Resilience to Major Life Events: Advancing Trajectory Modeling and Resilience Factor Identification by Controlling for Background Stressor Exposure.
Resilience has been defined as the maintenance or quick recovery of mental health during and after stressor exposure. One popular operationalization of this concept is to model prototypical trajectories of mental health in response to an adverse event, where trajectories of undisturbed low or rapidl...
| Publicado en: | American Psychologist Vol. 79; no. 8; pp. 1076 - 1092 |
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| Autores principales: | , , , , , , , , , , , , , , , , , |
| Formato: | Artículo |
| Publicado: |
American Psychological Association
Nov2024
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=180762907&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 180762907 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 0003066X APT jtl: American Psychologist issn: 0003066X maglogo: N pubinfo: dt: Nov2024 vid: 79 iid: 8 pid: 34 pub: American Psychological Association artinfo: ui: 180762907 10.1037/amp0001315 ppf: 1076 ppct: 16 formats: tig: atl: Resilience to Major Life Events: Advancing Trajectory Modeling and Resilience Factor Identification by Controlling for Background Stressor Exposure. aug: au: Ahrens, Kira F. Schenk, Charlotte Kollmann, Bianca Puhlmann, Lara M. C. Neumann, Rebecca J. Schäfer, Sarah K. Reis, Dorota Basten, Ulrike Weichert, Danuta Fiebach, Christian J. Lutz, Beat Wessa, Michèle Repple, Jonathan Lieb, Klaus Tüscher, Oliver Reif, Andreas Kalisch, Raffael Plichta, Michael M. affil: Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt, Goethe University Frankfurt Leibniz Institute for Resilience Research, Mainz, Germany Department of Psychiatry and Psychotherapy, University Medical Center of the Johannes Gutenberg University Department of Psychology, Clinical Psychology, Psychotherapy and Diagnostics, Technische Universität Braunschweig Department of Psychology, Saarland University Department of Psychology, Rhineland-Palatinate Technical University of Kaiserslautern-Landau Brain Imaging Center, Goethe University Frankfurt Department of Psychology, Goethe University Frankfurt Institute of Physiological Chemistry, University Medical Center of the Johannes Gutenberg University Department of Clinical Psychology and Neuropsychology, Institute for Psychology, Johannes Gutenberg University Mainz Institute for Translational Psychiatry, University of Münster Institute of Molecular Biology, Mainz, Germany Neuroimaging Center, Focus Program Translational Neuroscience, Johannes Gutenberg University Medical Center Mainz su: Germany Life change events Mental health Psychological stress Psychological resilience Research funding Descriptive statistics sug: subj: Life change events Mental health Psychological stress Germany Offices of Mental Health Practitioners (except Physicians) Psychological resilience Research funding Descriptive statistics keyword: k-means classification algorithm for longitudinal data Longitudinal Resilience Assessment resilience sense of coherence stressor reactivity k-means classification algorithm for longitudinal data Longitudinal Resilience Assessment resilience sense of coherence stressor reactivity ab: Resilience has been defined as the maintenance or quick recovery of mental health during and after stressor exposure. One popular operationalization of this concept is to model prototypical trajectories of mental health in response to an adverse event, where trajectories of undisturbed low or rapidly recovering symptoms both comply with the resilience definition. However, mental health responses are likely also influenced by other stressors occurring before or during the observation time window. These "background" stressors may affect a person's assignment to a trajectory class. When using these classes as dependent variables to identify resilience-predictive factors, this may lead to false estimates. A new method to build exposure-controlled trajectories based on time courses of stressor reactivity (SR), rather than pure mental health scores, is demonstrated on a data set of 707 initially healthy participants living in Germany (67.33% female; M = 29.20, SD = 8.27). SR scores express individual deviations from the sample's normative mental health reaction to observed real-life stressors during the observation time window, thus accounting for individual differences in exposure to background stressors. The resulting trajectory models are plausible. In analyses additionally controlling for background stressors occurring before the observation time window (past life events), low SR trajectories are predicted by the well-documented resilience factor sense of coherence, suggesting construct validity. Further, they are associated with lower odds of developing categorical mental health conditions, suggesting predictive validity. Our study provides the first proof of principle for a refined method to identify predictors of resilience to major stressor events. Public Significance Statement: Identifying factors that predict resilience is a major goal of mental health science. These factors might be targets for interventions aiming at preventing the development of stress-related mental health problems. To quantify a person's resilience, we must be sure that the individual does not simply show good mental health because they are less exposed to adversity. Our approach to the quantification of resilience tries to exclude this potential confound. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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