The Frequent Stressor and Mental Health Monitoring-Paradigm: A Proposal for the Operationalization and Measurement of Resilience and the Identification of Resilience Processes in Longitudinal Observational Studies

Resilience has been defined as the maintenance or quick recovery of mental health during and after times of adversity. How to operationalize resilience and to determine the factors and processes that lead to good long-term mental health outcomes in stressor-exposed individuals is a matter of ongoing...

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Published inFrontiers in psychology Vol. 12; p. 710493
Main Authors Kalisch, Raffael, Köber, Göran, Binder, Harald, Ahrens, Kira F., Basten, Ulrike, Chmitorz, Andrea, Choi, Karmel W., Fiebach, Christian J., Goldbach, Nele, Neumann, Rebecca J., Kampa, Miriam, Kollmann, Bianca, Lieb, Klaus, Plichta, Michael M., Reif, Andreas, Schick, Anita, Sebastian, Alexandra, Walter, Henrik, Wessa, Michèle, Yuen, Kenneth S. L., Tüscher, Oliver, Engen, Haakon
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Media S.A 26.08.2021
Subjects
Online AccessGet full text
ISSN1664-1078
1664-1078
DOI10.3389/fpsyg.2021.710493

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Abstract Resilience has been defined as the maintenance or quick recovery of mental health during and after times of adversity. How to operationalize resilience and to determine the factors and processes that lead to good long-term mental health outcomes in stressor-exposed individuals is a matter of ongoing debate and of critical importance for the advancement of the field. One of the biggest challenges for implementing an outcome-based definition of resilience in longitudinal observational study designs lies in the fact that real-life adversity is usually unpredictable and that its substantial qualitative as well as temporal variability between subjects often precludes defining circumscribed time windows of inter-individually comparable stressor exposure relative to which the maintenance or recovery of mental health can be determined. To address this pertinent issue, we propose to frequently and regularly monitor stressor exposure (E) and mental health problems (P) throughout a study's observation period [Frequent Stressor and Mental Health Monitoring (FRESHMO)-paradigm]. On this basis, a subject's deviation at any single monitoring time point from the study sample's normative E–P relationship (the regression residual) can be used to calculate that subject's current mental health reactivity to stressor exposure (“stressor reactivity,” SR). The SR score takes into account the individual extent of experienced adversity and is comparable between and within subjects. Individual SR time courses across monitoring time points reflect intra-individual temporal variability in SR, where periods of under-reactivity (negative SR score) are associated with accumulation of fewer mental health problems than is normal for the sample. If FRESHMO is accompanied by regular measurement of potential resilience factors, temporal changes in resilience factors can be used to predict SR time courses. An increase in a resilience factor measurement explaining a lagged decrease in SR can then be considered to index a process of adaptation to stressor exposure that promotes a resilient outcome (an allostatic resilience process). This design principle allows resilience research to move beyond merely determining baseline predictors of resilience outcomes, which cannot inform about how individuals successfully adjust and adapt when confronted with adversity. Hence, FRESHMO plus regular resilience factor monitoring incorporates a dynamic-systems perspective into resilience research.
AbstractList Resilience has been defined as the maintenance or quick recovery of mental health during and after times of adversity. How to operationalize resilience and to determine the factors and processes that lead to good long-term mental health outcomes in stressor-exposed individuals is a matter of ongoing debate and of critical importance for the advancement of the field. One of the biggest challenges for implementing an outcome-based definition of resilience in longitudinal observational study designs lies in the fact that real-life adversity is usually unpredictable and that its substantial qualitative as well as temporal variability between subjects often precludes defining circumscribed time windows of inter-individually comparable stressor exposure relative to which the maintenance or recovery of mental health can be determined. To address this pertinent issue, we propose to frequently and regularly monitor stressor exposure (E) and mental health problems (P) throughout a study's observation period [Frequent Stressor and Mental Health Monitoring (FRESHMO)-paradigm]. On this basis, a subject's deviation at any single monitoring time point from the study sample's normative E–P relationship (the regression residual) can be used to calculate that subject's current mental health reactivity to stressor exposure (“stressor reactivity,” SR). The SR score takes into account the individual extent of experienced adversity and is comparable between and within subjects. Individual SR time courses across monitoring time points reflect intra-individual temporal variability in SR, where periods of under-reactivity (negative SR score) are associated with accumulation of fewer mental health problems than is normal for the sample. If FRESHMO is accompanied by regular measurement of potential resilience factors, temporal changes in resilience factors can be used to predict SR time courses. An increase in a resilience factor measurement explaining a lagged decrease in SR can then be considered to index a process of adaptation to stressor exposure that promotes a resilient outcome (an allostatic resilience process). This design principle allows resilience research to move beyond merely determining baseline predictors of resilience outcomes, which cannot inform about how individuals successfully adjust and adapt when confronted with adversity. Hence, FRESHMO plus regular resilience factor monitoring incorporates a dynamic-systems perspective into resilience research.
