TY - JOUR
KW - Anxiety
KW - Bayesian networks
KW - Depression
KW - Sleep quality
KW - symptoms
AU - Daniel E. Yupanqui-Lorenzo
AU - Tomás Caycho-Rodríguez
AU - Jonatan Baños-Chaparro
AU - Tania Arauco-Lozada
AU - Luis Palao-Loayza
AU - Iván Barrios
AU - Julio Torales
AU - Renzo Felipe Carranza Esteban
AU - Luis Hualparuca-Olivera
AB - It has been suggested that individuals with sleep disorders tend to experience concurrent mental health disorders, such as anxiety and depression. Therefore, this study aimed to address this gap by utilizing Bayesian network analysis to explore the potential causal relationships between sleep quality, anxiety, and depressive symptoms in a sample of 451 Peruvian adults. The network structures for sleep quality, depression, and anxiety were estimated using the Jenkins Sleep Scale, Patient Health Questionnaire-2, and General Anxiety Disorder-2, respectively. The causal relationships between symptoms were estimated using Bayesian networks from a directed acyclic graph (DAG) model. Nighttime Awakenings and Anhedonia play significant and distinct roles in the symptom network dynamics. Nighttime Awakenings showed directional probabilities of four symptoms: Nervousness, Difficulty Falling, Stay Asleep, and Depressed Mood. Anhedonia also showed directional probabilities toward three symptoms: Tiredness on Awakening, Uncontrollable Worry, and Depressed Mood. Meanwhile, although Nervousness does not have outgoing arrows to other symptoms, it shows conditional dependence with Uncontrollable Worry, Depressed Mood, and Nighttime Awakenings. The findings suggest adopting a comprehensive approach to the treatment of sleep disorders, anxiety, and depression, considering the interconnections among various symptoms and addressing not only the core symptoms but also those that function as mediators or bridges within the symptom network.
IS - 3
M3 - Journal Article
N2 - It has been suggested that individuals with sleep disorders tend to experience concurrent mental health disorders, such as anxiety and depression. Therefore, this study aimed to address this gap by utilizing Bayesian network analysis to explore the potential causal relationships between sleep quality, anxiety, and depressive symptoms in a sample of 451 Peruvian adults. The network structures for sleep quality, depression, and anxiety were estimated using the Jenkins Sleep Scale, Patient Health Questionnaire-2, and General Anxiety Disorder-2, respectively. The causal relationships between symptoms were estimated using Bayesian networks from a directed acyclic graph (DAG) model. Nighttime Awakenings and Anhedonia play significant and distinct roles in the symptom network dynamics. Nighttime Awakenings showed directional probabilities of four symptoms: Nervousness, Difficulty Falling, Stay Asleep, and Depressed Mood. Anhedonia also showed directional probabilities toward three symptoms: Tiredness on Awakening, Uncontrollable Worry, and Depressed Mood. Meanwhile, although Nervousness does not have outgoing arrows to other symptoms, it shows conditional dependence with Uncontrollable Worry, Depressed Mood, and Nighttime Awakenings. The findings suggest adopting a comprehensive approach to the treatment of sleep disorders, anxiety, and depression, considering the interconnections among various symptoms and addressing not only the core symptoms but also those that function as mediators or bridges within the symptom network.
PB - Sociedad Española para el Estudio de la Ansiedad y el Estrés
PY - 2024
SN - 2174-0437/1134-7937
SP - 175
EP - 183
T2 - Ansiedad y Estrés
TI - A Bayesian network analysis of sleep quality, anxiety, and depression symptoms in Peruvian Adults
VL - 30
ER -