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IntroductionIn humanitarian settings, social-emotional learning (SEL) programs for children are often delivered using a field-feasible approach where the programs are more easily deployable and adaptable in the field, require minimal training, and depend less on the strict sequence and structure of the program components to elicit the intended treatment effect. However, evidence is lacking on what aspects of this implementation approach enable the SEL programming to be more beneficial to children’s SEL development.MethodIn this study, we propose and evaluate measures for three dimensions of dosage (quantity, duration, and temporal pattern) of two sets of brief and skill-targeted SEL activities (Mindfulness and Brain Games) implemented in 20 primary schools in two low-income chiefdoms of Sierra Leone.ResultsWe find preliminary evidence of predictive validity that these dosage measures could predict children’s attendance and classroom adaptive behavior.DiscussionThis study is the first to develop procedures to measure the dimensions of dosage of brief SEL activities in humanitarian settings. Our findings illuminate the need for future research on optimizing the dosage and implementation design of SEL programming using brief SEL activities.

Some patients with postoperative atrial fibrillation (POAF) after non-cardiac surgery need treatment, and a predictive model for these patients is clinically useful. Here, we developed a predictive model for POAF in non-cardiac surgery based on machine learning techniques. In a total of 201,864 patients who underwent non-cardiac surgery between January 2011 and June 2019 at our institution, 5,725 (2.8%) were treated for POAF. We used machine learning with an extreme gradient boosting algorithm to evaluate the effects of variables on POAF. Using the top five variables from this algorithm, we generated a predictive model for POAF and conducted an external validation. The top five variables selected for the POAF model were age, lung operation, operation duration, history of coronary artery disease, and hypertension. The optimal threshold of probability in this model was estimated to be 0.1, and the area under the receiver operating characteristic (AUROC) curve was 0.80 with a 95% confidence interval of 0.78–0.81. Accuracy of the model using the estimated threshold was 0.95, with sensitivity and specificity values of 0.28 and 0.97, respectively. In an external validation, the AUROC was 0.80 (0.78–0.81). The working predictive model for POAF requiring treatment in non-cardiac surgery based on machine learning techniques is provided online (https://sjshin.shinyapps.io/afib_predictor_0913/). The model needs further verification among other populations.

Background: The effects of serum folate levels on suicidal behavior, strongly associated with depression, have not been investigated. Therefore, this study investigated the associations between serum folate levels and suicidal behavior in patients with depressive disorders.Methods: Serum folate levels were measured at baseline in 1,094 patients with depressive disorder, 884 of whom were followed during a 12-month period of stepwise pharmacotherapy. Suicidal behaviors evaluated at baseline were (i) previous suicide attempt and (ii) baseline suicidal severity; behaviors evaluated at follow-up were (iii) increased suicidal severity and iv) fatal/non-fatal suicide attempt. Associations of serum folate levels with four types of suicidal behaviors were analyzed using logistic regression models after adjustment for relevant covariates; they were also examined using area under receiver operating characteristic (AUROC) curve analyses.Results: Reduced serum folate levels (