Psychobehavioral Intervention for Reducing Suicide Risk

Recruiting at 1 trial location

Overseen By Hilary Blumberg, MD

Age: < 65

Sex: Any

Trial Phase: Academic

Sponsor: Yale University

Must not be taking: Benzodiazepines, Cocaine, Amphetamines, others

Disqualifiers: Neurologic illness, Pregnancy, Psychosis, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 13

Duration: 12 weeks

65 Participants Needed

Trial Summary

What is the purpose of this trial?

The purpose of this study is to advance a non-pharmacologic suicide preventive intervention with wide dissemination potential as an innovative high-yield solution to reduce suicide rates. The investigators aim to achieve this with this study of Brain Emotion Circuitry Self-Monitoring and Regulation Therapy for Daily Rhythms (BE-SMART-DR), that provides self-directed strategies to regularize sleep and other DRs to reduce short-term suicide risk that can be used lifelong to potentially also reduce long-term suicide risk.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. However, it does exclude those currently receiving certain therapies like cognitive behavioral therapy or treatments targeting specific brain regions.

What data supports the effectiveness of the treatment BE-SMART-DR for reducing suicide risk?

The research highlights the importance of targeting brain circuits involved in emotion regulation and decision-making, which are relevant to the BE-SMART-DR treatment. Similar interventions, like cognitive therapy and transcranial magnetic stimulation, have shown promise in reducing suicidal thoughts by modulating these neural circuits. ^{1 2 3 4 5}

How is the BE-SMART-DR treatment different from other treatments for reducing suicide risk?

BE-SMART-DR is unique because it integrates brain emotion circuitry self-monitoring and regulation with daily rhythm adjustments, focusing on real-time tracking and modulation of neural circuits associated with suicide risk, unlike traditional treatments that may not address the temporal fluctuations in risk. ^{1 2 4 6 7}

Research Team

Hilary Blumberg, MD

Principal Investigator

Yale University

Eligibility Criteria

This trial is for young individuals with Bipolar Disorder or Major Depressive Disorder who have attempted suicide or have significant suicidal thoughts. They must be able to consent and not be pregnant, overly manic, psychotic, or under certain substance influences. Those with severe medical conditions or undergoing specific psychotherapies are excluded.

Inclusion Criteria

Patients with a history of 1 or more suicide attempts and/or a score of at least 3 on the SSI

I have been diagnosed with Bipolar Disorder or Major Depressive Disorder.

Exclusion Criteria

Pregnancy by urine test

Homicidal ideation

Positive urine screen for benzodiazepines, cocaine, amphetamines, phencyclidine, opiates, oxycodone; not cannabis as its use is common in this population and it can remain positive for a month

Timeline

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

Treatment

Participants receive the BE-SMART-DR intervention or a psychoeducational control comparator condition over 12 weekly sessions

12 weeks

12 visits (in-person)

Follow-up

Participants are monitored for safety and effectiveness after treatment, including in-person follow-up and assessments

6 months

1 visit (in-person)

Treatment Details

Interventions

• BE-SMART-DR
• psychoeducational control comparator condition (CC)

Trial Overview The study tests BE-SMART-DR, a non-drug intervention aiming to regularize daily rhythms like sleep to reduce suicide risk in adolescents and young adults. It's compared against a psychoeducational control condition to measure effectiveness.

Participant Groups

Group I: BE-SMART-DR Experimental Treatment 1 Intervention

Participation will include research clinical/behavioral interviews and symptom self-ratings, magnetic resonance imaging (MRI) scanning, actigraphy wearables, and use of smart phones for ecological momentary assessment (EMA). Subjects will participate in 12 weekly sessions and 6-month in person follow-up.

Group II: control comparator condition Active Control 1 Intervention

Matched for experimental, participation will include research clinical/behavioral interviews and symptom self-ratings, magnetic resonance imaging (MRI) scanning, actigraphy wearables, and use of smart phones for ecological momentary assessment (EMA). Subjects will participate in 12 weekly sessions and 6-month in person follow-up.

Who Is Running the Clinical Trial?

Yale University

Lead Sponsor

Trials

1,963

Recruited

3,046,000+

American Foundation for Suicide Prevention

Collaborator

Trials

36

Recruited

10,500+

Findings from Research

Despite advancements in psychiatric treatment, suicide rates have increased, highlighting a gap in effective interventions targeting suicidal thoughts and behaviors.

