Web Survey Predicts Risk of Adolescent Depression

By Johnson, Kate | Clinical Psychiatry News, February 2007 | Go to article overview
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Web Survey Predicts Risk of Adolescent Depression


Johnson, Kate, Clinical Psychiatry News


SAN ANTONIO -- Physicians may be able to quickly and accurately assess and stratify an adolescent's 1-year risk of developing new-onset major depression using a 20-item checklist, Dr. Benjamin W. Van Voorhees said at the annual meeting of the Society for Prevention Research.

The information could then help physicians guide patients and parents toward reducing the risk using a variety of therapeutic interventions, including a Web-based approach that he has developed and is now testing, according to Dr. Van Voorhees, who is both a pediatrician and an internist at the University of Chicago.

Dr. Voorhees said primary care physicians use a brief list of questions to stratify a person's 10-year risk of cardiovascular disease and to guide their interventions. "So we wanted to make this depression risk model just as easy to use in the primary care setting," Dr. Voorhees said in an interview.

He said primary care providers now have no alternative to medications or psychotherapy referrals for patients with mild to moderate depression symptoms. "We are trying to create an alternative--to reshape the current paradigm," Dr. Van Voorhees said.

He and his colleagues developed their depression risk prediction model using data from the National Longitudinal Study of Adolescent Health, which involved 6,504 adolescents in grades 7-12. Baseline data on the subjects, collected in 1995, included home, school, and parent surveys. Follow-up data were collected 1 year later on 4,791 subjects.

Using a subsample of 3,814 subjects, none of whom had major depression at baseline and for whom 1-year follow-up data were available, Dr. Van Voorhees identified gender, ethnicity, weight, height, and age as well as 15 independent variables that could be used to predict the patient's development of major depression in the coming year. The model, which has a sensitivity of 74% and a specificity of 87%, includes information on the adolescent's social connectedness, quality of life, mood, and other factors.

His research group plans to formally test the prediction model in a prospective study of youth at risk for developing major depression.

In a separate analysis of the same subset, Dr. Van Voorhees also identified a list of factors that appeared to protect against the development of depression. For example, on a personal level, an adolescent's self-rated health, adequate sleep, and self-efficacy seemed protective. On a family and community level, participation, attachment, and competence seemed protective.

"My idea is that if we have a good risk prediction model, we can basically calculate an adolescent's risk at a well-child visit and then give that information to the child and parent," he said. "Then they can choose whether they want to be involved in a preventive intervention. We believe that such interventions could be done at low cost and, if designed well, could be efficacious and very acceptable to patients and physicians in community settings.

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