Heterogeneity in suicide risk: Evidence from personalized dynamic models.

Most theories of suicide propose within-person changes in psychological states cause suicidal thoughts/behaviors; however, most studies use between-person analyses. Thus, there are little empirical data exploring current theories in the way they are hypothesized to occur. We used a form of statistical modeling called group iterative multiple model estimation (GIMME) to explore one theory of suicide: The Interpersonal Theory of Suicide (IPTS). GIMME estimates personalized statistical models for each individual and associations shared across individuals. Data were from a real-time monitoring study of individuals with a history of suicidal thoughts/behavior (adult sample: participants = 111, observations = 25,242; adolescent sample: participants = 145, observations = 26,182). Across both samples, none of theorized IPTS effects (i.e., contemporaneous effect from hopeless to suicidal thinking) were shared at the group level. There was significant heterogeneity in the personalized models, suggesting there are different pathways through which different people come to experience suicidal thoughts/behaviors. These findings highlight the complexity of suicide risk and the need for more personalized approaches to assessment and prediction.

Intervening on high-risk responses during ecological momentary assessment of suicidal thoughts: Is there an effect on study data?

Ecological momentary assessment (EMA) is increasingly used to study suicidal thoughts and behaviors (STBs). There is a potential ethical obligation for researchers to intervene when receiving information about suicidal thoughts in real time. A possible concern, however, is that intervening when receiving responses that indicate high risk for suicide during EMA research may impact how participants respond to questions about suicidal thoughts and thus affect the validity and integrity of collected data. We leveraged data from a study of adults and adolescents (N = 434) recruited during a hospital visit for STBs to examine whether monitoring and intervening on high-risk responses affects subsequent participant responding. Overall, we found mixed support for the notion that intervening on high-risk responses influences participants' ratings. Although we observed some evidence of discontinuity in subsequent responses at the threshold used to trigger response-contingent interventions, it was not clear that such discontinuity was caused by the interventions; lower subsequent responses could be due to effective intervention, participant desire to not be contacted again, or regression to the mean. Importantly, the likelihood of completing surveys did not change from before to after response-contingent intervention. Adolescents were significantly more likely than adults, however, to change their initial suicidal intent ratings from above to below the high-risk threshold after viewing automated response-contingent pop-up messages. Studies explicitly designed to assess the potential impact of intervening on high-risk responses in real-time monitoring research are needed, as this will inform effective, scalable strategies for intervening during moments of high suicide risk. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Prediction of Suicide Attempts Using Clinician Assessment, Patient Self-report, and Electronic Health Records.

Importance: Half of the people who die by suicide make a health care visit within 1 month of their death. However, clinicians lack the tools to identify these patients. Objective: To predict suicide attempts within 1 and 6 months of presentation at an emergency department (ED) for psychiatric problems. Design, Setting, and Participants: This prognostic study assessed the 1-month and 6-month risk of suicide attempts among 1818 patients presenting to an ED between February 4, 2015, and March 13, 2017, with psychiatric problems. Data analysis was performed from May 1, 2020, to November 19, 2021. Main Outcomes and Measures: Suicide attempts 1 and 6 months after presentation to the ED were defined by combining data from electronic health records (EHRs) with patient 1-month (n = 1102) and 6-month (n = 1220) follow-up surveys. Ensemble machine learning was used to develop predictive models and a risk score for suicide. Results: A total of 1818 patients participated in this study (1016 men [55.9%]; median age, 33 years [IQR, 24-46 years]; 266 Hispanic patients [14.6%]; 1221 non-Hispanic White patients [67.2%], 142 non-Hispanic Black patients [7.8%], 64 non-Hispanic Asian patients [3.5%], and 125 non-Hispanic patients of other race and ethnicity [6.9%]). A total of 137 of 1102 patients (12.9%; weighted prevalence) attempted suicide within 1 month, and a total of 268 of 1220 patients (22.0%; weighted prevalence) attempted suicide within 6 months. Clinicians' assessment alone was little better than chance at predicting suicide attempts, with externally validated area under the receiver operating characteristic curve (AUC) of 0.67 for the 1-month model and 0.60 for the 6-month model. Prediction accuracy was slightly higher for models based on EHR data (1-month model: AUC, 0.71; 6 month model: AUC, 0.65) and was best using patient self-reports (1-month model: AUC, 0.76; 6-month model: AUC, 0.77), especially when patient self-reports were combined with EHR and/or clinician data (1-month model: AUC, 0.77; and 6 month model: AUC, 0.79). A model that used only 20 patient self-report questions and an EHR-based risk score performed similarly well (1-month model: AUC, 0.77; 6 month model: AUC, 0.78). In the best 1-month model, 30.7% (positive predicted value) of the patients classified as having highest risk (top 25% of the sample) made a suicide attempt within 1 month of their ED visit, accounting for 64.8% (sensitivity) of all 1-month attempts. In the best 6-month model, 46.0% (positive predicted value) of the patients classified at highest risk made a suicide attempt within 6 months of their ED visit, accounting for 50.2% (sensitivity) of all 6-month attempts. Conclusions and Relevance: This prognostic study suggests that the ability to identify patients at high risk of suicide attempt after an ED visit for psychiatric problems improved using a combination of patient self-reports and EHR data.

Increase in Suicidal Thinking During COVID-19.

