Psychological Network Analysis of General Self-Efficacy in High vs. Low Resilient Functioning Healthy Adults
- Publikationstyp:
- Zeitschriftenaufsatz
- Metadaten:
-
- Autoren
- Katja Schueler
- Jessica Fritz
- Lena Dorfschmidt
- Anne-Laura van Harmelen
- Eike Stroemer
- Michele Wessa
- Autoren-URL
- https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=fis-test-1&SrcAuth=WosAPI&KeyUT=WOS:000726131200001&DestLinkType=FullRecord&DestApp=WOS_CPL
- DOI
- 10.3389/fpsyt.2021.736147
- Externe Identifier
- Clarivate Analytics Document Solution ID: XI5DE
- PubMed Identifier: 34867526
- ISSN
- 1664-0640
- Zeitschrift
- FRONTIERS IN PSYCHIATRY
- Schlüsselwörter
- resilience
- network analysis
- self-efficacy
- connectivity
- partial least squares regression
- Artikelnummer
- ARTN 736147
- Datum der Veröffentlichung
- 2021
- Status
- Published
- Titel
- Psychological Network Analysis of General Self-Efficacy in High vs. Low Resilient Functioning Healthy Adults
- Sub types
- Article
- Ausgabe der Zeitschrift
- 12
Datenquelle: Web of Science (Lite)
- Andere Metadatenquellen:
-
- Abstract
- <jats:p>Resilience to stress has gained increasing interest by researchers from the field of mental health and illness and some recent studies have investigated resilience from a network perspective. General self-efficacy constitutes an important resilience factor. High levels of self-efficacy have shown to promote resilience by serving as a stress buffer. However, little is known about the role of network connectivity of self-efficacy in the context of stress resilience. The present study aims at filling this gap by using psychological network analysis to study self-efficacy and resilience. Based on individual resilient functioning scores, we divided a sample of 875 mentally healthy adults into a high and low resilient functioning group. To compute these scores, we applied a novel approach based on Partial Least Squares Regression on self-reported stress and mental health measures. Separately for both groups, we then estimated regularized partial correlation networks of a ten-item self-efficacy questionnaire. We compared three different global connectivity measures–strength, expected influence, and shortest path length–as well as absolute levels of self-efficacy between the groups. Our results supported our hypothesis that stronger network connectivity of self-efficacy would be present in the highly resilient functioning group compared to the low resilient functioning group. In addition, the former showed higher absolute levels of general self-efficacy. Future research could consider using partial least squares regression to quantify resilient functioning to stress and to study the association between network connectivity and resilient functioning in other resilience factors.</jats:p>
- Autoren
- Katja Schueler
- Jessica Fritz
- Lena Dorfschmidt
- Anne-Laura van Harmelen
- Eike Stroemer
- Michèle Wessa
- DOI
- 10.3389/fpsyt.2021.736147
- eISSN
- 1664-0640
- Zeitschrift
- Frontiers in Psychiatry
- Online publication date
- 2021
- Status
- Published online
- Herausgeber
- Frontiers Media SA
- Herausgeber URL
- http://dx.doi.org/10.3389/fpsyt.2021.736147
- Datum der Datenerfassung
- 2021
- Titel
- Psychological Network Analysis of General Self-Efficacy in High vs. Low Resilient Functioning Healthy Adults
- Ausgabe der Zeitschrift
- 12
Datenquelle: Crossref
- Abstract
- Resilience to stress has gained increasing interest by researchers from the field of mental health and illness and some recent studies have investigated resilience from a network perspective. General self-efficacy constitutes an important resilience factor. High levels of self-efficacy have shown to promote resilience by serving as a stress buffer. However, little is known about the role of network connectivity of self-efficacy in the context of stress resilience. The present study aims at filling this gap by using psychological network analysis to study self-efficacy and resilience. Based on individual resilient functioning scores, we divided a sample of 875 mentally healthy adults into a high and low resilient functioning group. To compute these scores, we applied a novel approach based on Partial Least Squares Regression on self-reported stress and mental health measures. Separately for both groups, we then estimated regularized partial correlation networks of a ten-item self-efficacy questionnaire. We compared three different global connectivity measures-strength, expected influence, and shortest path length-as well as absolute levels of self-efficacy between the groups. Our results supported our hypothesis that stronger network connectivity of self-efficacy would be present in the highly resilient functioning group compared to the low resilient functioning group. In addition, the former showed higher absolute levels of general self-efficacy. Future research could consider using partial least squares regression to quantify resilient functioning to stress and to study the association between network connectivity and resilient functioning in other resilience factors.
- Addresses
- Department of Clinical Psychology and Neuropsychology, Institute of Psychology, Johannes Gutenberg-University of Mainz, Mainz, Germany.
