Suicidal thoughts have haunted nearly one of every 10 pre-teens in the United States, a new study reveals.
About 8.4% of children aged 9 or 10 said they’d temporarily or regularly harbored thoughts of suicide, researchers report.
Importantly, only around 1% of children that age reported a suicide attempt or planning their suicide.
But suicidal thoughts at that age are a warning sign of a future filled with woe, said senior researcher Dr. Sophia Frangou, a professor of psychiatry with the Icahn School of Medicine at Mount Sinai, in New York City.
“When you think of how young they are, 8% is quite a startling number,” Frangou said. “Thinking of killing yourself, and that life isn’t worth it, when you’re 9 is pretty extreme.”
Suicide is the second leading cause of death among 10- to 14-year-olds, researchers said in background notes, and these sorts of thoughts paint a picture of a troubled childhood.
“Being so seriously unhappy so early in life is a sign of vulnerability for adverse mental health outcomes in adulthood,” Frangou noted. “It’s not just about suicide.”
For this study, Frangou and her colleagues analyzed data from the Adolescent Brain and Cognitive Development study, which is tracking the growth and health of nearly 12,000 children across the United States.
Children and their caregivers filled out reports that included questions related to suicidal thoughts and behaviors.
Two factors played a strong role in whether a child would have suicidal thoughts, the research team found.
“Children that have some sort of psychological problems, even minor ones, and the ones that live in families that are in some way dysfunctional, those are the ones that are at the highest risk to have suicidal thoughts,” Frangou said.
Kids suffering from anxiety, depression or other psychological or behavior problems are 74% more likely to experience suicidal thoughts, results show.
And children who reported family conflict were 30% to 75% more likely to harbor thoughts of suicide, even after accounting for their psychological problems, the researchers said.
The findings were published online March 12 in The Lancet Psychiatry medical journal.
None of these numbers are surprising, said Mitch Prinstein, a professor of psychology and neuroscience with the University of North Carolina, Chapel Hill.
“We’ve been seeing the age where suicide ideation and suicidal behavior is occurring get lower and lower over the last few years,” Prinstein said.
“We know that suicide is very closely related to the experience of stress, not just the stress that kids are experiencing but the stress that parents and people around them are experiencing, which kids definitely pick up on.”
The number of children’s hospital admissions for suicidal thoughts or behavior has more than doubled over the last decade, rising from 0.7% in 2008 to 1.8% in 2015, the researchers said.
The research team also found two factors that appeared to protect kids against suicidal thoughts: active parental supervision and having a positive experience in school.
“The kids that liked going to school and felt the school environment was a good environment for them were less likely to have these types of thoughts,” Frangou said.
Parental supervision means “the degree to which parents are involved in their children’s lives,” she explained.
“They know where their kids are, they know the names of their friends,” Frangou said. “It’s not about quality time, it’s about knowing what your kid is doing and being involved in an active, meaningful way.”
These results indicate a need for school-based screening for suicide, much as vision and hearing tests are conducted with youngsters, Prinstein and Frangou said.
“Schools are a good place where we can start looking for kids who have difficulties and for families who have difficulties. We should think of schools as a means to help them,” Frangou said.
“You don’t have to look for the suicidal kid. You have to look for the unhappy one,” she continued. “You don’t have to specifically predict who will have suicidal thoughts.
You have to be more sensitized to children who are unhappy, either because their families are difficult or because they themselves experience anxiety.”
There are a number of telltale signs that a child is troubled enough to think about suicide, said Dr. Kimberly Gordon-Achebe, a child and adolescent psychiatrist in Baltimore. These include:
- Changes in behavior or eating habits.
- Sleeping in class.
- Withdrawing from peers or isolating themselves.
- Acting moody or irritable.
- Talking about death with peers.
- Drawing pictures or writing about death.
“These are great indicators of what could be going on in their mind,” Gordon-Achebe said.
Suicide is the tenth leading cause of death in the US, claiming the lives of more than 44,000 individuals in 2015. Over the past 15 years, the suicide rate has increased 24% from 10.5 (in 1999) to 13.7 (in 2015) per 100,000 people1.
Suicide is the third leading cause of death among individuals between the ages of 10 and 14, and the second leading cause of death among individuals between the ages of 15 and 34 2. Rates of suicide in several specific demographics, including veterans and native Americans, consistently exceed the national average2,3.
According to a CDC report, suicide accounted for economic losses of $50.8 billion in 2013, representing 24% of fatal injury costs2. A suicide attempt is a nonfatal, self-directed, potentially injurious behavior with lethal intent.
Surveys suggest that over one million people in the US each year engage in intentionally inflicted self-harm, and 0.6% of adults age 18 and older in the United States attempted suicide in 2015 5.
Since the presence of previous suicide attempts is the most powerful predictor of eventual death by suicide, efficiently identifying prior suicide attempts is a critical step towards reducing suicide deaths and saving lives6.
Various cohorts have shown that somewhere between 56 and 68% of suicides die on the first attempt, the index attempt7–11. Of the 32–44% who survive the index attempt and receive emergency or hospital level of care, rates of subsequent completed suicide are exceptionally high, ranging from 2.3 to 4%9,12–15.
Thus, a previous suicide attempt confers a very high risk of subsequent death by suicide. In one study9, 82% of the subsequent suicides in these hospitalized or ED-treated suicide attempt survivors occurred within 1 year of the index attempt.
Evidence from clinical trials and research suggests that encouraging help-seeking behaviors and increasing the likelihood of intervention by a third party are valuable strategies to reduce suicide in hotspots16.
Interventions for those high risk of suicide attempts are extremely important, and may help in preventing death by suicide. Therefore, suicide attempt prediction tool to stratify individuals into different risk groups at the population level would be useful in that it can assist providers in reaching the most vulnerable.
Various efforts have been made to identify risk factors of suicide thoughts and behaviors, and to predict the probability of future suicide attempts. Although a few high-performance models were reported in studies where the cohorts were enriched for cases17–21, prediction accuracy was limited when applied to a general population where the incidence of suicide attempts was extremely low22.
While univariate and multivariate analyses have been successful in revealing the different roles of individual-level and population-level factors in suicide attempts, reasons for a suicide attempt could be complex and associated to a multi-level network23.
Moreover, although some risk factors have higher weights than others in a specific model of predicting suicide attempt, the meta-analysis found that there is not a dominant factor that has significantly larger importance than the rest. According to a meta-analysis that summarized studies on suicide risk factors over the past 50 years24, there are two future directions:
(1) the implementation of advanced machine-learning technology to incorporate the relations between different risk factors;
(2) the utilization of a high-dimensional dataset containing comprehensive clinical profile of patients. The two directions are supportive to each other, in that the advanced machine-learning techniques can make the best of a large number of features through constructing a complex network to approach the outcome, and a large, high-dimension dataset ensure an effective use of the learning techniques and maximizes the power of the algorithm.
Therefore, using a large, longitudinal electronic health records (EHRs) routinely captured by hospitals, we applied deep learning methodology to develop a neural network model, and validated it within a different population.
Our study focused on a short-term prediction (within 1 year) to support the clinical utility in decision making25, and extended the concepts of early-warning system (EWS) to the next 1-year suicide attempt surveillance of a general population.
More information: Boston Children’s Hospital has more about child and teen suicide.