J 2025

Complex temporal dynamics of mental health indicators: A longitudinal network approach perspective

ADAMKOVIC, Matúš; Benjamin SIMSA; Bibiána JOZEFIAKOVÁ; Gabriela MIKULÁŠKOVÁ; Peter BABINČÁK et al.

Basic information

Original name

Complex temporal dynamics of mental health indicators: A longitudinal network approach perspective

Authors

ADAMKOVIC, Matúš; Benjamin SIMSA; Bibiána JOZEFIAKOVÁ; Gabriela MIKULÁŠKOVÁ; Peter BABINČÁK; Gabriel BANIK; Jaroslava BOČANOVÁ; Denisa FEDÁKOVÁ; Klára KAČMARIKOVÁ; Pavol KAČMÁR; Michal KENTOŠ; Viktória MAJDÁKOVÁ; Lenka VARGOVÁ; L'ubica ZIBRÍNOVA and Ivan ROPOVIK

Edition

PSYCHOLOGICAL MEDICINE, 2025, 0033-2917

Other information

Language

English

Type of outcome

Article in a journal

Field of Study

50101 Psychology

Country of publisher

United Kingdom of Great Britain and Northern Ireland

Confidentiality degree

is not subject to a state or trade secret

References:

Impact factor

Impact factor: 5.500 in 2024

Marked to be transferred to RIV

Yes

Organization unit

Ambis University

EID Scopus

Keywords in English

anxiety;depression;insomnia;longitudinal analysis;mental health;network analysis;panel networks;posttraumatic stress disorder

Tags

Changed: 10/3/2026 14:59, Ing. Kateřina Lendrová

Abstract

In the original language

Background Although mental disorders have long been considered complex dynamic systems, our understanding of the mutual interactions and temporal patterns of their symptoms remains limited.Methods In this longitudinal study, we examined the structure and dynamics of four key mental health indicators - depression, anxiety, post-traumatic stress disorder, and insomnia - in a representative sample of the Slovak population (effective N = 3,874) over 10 waves spanning 3.5 years. For each construct, a longitudinal panel network model was estimated.Results The temporal relationships between symptoms were mostly weak, with the autoregressive effects typically being stronger. In depression, anxiety, and insomnia, some causal chains and feedback loops were identified. In all constructs, both contemporaneous and between-person networks showed dense connections.Conclusions The findings provide critical insights into the complexity of mental health development, offering potential targets for intervention and prevention strategies.

In Czech

úzkost, deprese, nespavost, longitudinální analýza, duševní zdraví, síťová analýza, panelové sítě, posttraumatická stresová porucha