Emotional symptoms, mental fatigue and behavioral adherence after 72 continuous days of strict lockdown during the COVID-19 pandemic in Argentina
Notice bibliographique
Résumé
Abstract Background An early, total, and prolonged lockdown was adopted in Argentina during the first wave of COVID-19 as the main sanitary strategy to reduce the spread of the virus in the population. The aim of this study was to explore emotional symptoms, mental fatigue, and behavioral adherence associated with the COVID-19 pandemic after an average of 72 days of continuous lockdown in Argentina. Specifically, we intended to know: 1) if the prolongation of the lockdown was associated with elevated emotional symptoms; 2) if the prolonged lockdown affected adherence, a phenomenon called “behavioral fatigue”; and 3) how financial concerns in a developing country affected adherence to the lockdown and emotional status of the population. Method A survey was designed to evaluate the psychological impact of the pandemic and lockdown. The survey included standardized questionnaires to assess the severity of depressive (PHQ-9) and anxious (GAD-7) symptoms, a questionnaire to evaluate mental fatigue, and several additional instruments to assess other variables of interest: risk perception, lockdown adherence, financial concerns, daily stress, loneliness, intolerance to uncertainty, negative repetitive thinking, and cognitive problems. Three LASSO regression analyses were carried to evaluate the predictive role of the different variables over depression, anxiety, and lockdown adherence Results The survey was responded by 3617 individuals over the age of 18 (85.2% female) from all the provinces of Argentina. Using the Oxford stringency index, Argentina had one of the most stringent and prolonged lockdowns when the sample was collected with 63 to 77 continuous days with a stringency index of more than 85/100. 45.6% of the sample met the cut-off for depression and 27% for anxiety. Previous mental health treatment, low income, being younger, and being female were associated with higher levels of emotional symptoms. Mental fatigue, cognitive failures, and financial concerns were also associated with emotional and subjective complaints, but not with adherence to the lockdown. In the regression models, mental fatigue, cognitive failures, and loneliness were the most important variables to predict depression, meanwhile intolerance to uncertainty and lockdown difficulty were the most important in the case of anxiety. Perceived threat was the most important variable predicting lockdown adherence. Conclusions Emotional symptoms persisted and even increased during the extended lockdown, but we found no evidence of behavioral fatigue. Instead, mental fatigue, cognitive difficulties, and financial concerns were expressions of the emotional side of the pandemic and the restrictive measures.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 tête enseignante, 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 ».