Resilience has been defined as the maintenance or quick recovery of mental health during and after times of adversity. How to operationalize resilience and to determine the factors and processes that lead to good long-term mental health outcomes in stressor-exposed individuals is a matter of ongoing debate and of critical importance for the advancement of the field. One of the biggest challenges for implementing an outcome-based definition of resilience in longitudinal observational study designs lies in the fact that real-life adversity is usually unpredictable and that its substantial qualitative as well as temporal variability between subjects often precludes defining circumscribed time windows of inter-individually comparable stressor exposure relative to which the maintenance or recovery of mental health can be determined. To address this pertinent issue, we propose to frequently and regularly monitor stressor exposure (E) and mental health problems (P) throughout a study's observation period [Frequent Stressor and Mental Health Monitoring (FRESHMO)-paradigm]. On this basis, a subject's deviation at any single monitoring time point from the study sample's normative E-P relationship (the regression residual) can be used to calculate that subject's current mental health reactivity to stressor exposure ("stressor reactivity," SR). The SR score takes into account the individual extent of experienced adversity and is comparable between and within subjects. Individual SR time courses across monitoring time points reflect intra-individual temporal variability in SR, where periods of under-reactivity (negative SR score) are associated with accumulation of fewer mental health problems than is normal for the sample. If FRESHMO is accompanied by regular measurement of potential resilience factors, temporal changes in resilience factors can be used to predict SR time courses. An increase in a resilience factor measurement explaining a lagged decrease in SR can then be considered to index a process of adaptation to stressor exposure that promotes a resilient outcome (an allostatic resilience process). This design principle allows resilience research to move beyond merely determining baseline predictors of resilience outcomes, which cannot inform about how individuals successfully adjust and adapt when confronted with adversity. Hence, FRESHMO plus regular resilience factor monitoring incorporates a dynamic-systems perspective into resilience research.Resilience has been defined as the maintenance or quick recovery of mental health during and after times of adversity. How to operationalize resilience and to determine the factors and processes that lead to good long-term mental health outcomes in stressor-exposed individuals is a matter of ongoing debate and of critical importance for the advancement of the field. One of the biggest challenges for implementing an outcome-based definition of resilience in longitudinal observational study designs lies in the fact that real-life adversity is usually unpredictable and that its substantial qualitative as well as temporal variability between subjects often precludes defining circumscribed time windows of inter-individually comparable stressor exposure relative to which the maintenance or recovery of mental health can be determined. To address this pertinent issue, we propose to frequently and regularly monitor stressor exposure (E) and mental health problems (P) throughout a study's observation period [Frequent Stressor and Mental Health Monitoring (FRESHMO)-paradigm]. On this basis, a subject's deviation at any single monitoring time point from the study sample's normative E-P relationship (the regression residual) can be used to calculate that subject's current mental health reactivity to stressor exposure ("stressor reactivity," SR). The SR score takes into account the individual extent of experienced adversity and is comparable between and within subjects. Individual SR time courses across monitoring time points reflect intra-individual temporal variability in SR, where periods of under-reactivity (negative SR score) are associated with accumulation of fewer mental health problems than is normal for the sample. If FRESHMO is accompanied by regular measurement of potential resilience factors, temporal changes in resilience factors can be used to predict SR time courses. An increase in a resilience factor measurement explaining a lagged decrease in SR can then be considered to index a process of adaptation to stressor exposure that promotes a resilient outcome (an allostatic resilience process). This design principle allows resilience research to move beyond merely determining baseline predictors of resilience outcomes, which cannot inform about how individuals successfully adjust and adapt when confronted with adversity. Hence, FRESHMO plus regular resilience factor monitoring incorporates a dynamic-systems perspective into resilience research.
Author Köber, Göran
Tüscher, Oliver
Schick, Anita
Kampa, Miriam
Yuen, Kenneth S. L.
Lieb, Klaus
Fiebach, Christian J.
