Trends in psychotropic drug consumption among French military personnel during the COVID-19 epidemic
Notice bibliographique
Résumé
BACKGROUND: The coronavirus disease (COVID-19) pandemic may have had significant mental health consequences for military personnel, which is a population already exposed to psychological stress. To assess the potential impact of the COVID-19 pandemic, we analyzed the dispensing of three classes of psychotropic drugs (anxiolytics, hypnotics, and antidepressants) among French military personnel. METHODS: A retrospective analysis was conducted using the individualized medico-administrative data of persons insured by the National Military Social Security Fund from the National Health Data System. All active French military personnel aged 18-64 who received outpatient care and to whom drugs were dispensed between January 1, 2019, and April 30, 2021, were included from the French national health database. Rate ratios of dispensed anxiolytics, hypnotics and antidepressants (based on drug reimbursement) were estimated from negative binomial regressions before and after the start of the COVID-19 pandemic. RESULTS: Three hundred eighty-one thousand seven hundred eleven individuals were included. Overall, 45,148 military personnel were reimbursed for anxiolytics, 10,637 for hypnotics, and 4328 for antidepressants. Drugs were dispensed at a higher rate in 2020 and 2021 than in 2019. There was a notable peak at the beginning of the first lockdown followed by a decrease limited to the duration of the first lockdown. During the first lockdown only, there were temporary phenomena including a brief increase in drug dispensing during the first week followed by a decrease during the rest of lockdown, possibly corresponding to a stocking-up effect. For the study period overall, while there was a significant downward trend in psychotropic drug dispensing before the occurrence of COVID-19 (p < 0.001), the pandemic period was associated with an increase in dispensed anxiolytics (rate ratio, 1.03; 95% CI, 1.02-1.04, p < 0.05), hypnotics (rate ratio, 1.13; 95% CI, 1.11-1.16, p < 0.001) and antidepressants (rate ratio, 1.12; 95% CI, 1.10-1.13, p < 0.001) in the military population. CONCLUSIONS: The COVID-19 pandemic has probably had a significant impact on the mental health of French military personnel, as suggested by the trends in dispensed psychotropic drugs. The implementation of mental health prevention measures should be investigated for this population.
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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) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,016 | 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 ».