Dynamic time warping network analysis of posttraumatic stress symptoms in Japanese first responders.
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| Title: | Dynamic time warping network analysis of posttraumatic stress symptoms in Japanese first responders. |
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| Alternate Title: | Análisis de redes dinámicas de distorsión temporal de síntomas de estrés postraumático en personal de primera línea de Japón. |
| Authors: | van der Does, Florentine H. S. (AUTHOR), Kitano, Masato (AUTHOR), Nagamine, Masanori (AUTHOR), Saito, Taku (AUTHOR), van der Wee, Nic J. A. (AUTHOR), Chiba, Toshinori (AUTHOR), Edo, Naoki (AUTHOR), Vermetten, Eric (AUTHOR), Giltay, Erik J. (AUTHOR) |
| Source: | European Journal of Psychotraumatology. Dec2025, Vol. 16 Issue 1, p1-12. 12p. |
| Subjects: | Post-traumatic stress disorder, First responders, Time series analysis, Dissociation (Psychology), Therapeutics, Mental health |
| Abstract (English): | Background: A more inclusive approach for addressing the diverse spectrum of mental health experiences is needed. Network theory frames psychopathological complaints as complex dynamic systems, that can be modelled in a network of mutually interacting symptoms. These networks may provide important markers of symptom improvement or exacerbation, and inform strategies for early intervention and treatment. In previous research, we identified five distinct Post-Traumatic Stress Disorder (PTSD) symptom severity trajectories within a cohort of first responders from the Japan Ground Self-Defense Force (JGSDF), deployed following the Great East Japan Earthquake (GEJE) of 2011: Resilient, Recovery, Incomplete Recovery, Late-Onset, and Chronic. Objective: The current study was aimed at investigating differences in symptom dynamics within the four non-resilient PTSD symptom severity trajectories using the innovative method of Dynamic Time Warping (DTW). Method: This study sample was selected from a cohort of 55 632 JGSDF personnel, who completed at least four yearly mental health surveys between 2013 and 2018, and experienced PTSD symptoms over the course of follow-up. DTW, a statistical technique for identifying patterns in time-series data, was employed to model undirected and directed (temporal) symptom networks. Results: The sample consisted of 10211 personnel [97.8% male, mean age 36.7 (SD = 7.5)]. In the undirected DTW analyses, we found that lower network density was associated with a chronic symptom severity trajectory. Directed DTW analyses revealed that in improving post-traumatic stress, dissociation-like symptoms were the first to decrease, whereas emotional reactivity to trauma reminders was the most persistent symptom. In worsening post-traumatic stress, avoidance symptoms emerged earliest, while dissociation-like symptoms were the last to intensify. Conclusions: These findings highlight the importance of DTW network density in the chronicity of symptoms of post-traumatic stress. Furthermore, an increase in avoidance symptoms may serve as an early marker of worsening PTSD, signalling a need for timely intervention. HIGHLIGHTS: Network analysis offers methods to map the interactions between an individual's symptoms over time as a self-propagating system, where symptoms can cause and exacerbate each other and create feedback loops. The novel Dynamic Time Warping algorithm was used to create dynamic PTSD symptom networks in a cohort of Japanese Self-Defense Force first responders, potentially furthering our understanding of PTSD, and facilitating the selection of targets for monitoring and early intervention. In those with improving PTSD symptom severity trajectories, dissociation symptoms improved first and emotional reactivity to trauma reminders improved last. In those with worsening PTSD symptom severity trajectories, avoidance symptoms worsened first and dissociation symptoms worsened last. [ABSTRACT FROM AUTHOR] |
| Abstract (Spanish): | Antecedentes: Se necesita un enfoque más inclusivo para abordar el diverso espectro de experiencias de salud mental. La teoría de redes define las quejas psicopatológicas como sistemas dinámicos complejos, que pueden modelarse en una red de síntomas que interactúan entre sí. Estas redes pueden proporcionar indicadores importantes de la mejoría o exacerbación de los síntomas, e informar sobre estrategias para la intervención y tratamientos tempranos. En investigaciones previas, identificamos cinco distintas trayectorias de gravedad de los síntomas del Trastorno de Estrés Postraumático (TEPT) en una cohorte de personal de primera línea de la Fuerza Terrestre de Autodefensa de Japón (JGSDF por sus siglas en inglés), desplegado tras el Gran Terremoto del Este de Japón de 2011: Resiliente, Recuperación, Recuperación Incompleta, Inicio Tardío y Crónico. Objetivo: El presente estudio tuvo como objetivo