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Enregistrement W4390078638 · doi:10.1017/s1355617723010780

1 Perceived Cognitive Impairment in High School Students in the United States During the COVID-19 Pandemic

2023· article· en· W4390078638 sur OpenAlexaff
Ila A. Iverson, Charles E. Gaudet, Nathan E. Cook

Notice bibliographique

RevueJournal of the International Neuropsychological Society · 2023
Typearticle
Langueen
DomainePsychology
ThématiqueCOVID-19 and Mental Health
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésYouth Risk Behavior SurveyMental healthCognitionPsychologyPandemicCoronavirus disease 2019 (COVID-19)Clinical psychologyMedicineSuicide preventionPsychiatryPoison controlDiseaseEnvironmental healthInfectious disease (medical specialty)

Résumé

récupéré en direct d'OpenAlex

Objective: The Youth Risk Behavior Survey (YRBS), conducted by the United States Centers for Disease Control and Prevention (CDC) in 2019, revealed that a large percentage of boys (30%) and girls (45%) reported serious difficulty concentrating, remembering, or making decisions as a result of a physical, mental, or emotional problem. In 2021, the CDC conducted the Adolescent Behaviors and Experiences Survey (ABES). The ABES included similar methodology and content as the YRBS. This study analyzed ABES data to examine correlates of perceived cognitive impairment among high school students in the United States during the COVID-19 pandemic. Participants and Methods: The ABES was a one-time, online survey that was conducted to assess and evaluate the challenges that high-school aged youth experienced during the COVID-19 pandemic. Students’ perceived cognitive impairment was assessed using the same question used in the 2019 YRBS: 'Because of a physical, mental, or emotional problem, do you have serious difficulty concentrating, remembering, or making decisions?' Response options were binary: 'Yes’ or 'No.' The students’ responses were evaluated in relation to nine adversity, mental health, and lifestyle variables. Results: Participants were 6,992 students, age 14 to 18, with 3,294 boys (47%) and 3,698 girls (53%). A large proportion endorsed experiencing serious difficulties concentrating, remembering, and making decisions (45%). Girls (56%) were significantly more likely to endorse perceived cognitive impairment compared to boys (33%) [X2(1)=392.55, p<.001; OR=2.66, 95% CI=2.41-2.93]. Youth who reported that their mental health was poor most of the time or always were very likely to report perceived cognitive impairment (boys: 67%; girls: 81%). Binary logistic regressions were used to examine the associations between perceived cognitive impairment, adversity, and lifestyle variables while controlling for mental health. These analyses were conducted separately for boys [X2(9)=596.70, p<.001; Nagelkerke R2=.24] and girls [x2(9)=883.35, p<.001; Nagelkerke R2=.30]. After controlling for current mental health, significant independent predicters of cognitive problems in boys and girls included: a lifetime history of discrimination based on race or ethnicity, lifetime history of being sexually assaulted or abused, lifetime history of using illicit drugs, being bullied in the past year, current marijuana use, and getting insufficient sleep (5 of fewer hours per night). Participation in sports and exercising regularly were both independently associated with lower rates of cognitive impairment. Conclusions: Perceived cognitive impairment was endorsed by a strikingly high percentage of high school students in 2021 during the COVID-19 pandemic. More than half of high school aged girls and one third of boys reported having serious difficulty concentrating, remembering, and making decisions. These rates are considerably higher than in 2019. Current mental health, unfair treatment because of race or ethnicity, being sexually assaulted, being bullied, drug use, and insufficient sleep were associated with perceived cognitive impairment. Indicators of a physically active lifestyle (participation in sports and exercising regularly) were associated with lower rates of cognitive problems.

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)0,001
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 enseignants0,023
Score d'incertitude au seuil0,046

Scores du classifieur distillé par catégorie (deux têtes)

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

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 Opus0,095
Tête enseignante GPT0,449
Écart entre enseignants0,354 · 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

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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