COVID-19 Concerns, Information Needs, and Adverse Mental Health Outcomes among U.S. Soldiers
Notice bibliographique
Résumé
INTRODUCTION: The coronavirus disease 2019 (COVID-19) pandemic disrupted U.S. Military operations and potentially compounded the risk for adverse mental health outcomes by layering unique occupational stress on top of general restrictions, fears, and concerns. The objective of the current study was to characterize the prevalence of COVID-19 concerns and information needs, demographic disparities in these outcomes, and the degree to which COVID-19 concerns and information needs were associated with heightened risk for adverse mental health outcomes among U.S. Army soldiers. MATERIALS AND METHODS: Command-directed anonymous surveys were administered electronically to U.S. soldiers assigned to one of three regional commands in the Northwest United States, Europe, and Asia-Pacific Region. Surveys were administered in May to June 2020 to complete (time 1: n = 21,294) and again in December 2020 to January 2021 (time 2: n = 10,861). Only active duty or active reservists/national guard were eligible to participate. Members from other branches of service were also not eligible. RESULTS: Highly prevalent COVID-19 concerns included the inability to spend time with friends/family, social activities, and changing rules, regulations, and guidance related to COVID-19. Some information needs were endorsed by one quarter or more soldiers at both time points, including stress management/coping, travel, how to protect oneself, and maintaining mission readiness. COVID-19 concerns and information needs were most prevalent among non-White soldiers. Concerns and information needs did not decline overall between the assessments. Finally, COVID-19 concerns were associated with greater risk of multiple adverse mental health outcomes at both time points. CONCLUSIONS: COVID-19 concerns and information needs were prevalent and showed little evidence of decrement over the course of the first 6 months of the pandemic. COVID-19 concerns were consistently associated with adverse mental health outcomes. These data highlight two targets and potential demographic subgroups such that local leadership and Army medicine and public health enterprises can be better prepared to monitor and address to maintain force health and readiness in the face of possible future biomedical threats.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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) | 0,000 | 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 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».