Detecting adolescent depression through passive monitoring of linguistic markers in smartphone communication / Esha TRIVEDI ; Lilian Y. LI ; Fiona HELGREN ; Emily ZHANG ; Aishwarya SRITHARAN ; Rachel A. CHERNER ; David PAGLIACCIO ; Katherine DURHAM ; Mia KYLER ; Trinity C. TSE ; Savannah N. BUCHANAN ; Nicholas B. ALLEN ; Stewart A. SHANKMAN ; Randy P. AUERBACH in Journal of Child Psychology and Psychiatry, 65-7 (July 2024)  

Public ISBD [article]  inJournal of Child Psychology and Psychiatry > 65-7 (July 2024) . - p.932-941 Titre : Detecting adolescent depression through passive monitoring of linguistic markers in smartphone communication Type de document : texte imprimé Auteurs : Esha TRIVEDI, Auteur ; Lilian Y. LI, Auteur ; Fiona HELGREN, Auteur ; Emily ZHANG, Auteur ; Aishwarya SRITHARAN, Auteur ; Rachel A. CHERNER, Auteur ; David PAGLIACCIO, Auteur ; Katherine DURHAM, Auteur ; Mia KYLER, Auteur ; Trinity C. TSE, Auteur ; Savannah N. BUCHANAN, Auteur ; Nicholas B. ALLEN, Auteur ; Stewart A. SHANKMAN, Auteur ; Randy P. AUERBACH, Auteur Article en page(s) : p.932-941 Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : Background Cross sectional studies have identified linguistic correlates of major depressive disorder (MDD) in smartphone communication. However, it is unclear whether monitoring these linguistic characteristics can detect when an individual is experiencing MDD, which would facilitate timely intervention. Methods Approximately 1.2 million messages typed into smartphone social communication apps (e.g. texting, social media) were passively collected from 90 adolescents with a range of depression severity over a 12-month period. Sentiment (i.e. positive vs. negative valence of text), proportions of first-person singular pronouns (e.g. 'I'), and proportions of absolutist words (e.g. 'all') were computed for each message and converted to weekly aggregates temporally aligned with weekly MDD statuses obtained from retrospective interviews. Idiographic, multilevel logistic regression models tested whether within-person deviations in these linguistic features were associated with the probability of concurrently meeting threshold for MDD. Results Using more first-person singular pronouns in smartphone communication relative to one's own average was associated with higher odds of meeting threshold for MDD in the concurrent week (OR = 1.29; p = .007). Sentiment (OR = 1.07; p = .54) and use of absolutist words (OR = 0.99; p = .90) were not related to weekly MDD. Conclusions Passively monitoring use of first-person singular pronouns in adolescents' smartphone communication may help detect MDD, providing novel opportunities for early intervention. En ligne : https://doi.org/10.1111/jcpp.13931 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=532 [article] Detecting adolescent depression through passive monitoring of linguistic markers in smartphone communication [texte imprimé] / Esha TRIVEDI, Auteur ; Lilian Y. LI, Auteur ; Fiona HELGREN, Auteur ; Emily ZHANG, Auteur ; Aishwarya SRITHARAN, Auteur ; Rachel A. CHERNER, Auteur ; David PAGLIACCIO, Auteur ; Katherine DURHAM, Auteur ; Mia KYLER, Auteur ; Trinity C. TSE, Auteur ; Savannah N. BUCHANAN, Auteur ; Nicholas B. ALLEN, Auteur ; Stewart A. SHANKMAN, Auteur ; Randy P. AUERBACH, Auteur . - p.932-941. Langues : Anglais (eng) in Journal of Child Psychology and Psychiatry > 65-7 (July 2024) . - p.932-941 Index. décimale : PER Périodiques Résumé : Background Cross sectional studies have identified linguistic correlates of major depressive disorder (MDD) in smartphone communication. However, it is unclear whether monitoring these linguistic characteristics can detect when an individual is experiencing MDD, which would facilitate timely intervention. Methods Approximately 1.2 million messages typed into smartphone social communication apps (e.g. texting, social media) were passively collected from 90 adolescents with a range of depression severity over a 12-month period. Sentiment (i.e. positive vs. negative valence of text), proportions of first-person singular pronouns (e.g. 'I'), and proportions of absolutist words (e.g. 'all') were computed for each message and converted to weekly aggregates temporally aligned with weekly MDD statuses obtained from retrospective interviews. Idiographic, multilevel logistic regression models tested whether within-person deviations in these linguistic features were associated with the probability of concurrently meeting threshold for MDD. Results Using more first-person singular pronouns in smartphone communication relative to one's own average was associated with higher odds of meeting threshold for MDD in the concurrent week (OR = 1.29; p = .007). Sentiment (OR = 1.07; p = .54) and use of absolutist words (OR = 0.99; p = .90) were not related to weekly MDD. Conclusions Passively monitoring use of first-person singular pronouns in adolescents' smartphone communication may help detect MDD, providing novel opportunities for early intervention. En ligne : https://doi.org/10.1111/jcpp.13931 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=532