investigar las diferencias en la dinámica de los síntomas dentro de las cuatro trayectorias de gravedad de los síntomas del TEPT no resilientes utilizando el método innovador de deformación temporal dinámica (DTW por sus siglas en inglés). Método: Esta muestra de estudio se seleccionó de una cohorte de 55.632 miembros del personal de la JGSDF, quienes completaron al menos cuatro encuestas anuales de salud mental entre 2013 y 2018 y experimentaron síntomas de TEPT durante el seguimiento. Se empleó la técnica estadística DTW para identificar patrones en datos de series temporales, con el fin de modelar redes de síntomas dirigidas y no dirigidas (temporales). Resultados: -La muestra consistió en 10.211 personas (97,8% hombres, edad media 36,7 (DE = 7,5). En los análisis DTW no dirigidos, encontramos una menor densidad de red asociada con una trayectoria de gravedad de los síntomas crónicos. Los análisis DTW dirigidos revelaron que al mejorar el estrés postraumático, los síntomas relacionados a la disociación fueron los primeros en disminuir, mientras que la reactividad emocional a los recuerdos del trauma fue el síntoma más persistente. Al empeorar el estrés postraumático, los síntomas de evitación emergieron primero, mientras que los síntomas relacionados a la disociación fueron los últimos en intensificarse. Conclusiones: Estos hallazgos resaltan la importancia de la densidad de la red DTW para la cronicidad de los síntomas de estrés postraumático. Además, un aumento en los síntomas de evitación puede servir como un marcador temprano de empeoramiento del TEPT, lo que indica la necesidad de una intervención oportuna. [ABSTRACT FROM AUTHOR] |
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| Database: | Psychology and Behavioral Sciences Collection |
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| Abstract: | Background: A more inclusive approach for addressing the diverse spectrum of mental health experiences is needed. Network theory frames psychopathological complaints as complex dynamic systems, that can be modelled in a network of mutually interacting symptoms. These networks may provide important markers of symptom improvement or exacerbation, and inform strategies for early intervention and treatment. In previous research, we identified five distinct Post-Traumatic Stress Disorder (PTSD) symptom severity trajectories within a cohort of first responders from the Japan Ground Self-Defense Force (JGSDF), deployed following the Great East Japan Earthquake (GEJE) of 2011: Resilient, Recovery, Incomplete Recovery, Late-Onset, and Chronic. Objective: The current study was aimed at investigating differences in symptom dynamics within the four non-resilient PTSD symptom severity trajectories using the innovative method of Dynamic Time Warping (DTW). Method: This study sample was selected from a cohort of 55 632 JGSDF personnel, who completed at least four yearly mental health surveys between 2013 and 2018, and experienced PTSD symptoms over the course of follow-up. DTW, a statistical technique for identifying patterns in time-series data, was employed to model undirected and directed (temporal) symptom networks. Results: The sample consisted of 10211 personnel [97.8% male, mean age 36.7 (SD = 7.5)]. In the undirected DTW analyses, we found that lower network density was associated with a chronic symptom severity trajectory. Directed DTW analyses revealed that in improving post-traumatic stress, dissociation-like symptoms were the first to decrease, whereas emotional reactivity to trauma reminders was the most persistent symptom. In worsening post-traumatic stress, avoidance symptoms emerged earliest, while dissociation-like symptoms were the last to intensify. Conclusions: These findings highlight the importance of DTW network density in the chronicity of symptoms of post-traumatic stress. Furthermore, an increase in avoidance symptoms may serve as an early marker of worsening PTSD, signalling a need for timely intervention. HIGHLIGHTS: Network analysis offers methods to map the interactions between an individual's symptoms over time as a self-propagating system, where symptoms can cause and exacerbate each other and create feedback loops. The novel Dynamic Time Warping algorithm was used to create dynamic PTSD symptom networks in a cohort of Japanese Self-Defense Force first responders, potentially furthering our understanding of PTSD, and facilitating the selection of targets for monitoring and early intervention. In those with improving PTSD symptom severity trajectories, dissociation symptoms improved first and emotional reactivity to trauma reminders improved last. In those with worsening PTSD symptom severity trajectories, avoidance symptoms worsened first and dissociation symptoms worsened last. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 20008066 |
| DOI: | 10.1080/20008066.2025.2528313 |
