Finding the Way Forward for Youth Suicide Prevention and Intervention

CHOP researchers are leading several studies on suicide prevention and intervention.

By Emily Shafer

Children’s Hospital of Philadelphia physician scientists with wide-ranging expertise are focused on making life-saving connections through rigorous research to identify those at risk for youth suicide and find novel ways to intervene.

The Youth Suicide Prevention, Intervention and Research Center (Y-SPIRC) at CHOP launched in 2019, as clinicians in the Department of Child and Adolescent Psychiatry and Behavioral Sciences (DCAPBS) realized they were seeing many patients with suicidal ideation and behaviors. Suicide is the second leading cause of death for children and young adults aged 10 to 24 years, and this rate continues to increase.

The suicide of Cayman Naib, a 13-year-old boy from nearby Newtown Square, Pennsylvania, in 2015 is a stark reminder for Tami Benton, MD, psychiatrist-in-chief, and executive director and chair of DCAPBS, of the great deal of work that must be accomplished to establish more effective ways to lower rates of youth suicide attempts and deaths by suicide. The multidisciplinary Y-SPIRC team’s goal is zero youth suicides.

“Following Cayman’s death, there was community outrage, and people were wondering how could this happen,” Dr. Benton said. “We learned that suicide rates have been steadily increasing among young people in the last 10 years, and somehow, we missed that.”

Cayman’s death led to CHOP and other institutions in Philadelphia expanding their clinical and research programs around suicide prevention. Y-SPIRC, co-led by Dr. Benton and Rhonda Boyd, PhD, a psychologist in DCAPBS, and associate professor of Psychiatry at Perelman School of Medicine at the University of Pennsylvania grew from a data registry and repository of patients who come to the outpatient Child and Adolescent Mood Program at CHOP.

“This actually was a big focus of our clinical work, and we decided that we needed to focus more on suicide, both on training providers and the community, but also on research,” Dr. Boyd said. “Our goal is to be able to use that data to foster research and identify research questions.”

These research efforts are gaining momentum as CHOP experts bring their unique skills and perspectives to the field of suicide prevention. Scientists are taking a deeper look at parental awareness of suicidal ideation, studying the effectiveness of a brief intervention model, and testing the utility of machine learning methods to facilitate the prevention of suicide attempts. A clinical decision support tool for primary care clinicians to stratify patients with mental health concerns also is under development.

Family Awareness of Potential Risk Factors

An eye-opening study published in Pediatrics involved 5,100 participants ages 11 to 17 from the Philadelphia Neurodevelopmental Cohort (PNC), a large-scale, deep phenotyping collaborative effort between Penn Medicine and CHOP that provides the neuroscience community with data characterizing brain and behavior interaction with genetics. Jason D. Jones, PhD, research assistant professor of Psychiatry at Perelman School of Medicine at the University of Pennsylvania, and research scientist in DCAPBS and PolicyLab at CHOP, and colleagues from the Lifespan Brain Institute (LiBI) found that among the adolescents who reported suicidal ideation, one out of every two parents was unaware that their adolescent had ever had thoughts of committing suicide.

“The discrepancy between parent and teen reports is quite alarming,” Dr. Jones said. “Parental unawareness and adolescent denial of suicidal thoughts may prevent at-risk teens from receiving the mental health services they need.”

Another study led by Dr. Jones highlighted the need to investigate neurocognitive functioning as an endophenotype for suicide risk. The study included 501 participants ages 8 to 21 years who had a family history of suicide attempts. Researchers matched this group with 3,006 participants of similar age, sex, race, and lifetime depression, but no family history of suicide attempts.

“It is well documented that suicidal behavior runs in families and having a family history is considered a risk factor for suicide,” Dr. Jones said. “One approach to studying how this risk is transmitted is to compare a group of individuals with a family history of suicidal behavior to a group of individuals without a family history to see if they differ on some heritable trait or characteristic that is thought to be associated with suicide risk.”

The study team found that youth with a family history of suicide had small differences in executive function, attention, and language reasoning. Such deficits have been linked to suicide risk previously, Dr. Jones said. The research results appeared online in the Journal of Child Psychology and Psychiatry.

Both studies suggest additional research opportunities for early identification and prevention of suicidal behaviors. They also emphasize the need for multiple sources, including healthcare teams, to receive continued training on how to pay attention to risk factors for youth suicide and to facilitate access to mental health services.

Brief Suicide Interventions in Acute Care

Brief suicide prevention interventions, delivered in a single in-person encounter, were associated with reduced suicide attempts, according to a meta-analysis of 14 studies representing outcomes for 4,270 patients.

