CovSocial Phase 2 – Investigating differential effects of socio-emotional versus mindfulness-based online trainings on acute stress reactions in psychosocial Trier Social Stress Test (TSST) during the Covid19-Pandemic
Notice bibliographique
Résumé
This investigation of differential effects of online mental trainings on acute psychosocial stress reactions is embedded in the CovSocial project, which consists of two phases. Phase 1 of the CovSocial project (www.covsocial.de) focused on longitudinal changes in a variety of markers of vulnerability, resilience and social cohesion during the SARS-CoV-2 pandemic (osf.io/jvb98). Phase 2 of the CovSocial project investigates and compares the effectiveness of two online mental interventions in reducing stress and loneliness and increasing psychological well-being, prosocial behavior and social competencies in a subsample of the first phase (osf.io/3nsjc). Phase 2 participants were split up in three groups, of which two groups are each undergoing one of two 10-week interventions, that is, approximatively n=100 participants are undergoing a socio-emotional training and n=100 participants are undergoing a mindfulness-based training. Additionally, there is a retest control group of n=100 participants without training during the first 10 weeks, who will receive the socio-emotional training of 10 weeks after the other intervention groups have completed their posttest (see Figure 1). The standardized psychosocial stress test, Trier Social Stress Test (TSST; Kirschbaum et al., 1993) will be conducted as part of the phase 2 posttest. The additional implementation of the TSST is intended to complement the CovSocial project with findings regarding the acute stress response in psychosocial situations. The TSST is worldwide considered as a standard protocol for the induction of psychological stress under controlled conditions and has been routinely performed for over 20 years in numerous countries, most notably Germany, the USA, and Canada. Empirical studies on the impact of the SARS-CoV-2-pandemic have shown that there has been an increase in mental health problems in the general population (Dubey et al., 2020; Vindegaard & Benros, 2020; Xiong et al., 2020). Particularly, the related governmental restrictions of social interactions throughout lockdowns can be assumed to impose psychosocial stress, amplifying the impact of the pandemic on psychological well-being and mental health (Vinkers et al., 2020) Previously, it has been shown that mental training can be an effective way to reduce acute stress responses in psychosocial stressful situations (Engert et al., 2017; Morton et al., 2020). However, previous findings have been inconclusive in this regard (Creswell et al., 2014; Hoge et al., 2013), which has been attributed to differences in the type and duration of interventions (Morton et al., 2020). It was shown that especially those procedures in which social skills are trained, such as by the socio-emotional training developed by Singer et al. (2016), can be an effective way to reduce stress reactions in psychosocial stress situations (Engert et al., 2017). To test the effect of a socio-emotional training on psychosocial stress in the context of the SARS-CoV-2 pandemic, it is planed that n = 120 participants from phase 1 and 2 will take part at the TSST. This subsample consists of n = 40 participants who did the socio-emotional training, n = 40 participants who did the mindfulness training and n = 40 people from phase 1 who didn’t participate in any training and who will be used as a control group. During the TSST, psychological and biological parameters will be recorded from the subjects. Psychological data will be collected using questionnaires to be completed in the laboratory before and after the stress induction. Biological markers include saliva samples before and after the induced stress, which can be used to measure cortisol levels.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».