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A structured search of MEDLINE (PubMed) (1950 through August 2013) and Embase (1980 through August 2013) databases was conducted to assess the accuracy of a predictive model for predicting high-quality evidence-based interventions published in the journal Journal of the American Medical Association. A predictive, numeric model was developed and examined for accuracy using data published between January 2000 and August 2013. Of 124 psychosocial counseling and psychotherapy interventions, the 2-year trial-based predictive model, using only the 11 predictors associated with ratings of high quality, demonstrated an area under the curve of 0.794, a sensitivity of 0.873, a specificity of 0.611, and a positive likelihood ratio of 3.42 (95% confidence interval, 2.35-4.99). The predictive model performed as well as, and in some cases was better, than previous models developed by 2 of the current authors.
JAMA Maintains its commitment to the highest standards of objectivity and integrity. We welcome comments and suggestions about [Journal of the American Medical Association] section information. To construct a model for predicting high-quality evidence-based interventions published in Journal of the American Medical Association using data published between January 2000 and August 2013, we developed and validated a multiclass prediction algorithm to classify a set of 124 psychosocial counseling and psychotherapy interventions published in the Journal of the American Medical Association. This study was performed to promote improved assessment of the quality of the medical literature and promote ongoing educational efforts in the form of commentary, review, updates, and debate. d2c66b5586