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Objective To validate the use of electronic health records (EHRs) for the diagnosis of bipolar disorder (BD) and controls. Methods EHR data were obtained from a healthcare system of more than 4.2 million patients spanning more than 20 years. Chart review by experienced clinicians was used to identify text features and coded data consistent or inconsistent with a diagnosis of BD. Natural language processing (NLP) was used to train a diagnostic algorithm with 95% specificity for classifying BD. Filtered coded data were used to derive three additional classification rules for cases and one for controls. The positive predictive value (PPV) of EHR-based BD and subphenotype diagnoses was calculated against direct semi-structured interview diagnoses by trained clinicians blind to EHR diagnosis in a sample of 190 patients. Results The PPV of NLP-defined BD was 0.85. A coded classification based on strict filtering achieved a PPV of 0.79, but BD classifications based on less stringent criteria performed less well. None of the EHR-classified controls was given a diagnosis of BD on direct interview (PPV = 1.0). For most subphenotypes, PPVs exceeded 0.80. The EHR-based classifications were used to accrue 4500 BD cases and 5000 controls for genetic analyses. Conclusions Semi-automated mining of EHRs can be used to ascertain BD cases and controls with high specificity and predictive value compared to a gold-standard diagnostic interview. EHRs provide a powerful resource for high-throughput phenotyping for genetic and clinical research.

As our field seeks to elucidate the biopsychosocial etiologies of mental health disorders, many traditional psychological and social science researchers have added, or plan to add, genetic components to their programs of research. An understanding of the history, methods, and perspectives of the psychiatric genetics community is useful in this pursuit. In this article we provide a brief overview of psychiatric genetic methods and findings. This overview lays the groundwork for a more thorough review of gene-environment interaction (G×E) research and the candidate gene approach to G×E research that remains popular among many psychologists and social scientists. We describe the differences in perspective between psychiatric geneticists and psychological scientists that have contributed to a growing divide between the research cited and conducted by these two related disciplines. Finally, we outline a strategy for the future of research on gene-environment interactions that capitalizes on the relative strengths of each discipline. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Past research on the self-esteem of bullies has produced equivocal results. Recent studies have suggested that the inconsistent findings may be due, in part, to the failure to account for bully/victims: those children who both bully and are victims of bullying. In this longitudinal study, we examined the distinctions among pure bullies, pure victims, bully/victims, and noninvolved children in a sample of 307 middle school students. Analyses of cross-sectional and longitudinal results supported the importance of distinguishing between pure bullies and bully/victims. In addition, results revealed some interesting sex differences: girls in the pure bully and bully/victim groups reported significant increases in self-esteem over time, with girls in the pure bully group reporting the greatest increase, whereas boys in these groups reported no significant changes in self-esteem over time.