of HRS respondents who screened negative for depression would have reported passive suicidal ideation had they been assessed. Correcting for this selection bias, between 10.9% and 13.4% of U.S. adults over age 50 experienced passive suicidal ideation in 2012.

Conclusions:Population surveillance of suicidal ideation among older adults is biased by survey approaches that only assess ideation in the context of depression.

SUBMITTER: Dong L

PROVIDER: S-EPMC6842696 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Beyond Depression: Estimating 12-Months Prevalence of Passive Suicidal Ideation in Mid- and Late-Life in the Health and Retirement Study.

Dong Liming L Kalesnikava Viktoryia A VA Gonzalez Richard R Mezuk Briana B

The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry 20190702 12

<h4>Objectives</h4>To provide valid estimates of the 12-month prevalence of passive suicidal ideation among older adults, without conditioning on depression status, using the Health and Retirement Study (HRS).<h4>Methods</h4>Data come from the 2012 HRS (n = 17,434) and 2004/5 Baltimore Epidemiologic Catchment Area (ECA) Study (n = 755). In the HRS, passive suicidal ideation (i.e., thought a lot about death-your own, someone else's, or death in general) is only assessed on respondents who reporte ...[more]

PMID: 31353189

Similar Datasets

Project description:ImportanceAdvancements in technology, including mobile-based ecological momentary assessments (EMAs) and passive sensing, have immense potential to identify short-term suicide risk. However, the extent to which EMA and passive data, particularly in combination, have utility in detecting short-term risk in everyday life remains poorly understood.ObjectiveTo examine whether and what combinations of self-reported EMA and sensor-based assessments identify next-day suicidal ideation.Design, setting, and participantsIn this intensive longitudinal prognostic study, participants completed EMAs 4 times daily and wore a sensor wristband (Fitbit Charge 3) for 8 weeks. Multilevel machine learning methods, including penalized generalized estimating equations and classification and regression trees (CARTs) with repeated 5-fold cross-validation, were used to optimize prediction of next-day suicidal ideation based on time-varying features from EMAs (affective, cognitive, behavioral risk factors) and sensor data (sleep, activity, heart rate). Young adult patients who visited an emergency department with recent suicidal ideation and/or suicide attempt were recruited. Identified via electronic health record screening, eligible individuals were contacted remotely to complete enrollment procedures. Participants (aged 18 to 25 years) completed 14 708 EMA observations (64.4% adherence) and wore a sensor wristband approximately half the time (55.6% adherence). Data were collected between June 2020 and July 2021. Statistical analysis was performed from January to March 2023.Main outcomes and measuresThe outcome was presence of next-day suicidal ideation.ResultsAmong 102 enrolled participants, 83 (81.4%) were female; 6 (5.9%) were Asian, 5 (4.9%) were Black or African American, 9 (8.8%) were more than 1 race, and 76 (74.5%) were White; mean (SD) age was 20.9 (2.1) years. The best-performing model incorporated features from EMAs and showed good predictive accuracy (mean [SE] cross-validated area under the receiver operating characteristic curve [AUC], 0.84 [0.02]), whereas the model that incorporated features from sensor data alone showed poor prediction (mean [SE] cross-validated AUC, 0.56 [0.02]). Sensor-based features did not improve prediction when combined with EMAs. Suicidal ideation-related features were the strongest predictors of next-day ideation. When suicidal ideation features were excluded, an alternative EMA model had acceptable predictive accuracy (mean [SE] cross-validated AUC, 0.76 [0.02]). Both EMA models included features at different timescales reflecting within-day, end-of-day, and time-varying cumulative effects.Conclusions and relevanceIn this prognostic study, self-reported risk factors showed utility in identifying near-term suicidal thoughts. Best-performing models required self-reported information, derived from EMAs, whereas sensor-based data had negligible predictive accuracy. These results may have implications for developing decision algorithms identifying near-term suicidal thoughts to guide risk monitoring and intervention delivery in everyday life.

Project description:IntroductionThere are few studies investigating genetic factors related to suicidal ideation or behavior in older adult populations. Our aim was to test associations between passive and active suicidal ideation and polygenic risk scores (PRSs) for suicidality and other traits of relevance for suicidality in old age (i.e. depression, neuroticism, loneliness, Alzheimer's disease, cognitive performance, educational attainment, and several specified vascular diseases) in a population-based sample aged 70 years and older.MethodsParticipants in the prospective H70 study in Gothenburg, Sweden, took part in a psychiatric examination that included the Paykel questions on active and passive suicidal ideation. Genotyping was performed with the Neurochip (Illumina). After quality control of the genetic data the sample included 3467 participants. PRSs for suicidality and other related traits were calculated based on summary statistics from recent GWASs of relevance. Exclusion of persons with dementia or incomplete data on suicidal ideation yielded 3019 participants, age range 70-101 years. Associations between past year suicidal ideation (any level) and selected PRSs were analysed using general estimation equation (GEE) models, adjusted for sex and age.ResultsWe observed associations between passive/active suicidal ideation and PRSs for depression (three versions), neuroticism, and general cognitive performance. After excluding individuals with current major depressive disorder (MDD), similar associations were seen with PRS for neuroticism, general cognitive performance and two PRSs for depression. No associations were found between suicidal ideation and PRSs for suicidality, loneliness, Alzheimer's disease, educational attainment, or vascular disease.DiscussionOur results could indicate which types of genetic susceptibility that are of importance for suicidality in old age, and these findings can help to shed light on potential mechanisms that may be involved in passive and active suicidal ideation in late-life, also in those with no current MDD. However, due to the limited sample size, the results need to be interpreted with caution until replicated in larger samples.

Project description:BACKGROUND:Suicidal behavior is associated with impaired decision making in contexts of uncertainty. Existing studies, however, do not definitively address whether suidice attempers have 1) impairment in learning from experience or 2) impairment in choice based on comparison of estimated option values. Our reinforcement learning model-based behavioral study tested these hypotheses directly in middle-aged and older suicide attempters representative of those who die by suicide. METHODS:Two samples (sample 1, n = 135; sample 2, n = 125) of suicide attempters with depression (nattempters = 54 and 39, respectively), suicide ideators, nonsuicidal patients with depression, and healthy control participants completed a probabilistic three-choice decision-making task. A second experiment in sample 2 experimentally dissociated long-term learned value from reward magnitude. Analyses combined computational reinforcement learning and mixed-effects models of decision times and choices. RESULTS:With regard to learning, suicide attempters (vs. all comparison groups) were less sensitive to one-back reinforcement, as indicated by a reduced effect on both choices and decision times. Learning deficits scaled with attempt lethality and were partially explained by poor cognitive control. With regard to value-based choice, suicide attempters (vs. all comparison groups) displayed abnormally long decision times when choosing between similarly valued options and were less able to distinguish between the best and second-best options. Group differences in value-based choice were robust to controlling for cognitive performance, comorbidities, impulsivity, psychotropic exposure, and possible brain damage from attempts. CONCLUSIONS:Serious suicidal behavior is associated with impaired reward learning, likely undermining the search for alternative solutions. Attempted suicide is associated with impaired value comparison during the choice process, potentially interfering with the consideration of deterrents and alternatives in a crisis.

Dataset Information

Beyond Depression: Estimating 12-Months Prevalence of Passive Suicidal Ideation in Mid- and Late-Life in the Health and Retirement Study.

Publications

Beyond Depression: Estimating 12-Months Prevalence of Passive Suicidal Ideation in Mid- and Late-Life in the Health and Retirement Study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets