Background Depression is common and frequently undiagnosed among college students. Social networking sites are popular among college students and can include displayed depression references. The purpose of this study was to evaluate college students' Facebook disclosures that met DSM criteria for a depression symptom or a major depressive episode (MDE). Methods We selected public Facebook profiles from sophomore and junior undergraduates and evaluated personally written text: “status updates.” We applied DSM criteria to one year of status updates from each profile to determine prevalence of displayed depression symptoms and MDE criteria. Negative binomial regression analysis was used to model the association between depression disclosures and demographics or Facebook use characteristics. Results A total of 200 profiles were evaluated, profile owners were 43.5% female with a mean age of 20 years. Overall, 25% of profiles displayed depressive symptoms and 2.5% met criteria for MDE. Profile owners were more likely to reference depression if they averaged at least one online response from their friends to a status update disclosing depressive symptoms (exp(B)=2.1, p<0.001), or if they used Facebook more frequently (p<0.001). Conclusion College students commonly display symptoms consistent with depression on Facebook. Our findings suggest that those who receive online reinforcement from their friends are more likely to discuss their depressive symptoms publicly on Facebook. Given the frequency of depression symptom displays on public profiles, SNSs could be an innovative avenue for combating stigma surrounding mental health conditions, or for identifying students at risk for depression.

Internet addiction is a growing concern; however, both a clear understanding of the mechanisms driving problematic behaviors and a gold standard instrument for assessing symptoms are lacking. The purpose of this study was to perform a psychometric analysis of the most widely used screening instrument, the Young Internet Addiction Test (IAT), using a sample of US college students. 215 (70% response rate) undergraduate college students were recruited from two US universities to complete an online version of the IAT. Using exploratory factor analysis, two factors were extracted, “dependent use” and “excessive use” which together explained 91% of the total variance. Participants who scored into the problematic user category of the IAT scored items on the dependent use scale an average of 0.8±1.5 points higher and items on the excessive use scale an average of 1.4±1.5 points higher than participants who scored in the average user category. Results suggest that Internet addiction symptoms may cluster into two separate components, dependent and excessive use. Further, the IAT appears to be a valid instrument for assessing Internet addiction in US college students.

The objective of this study was to determine associations between displayed depression symptoms on Facebook and self-reported depression symptoms using a clinical screen. Public Facebook profiles of undergraduates from two universities were examined for displayed depression references. Profiles were categorized as depression symptom displayers or non-displayers. Participants completed an online PHQ-9 depression scale. Analyses examined associations between PHQ-9 score and depression symptom displayers versus non-displayers. The mean PHQ-9 score for non-displayers was 4.7 (SD= 4.0), the mean PHQ-9 score for depression symptom displayers was 6.4 (SD=5.1; p=0.018). A trend approaching significance was noted that participants who scored into a depression category by their PHQ-9 score were more likely to display depression symptom references. Displayed references to depression symptoms were associated with self-reported depression symptoms.

SUMMARYPurpose: To characterize patterns and determinants of normal and abnormal cognitive development in children with new onset epilepsy compared to healthy controls. Methods: Longitudinal (2-year) cognitive growth was examined in 100 children, age 8-18 years, including healthy controls (n ¼ 48) and children with new onset epilepsy (n ¼ 52). Cognitive maturation was examined as a function of the presence/ absence of two neurobehavioral comorbitiies (attention deficit hyperactivity disorder and/or academic problems) identified at the time of epilepsy diagnosis. Groups were compared across a comprehensive neuropsychological battery assessing intelligence, academic achievement, language, memory, executive function, and psychomotor speed. Results: Children with new onset epilepsy without neurobehavioral comorbidities were comparable to healthy controls at baseline, rate of cognitive development, and follow-up assessment across all neuropsychological domains. In contrast, the presence of neurobehavioral comorbidities was associated with significantly worse baseline and prospective cognitive trajectories across all cognitive domains, especially executive functions. Conclusion: The presence of neurobehavioral comorbidities at the time of epilepsy onset is a major marker of abnormal cognitive development both prior to and after the onset of epilepsy.

The topographical configuration of the spontaneous brain electric fields is considered to contain relevant information about the pattern of the generating cortical electrochemical activation and the associated cognitive processes. Space oriented segmentation allows to break down the stream of the spontaneous EEG into brain electric microstates with stable configuration of the fields. It has been shown that the mean duration of the microstates was consistent with the duration of elementary steps of cognitive processes, and that different topographies of the microstates are associated with different cognitive modalities. Space-oriented segmentation was applied to the resting EEG of 22 depressive patients and of 22 controls. The topographical variance was larger, and the most prominent brain electrical microstates of the EEG epochs were significantly shorter in the depressive group than in controls. No differences were found for the shortest microstates. This result cannot be explained by group differences in the frequency domain of the EEG. No topographical differences were found between the microstates of depressives and those of controls. Based on previous results in healthy volunteers during spontaneous cognition and in schizophrenic patients, the findings indicate that formal aspects rather than the modalities of the stream of cognition are altered in depression. Automatic and schematic processing, and attentional deficits as described in depressive patients might account for the finding of less sustained brain electrical microstates.