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• W3096853025 endingPage "e22634" @default.
• W3096853025 startingPage "e22634" @default.
• W3096853025 abstract "Background In many countries, depressed individuals often first visit primary care settings for consultation, but a considerable number of clinically depressed patients remain unidentified. Introducing additional screening tools may facilitate the diagnostic process. Objective This study aimed to examine whether experience sampling method (ESM)-based measures of depressive affect and behaviors can discriminate depressed from nondepressed individuals. In addition, the added value of actigraphy-based measures was examined. Methods We used data from 2 samples to develop and validate prediction models. The development data set included 14 days of ESM and continuous actigraphy of currently depressed (n=43) and nondepressed individuals (n=82). The validation data set included 30 days of ESM and continuous actigraphy of currently depressed (n=27) and nondepressed individuals (n=27). Backward stepwise logistic regression analysis was applied to build the prediction models. Performance of the models was assessed with goodness-of-fit indices, calibration curves, and discriminative ability (area under the receiver operating characteristic curve [AUC]). Results In the development data set, the discriminative ability was good for the actigraphy model (AUC=0.790) and excellent for both the ESM (AUC=0.991) and the combined-domains model (AUC=0.993). In the validation data set, the discriminative ability was reasonable for the actigraphy model (AUC=0.648) and excellent for both the ESM (AUC=0.891) and the combined-domains model (AUC=0.892). Conclusions ESM is a good diagnostic predictor and is easy to calculate, and it therefore holds promise for implementation in clinical practice. Actigraphy shows no added value to ESM as a diagnostic predictor but might still be useful when ESM use is restricted." @default.
• W3096853025 created "2020-11-09" @default.
• W3096853025 creator A5003290221 @default.
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• W3096853025 date "2020-12-01" @default.
• W3096853025 modified "2023-10-01" @default.
• W3096853025 title "Screening for Depression in Daily Life: Development and External Validation of a Prediction Model Based on Actigraphy and Experience Sampling Method" @default.
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• W3096853025 doi "https://doi.org/10.2196/22634" @default.
• W3096853025 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7894744" @default.
• W3096853025 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33258783" @default.
• W3096853025 hasPublicationYear "2020" @default.
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