Smartphone language and resting-state EEG indicators of self-focused attention prospectively predict major depressive disorder risk in adolescents / Lilian Y. LI in Journal of Child Psychology and Psychiatry, 67-6 (June 2026)  

Public ISBD [article]  inJournal of Child Psychology and Psychiatry > 67-6 (June 2026) . - p.941-950 Titre : Smartphone language and resting-state EEG indicators of self-focused attention prospectively predict major depressive disorder risk in adolescents Type de document : texte imprimé Auteurs : Lilian Y. LI, Auteur ; Nayoung KIM, Auteur ; Esha TRIVEDI, Auteur ; Sarah E. SARKAS, Auteur ; Madeline M. MCGREGOR, Auteur ; Aishwarya SRITHARAN, Auteur ; Katherine DURHAM, Auteur ; Ivan ALEKSEICHUK, Auteur ; Allison M. LETKIEWICZ, Auteur ; Vijay A. MITTAL, Auteur ; David PAGLIACCIO, Auteur ; Nicholas B. ALLEN, Auteur ; Randy P. AUERBACH, Auteur ; Stewart A. SHANKMAN, Auteur Article en page(s) : p.941-950 Langues : Anglais (eng) Mots-clés : Depression  adolescence  self-focused attention  digital phenotyping  EEG alpha oscillations Index. décimale : PER Périodiques Résumé : Background Central to major depressive disorder (MDD) onset and maintenance is maladaptive self-focused attention, which can be reliably indexed by greater: (a) usage of first-person singular pronouns (e.g., I) in natural language and (b) alpha oscillations in resting-state EEG. Integrating these largely parallel bodies of research, the present study sought to explicate the associations between, and prospective predictive utility of, linguistic and neural indicators of self-focused attention in adolescents with remitted MDD over 12?months. Methods At baseline, 126 adolescents (ages 13?18) with (n?=?66) and without (n?=?60) remitted MDD completed resting-state EEG. Retrospective interviews determined the occurrence of major depressive episodes (MDEs) during the follow-up period. A total of ~2.3?million messages were passively acquired from adolescents' smartphones, on which the proportion of first-person singular pronouns was derived. Results During the 12?months, 29 (23.0%) participants developed an MDE (28 remitted MDD, 1 control). Cox regression showed that while greater usage of first-person singular pronouns prior to MDE increased the risk for MDE (hazard ratio [HR]?=?2.02, p? En ligne : https://doi.org/10.1111/jcpp.70096 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=587 [article] Smartphone language and resting-state EEG indicators of self-focused attention prospectively predict major depressive disorder risk in adolescents [texte imprimé] / Lilian Y. LI, Auteur ; Nayoung KIM, Auteur ; Esha TRIVEDI, Auteur ; Sarah E. SARKAS, Auteur ; Madeline M. MCGREGOR, Auteur ; Aishwarya SRITHARAN, Auteur ; Katherine DURHAM, Auteur ; Ivan ALEKSEICHUK, Auteur ; Allison M. LETKIEWICZ, Auteur ; Vijay A. MITTAL, Auteur ; David PAGLIACCIO, Auteur ; Nicholas B. ALLEN, Auteur ; Randy P. AUERBACH, Auteur ; Stewart A. SHANKMAN, Auteur . - p.941-950. Langues : Anglais (eng) in Journal of Child Psychology and Psychiatry > 67-6 (June 2026) . - p.941-950 Mots-clés : Depression  adolescence  self-focused attention  digital phenotyping  EEG alpha oscillations Index. décimale : PER Périodiques Résumé : Background Central to major depressive disorder (MDD) onset and maintenance is maladaptive self-focused attention, which can be reliably indexed by greater: (a) usage of first-person singular pronouns (e.g., I) in natural language and (b) alpha oscillations in resting-state EEG. Integrating these largely parallel bodies of research, the present study sought to explicate the associations between, and prospective predictive utility of, linguistic and neural indicators of self-focused attention in adolescents with remitted MDD over 12?months. Methods At baseline, 126 adolescents (ages 13?18) with (n?=?66) and without (n?=?60) remitted MDD completed resting-state EEG. Retrospective interviews determined the occurrence of major depressive episodes (MDEs) during the follow-up period. A total of ~2.3?million messages were passively acquired from adolescents' smartphones, on which the proportion of first-person singular pronouns was derived. Results During the 12?months, 29 (23.0%) participants developed an MDE (28 remitted MDD, 1 control). Cox regression showed that while greater usage of first-person singular pronouns prior to MDE increased the risk for MDE (hazard ratio [HR]?=?2.02, p? En ligne : https://doi.org/10.1111/jcpp.70096 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=587

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