The review emphasizes the importance of understanding the temporal nature of suicide risk and suggests integrating neurobiological insights with real-time tracking of risk to develop more effective treatment strategies.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Translating Interventional Neuroscience to Suicide: It's About Time. Barredo, J., Bozzay, ML., Primack, JM., et al.[2023]

This review highlights the need for rapid-acting interventions in suicide crisis treatment and discusses innovative assessment methods that can track quick changes in suicidal thoughts and behaviors.

New techniques such as ecological momentary assessment and neuroimaging are being developed to improve our understanding of the psychological and biological factors related to suicide risk, potentially leading to better clinical outcomes.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

New Methods for Assessing Rapid Changes in Suicide Risk. Ballard, ED., Gilbert, JR., Wusinich, C., et al.[2023]

Suicide is a major public health issue, with nearly a million deaths globally each year, and is linked to complex interactions of biological, psychological, and sociocultural factors.

The paper suggests using machine learning to combine neurobiological data with mood dysregulation symptoms to better understand the inflammatory processes that may increase suicide risk.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Integrating biobehavioral information to predict mood disorder suicide risk. Jackson, NA., Jabbi, MM.[2022]

A study involving 75 adults used magnetoencephalography (MEG) to identify neural correlates of suicide risk, revealing that those at the highest risk had stronger implicit associations with death and distinct gamma power patterns in specific brain regions.

In a pilot study of five high-risk participants, ketamine administration increased gamma power related to self-death associations in the left insula, suggesting that pharmacotherapies targeting gamma activity may help reduce suicide risk.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Clinical, behavioral, and electrophysiological profiles along a continuum of suicide risk: evidence from an implicit association task. Lamontagne, SJ., Gilbert, JR., Zabala, PK., et al.[2023]

This study aims to explore the brain circuits related to suicidal thoughts and behaviors (STBs) in a sample of 136 US military veterans, half of whom have STBs, using advanced neuroimaging techniques like fMRI.

By comparing brain activity and connectivity in veterans with and without STBs, the research seeks to identify how these brain circuits influence decision-making and impulsivity, potentially leading to better understanding and treatment of STBs.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Suicidal thoughts and behaviours among military veterans: protocol for a prospective, observational, neuroimaging study. Namaky, N., Swearingen, HR., Winter, J., et al.[2023]

A study involving 78 young adults (ages 18-25) identified key factors associated with suicidal thoughts and behaviors, including age, education level, depression, psychiatric distress, and left amygdala activity during emotional processing.

The left amygdala's activity was found to be a significant neurobiological marker for predicting suicidal thoughts and behaviors, suggesting that neuroimaging could play a crucial role in understanding and addressing suicide risk in young adults.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Informing the study of suicidal thoughts and behaviors in distressed young adults: The use of a machine learning approach to identify neuroimaging, psychiatric, behavioral, and demographic correlates. Oppenheimer, CW., Bertocci, M., Greenberg, T., et al.[2022]

In a study involving 15 adolescent suicide attempters, 15 adolescents with depression but no suicide attempts, and 14 healthy controls, it was found that the neural circuitry related to attentional and behavioral control did not show abnormal activity in suicide attempters during a response inhibition task.

The research revealed that while suicide attempters did not differ from healthy controls in brain activity during the task, they exhibited different activation patterns in the right anterior cingulate gyrus compared to adolescents with depression who had not attempted suicide, suggesting distinct neural mechanisms underlying suicidal behavior in adolescents.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Dissociable patterns of neural activity during response inhibition in depressed adolescents with and without suicidal behavior. Pan, LA., Batezati-Alves, SC., Almeida, JR., et al.[2021]

References

1. United States pubmed.ncbi.nlm.nih.gov

Translating Interventional Neuroscience to Suicide: It's About Time. [2023]

2. Switzerland pubmed.ncbi.nlm.nih.gov

New Methods for Assessing Rapid Changes in Suicide Risk. [2023]

3. United States pubmed.ncbi.nlm.nih.gov

Integrating biobehavioral information to predict mood disorder suicide risk. [2022]

4. England pubmed.ncbi.nlm.nih.gov

Clinical, behavioral, and electrophysiological profiles along a continuum of suicide risk: evidence from an implicit association task. [2023]

5. England pubmed.ncbi.nlm.nih.gov

Suicidal thoughts and behaviours among military veterans: protocol for a prospective, observational, neuroimaging study. [2023]

6. Netherlands pubmed.ncbi.nlm.nih.gov

Informing the study of suicidal thoughts and behaviors in distressed young adults: The use of a machine learning approach to identify neuroimaging, psychiatric, behavioral, and demographic correlates. [2022]

7. United States pubmed.ncbi.nlm.nih.gov

Dissociable patterns of neural activity during response inhibition in depressed adolescents with and without suicidal behavior. [2021]