STRESS, ANXIETY AND PTSD PREVALENCE AMONG UKRAINIANS GREW DRAMATICALLY DURING THE FIRST YEAR OF RUSSIAN INVASION: RESULTS OF NATIONWIDE SURVEY
Notice bibliographique
Résumé
Abstract Background In February 2022 the Russian federation started a new invasion of Ukraine as an escalation of the ongoing war since 2014. After nine years of war and the COVID-19 pandemic, the mental health state of Ukrainians requires systematic monitoring and relevant action. Methods This study was designed as an online survey arranged in the 9-12 months after the start of the new invasion of Ukraine and includes sociodemographic data collection, evaluation of stress intensity by PSS-10, anxiety with GAD-7, and symptoms of posttraumatic stress disorder with PCL-5. The sample size of 3173 Ukrainians consisted of 1954 (61.6%) respondents that were not displaced persons (NDPs), 505 (15.9%) internally displaced persons within Ukraine (IDPs), and 714 (22.5%) refugees that left Ukraine. Findings Moderate and high stress was prevalent among 64.7% and 15.5% of NDPs, 64.4% and 21.6% of IDPs, and 68.2% and 25.2% of refugees, respectively. Moderate and severe anxiety was prevalent among 25.6% and 19.0% of NDPs, 25.7% and 23.4% of IDPs, and 26.2% and 25.8% of refugees. High levels of PTSD (33 and higher) were prevalent among 32.8% of NDPs, 39.4% of IDPs, and 47.2% of refugees. DSM-V criteria for PTSD diagnosis was met by 50.8% of NDPs, 55.4% of IDPs, and 62.2% of refugees. Interpretations The lowest stress, anxiety, and PTSD severity was observed among NDPs, with significantly higher levels among IDPs and the highest among refugees. Being forcibly displaced from the previous living area and, especially, entering a new cultural environment significantly contributes to the mental health issues caused by war exposure, particularly for people who have directly witnessed the results of war. Fundings Ministry of Education and Science of Ukraine Research in context Evidence before this study Previously published evidence suggested an increase and specificity of stress, anxiety, and PTSD prevalence among Ukrainians by August 2022. Some research provided a data comparison between IDPs and refugees. However, to date, no study has reported a comparison of three groups of Ukrainians: NDPs, IDPs, and refugees abroad. Added value of this study This is the first study that provides evidence of the mental health state of Ukrainians after 9-12 months of the Russian invasion in 2022. Furthermore, the research presented was designed as a nationwide survey involving three groups for comparison: NDPs and IDPs within Ukraine, and refugees in other countries. The results of the study show a significant difference between these groups in stress, anxiety, and prevalence of PTSD symptoms. Implications of all available evidence The present study contributes to the comprehension of the dynamics in mental health of Ukrainians in response to the war. This data will be helpful both in mental health strategy development by governmental and international policy and in the local clinical work of mental health professionals working with Ukrainians.
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 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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| 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 | 0,000 |
| 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 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 ».