Multilevel logistic regression models with each negative emotions as a predictor.

Multilevel logistic regression models with each negative emotions as a predictor.

<p>Multilevel logistic regression models with each negative emotions as a predictor.</p>

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Détails bibliographiques
Auteur principal:	Chan-Young Ahn (22683343) (author)
Autres auteurs:	Jin-Ha Kim (10300456) (author), Sojung Kim (46675) (author), Jae-Won Kim (172504) (author), Jung-Jo Na (22683346) (author), Dong Gi Seo (11119119) (author), Jong-Sun Lee (4252801) (author)
Publié:	2025
Sujets:	Medicine Sociology Mental Health Biological Sciences not elsewhere classified xlink "> non providing practical insights multilevel logistic regression low ecological validity justifying multilevel modeling experimental methods rely ecological momentary assessment address social connections 26 indicated substantial identify emotional predictors adolescents &# 8217 repeatedly sample nssi significant individual differences combining machine learning anger towards others experiencing nssi thoughts 40 ), anxiety findings highlight loneliness significant predictors machine learning nssi thoughts individual variance adolescents engaging 18 ), therefore vulnerable study aimed smartphone application related feelings past year participants reported often linked negative emotions integrated application influential predictor icc value feature importance developing tailored daily life autobiographical recall 15 years
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Résumé:	<p>Multilevel logistic regression models with each negative emotions as a predictor.</p>

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