Neumann, Rebecca J.
Reif, Andreas
Wessa, Michèle
Binder, Harald
Walter, Henrik
Basten, Ulrike
Ahrens, Kira F.
Chmitorz, Andrea
Kollmann, Bianca
Goldbach, Nele
Choi, Karmel W.
Engen, Haakon
Plichta, Michael M.
Kalisch, Raffael
Sebastian, Alexandra
AuthorAffiliation 17 Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health , Berlin , Germany
16 Department of Public Mental Health, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University , Mannheim , Germany
6 Department of Psychology, Goethe University Frankfurt , Frankfurt , Germany
15 Department of Psychology, Bender Institute of Neuroimaging, Justus Liebig University , Gießen , Germany
8 Department of Psychiatry and Psychotherapy, Johannes Gutenberg University Medical Center , Mainz , Germany
13 Brain Imaging Center, Goethe University Frankfurt , Frankfurt , Germany
14 Department of Clinical Psychology and Psychotherapy, University of Siegen , Siegen , Germany
18 Department of Clinical Psychology and Neuropsychology, Institute of Psychology, Johannes Gutenberg University , Mainz , Germany
4 Freiburg Center of Data Analysis and Modelling, Univers
AuthorAffiliation_xml – name: 12 Lee Kum Sheung Center for Health and Happiness, Harvard T.H. Chan School of Public Health , Boston, MA , United States
– name: 8 Department of Psychiatry and Psychotherapy, Johannes Gutenberg University Medical Center , Mainz , Germany
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– name: 19 Department of Psychology, University of Oslo , Oslo , Norway
– name: 7 Department of Psychology, University of Koblenz-Landau , Landau , Germany
– name: 5 Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital Frankfurt , Frankfurt , Germany
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ContentType Journal Article
Copyright Copyright © 2021 Kalisch, Köber, Binder, Ahrens, Basten, Chmitorz, Choi, Fiebach, Goldbach, Neumann, Kampa, Kollmann, Lieb, Plichta, Reif, Schick, Sebastian, Walter, Wessa, Yuen, Tüscher and Engen.
Copyright © 2021 Kalisch, Köber, Binder, Ahrens, Basten, Chmitorz, Choi, Fiebach, Goldbach, Neumann, Kampa, Kollmann, Lieb, Plichta, Reif, Schick, Sebastian, Walter, Wessa, Yuen, Tüscher and Engen. 2021 Kalisch, Köber, Binder, Ahrens, Basten, Chmitorz, Choi, Fiebach, Goldbach, Neumann, Kampa, Kollmann, Lieb, Plichta, Reif, Schick, Sebastian, Walter, Wessa, Yuen, Tüscher and Engen
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– notice: Copyright © 2021 Kalisch, Köber, Binder, Ahrens, Basten, Chmitorz, Choi, Fiebach, Goldbach, Neumann, Kampa, Kollmann, Lieb, Plichta, Reif, Schick, Sebastian, Walter, Wessa, Yuen, Tüscher and Engen. 2021 Kalisch, Köber, Binder, Ahrens, Basten, Chmitorz, Choi, Fiebach, Goldbach, Neumann, Kampa, Kollmann, Lieb, Plichta, Reif, Schick, Sebastian, Walter, Wessa, Yuen, Tüscher and Engen
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Keywords homeostasis
stress
adversity
mental health
allostasis
adaptation
dynamic system
coping
Language English
License Copyright © 2021 Kalisch, Köber, Binder, Ahrens, Basten, Chmitorz, Choi, Fiebach, Goldbach, Neumann, Kampa, Kollmann, Lieb, Plichta, Reif, Schick, Sebastian, Walter, Wessa, Yuen, Tüscher and Engen.
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This article was submitted to Health Psychology, a section of the journal Frontiers in Psychology
Edited by: Hyemin Han, University of Alabama, United States
These authors have contributed equally to this work
Reviewed by: David M. Lyons, Stanford University, United States; John Grych, Marquette University, United States; Dawn Carr, Florida State University, United States
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Snippet Resilience has been defined as the maintenance or quick recovery of mental health during and after times of adversity. How to operationalize resilience and to...
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SubjectTerms adaptation
adversity
allostasis
homeostasis
mental health
Psychology
stress
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Title The Frequent Stressor and Mental Health Monitoring-Paradigm: A Proposal for the Operationalization and Measurement of Resilience and the Identification of Resilience Processes in Longitudinal Observational Studies
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