Risk factors for mental health symptoms during the COVID-19 pandemic in ophthalmic personnel and students in USA (& Canada): a cross-sectional survey study
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
BACKGROUND: The COVID-19 pandemic poses mental health challenges to frontline healthcare workers. Eye care professionals may be especially susceptible to mental health problems due to high-risk exposures to patients. Yet, no prior research has studied mental health issues among eye care professionals during the COVID-19 pandemic. OBJECTIVE: The purpose of this study was to identify risk factors for mental health problems during the COVID-19 pandemic among eye care professionals. METHODS: We conducted a cross-sectional survey study among eye care professionals and students in the United States and Canada from June 23 to July 8, 2020 during the COVID-19 pandemic. A total of 8505 eye care professionals and students received email invitations to the survey and 2134 participated. We measured mental health outcomes including symptoms of depression, anxiety, and stress using validated scales, as well as potential risk factors including demographic characteristics, state-level COVID-19 case counts, participants' patient interactions, childcare responsibilities, and pre-pandemic stress levels. Linear multiple regression and logistic regression analyses were used to determine relationships between risk factors and mental health outcomes. RESULTS: We found that 38.4% of eyecare professional participants in the survey met screening threshold as probable cases of anxiety, depression, or both during the COVID-19 pandemic. Controlling for self-reported pre-pandemic stress level and state COVID-19 case daily cases, significant risk factors for depression, anxiety, and psychological stress during the COVID-19 pandemic included: being female, younger age, and being Black or Asian. Interestingly, we found two somewhat surprising protective factors against depression symptoms: more frequent interactions with patients and having a greater proportion of childcare responsibilities at home. CONCLUSIONS: This study showed a high prevalence of mental health problems and revealed disparities in mental health among eye care personnel and students: Female, younger, Black, and Asian populations are particularly vulnerable to mental health issues. These results indicate that it is critical to identify mental health issues more effectively and develop interventions among this population to address this significant and growing public health issue. The strategies and policies should be reflective of the demographic disparities in this vulnerable population.
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.
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) | 0,000 | 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 découle