2021
Porras-Segovia, Alejandro; Cobo, Aurora; Díaz-Oliván, Isaac; Artés-Rodríguez, Antonio; Berrouiguet, Sofian; Lopez-Castroman, Jorge; Courtet, Philippe; Barrigón, Maria Luisa; Oquendo, María A; Baca-García, Enrique
Disturbed sleep as a clinical marker of wish to die: A smartphone monitoring study over three months of observation Artículo de revista
En: Journal of Affective Disorders, 2021, ISSN: 0165-0327.
Resumen | Enlaces | BibTeX | Etiquetas: Mhealth, Sleep, Smartphone, Suicide, Suicide attempt, Suicide ideation
@article{PORRASSEGOVIA2021,
title = {Disturbed sleep as a clinical marker of wish to die: A smartphone monitoring study over three months of observation},
author = {Alejandro Porras-Segovia and Aurora Cobo and Isaac D\'{i}az-Oliv\'{a}n and Antonio Art\'{e}s-Rodr\'{i}guez and Sofian Berrouiguet and Jorge Lopez-Castroman and Philippe Courtet and Maria Luisa Barrig\'{o}n and Mar\'{i}a A Oquendo and Enrique Baca-Garc\'{i}a},
url = {https://www.sciencedirect.com/science/article/pii/S0165032721001932},
doi = {https://doi.org/10.1016/j.jad.2021.02.059},
issn = {0165-0327},
year = {2021},
date = {2021-01-01},
journal = {Journal of Affective Disorders},
abstract = {Background
: Smartphone monitoring could contribute to the elucidation of the correlates of suicidal thoughts and behaviors (STB). In this study, we employ smartphone monitoring and machine learning techniques to explore the association of wish to die (passive suicidal ideation) with disturbed sleep, altered appetite and negative feelings.
Methods
: This is a prospective cohort study carried out among adult psychiatric outpatients with a history of STB. A daily questionnaire was administered through the MEmind smartphone application. Participants were followed-up for a median of 89.8 days, resulting in 9,878 person-days. Data analysis employed a machine learning technique called Indian Buffet Process.
Results
: 165 patients were recruited, 139 had the MEmind mobile application installed on their smartphone, and 110 answered questions regularly enough to be included in the final analysis. We found that the combination of wish to die and sleep problems was one of the most relevant latent features found across the sample, showing that these variables tend to be present during the same time frame (96 hours).
Conclusions
: Disturbed sleep emerges as a potential clinical marker for passive suicidal ideation. Our findings stress the importance of evaluating sleep as part of the screening for suicidal behavior. Compared to previous smartphone monitoring studies on suicidal behavior, this study includes a long follow-up period and a large sample.},
keywords = {Mhealth, Sleep, Smartphone, Suicide, Suicide attempt, Suicide ideation},
pubstate = {published},
tppubtype = {article}
}
Background
: Smartphone monitoring could contribute to the elucidation of the correlates of suicidal thoughts and behaviors (STB). In this study, we employ smartphone monitoring and machine learning techniques to explore the association of wish to die (passive suicidal ideation) with disturbed sleep, altered appetite and negative feelings.
Methods
: This is a prospective cohort study carried out among adult psychiatric outpatients with a history of STB. A daily questionnaire was administered through the MEmind smartphone application. Participants were followed-up for a median of 89.8 days, resulting in 9,878 person-days. Data analysis employed a machine learning technique called Indian Buffet Process.
Results
: 165 patients were recruited, 139 had the MEmind mobile application installed on their smartphone, and 110 answered questions regularly enough to be included in the final analysis. We found that the combination of wish to die and sleep problems was one of the most relevant latent features found across the sample, showing that these variables tend to be present during the same time frame (96 hours).
Conclusions
: Disturbed sleep emerges as a potential clinical marker for passive suicidal ideation. Our findings stress the importance of evaluating sleep as part of the screening for suicidal behavior. Compared to previous smartphone monitoring studies on suicidal behavior, this study includes a long follow-up period and a large sample.
: Smartphone monitoring could contribute to the elucidation of the correlates of suicidal thoughts and behaviors (STB). In this study, we employ smartphone monitoring and machine learning techniques to explore the association of wish to die (passive suicidal ideation) with disturbed sleep, altered appetite and negative feelings.
Methods
: This is a prospective cohort study carried out among adult psychiatric outpatients with a history of STB. A daily questionnaire was administered through the MEmind smartphone application. Participants were followed-up for a median of 89.8 days, resulting in 9,878 person-days. Data analysis employed a machine learning technique called Indian Buffet Process.
Results
: 165 patients were recruited, 139 had the MEmind mobile application installed on their smartphone, and 110 answered questions regularly enough to be included in the final analysis. We found that the combination of wish to die and sleep problems was one of the most relevant latent features found across the sample, showing that these variables tend to be present during the same time frame (96 hours).
Conclusions
: Disturbed sleep emerges as a potential clinical marker for passive suicidal ideation. Our findings stress the importance of evaluating sleep as part of the screening for suicidal behavior. Compared to previous smartphone monitoring studies on suicidal behavior, this study includes a long follow-up period and a large sample.