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By: Cassidy Delamarter, University Communications and Marketing

Diagnosing post-traumatic stress disorder in children can be notoriously difficult.
Many, especially those with limited communication skills or emotional awareness, struggle
to explain what they’re feeling. Researchers at the University of South Florida are
working to address those gaps and improve patient outcomes by merging their expertise
in childhood trauma and artificial intelligence. 

Led by Alison Salloum, professor in the USF School of Social Work, and Shaun Canavan, associate professor in the Bellini Center for Artificial Intelligence, Cybersecurity and Computing, the interdisciplinary team is building a system that could provide clinicians with
an objective, cost-effective tool to help identify PTSD in children and adolescents,
while tracking their recovery over time.

Traditionally, diagnosing PTSD in children relies on subjective clinical interviews
and self-reported questionnaires, which can be limited by cognitive development, language
skills, avoidance behaviors or emotional suppression. 

“This really started when I noticed how intense some children’s facial expressions
became during trauma interviews,” Salloum said. “Even when they weren’t saying much,
you could see what they were going through on their faces. That’s when I talked to
Shaun about whether AI could help detect that in a structured way.”

Canavan, who specializes in facial analysis and emotion recognition, repurposed existing
tools in his lab to build a new system that prioritizes patient privacy. The technology
strips away identifying details and only analyzes de-identified data, including head
pose, eye gaze and facial landmarks, such as the eyes and mouth. 

“That’s what makes our approach unique,” Canavan said. “We don’t use raw video. We
completely get rid of the subject identification and only keep data about facial movement,
and we factor in whether the child was talking to a parent or a clinician.”

The study, published in Science Direct, is the first of its kind to incorporate context-aware PTSD classification while
fully preserving participant privacy. The team built a dataset from 18 sessions with
children as they shared emotional experiences. With more than 100 minutes of video
per child and each video containing roughly 185,000 frames, Canavan’s AI models extracted
a range of subtle facial muscle movements linked to emotional expression.

The findings revealed distinct patterns are detectable in the facial movements of
children with PTSD.  The researchers also found that facial expressions during clinician-led
interviews were more revealing than parent-child conversations. This aligns with existing
psychological research showing children may be more emotionally expressive with therapists
and may avoid sharing distress with parents due to shame or their cognitive abilities.

“That’s where the AI could offer a valuable supplement,” Salloum said. “Not replacing
clinicians, but enhancing their tools. The system could eventually be used to give
practitioners real-time feedback during therapy sessions and help monitor progress
without repeated, potentially distressing interviews.”

The team hopes to expand the study to further examine any potential bias from gender,
culture and age, especially preschoolers, where verbal communication is limited and
diagnosis relies almost entirely on parent observation. 

Though the study is still in its early stages, Salloum and Canavan feel the potential
applications are far-reaching. Many of the current participants had complex clinical
pictures, including co-occurring conditions like depression, ADHD or anxiety, mirroring
real-world cases and offering promise for the system’s accuracy. 

“Data like this is incredibly rare for AI systems, and we’re proud to have conducted
such an ethically sound study. That’s crucial when you’re working with vulnerable
subjects,” Canavan said. “Now we have promising potential from this software to give
informed, objective insights to the clinician.”

If validated in larger trials, USF’s approach could redefine how PTSD in children
is diagnosed and tracked, using everyday tools like video and AI to bring mental health
care into the future.

Robert Volpe, a professor of applied psychology, says help is available for adults with ADHD, but self-diagnosis is dangerous

Attention problems and overactivity have long been associated with childhood.  

It was first included in the Diagnostic and Statistical Manual of the American Psychiatric Association in 1968 — at that time, it was called hyperkinetic reaction of childhood, says Robert Volpe, a professor of applied psychology at Northeastern and an expert on Attention Deficit Hyperactivity Disorder. 

It was understood to refer to the type of ants-in-your-pants behavior that distinguished children with severe motor activity, restlessness, distractibility and short attention spans.

These days, many adults are wondering whether their distractibility and difficulty with managing the tasks of everyday life stem from undiagnosed ADHD. Online discussion boards buzz with their concerns, and diagnostic internet quizzes are available with the click of a keyboard.

“Self-diagnosis is a risky thing to do,” says Volpe, who adds that only licensed psychologists and medical doctors, such as psychiatrists, are qualified to diagnose the condition and recommend treatment. 

There’s a danger people may misdiagnose themselves with ADHD when they need to be treated for anxiety or depression, he says.

But adult ADHD is a real phenomenon, Volpe says. And understanding what ADHD is — and isn’t — can be the first step in getting help.

ADHD is a neurodevelopmental disorder

Volpe says ADHD is a neurodevelopmental disorder that is associated with a complex set of interactions between genes and the environment, but for which there is no biological test.

“There are certainly some genetics involved, but it’s not one gene. It’s a combination of genes,” he says. The environment also must be factored in, as is the case with most psychiatric disorders.

There are different types of ADHD

In the 1980s, the disorder was referred to as simply attention deficit disorder. 

There are three subtypes now of ADHD now, Volpe says.

“Hyperactivity only is very rare and only found in young children. Hyperactivity is also very rare in adults. The two common subtypes for children and adolescents are ADHD Predominantly Inattentive Type and ADHD Combined Type.”  

Two sets of nine symptoms

There are two sets of symptom criteria, one for inattentive ADHD and one for hyperactive/impulsive ADHD, Volpe says.

People with the disorder must have at least six out of nine symptoms for one or both, he says.

The Cleveland Clinic says symptoms for inattentive ADHD include trouble paying attention to detail, listening to others or staying focused on long-winded tasks such as reading or listening to a presentation.

The symptom list also includes lack of follow-through on tasks and obligations as well as difficulty keeping track of everyday items such as pencils, wallets and keys, or staying in the moment without distractions.