Examples of predicted probabilities of anxiety at baseline.

<p>(*)The possible range of the SF-12 is 0–100. High scores indicate good health/well-being. Mean (Standard Deviation) Short Form 12 (SF-12) mental and physical subscale scores for Spain are 47.1 (12.4) and 43.8 (11.4), respectively <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0106370#pone.0106370-Belln3" target="_blank">[39]</a>.</p><p>Examples of predicted probabilities of anxiety at baseline.</p

Predicted probability cut-points to predict anxiety syndromes at 12 months and their associated validity.

<p>LR+ Likelihood ratio of the positive test; LR- Likelihood ratio of the negative test.</p><p>*Cutpoint where Youden's J statistic (J  =  Sensitivity + Specificity -1) was greater.</p><p>Predicted probability cut-points to predict anxiety syndromes at 12 months and their associated validity.</p

Incidence of anxiety by age and sex.

<p>Incidence of anxiety by age and sex.</p

Incidence of anxiety by age and dissatisfaction at work.

<p>Incidence of anxiety by age and dissatisfaction at work.</p

Area under the ROC curve for the models with/without interactions.

<p>Footnote toFigure 5: <i>predictA: model without interactions predictA3: model with 3 interactions</i>.</p

Comparison of the base model with the models including each of the interactions tested.

#<p>The model sex*province did not converge.</p><p>Comparison of the base model with the models including each of the interactions tested.</p

Model to predict drop-out.

<p>(*) Multi-level logistic regression with health center as a random component. We selected variables included in the final model from the 39 measured in this study using a threshold for inclusion of p<0.20 in bivariate regression. From the model thus obtained, those variables with p>0.05 were extracted step by step to obtain a more parsimonious model.</p><p>Model to predict drop-out.</p

Demographic characteristics of participants without anxiety at baseline (population at risk).

<p>Demographic characteristics of participants without anxiety at baseline (population at risk).</p

Calibration plots (mean predicted probability versus observed probability of anxiety within deciles of predicted risk) of the predictA-Spain risk algorithm.

<p>Calibration plots (mean predicted probability versus observed probability of anxiety within deciles of predicted risk) of the predictA-Spain risk algorithm.</p

Models^a for predicting the onset of anxiety at 12 months (N = 2.103).

a<p>Model derived weighting for the inverse probability of remaining in the follow-up to 12 months.</p>b<p>Discriminative validity: C-Index: 0.7917 (C.I.95% = 0.7653–0.8181) and Effect size (Hedges' g): 1.1058 (C.I.95% = 0.9854–1.2261). Overfitting estimate: Copas' shrinkage factor: 0.9162.</p>c<p>Discriminative validity: C-Index: 0.80 (C.I.95% = 0.78–0.83) and Effect size (Hedges' g): 1.17 (C.I.95% = 1.04–1.29). Overfitting estimate: Copas' shrinkage factor: 0.9793.</p>d<p>Coefficient after Copas shrinkage. S.E.: Standard error.</p><p>Models^{<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0106370#nt102" target="_blank">a</a>} for predicting the onset of anxiety at 12 months (N = 2.103).</p