Psycho-social factors associated with mental resilience in the Corona lockdown

Ilya M Veer, Antje Riepenhausen, Matthias Zerban, Carolin Wackerhagen, Lara M C Puhlmann, Haakon Engen, Göran Köber, Sophie A Bögemann, Jeroen Weermeijer, Aleksandra Uściłko, Netali Mor, Marta A Marciniak, Adrian Dahl Askelund, Abbas Al-Kamel, Sarah Ayash, Giulia Barsuola, Vaida Bartkute-Norkuniene, Simone Battaglia, Yaryna Bobko, Sven Bölte, Paolo Cardone, Edita Chvojková, Kaja Damnjanović, Joana De Calheiros Velozo, Lena de Thurah, Yacila I Deza-Araujo, Annika Dimitrov, Kinga Farkas, Clémence Feller, Mary Gazea, Donya Gilan, Vedrana Gnjidić, Michal Hajduk, Anu P Hiekkaranta, Live S Hofgaard, Laura Ilen, Zuzana Kasanova, Mohsen Khanpour, Bobo Hi Po Lau, Dionne B Lenferink, Thomas B Lindhardt, Dávid Á Magas, Julian Mituniewicz, Laura Moreno-López, Sofiia Muzychka, Maria Ntafouli, Aet O'Leary, Ilenia Paparella, Nele Põldver, Aki Rintala, Natalia Robak, Anna M Rosická, Espen Røysamb, Siavash Sadeghi, Maude Schneider, Roma Siugzdaite, Mirta Stantić, Ana Teixeira, Ana Todorovic, Wendy W N Wan, Rolf van Dick, Klaus Lieb, Birgit Kleim, Erno J Hermans, Dorota Kobylińska, Talma Hendler, Harald Binder, Inez Myin-Germeys, Judith M C van Leeuwen, Oliver Tüscher, Kenneth S L Yuen, Henrik Walter, Raffael Kalisch, Ilya M Veer, Antje Riepenhausen, Matthias Zerban, Carolin Wackerhagen, Lara M C Puhlmann, Haakon Engen, Göran Köber, Sophie A Bögemann, Jeroen Weermeijer, Aleksandra Uściłko, Netali Mor, Marta A Marciniak, Adrian Dahl Askelund, Abbas Al-Kamel, Sarah Ayash, Giulia Barsuola, Vaida Bartkute-Norkuniene, Simone Battaglia, Yaryna Bobko, Sven Bölte, Paolo Cardone, Edita Chvojková, Kaja Damnjanović, Joana De Calheiros Velozo, Lena de Thurah, Yacila I Deza-Araujo, Annika Dimitrov, Kinga Farkas, Clémence Feller, Mary Gazea, Donya Gilan, Vedrana Gnjidić, Michal Hajduk, Anu P Hiekkaranta, Live S Hofgaard, Laura Ilen, Zuzana Kasanova, Mohsen Khanpour, Bobo Hi Po Lau, Dionne B Lenferink, Thomas B Lindhardt, Dávid Á Magas, Julian Mituniewicz, Laura Moreno-López, Sofiia Muzychka, Maria Ntafouli, Aet O'Leary, Ilenia Paparella, Nele Põldver, Aki Rintala, Natalia Robak, Anna M Rosická, Espen Røysamb, Siavash Sadeghi, Maude Schneider, Roma Siugzdaite, Mirta Stantić, Ana Teixeira, Ana Todorovic, Wendy W N Wan, Rolf van Dick, Klaus Lieb, Birgit Kleim, Erno J Hermans, Dorota Kobylińska, Talma Hendler, Harald Binder, Inez Myin-Germeys, Judith M C van Leeuwen, Oliver Tüscher, Kenneth S L Yuen, Henrik Walter, Raffael Kalisch

Abstract

The SARS-CoV-2 pandemic is not only a threat to physical health but is also having severe impacts on mental health. Although increases in stress-related symptomatology and other adverse psycho-social outcomes, as well as their most important risk factors have been described, hardly anything is known about potential protective factors. Resilience refers to the maintenance of mental health despite adversity. To gain mechanistic insights about the relationship between described psycho-social resilience factors and resilience specifically in the current crisis, we assessed resilience factors, exposure to Corona crisis-specific and general stressors, as well as internalizing symptoms in a cross-sectional online survey conducted in 24 languages during the most intense phase of the lockdown in Europe (22 March to 19 April) in a convenience sample of N = 15,970 adults. Resilience, as an outcome, was conceptualized as good mental health despite stressor exposure and measured as the inverse residual between actual and predicted symptom total score. Preregistered hypotheses (osf.io/r6btn) were tested with multiple regression models and mediation analyses. Results confirmed our primary hypothesis that positive appraisal style (PAS) is positively associated with resilience (p < 0.0001). The resilience factor PAS also partly mediated the positive association between perceived social support and resilience, and its association with resilience was in turn partly mediated by the ability to easily recover from stress (both p < 0.0001). In comparison with other resilience factors, good stress response recovery and positive appraisal specifically of the consequences of the Corona crisis were the strongest factors. Preregistered exploratory subgroup analyses (osf.io/thka9) showed that all tested resilience factors generalize across major socio-demographic categories. This research identifies modifiable protective factors that can be targeted by public mental health efforts in this and in future pandemics.

Conflict of interest statement

The authors declare to have no direct conflicts of interest related to this article. S.B. has in the last 3 years acted as an author, consultant, or lecturer for Medice and Roche. He receives royalties for text books and diagnostic tools from Hogrefe, Kohlhammer and UTB. T.H. is a chief medical scientist for GrayMatters Health Co., Haifa, Israel. R.K. receives advisory honoraria from JoyVentures, Herzlia, Israel.

Figures

Fig. 1. Associations of hypothesized resilience factors…
Fig. 1. Associations of hypothesized resilience factors with outcome-based resilience (RES) and mediation effects.
A Multiple regressions with covariates of resilience factors on resilience, calculated separately for each factor. Shown are the regression coefficients (β) and 99% confidence intervals (CI). Effects are similar for resilience to all stressors combined (RESC), resilience to general (RESG), and resilience to Corona-specific stressors (RESS). Resilience factors: PAS, positive appraisal style; PSS, perceived social support; CSS, perceived increase in social support during the Corona crisis; OPT, optimism; GSE, perceived general self-efficacy; REC, perceived good stress recovery; NEU, neuroticism; BCS, behavioral coping style; PAC, positive appraisal specifically of the Corona crisis. B Mediation analyses testing if the positive association of PSS with RESC is mediated by PAS (top) and if the positive association of PAS on RESC is mediated by REC (bottom). Shown are β of all paths. Indirect path a × b: β with 99% CI. ***p < 0.0001.
Fig. 2. Combined multi-variable analysis (LASSO) of…
Fig. 2. Combined multi-variable analysis (LASSO) of the relative associations of resilience factors and covariates with resilience (RESC).
To identify the strongest of the partly correlated resilience factors, sparse regression was performed with an optimal penalty term λ (vertical broken line), as determined by cross-validation. Resilience factors are indicated in color, covariates in gray. The initial position of a curve on the y-axis signifies the association of the corresponding resilience factor or covariate with RESC in the case of very low penalization. By increasing λ (x-axis), regression coefficients (β) get increasingly drawn to zero, to leave only the strongest associations. The order of resilience factors in the color legend corresponds to their determined relative strengths (absolute values) at optimal λ (broken line). Except for BCS (behavioral coping style), all resilience factors were selected in all 800 repeated LASSO runs, indicating strong replication stability.

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