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Mapping the timescale of suicidal thinking

This study aims to identify the timescale of suicidal thinking, leveraging real-time monitoring data and a number of different analytic approaches. Participants were 105 adults with past week suicidal thoughts who completed a 42-d real-time monitoring study (total number of observations = 20,255). P...

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Autores principales: Coppersmith, Daniel D.L., Ryan, Oisín, Fortgang, Rebecca G., Millner, Alexander J., Kleiman, Evan M., Nock, Matthew K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10151607/
https://www.ncbi.nlm.nih.gov/pubmed/37071683
http://dx.doi.org/10.1073/pnas.2215434120
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author Coppersmith, Daniel D.L.
Ryan, Oisín
Fortgang, Rebecca G.
Millner, Alexander J.
Kleiman, Evan M.
Nock, Matthew K.
author_facet Coppersmith, Daniel D.L.
Ryan, Oisín
Fortgang, Rebecca G.
Millner, Alexander J.
Kleiman, Evan M.
Nock, Matthew K.
author_sort Coppersmith, Daniel D.L.
collection PubMed
description This study aims to identify the timescale of suicidal thinking, leveraging real-time monitoring data and a number of different analytic approaches. Participants were 105 adults with past week suicidal thoughts who completed a 42-d real-time monitoring study (total number of observations = 20,255). Participants completed two forms of real-time assessments: traditional real-time assessments (spaced hours apart each day) and high-frequency assessments (spaced 10 min apart over 1 h). We found that suicidal thinking changes rapidly. Both descriptive statistics and Markov-switching models indicated that elevated states of suicidal thinking lasted on average 1 to 3 h. Individuals exhibited heterogeneity in how often and for how long they reported elevated suicidal thinking, and our analyses suggest that different aspects of suicidal thinking operated on different timescales. Continuous-time autoregressive models suggest that current suicidal intent is predictive of future intent levels for 2 to 3 h, while current suicidal desire is predictive of future suicidal desire levels for 20 h. Multiple models found that elevated suicidal intent has on average shorter duration than elevated suicidal desire. Finally, inferences about the within-person dynamics of suicidal thinking on the basis of statistical modeling were shown to depend on the frequency at which data was sampled. For example, traditional real-time assessments estimated the duration of severe suicidal states of suicidal desire as 9.5 h, whereas the high-frequency assessments shifted the estimated duration to 1.4 h.
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spelling pubmed-101516072023-10-18 Mapping the timescale of suicidal thinking Coppersmith, Daniel D.L. Ryan, Oisín Fortgang, Rebecca G. Millner, Alexander J. Kleiman, Evan M. Nock, Matthew K. Proc Natl Acad Sci U S A Social Sciences This study aims to identify the timescale of suicidal thinking, leveraging real-time monitoring data and a number of different analytic approaches. Participants were 105 adults with past week suicidal thoughts who completed a 42-d real-time monitoring study (total number of observations = 20,255). Participants completed two forms of real-time assessments: traditional real-time assessments (spaced hours apart each day) and high-frequency assessments (spaced 10 min apart over 1 h). We found that suicidal thinking changes rapidly. Both descriptive statistics and Markov-switching models indicated that elevated states of suicidal thinking lasted on average 1 to 3 h. Individuals exhibited heterogeneity in how often and for how long they reported elevated suicidal thinking, and our analyses suggest that different aspects of suicidal thinking operated on different timescales. Continuous-time autoregressive models suggest that current suicidal intent is predictive of future intent levels for 2 to 3 h, while current suicidal desire is predictive of future suicidal desire levels for 20 h. Multiple models found that elevated suicidal intent has on average shorter duration than elevated suicidal desire. Finally, inferences about the within-person dynamics of suicidal thinking on the basis of statistical modeling were shown to depend on the frequency at which data was sampled. For example, traditional real-time assessments estimated the duration of severe suicidal states of suicidal desire as 9.5 h, whereas the high-frequency assessments shifted the estimated duration to 1.4 h. National Academy of Sciences 2023-04-18 2023-04-25 /pmc/articles/PMC10151607/ /pubmed/37071683 http://dx.doi.org/10.1073/pnas.2215434120 Text en Copyright © 2023 the Author(s). Published by PNAS. https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND) (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Social Sciences
Coppersmith, Daniel D.L.
Ryan, Oisín
Fortgang, Rebecca G.
Millner, Alexander J.
Kleiman, Evan M.
Nock, Matthew K.
Mapping the timescale of suicidal thinking
title Mapping the timescale of suicidal thinking
title_full Mapping the timescale of suicidal thinking
title_fullStr Mapping the timescale of suicidal thinking
title_full_unstemmed Mapping the timescale of suicidal thinking
title_short Mapping the timescale of suicidal thinking
title_sort mapping the timescale of suicidal thinking
topic Social Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10151607/
https://www.ncbi.nlm.nih.gov/pubmed/37071683
http://dx.doi.org/10.1073/pnas.2215434120
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