“General emergency departments and hospitals commonly see patients who are at risk of suicide, or who have made a suicide attempt, but those settings aren’t necessarily always set up with many mental healthcare providers,” said Stephanie Doupnik, MD, MSHP, former co-director of the inpatient Medical Behavioral Unit at CHOP, faculty member of PolicyLab and the Center for Pediatric Clinical Effectiveness, and assistant professor of Pediatrics at Perelman School of Medicine at the University of Pennsylvania, who led the meta-analysis that appeared in JAMA Psychiatry. “So I looked into what can be done in general hospital settings to support these patients.”

The research team categorized the interventions into four groups. One type of intervention is a “caring or brief contact,” in which the hospital or emergency department extends a follow-up phone call, postcard, or text message to check in on the patient. A second type of intervention is a safety planning intervention that helps the patient develop a coping plan for suicidal thoughts. The third is care coordination, in which someone from the emergency department helps coordinate follow-up care for the patient. A fourth type of intervention included other types of psychotherapy.

“I think the next step is to figure out how we can implement these interventions in routine practice,” Dr. Doupnik said. “These interventions may be helpful in other settings, such as jails and homeless shelters, so another line of future research is trying to understand how these interventions can work in arenas outside of the healthcare setting.”

In addition to her collaborators at CHOP and Penn, Dr. Doupnik collaborated with researchers from Yale School of Medicine, New Haven, Connecticut; Massachusetts General Hospital, Boston; and Nationwide Children's Hospital, The Ohio State University, Columbus.

Predicting Suicide Attempts Using Machine Learning

The National Institute of Mental Health awarded CHOP researchers a grant to study the utility of machine learning methods to facilitate the prevention of suicide attempts among youth in a primary care pediatric setting. Ran Barzilay, MD, PhD, an attending psychiatrist at CHOP and assistant professor of Psychiatry at Perelman School of Medicine at the University of Pennsylvania who works with LiBI, will lead the study with Fuchiang (Rich) Tsui, PhD, associate professor in the Department of Biomedical and Health Informatics.

Drs. Barzilay and Tsui will analyze demographic, behavioral, cognitive, and imaging variables collected from the PNC, and then integrate it with data collected via CHOP electronic health records (EHRs) to try and identify patterns in the data that are associated with a risk of a suicide attempt. Using machine learning methods, the research team will try to determine which variables (features) should be part of pediatric EHRs in order to optimize such prediction.

“This is a proof-of-concept study where we aim to use predictive modeling of multiple types of data to predict the outcome of suicide attempts in youth,” Dr. Barzilay said. “Predicting suicide is considered the ‘Holy Grail’ in mental health, especially among youth.”

At the end of the two-year study, they plan to leverage the knowledge gathered to create a a platform that aims to help clinicians “flag” youths at greater risk for suicide, and hopefully translate the findings to a clinical level.

Harnessing Technology to Link Mental Health Care

Development of a technology-enabled suicide screener for primary care clinicians to stratify patients with mental health concerns and refer them to the appropriate level of care also is underway. Primary care clinics right now do not have a standardized way of screening for suicide; they sometimes use the PHQ-9, which is a depression scale, but is not a comprehensive suicide screening method. A grant from Twilio Impact Fund is supporting work by Lan Chi “Krysti” Vo, MD, medical director of telehealth with DCAPBS, to adapt a suicide risk screener into a chatbot.

“Most mental health concerns, including suicidality, are first brought up in primary care, and thus suicidal screening in primary care is an important preventive measure,” Dr. Vo said. “However, primary care providers are not trained on what to do after a positive depression screen that has some suicidality. They may send low-risk patients to the already overburdened crisis centers and emergency departments. This digital health product provides actionable recommendations for primary care providers to use after a positive mental health screening by triaging patients into different levels of risk, and connecting them to the appropriate level of mental care.”

For low-risk patients, the chatbot will refer the patient to an appointment with a behavioral healthcare provider. For moderate-risk patients, the chatbot will connect the patient and primary care provider to a telepsychiatry consult via video before the patient leaves the primary care office. High-risk patients will be referred to the nearby emergency department or crisis center.

“The linkage to care is the most important part of this study,” Dr. Vo said.

Patients will have the opportunity to be part of a care coordination study, in which they are provided with a referral to mental health services based on their location and insurance eligibility. The software will facilitate a seamless process to assist families in accessing mental health care, such as asynchronous two-way communication between a care coordinator and families, to identify barriers to making appointments.

“This information can prompt care coordinators to call families, when appropriate,” Dr. Vo said. “This digital health product has tremendous potential to improve outpatient appointment retention, lower the frequency of emergency department visits for mental health care needs, and ultimate lower the barriers families have to accessing mental healthcare.”

The research is not stopping there: Several projects are in the planning stages. Large grant applications are in the works for studies involving suicide among ethnically diverse youth, preadolescent suicide, and to identify effective suicide prevention strategies in collaboration with other institutions, Drs. Benton and Boyd said.