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Enregistrement W3034296587 · doi:10.1101/2020.06.13.20128694

Comparison of Mental Health Symptoms Prior to and During COVID-19 among Patients with Systemic Sclerosis from Four Countries: A Scleroderma Patient-centered Intervention Network (SPIN) Cohort Study

2020· preprint· en· W3034296587 sur OpenAlexafffundabout
Brett D. Thombs, Linda Kwakkenbos, Richard S. Henry, Marie‐Eve Carrier, Scott B. Patten, Sami Harb, Angelica Bourgeault, Lydia Tao, Susan J. Bartlett, Luc Mouthon, John Varga, Andrea Benedetti

Notice bibliographique

RevuemedRxiv · 2020
Typepreprint
Langueen
DomaineMedicine
ThématiqueSystemic Sclerosis and Related Diseases
Établissements canadiensAlberta Children's HospitalMcGill University Health CentreUniversity of CalgaryMcGill UniversityJewish General Hospital
Organismes subventionnairesMcGill University
Mots-clésMinimal clinically important differenceMedicineAnxietyDepression (economics)Odds ratioCohortConfidence intervalMental healthHospital Anxiety and Depression ScalePatient Health QuestionnairePhysical therapyLogistic regressionOddsDemographyPsychiatryInternal medicineRandomized controlled trialDepressive symptoms

Résumé

récupéré en direct d'OpenAlex

ABSTRACT Background No studies have reported comparisons of mental health symptoms prior to and during COVID-19 in vulnerable populations. Objectives were to compare anxiety and depression symptoms among people with a pre-existing medical condition, the autoimmune disease systemic sclerosis (SSc; scleroderma), including continuous change scores, proportion with change ≥ 1 minimal clinically important difference (MCID), and factors associated with changes, including country. Methods Pre-COVID-19 Scleroderma Patient-centered Intervention Network Cohort data were linked to COVID-19 data collected April 9 to April 27, 2020. Anxiety symptoms were assessed with the PROMIS Anxiety 4a v1.0 scale (MCID = 4 points) and depression symptoms with the Patient Health Questionnaire-8 (MCID = 3 points). Multiple linear and logistic regression were used to assess factors associated with continuous change and change ≥ 1 MCID. Findings Among 435 participants (Canada = 98; France = 159; United Kingdom = 50; United States = 128), mean anxiety symptoms increased 4.9 points (95% confidence interval [CI] 4.0 to 5.7). Depression symptom change was negligible (0.3 points; 95% CI −0.7 to 0.2). Compared to France, adjusted scores from the United States and United Kingdom were 3.8 points (95% CI 1.7 to 5.9) and 2.9 points higher (95% CI 0.0 to 5.7); scores for Canada were not significantly different. Odds of increasing by ≥ 1 MCID were twice as high for the United Kingdom (2.0, 95% CI 1.0 to 4.2) and United States (1.9, 95% CI 1.1 to 3.2). Participants who used mental health services pre-COVID had adjusted increases 3.7 points (95% CI 1.7 to 5.7) less than other participants. Interpretation Anxiety symptoms, but not depression symptoms, increased dramatically during COVID-19 among people with a pre-existing medical condition. Increase was larger in the United Kingdom and United States than in Canada and France but substantially less for people with pre-COVID-19 mental health treatment. RESEARCH IN CONTEXT Evidence before this study We referred to a living systematic review that is evaluating mental health changes from pre-COVID-19 to COVID-19 by searching 7 databases, including 2 Chinese language databases, plus preprint servers, with daily updates ( https://www.depressd.ca/covid-19-mental-health ). As of June 13, 2020, only 5 studies had compared mental health symptoms prior to and during COVID-19. In 4 studies of university students, there were small increases in depression or general mental health symptoms but minimal or no increases in anxiety symptoms. A general population study from the United Kingdom reported a small increase in general mental health symptoms but did not differentiate between types of symptoms. No studies have reported changes from pre-COVID-19 among people vulnerable due to pre-existing medical conditions. No studies have compared mental health changes between countries, despite major differences in pandemic responses. Added value of this study We evaluated changes in anxiety and depression symptoms among 435 participants with the autoimmune condition systemic sclerosis and compared results from Canada, France, the United Kingdom, and the United States. To our knowledge, this is the first study to compare mental health symptoms prior to and during COVID-19 in any vulnerable population. These are the first data to document the substantial degree to which anxiety symptoms have increased and the minimal changes in depression symptoms among vulnerable individuals. It is also the first study to examine the association of symptom changes with country of residence and to identify that people receiving pre-COVID-19 mental health services may be more resilient and experience less substantial symptom increases than others. Implications of all the available evidence Although this was an observational study, it provided evidence that vulnerable people with a pre-existing medical condition have experienced substantially increased anxiety symptoms and that these increases appear to be associated with where people live and, possibly, different experiences of the COVID-19 pandemic across countries. By comparing with evidence from university samples, which found that depression symptoms were more prominent, these data underline the need for accessible interventions tailored to specific needs of different populations. They also suggest that mental health treatments may help people to develop skills or create resilience, which may reduce vulnerability to major stressors such as COVID-19.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,078
Score d'incertitude au seuil0,156

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,003
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0010,000
Communication savante0,0010,001
Science ouverte0,0010,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,035
Tête enseignante GPT0,300
Écart entre enseignants0,265 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2020
Routes d'admission3
Résumé présentoui

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