A Network Approach to Early Life Adversity, Sleep Disturbance, and Depressive Symptoms

dc.contributorXia, Mengya
dc.contributorDecaro, Jason
dc.contributor.advisorCribbet, Matthew R
dc.contributor.authorMarquez, Francisco De Jesus
dc.contributor.otherUniversity of Alabama Tuscaloosa
dc.date.accessioned2023-01-27
dc.date.available2023-01-27
dc.date.issued2022
dc.descriptionElectronic Thesis or Dissertationen_US
dc.description.abstractABSTRACTExperiences of early life adversity (ELA) engender a variety of adverse health outcomes, such as obesity, the metabolic syndrome, and major depressive disorder. Compared to individuals without exposure to adversity, individuals with ELA experience a greater likelihood of sleep disturbance. Associations between early adversity and sleep disturbance may explain increased risk for depressive symptoms in individuals with ELA. However, the bidirectional nature of the relationship between sleep disturbance and major depression presents a challenge in unraveling the temporality of these associations. Moreover, the underlying affective, somatic, and interpersonal factors that influence sleep disturbance in individuals with ELA are poorly understood. To address this gap, we employed a nomothetic network analytic approach to assess ELA-specific differences between the presentation of comorbid sleep disturbance and depressive symptoms. To this end, data from the second wave of the National Survey of Midlife Development in the United States study (MIDUS2, N=1255, 56.8%=Female) were used to generate ELA-specific networks of sleep disturbance and depressive symptoms. Individuals exposed to ELA experienced greater comorbid somatic, cognitive, and interpersonal symptoms of depression compared to those without ELA (M = 0.15; p < 0.05). Moreover, we found that depressive symptoms were more severe among those with ELA, relative to those without (S = 0.24; 1.4 vs 1.1, p < 0.01). Bridged network analysis indicated that there was increased sleep disturbance and depressive symptom comorbidity among those with ELA, relative to those without ELA (S = 0.54; 4.1 vs 3.6, p < 0.01). In adherence with the NIH's Research Domain Criteria, our findings underscore the utility of novel statistical approaches to identify transdiagnostic mechanisms of risk that may result from environmental exposures. Statistical approaches which uncover these transdiagnostic mechanisms of risk may serve to develop trauma-informed interventions, thereby serving to assuage the public health burden of ELA.en_US
dc.format.mediumelectronic
dc.format.mimetypeapplication/pdf
dc.identifier.otherhttp://purl.lib.ua.edu/186765
dc.identifier.otheru0015_0000001_0004589
dc.identifier.otherMarquez_alatus_0004M_15089
dc.identifier.urihttps://ir.ua.edu/handle/123456789/9877
dc.languageEnglish
dc.language.isoen_US
dc.publisherUniversity of Alabama Libraries
dc.relation.hasversionborn digital
dc.relation.ispartofThe University of Alabama Electronic Theses and Dissertations
dc.relation.ispartofThe University of Alabama Libraries Digital Collections
dc.rightsAll rights reserved by the author unless otherwise indicated.en_US
dc.subjectComorbidity
dc.subjectDepression
dc.subjectEarly life adversity
dc.subjectHealth psychology
dc.subjectNetwork analysis
dc.subjectSleep
dc.titleA Network Approach to Early Life Adversity, Sleep Disturbance, and Depressive Symptomsen_US
dc.typethesis
dc.typetext
etdms.degree.departmentUniversity of Alabama. Department of Psychology
etdms.degree.disciplineClinical psychology
etdms.degree.grantorThe University of Alabama
etdms.degree.levelmaster's
etdms.degree.nameM.A.
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