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The Patient Reported Outcomes Measurement Information System (PROMIS) was devised to facilitate assessment of patient self-reported health status, taking advantage of Item Response Theory. We aimed to assess measurement properties of the PROMIS Depression item bank and an 8-item static short form in a Spanish clinical sample. A three-month follow-up study of patients with active mood/anxiety symptoms (n = 218) was carried out. We assessed model unidimensionality (Confirmatory Item Factor Analysis), reliability (internal consistency and Item Information Curves), and validity (convergent-discriminant with correlations; known-groups with comparison of means and effect sizes; and criterion validity with Receiver operating Characteristics (ROC) analysis). We also assessed 3-month responsiveness to change (Cohen's effect sizes (d) in stable and recovered patients). The unidimensional model showed adequate fit (CFI = 0.97, RMSEA = 0.08). Information Curves had reliabilities over 0.90 throughout most of the score continuum. As expected, we observed high correlations with external self-reported depression, and moderate with self-reported anxiety and clinical measures. The item bank showed an increasing severity gradient from no disorder (mean = 48, SE = 0.6) to depression with comorbid anxiety (mean = 55.8, SE = 0.4). PROMIS detected depression disorder with great accuracy according to the area under the curve (AUC = 0.89). Both formats, item bank and short form, were highly responsive to change in recovered patients (d > 0.7) and had small changes in stable patients (d < 0.2). The good metric properties of the Spanish PROMIS Depression measures provide further evidence of their adequacy for monitoring depression levels of patients in clinical settings. This double check of quality (within countries and populations) supports the ability of PROMIS measures for guaranteeing fair comparisons across languages and countries in specific clinical populations.

Evidence suggests that general practitioners (GPs) fail to diagnose up to half of common mental disorder cases. Yet no previous research has systematically summarized the evidence in the case of anxiety disorders. The aim of this review was to systematically assess and meta-analyze the diagnostic accuracy of GPs' assisted (i.e., using severity scales/diagnostic instruments) and unassisted (without such tools) diagnoses of anxiety disorders.Systematic review (PROSPERO registry CRD42013006736) was conducted. Embase, Ovid Journals--Ovid SP Medline, Pubmed, PsycINFO, Scopus, Web of Science, and Science Direct were searched from January 1980 through June 2014. Seven investigators, working in pairs, evaluated studies for eligibility. The quality of included studies was assessed with the Quality Assessment of Diagnostic Accuracy Studies tool version 2 (QUADAS-2). The main outcome measures were sensitivity and specificity of clinical diagnoses of any anxiety disorder. We pooled sensitivity and specificity levels from included studies using bivariate meta-analyses.Twenty-four studies were included in the meta-analysis with a total sample of 34,902 patients. Pooled sensitivity and specificity were estimated at 44.5% (95% CI 33.7-55.9%) and 90.8% (95% CI 87-93.5%). GPs' sensitivity was higher when diagnoses were assisted (63.6%, 95% CI 50.3-75.1%) than when unassisted (30.5%, 95% CI 20.7-42.5%) to the expense of some specificity loss (87.9%, 95% CI 81.3-92.4% vs. 91.4%, 95% CI 86.6-94.6%, respectively). Identification rates remained constant over time (P-value = .998).The use of diagnostic tools might improve detection of anxiety disorders in "primary care."