- Autoren
- Katja Schueler
- Jessica Fritz
- Lena Dorfschmidt
- Anne-Laura van Harmelen
- Eike Stroemer
- Michèle Wessa
- DOI
- 10.3389/fpsyt.2021.736147
- eISSN
- 1664-0640
- Externe Identifier
- PubMed Identifier: 34867526
- PubMed Central ID: PMC8635703
- Funding acknowledgements
- Medical Research Foundation: MRF-160-0007-ELP-VANHA
- Medical Research Council: 1800905
- MRF: MRF_MRF-160-0007-ELP-VANHA
- Open access
- true
- ISSN
- 1664-0640
- Zeitschrift
- Frontiers in psychiatry
- Sprache
- eng
- Medium
- Electronic-eCollection
- Online publication date
- 2021
- Open access status
- Open Access
- Paginierung
- 736147
- Datum der Veröffentlichung
- 2021
- Status
- Published
- Publisher licence
- CC BY
- Datum der Datenerfassung
- 2021
- Titel
- Psychological Network Analysis of General Self-Efficacy in High vs. Low Resilient Functioning Healthy Adults.
- Sub types
- research-article
- Journal Article
- Ausgabe der Zeitschrift
- 12
Files
https://europepmc.org/articles/PMC8635703?pdf=render
Datenquelle: Europe PubMed Central
- Abstract
- Resilience to stress has gained increasing interest by researchers from the field of mental health and illness and some recent studies have investigated resilience from a network perspective. General self-efficacy constitutes an important resilience factor. High levels of self-efficacy have shown to promote resilience by serving as a stress buffer. However, little is known about the role of network connectivity of self-efficacy in the context of stress resilience. The present study aims at filling this gap by using psychological network analysis to study self-efficacy and resilience. Based on individual resilient functioning scores, we divided a sample of 875 mentally healthy adults into a high and low resilient functioning group. To compute these scores, we applied a novel approach based on Partial Least Squares Regression on self-reported stress and mental health measures. Separately for both groups, we then estimated regularized partial correlation networks of a ten-item self-efficacy questionnaire. We compared three different global connectivity measures-strength, expected influence, and shortest path length-as well as absolute levels of self-efficacy between the groups. Our results supported our hypothesis that stronger network connectivity of self-efficacy would be present in the highly resilient functioning group compared to the low resilient functioning group. In addition, the former showed higher absolute levels of general self-efficacy. Future research could consider using partial least squares regression to quantify resilient functioning to stress and to study the association between network connectivity and resilient functioning in other resilience factors.
- Date of acceptance
- 2021
- Autoren
- Katja Schueler
- Jessica Fritz
- Lena Dorfschmidt
- Anne-Laura van Harmelen
- Eike Stroemer
- Michèle Wessa
- Autoren-URL
- https://www.ncbi.nlm.nih.gov/pubmed/34867526
- DOI
- 10.3389/fpsyt.2021.736147
- Externe Identifier
- PubMed Central ID: PMC8635703
- Funding acknowledgements
- MRF: MRF_MRF-160-0007-ELP-VANHA
- ISSN
- 1664-0640
- Zeitschrift
- Front Psychiatry
- Schlüsselwörter
- connectivity
- network analysis
- partial least squares regression
- resilience
- self-efficacy
- Sprache
- eng
- Country
- Switzerland
- Paginierung
- 736147
- Datum der Veröffentlichung
- 2021
- Status
- Published online
- Titel
- Psychological Network Analysis of General Self-Efficacy in High vs. Low Resilient Functioning Healthy Adults.
- Sub types
- Journal Article
- Ausgabe der Zeitschrift
- 12
Datenquelle: PubMed
- Author's licence
- CC-BY
- Autoren
- Katja Schueler
- Jessica Fritz
- Lena Dorfschmidt
- Anne-Laura van Harmelen
- Eike Stroemer
- Michèle Wessa
- Hosting institution
- Universitätsbibliothek Mainz
- Sammlungen
- JGU-Publikationen
- Resource version
- Published version
- DOI
- 10.3389/fpsyt.2021.736147
- Funding acknowledgements
- Open Access-Publizieren Universität Mainz / Universitätsmedizin Mainz
- File(s) embargoed
- false
- Open access
- true
- ISSN
- 1664-0640
- Zeitschrift
- Frontiers in psychiatry
- Schlüsselwörter
- 150 Psychologie
- 150 Psychology
- Sprache
- eng
- Open access status
- Open Access
- Paginierung
- 736147
- Datum der Veröffentlichung
- 2021
- Public URL
- https://openscience.ub.uni-mainz.de/handle/20.500.12030/6850
- Herausgeber
- Frontiers Research Foundation
- Datum der Datenerfassung
- 2022
- Datum, an dem der Datensatz öffentlich gemacht wurde
- 2022
- Zugang
- Public
- Titel
- Psychological network analysis of general self-efficacy in high vs. low resilient Functioning healthy adults
- Ausgabe der Zeitschrift
- 12
Files
psychological_network_analysi-20220322105718112.pdf
Datenquelle: OPENSCIENCE.UB
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