Network comparison methods detect temporal reorganization of psychophysiological integration invisible to conventional univariate analysis: Proof-of-concept using lunar-phase-timed measurements in elite athletes

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Özet

Field studies using conventional univariate methods fail to detect physiological rhythms (melatonin, cortisol, sleep architecture) that are consistently documented under laboratory-controlled conditions, suggesting that temporal factors operate on systemic organization rather than isolated metrics. Network analysis quantifies conditional dependencies among variables simultaneously, enabling the detection of organizational changes independent of mean-level shifts. As an exploratory proof-of-concept, this study examines whether network comparison methods detect temporal reorganization of psychophysiological integration invisible to conventional repeated-measures analysis in elite athletes; no confirmatory causal inference is drawn. Twelve elite male athletes completed psychophysiological assessments (mood states, subjective well-being, neurocognitive performance, postural control, intermittent endurance) at three lunar phases (New Moon, First Quarter, Full Moon) in a counterbalanced design. Conventional repeated-measures ANOVA detected no temporal effects on isolated variables (all F < 2.87, p > 0.05, eta(2)p < 0.21). Network comparison revealed marked organizational differences: New Moon versus Full Moon networks exhibited distinct architecture (M = 0.31, padj = 0.008) and connectivity (S = 8.42, padj = 0.029). Centrality systematically redistributed from capacity and well-being constructs (New Moon: vigour z = 1.82) to recovery markers (Full Moon: stress z = 2.13). Twelve connections differed significantly, including enhanced stress-confusion coupling (Delta r = +0.39, p = 0.003). This proof-of-concept demonstrates that temporal measurements can exhibit systemic reorganization despite stable component means, resolving apparent contradictions between laboratory-detected physiological rhythms and field-based null findings. Temporal control measurements and multi-cycle replication are required to definitively attribute observed reorganization to lunar periodicity rather than generic temporal variation.

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dc.contributor.authorYousfi, Narimen
dc.contributor.authorDhahbi, Wissem
dc.contributor.authorGhouili, Hatem
dc.contributor.authorMejri, Mohamed Arbi
dc.contributor.authorBessifi, Manel
dc.contributor.authorCeylan, Halil Ibrahim
dc.contributor.authorValentina, Stefanica
dc.contributor.authorCeylan, Nagihan Burcak
dc.contributor.authorChtourou, Hamdi
dc.contributor.authorDergaa, Ismail
dc.contributor.authorChamari, Karim
dc.date.accessioned2026-10-29T17:19:28.200979073Z
dc.date.available2026-10-29T17:19:28.200979073Z
dc.date.issued2026-07
dc.description.abstractField studies using conventional univariate methods fail to detect physiological rhythms (melatonin, cortisol, sleep architecture) that are consistently documented under laboratory-controlled conditions, suggesting that temporal factors operate on systemic organization rather than isolated metrics. Network analysis quantifies conditional dependencies among variables simultaneously, enabling the detection of organizational changes independent of mean-level shifts. As an exploratory proof-of-concept, this study examines whether network comparison methods detect temporal reorganization of psychophysiological integration invisible to conventional repeated-measures analysis in elite athletes; no confirmatory causal inference is drawn. Twelve elite male athletes completed psychophysiological assessments (mood states, subjective well-being, neurocognitive performance, postural control, intermittent endurance) at three lunar phases (New Moon, First Quarter, Full Moon) in a counterbalanced design. Conventional repeated-measures ANOVA detected no temporal effects on isolated variables (all F < 2.87, p > 0.05, eta(2)p < 0.21). Network comparison revealed marked organizational differences: New Moon versus Full Moon networks exhibited distinct architecture (M = 0.31, padj = 0.008) and connectivity (S = 8.42, padj = 0.029). Centrality systematically redistributed from capacity and well-being constructs (New Moon: vigour z = 1.82) to recovery markers (Full Moon: stress z = 2.13). Twelve connections differed significantly, including enhanced stress-confusion coupling (Delta r = +0.39, p = 0.003). This proof-of-concept demonstrates that temporal measurements can exhibit systemic reorganization despite stable component means, resolving apparent contradictions between laboratory-detected physiological rhythms and field-based null findings. Temporal control measurements and multi-cycle replication are required to definitively attribute observed reorganization to lunar periodicity rather than generic temporal variation.
dc.identifier.doi10.1080/07420528.2026.2648754
dc.identifier.eissn1525-6073
dc.identifier.endpage1114
dc.identifier.issn0742-0528
dc.identifier.issue7
dc.identifier.pmid41972794
dc.identifier.scopus2-s2.0-105035793092
dc.identifier.startpage1099
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/bayburt/10762
dc.identifier.volume43
dc.identifier.wosWOS:001739788300001
dc.language.isoen
dc.publisherTAYLOR & FRANCIS INC
dc.relation.ispartofCHRONOBIOLOGY INTERNATIONAL
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectBiomarkers
dc.subjectchronobiology
dc.subjectGraphical Gaussian Models
dc.subjectmood states
dc.subjectpostural balance
dc.subjectsleep quality
dc.subjecttask performance
dc.subject.classificationBiology
dc.subject.classificationPhysiology
dc.subject.classificationLife Sciences & Biomedicine - Other Topics
dc.subject.otherPERSPECTIVES
dc.subject.otherRHYTHMS
dc.subject.otherSLEEP
dc.titleNetwork comparison methods detect temporal reorganization of psychophysiological integration invisible to conventional univariate analysis: Proof-of-concept using lunar-phase-timed measurements in elite athletes
dc.typeArticle
rdl.citation.openalex0
rdl.citation.scopus0
rdl.citation.wos0
rdl.departmentResearch Unit (UR22JS01) "Sport Sciences, Health and Movement", High Institute of Sport and Physical Education of Kef, University of Jendouba, Le Kef, Tunisia
rdl.departmentTunisian Research Laboratory "Sport Performance Optimisation", National Center of Medicine and Science in Sport, Tunis, Tunisia
rdl.departmentQatar Police Academy, Police College, Training Department, Doha, Qatar
rdl.departmentHigh Institute of Sport and Physical Education, University of Manouba, Ksar Said, Tunisia
rdl.departmentPhysical Education of Sports Teaching Department, Faculty of Sports Sciences, Atatürk University, Erzurum, Türkiye
rdl.departmentDepartment of Physical Education and Sport, Faculty of Sciences, Physical Education and Informatics, National University of Science and Technology Politehnica Bucharest, Pitești, Romania
rdl.departmentGraduate Education Institute, Bayburt University, Bayburt, Türkiye
rdl.departmentHigh Institute of Sport and Physical Education, University of Sfax, Sfax, Tunisia
rdl.departmentPhysical Activity, Sport and Health, Tunis, National Observatory of Sport, Tunisia
rdl.departmentResearch & Education Department, Wellness and Recovery Center Doha, Qatar
rdl.oa.statushybrid
rdl.oa.urlhttps://www.tandfonline.com/doi/pdf/10.1080/07420528.2026.2648754?needAccess=true
rdl.scopus.quartileQ2
rdl.source.indexWOS
rdl.source.indexSCOPUS
rdl.source.indexPUBMED
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)