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Global Prevalence of Depressive and Anxiety Symptoms in Children and Adolescents During COVID-19

2021· review· en· W3190876559 on OpenAlexaff
Nicole Racine, Brae Anne McArthur, Jessica E. Cooke, Rachel Eirich, Jenney Zhu, Sheri Madigan

Bibliographic record

VenueJAMA Pediatrics · 2021
Typereview
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsMedicineAnxietyPsycINFODepression (economics)Mental healthMEDLINEPsychiatryPrevalencePediatricsEpidemiologyInternal medicine

Abstract

fetched live from OpenAlex

Importance: Emerging research suggests that the global prevalence of child and adolescent mental illness has increased considerably during COVID-19. However, substantial variability in prevalence rates have been reported across the literature. Objective: To ascertain more precise estimates of the global prevalence of child and adolescent clinically elevated depression and anxiety symptoms during COVID-19; to compare these rates with prepandemic estimates; and to examine whether demographic (eg, age, sex), geographical (ie, global region), or methodological (eg, pandemic data collection time point, informant of mental illness, study quality) factors explained variation in prevalence rates across studies. Data Sources: Four databases were searched (PsycInfo, Embase, MEDLINE, and Cochrane Central Register of Controlled Trials) from January 1, 2020, to February 16, 2021, and unpublished studies were searched in PsycArXiv on March 8, 2021, for studies reporting on child/adolescent depression and anxiety symptoms. The search strategy combined search terms from 3 themes: (1) mental illness (including depression and anxiety), (2) COVID-19, and (3) children and adolescents (age ≤18 years). For PsycArXiv, the key terms COVID-19, mental health, and child/adolescent were used. Study Selection: Studies were included if they were published in English, had quantitative data, and reported prevalence of clinically elevated depression or anxiety in youth (age ≤18 years). Data Extraction and Synthesis: A total of 3094 nonduplicate titles/abstracts were retrieved, and 136 full-text articles were reviewed. Data were analyzed from March 8 to 22, 2021. Main Outcomes and Measures: Prevalence rates of clinically elevated depression and anxiety symptoms in youth. Results: Random-effect meta-analyses were conducted. Twenty-nine studies including 80 879 participants met full inclusion criteria. Pooled prevalence estimates of clinically elevated depression and anxiety symptoms were 25.2% (95% CI, 21.2%-29.7%) and 20.5% (95% CI, 17.2%-24.4%), respectively. Moderator analyses revealed that the prevalence of clinically elevated depression and anxiety symptoms were higher in studies collected later in the pandemic and in girls. Depression symptoms were higher in older children. Conclusions and Relevance: Pooled estimates obtained in the first year of the COVID-19 pandemic suggest that 1 in 4 youth globally are experiencing clinically elevated depression symptoms, while 1 in 5 youth are experiencing clinically elevated anxiety symptoms. These pooled estimates, which increased over time, are double of prepandemic estimates. An influx of mental health care utilization is expected, and allocation of resources to address child and adolescent mental health concerns are essential.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.051
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.019
Threshold uncertainty score0.065

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.051
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0080.011
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.029
GPT teacher head0.391
Teacher spread0.363 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations2,762
Published2021
Admission routes1
Has abstractyes

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