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      Romantic relationship breakup: An experimental model to study effects of stress on depression (-like) symptoms

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          Abstract

          The occurrence of a stressful event is considered to increase the risk of developing depression. In the present study we explore whether the breakup of a romantic relationship can be used as an experimental model to study a depression-like state during a period of stress in individuals without a psychiatric disorder. The primary aim of our study was to investigate: 1) whether individuals with a recent romantic relationship breakup (‘‘heartbreak”) demonstrate symptoms of depression, 2) how to describe heartbreak characteristics based on data from a comprehensive questionnaire battery, and 3) whether this description can capture severity of depression symptoms. Secondary, we were interested in gender differences with regard to the above study objectives. Subjects who have experienced a relationship breakup in the preceding six months ( N = 71) or are in a romantic relationship ( N = 46) participated in our study. A questionnaire battery was administered to acquire information related to depression, mood, the breakup and (former) relationship. Principal Component Analysis with Procrustes bootstrapping was performed to extract components from the questionnaire data. Even though our sample of individuals who recently have experienced a relationship breakup can be on average considered non-depressed, group-level depression scores were elevated compared to individuals in a relationship ( p = .001) and 26.8% reported symptoms corresponding to mild, moderate or severe depression. We described heartbreak by two principal components interpreted as ‘‘sudden loss” and ‘‘lack of positive affect”, respectively. Highly significant correlations between the component scores and depression scores were found ( p < .001 and p < .001, respectively), although these correlations differed between the genders. Based on these findings, we propose that the experience of a romantic relationship breakup is a viable experimental model to examine symptoms of depression in individuals without a psychiatric disorder. This way, stress-related coping and depression vulnerability can be studied in further research.

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          The positive and negative affect schedule (PANAS): construct validity, measurement properties and normative data in a large non-clinical sample.

          To evaluate the reliability and validity of the PANAS (Watson, Clark, & Tellegen, 1988b) and provide normative data. Cross-sectional and correlational. The PANAS was administered to a non-clinical sample, broadly representative of the general adult UK population (N = 1,003). Competing models of the latent structure of the PANAS were evaluated using confirmatory factor analysis. Regression and correlational analysis were used to determine the influence of demographic variables on PANAS scores as well as the relationship between the PANAS with measures of depression and anxiety (the HADS and the DASS). The best-fitting model (robust comparative fit index = .94) of the latent structure of the PANAS consisted of two correlated factors corresponding to the PA and NA scales, and permitted correlated error between items drawn from the same mood subcategories (Zevon & Tellegen, 1982). Demographic variables had only very modest influences on PANAS scores and the PANAS exhibited measurement invariance across demographic subgroups. The reliability of the PANAS was high, and the pattern of relationships between the PANAS and the DASS and HADS were consistent with tripartite theory. The PANAS is a reliable and valid measure of the constructs it was intended to assess, although the hypothesis of complete independence between PA and NA must be rejected. The utility of this measure is enhanced by the provision of large-scale normative data. Copyright 2004 The British Psychological Society
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            The Measurement of Perceived Relationship Quality Components: A Confirmatory Factor Analytic Approach

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              Sex and depression in the National Comorbidity Survey. I: Lifetime prevalence, chronicity and recurrence.

              Basic epidemiologic prevalence data are presented on sex differences in DSM-III-R major depressive episodes (MDE). The data come from the National Comorbidity Survey (NCS), the first survey in the U.S. to administer a structured psychiatric interview to a nationally representative sample of the general population. Consistent with previous research, women are approximately 1.7 times as likely as men to report a lifetime history of MDE. Age of onset analysis shows that this sex difference begins in early adolescence and persists through the mid-50s. Women also have a much higher rate of 12-month depression than men. However, women with a history of depression do not differ from men with a history of depression in either the probability of being chronically depressed in the past year or in the probability of having an acute recurrence in the past year. This means that the higher prevalence of 12-month depression among women than men is largely due to women having a higher risk of first onset. The implications of these results for future research are discussed in a closing section of the paper.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: Writing – original draft
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                31 May 2019
                2019
                : 14
                : 5
                : e0217320
                Affiliations
                [001]University of Groningen, University Medical Center Groningen, Department of Biomedical Sciences of Cells & Systems, Cognitive Neuroscience Center, Groningen, the Netherlands
                University of Lleida, SPAIN
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-0022-6291
                Article
                PONE-D-19-04833
                10.1371/journal.pone.0217320
                6544239
                31150432
                307552f0-2635-4c5e-bb7a-59f7ba58d6c7
                © 2019 Verhallen et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 18 February 2019
                : 8 May 2019
                Page count
                Figures: 2, Tables: 1, Pages: 13
                Funding
                The study was funded by a donation of Mr Hazewinkel to the Research School of Behavioural and Cognitive Neurosciences and Prof G.J. ter Horst. Mr Hazewinkel had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Mood Disorders
                Depression
                Medicine and Health Sciences
                Mental Health and Psychiatry
                Psychological Stress
                Biology and Life Sciences
                Psychology
                Psychological Stress
                Social Sciences
                Psychology
                Psychological Stress
                Biology and Life Sciences
                Psychology
                Emotions
                Social Sciences
                Psychology
                Emotions
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Multivariate Analysis
                Principal Component Analysis
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Multivariate Analysis
                Principal Component Analysis
                Biology and Life Sciences
                Psychology
                Psychometrics
                Social Sciences
                Psychology
                Psychometrics
                Physical Sciences
                Mathematics
                Algebra
                Linear Algebra
                Eigenvalues
                Research and Analysis Methods
                Research Design
                Survey Research
                Questionnaires
                Biology and Life Sciences
                Neuroscience
                Brain Mapping
                Functional Magnetic Resonance Imaging
                Medicine and Health Sciences
                Diagnostic Medicine
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Functional Magnetic Resonance Imaging
                Research and Analysis Methods
                Imaging Techniques
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Functional Magnetic Resonance Imaging
                Medicine and Health Sciences
                Radiology and Imaging
                Diagnostic Radiology
                Magnetic Resonance Imaging
                Functional Magnetic Resonance Imaging
                Research and Analysis Methods
                Imaging Techniques
                Neuroimaging
                Functional Magnetic Resonance Imaging
                Biology and Life Sciences
                Neuroscience
                Neuroimaging
                Functional Magnetic Resonance Imaging
                Custom metadata
                The data will not be stored at a public repository due to restrictions from the informed consent (subjects have not given consent to have their data publicly stored) and European data privacy regulations (GDPR). The data are available on request. A data access committee has been put in place, consisting of Prof G.J. ter Horst (Principal Investigator of the study), J.B.C. Marsman and Prof A. Aleman (head of the Cognitive Neuroscience Center), who will review requests and assure accessibility of the data. This access committee can be reached via a.aleman@ 123456umcg.nl .

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