146951 20260217205606.0 doi 10.1111/psyp.14729 sideral 140641 ART-2024-140641 eng Pagès, Esther García Contribution of physiological dynamics in predicting major depressive disorder severity 2024 Access copy available to the general public Unrestricted This study aimed to explore the physiological dynamics of cognitive stress in patients with Major Depressive Disorder (MDD) and design a multiparametric model for objectively measuring severity of depression. Physiological signal recordings from 40 MDD patients and 40 healthy controls were collected in a baseline stage, in a stress‐inducing stage using two cognitive tests, and in the recovery period. Several features were extracted from electrocardiography, photoplethysmography, electrodermal activity, respiration, and temperature. Differences between values of these features under different conditions were used as indexes of autonomic reactivity and recovery. Finally, a linear model was designed to assess MDD severity, using the Beck Depression Inventory scores as the outcome variable. The performance of this model was assessed using the MDD condition as the response variable. General physiological hyporeactivity and poor recovery from stress predict depression severity across all physiological signals except for respiration. The model to predict depression severity included gender, body mass index, cognitive scores, and mean heart rate recovery, and achieved an accuracy of 78%, a sensitivity of 97% and a specificity of 59%. There is an observed correlation between the behavior of the autonomic nervous system, assessed through physiological signals analysis, and depression severity. Our findings demonstrated that decreased autonomic reactivity and recovery are linked with an increased level of depression. Quantifying the stress response together with a cognitive evaluation and personalization variables may facilitate a more precise diagnosis and monitoring of depression, enabling the tailoring of therapeutic interventions to individual patient needs. info:eu-repo/grantAgreement/ES/AEI/RTI2018-096072-B-I00 info:eu-repo/grantAgreement/ES/DGA/T39-23R info:eu-repo/grantAgreement/EC/H2020/115902/EU/Remote Assessment of Disease and Relapse in Central Nervous System Disorders/RADAR-CNS This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 115902-RADAR-CNS info:eu-repo/grantAgreement/ES/ISCIII/CB06-01-0049 info:eu-repo/grantAgreement/EUR/MICINN/TED2021-131106B-I00 info:eu-repo/semantics/openAccess by-nc https://creativecommons.org/licenses/by-nc/4.0/deed.es 2.8 2024 PSYCHOLOGY, EXPERIMENTAL 25 / 102 = 0.245 2024 Q1 T1 PHYSIOLOGY 30 / 87 = 0.345 2024 Q2 T2 PSYCHOLOGY 28 / 93 = 0.301 2024 Q2 T1 PSYCHOLOGY, BIOLOGICAL 5 / 18 = 0.278 2024 Q2 T1 NEUROSCIENCES 162 / 314 = 0.516 2024 Q3 T2 1.265 2024 Cognitive Neuroscience 2024 Q1 Developmental and Educational Psychology 2024 Q1 Developmental Neuroscience 2024 Q1 Physiology 2024 Q1 Neurology 2024 Q1 Neuropsychology and Physiological Psychology 2024 Q1 Neuroscience (miscellaneous) 2024 Q1 Experimental and Cognitive Psychology 2024 Q1 5.7 2024 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Kontaxis, Spyridon (orcid)0000-0002-1297-0691 Siddi, Sara Posadas de Miguel, Mar Cámara, Concepción de la Universidad de Zaragoza (orcid)0000-0003-2284-7862 Bernal, Maria Luisa Universidad de Zaragoza (orcid)0000-0002-8222-1418 Ribeiro, Thais Castro Laguna, Pablo Universidad de Zaragoza (orcid)0000-0003-3434-9254 Badiella, Llorenç Bailón, Raquel Universidad de Zaragoza (orcid)0000-0003-1272-0550 Haro, Josep Maria Aguiló, Jordi 1012 315 Universidad de Zaragoza Dpto. Farmac.Fisiol.y Med.L.F. Área Farmacología 1007 745 Universidad de Zaragoza Dpto. Medicina, Psiqu. y Derm. Area Psiquiatría 5008 800 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Teoría Señal y Comunicac. 62, 2 (2024), e14729 [22 pp.] Psychophysiology PSYCHOPHYSIOLOGY 0048-5772 1058228 http://zaguan.unizar.es/record/146951/files/texto_completo.pdf Versión publicada 2365192 http://zaguan.unizar.es/record/146951/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:146951 articulos driver 2026-02-17-20:46:59 ARTICLE