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Objective: We sought to evaluate two approaches with varying time and complexity in engaging adolescents with an Internet-based preventive intervention for depression in primary care. We conducted a randomized controlled trial comparing primary care physician motivational interview (MI, 10–15 minutes) + Internet program versus brief advice (BA, 2–3 minutes) + Internet program. Setting: Adolescent primary care patients in the United States, ages 14–21. Participants: 83 individuals (40% non-white) at increased risk for depressive disorders (sub-threshold depressed mood > 3–4 weeks) were randomly assigned to either the MI group (n=43) or the BA group (n=40). Main Outcome Measures: Patient Health Questionnaire (PHQ-A) – Adolescent and Center for Epidemiologic Studies Depression Scale (CES-D). Results: Both groups substantially engaged the Internet site (MI, 90.7% versus BA 77.5%). For both groups, CES-D-10 scores declined (MI, 24.0 to 17.0 p < 0.001; BA, 25.2 to 15.5, p < 0.001). The percentage of those with clinically significant depression symptoms based on CES-D-10 scores declined in both groups from baseline to twelve weeks, (MI, 52% to 12%, p < 0.001; BA, 50% to 15%, p < 0.001). The MI group demonstrated declines in self-harm thoughts and hopelessness and was significantly less likely than the BA group to experience a depressive episode (4.65% versus 22.5%, p = 0.023) or to report hopelessness (MI group of 2% versus 15% for the BA group, p=0.044) by twelve weeks. Conclusions: An Internet-based prevention program in primary care is associated with declines in depressed mood and the likelihood of having clinical depression symptom levels in both groups. Motivational interviewing in combination with an Internet behavior change program may reduce the likelihood of experiencing a depressive episode and hopelessness.

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Further research is needed to better understand and intervene upon pathways that lead to poor outcomes such as delayed milestones among emerging adults with depression. Health care providers should be conscious of the unique vulnerabilities posed by depressive disorders in this age group.

PURPOSE Negative attitudes and beliefs about depression treatment may prevent many young adults from accepting a diagnosis and treatment for depression. We undertook a study to determine the association between depressive symptom severity, beliefs about and attitudes toward treatment, subjective social norms, and past behavior on the intent not to accept a physician's diagnosis of depression. METHODSWe conducted a cross-sectional study of 10,962 persons aged 16 to 29 years who participated and had positive screening results on the Center for Epidemiologic Studies Depression (CES-D) score in an Internet-based public health depression screening program. Participants reported whether they would accept their physician's diagnosis of depression. Based on the theory of reasoned action, we developed a multivariate model of the factors that predict intent not to accept a diagnosis of depression.RESULTS Twenty-six percent of the participants stated their intent not to accept their physician's diagnosis of depression. Disagreeing that medications are effective in treating depression (strongly disagree, odds ratio ( OR ) = 6.5, 95% confi dence interval (CI), 4.6-9.3), that there is a biological cause for depression (strongly disagree, OR = 1.9, 95% CI, 1.3-2.7), and agreeing that you would be embarrassed if your friends knew you had depression were associated with the intent not to accept a diagnosis of depression (strongly agree, OR = 2.3, 95% CI, 1.8-2.9). Beliefs and attitudes, subjective social norms, and past behavior explained most of the variance in this model (84%).CONCLUSIONS Negative beliefs and attitudes, subjective social norms, and lack of past helpful treatment experiences are associated with the intent to not accept the diagnosis of depression and may contribute to low rates of treatment among young adults. INTRODUCTIONT wenty-fi ve percent of young adults will experience a depressive episode by age 24 years, the highest incidence rate of any adult agegroup.1-3 Although depression during this critical period may increase the likelihood of substance abuse, impair work and relationship function, and negatively infl uence an individual' s subsequent development, 1,4-11 fewer than 20% of young adults with depression receive high-quality care. 12Lack of health insurance coverage and affi liation with a primary care physician do not fully explain these low treatment rates. 13,14 Obtaining treatment for depression is a multistage process that includes self-evaluation of need for care, seeking services, and fi nally accepting a diagnosis and treatment for the disorder, which is substantially infl uenced by patient attitudes. 15,16 Patient reluctance to accept diagnosis and treatment for depression has been identifi ed by primary care physicians as a major barrier to implementing 17 and may be associated with poor quality of care and outcomes. [18][19][20][21][22][23][24] Why patients refuse the diagnosis and treatment for depression remains poorly understood, however.The theory of reasoned action, which ha...

We examine school performance among 83 adolescents at-risk for major depression. Negative mood interfered with subjective measures of school performance, including ability to do well in school, homework completion, concentrate in class, interact with peers, and going to class. No significant relationships were found for mood and objective measures of school performance (school attendance, English and math grades). Students with a college-educated parent had stronger performance in objective measures (school attendance and math grades), while males had lower English grades. In qualitative interviews, adolescents reported that negative thinking led to procrastination, which led to poor school performance, which led to more negative thinking. Adolescents with depressive symptoms that do not meet the threshold for referral report struggles in school. Understanding the specific challenges faced by adolescents with even low levels of depressive symptoms can help school nurses, teachers, and parents identify appropriate interventions to help adolescents succeed in school.

Lack of helpful treatment experiences and/or confidence in either of the currently practiced depression treatment models may prevent many young adults from seeking depression treatment.

PURPOSE A risk prediction index, similar to those used for other disorders, such as cardiovascular disease, would facilitate depression prevention by identifying those who would benefi t most from preventative measures in primary care settings. METHODSThe National Longitudinal Study of Adolescent Health enrolled a representative sample of US adolescents and included a baseline survey in 1995 and a 1-year follow-up survey in 1996 (n = 4,791). We used baseline risk factors (social and cognitive vulnerability and mood) to predict onset of a depressive episode at 1-year follow-up (eg, future risk of episode) and used boosted classifi cation and regression trees to develop a prediction index, The Chicago Adolescent Depression Risk Assessment, suitable for a personal computer or hand-held device. True and false positives and negatives were determined based on concordance and discordance, respectively, between the prediction-category-based index and actual classifi cation-category-based 1-year follow-up outcome. We evaluated the performance of the index for the entire sample and with several depressive episode outcomes using the standard Center for Epidemiologic Studies Depression (CES-D) scale cutoffs.RESULTS The optimal prediction model (including depressed mood and social vulnerability) was a 20-item model with an area under the receiver operating characteristics curve of 0.80 (95% CI, 0.714-0.870), a sensitivity of 75%, and a specifi city of 76.5%. For depressive episode, the positive predictive values in the highest risk group (level 4) was from 13.75% for a depressive episode to 63.57% for CES-D score of greater than 16 (mild to moderate depressed mood or above) at follow-up. Conversely, the negative predictive value of being in the lowest 2 levels (0 or 1) was 99.38% for a depressive episode and 89.19% for a CES-D score of greater than 16.CONCLUSIONS Our model predicts a depressive episode and other depressive outcomes at 1-year follow-up. Positive and negative predictive values could enable primary care physicians and families to intervene on adolescents at highest risk.