There is concern that the COVID-19 pandemic may cause increased risk of suicide. In the current study, we tested whether suicidal thinking has increased during the COVID-19 pandemic and whether such thinking was predicted by increased feelings of social isolation. In a sample of 55 individuals recently hospitalized for suicidal thinking or behaviors and participating in a 6-month intensive longitudinal smartphone monitoring study, we examined suicidal thinking and isolation before and after the COVID-19 pandemic was declared a national emergency in the United States. We found that suicidal thinking increased significantly among adults (odds ratio [OR] = 4.01, 95% confidence interval [CI] = [3.28, 4.90], p < .001) but not adolescents (OR = 0.84, 95% CI = [0.69, 1.01], p = .07) during the onset of the COVID-19 pandemic. Increased feelings of isolation predicted suicidal thinking during the pandemic phase. Given the importance of social distancing policies, these findings support the need for digital outreach and treatment.

Keeping Patients at Risk for Self-Harm Safe in the Emergency Department: A Protocolized Approach.

BACKGROUND: Increasing numbers of patients with psychiatric illness are boarding in emergency departments (EDs) for longer periods. Many patients are at high risk of harm to self, and maintaining their safety is critical. The objectives of this study are to describe the development and implementation of a comprehensive safety precautions protocol for ED patients at risk for self-harm and to report the observed changes in rates of self-harm. METHODS: A multidisciplinary team developed comprehensive safety precautions, including the creation of safe bathrooms, increasing the number and training of observers, protocols to manage access to belongings and for clothing search or removal, and additional interventions for exceptionally high-risk patients. Events of attempted self-harm were measured for 12 months before and after new safety precautions were enacted. RESULTS: In the 12 months prior to the protocol initiation, among 4,408 at-risk patients, there were 13 episodes of attempted self-harm (2.95 per 1,000 at-risk patients), and 6 that resulted in actual self-harm (1.36 per 1,000 at-risk patients). In the 12 months after the protocol was introduced, among the 4,523 at-risk patients, there were 6 episodes of attempted self-harm (1.33 per 1,000 at-risk patients, p = 0.11) and only 1 that resulted in actual self-harm (0.22 per 1,000 at-risk patients, p = 0.07). There were no deaths. CONCLUSION: Comprehensive safety precautions can be successfully developed and implemented in the ED. These precautions correlated with lower, although not statistically significant, rates of self-harm. Further study of similar interventions with adequately powered samples could be beneficial.

"Call Me, Maybe": Supervisor and Resident Comfort With Indirect Supervision in Psychiatry Training.

BACKGROUND: Resident supervision is critical for education and ensuring patient safety. After hours, communication with attendings is variable. OBJECTIVE: The objective was to identify differences among psychiatry residents and attendings regarding the desired level of supervision for issues that arise overnight in the psychiatric emergency department (ED). METHODS: In a single-site psychiatric ED, an electronic survey containing 30 hypothetical scenarios was administered. For each scenario, residents were asked if they would call attendings and attendings whether they would want to be called. RESULTS: 35/44 psychiatry residents and 15/17 faculty participated, yielding a response rate of 82%. For five scenarios, faculty preferred that residents call for supervision more frequently than residents indicated they would. These included staff or house staff injuries (60% vs. 22.9%, p = 0.011; 93.3% vs. 62.9%, p = 0.039), a patient using heroin in the ED (53.3% vs. 5.7%, p < 0.001), a conflict with the medical ED attending (100% vs. 65.7%, p = 0.010), and a decision about calling in a backup resident (60% vs. 28.6%, p = 0.036). CONCLUSIONS: In a psychiatric ED, attendings prefer greater involvement in cases relating to psychosocial issues, legal concerns, and conflicts with patients. More work is needed to fully understand these differences and their potential impact on patient care and training.

The prescription of psychotropic medications for patients discharged from a psychiatric emergency service.

OBJECTIVE: Considerable debate exists about the value and wisdom of initiating "definitive" pharmacotherapies, particularly antidepressants, in the psychiatric emergency setting. We evaluated the nature and prevalence of medication prescriptions for patients discharged from an urban psychiatric emergency service and the extent to which pharmacotherapy initiation was predictive of follow-through with aftercare. METHOD: Records were reviewed for 675 consecutive individuals evaluated and discharged from a community-based psychiatric emergency service over a 3-month period (January 2003-March 2003). Information was obtained regarding diagnoses, past and current treatments, and demographic and clinical features, as well as outcomes for the subgroup of patients who received aftercare appointments within the institutional system. RESULTS: Fifty-five percent of psychiatric emergency service visits resulted in discharge, with psychotropic drug prescriptions given to about 30% of this group. Prescriptions most often included antidepressants (64%), benzodiazepines (25%), nonbenzodiazepine sedatives (20%), anti-psychotics (18%), and mood stabilizers (10%). After controlling for potential confounders, the decision to prescribe was significantly associated with a clinical diagnosis of major depressive disorder or bipolar disorder and the preexisting use of psychotropic medications. Nonprescribing occurred most often in discharged patients who had suicidal ideation, substance abuse or dependence, and an existing outpatient psychiatrist. Follow-up emergency service and new outpatient appointments were more often given to patients discharged with a prescription, but follow-through with aftercare was not more likely in this group. CONCLUSIONS: Psychiatrists in an emergency service prescribe antidepressants or other major psychotropics for about one third of discharged patients, rarely in the presence of suicidality or substance abuse or dependence, and with little evidence that initiating such medications in the emergency setting promotes more successful bridging to outpatient treatment.