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Mental Health Hospitalizations in Canadian Children, Adolescents, and Young Adults Over the COVID-19 Pandemic

2024· article· en· W4400414097 on OpenAlexafffundabout
Nadia Roumeliotis, Matthew Carwana, Ofélie Trudeau, Katia Charland, Kate Zinszer, Mike Benigeri, Mamadou Diop, Jesse Papenburg, Samina Ali, Maryna Yaskina, Gita Wahi, Baudouin Forgeot d’Arc, Sylvana M. Côté, Manish Sadarangani, Nicole E. Basta, Patrícia S. Fontela, Soren Gantt, Terry P. Klassen, Caroline Quach, Quynh Doan, Sarah Ahira, Upton Allen, Krista Baerg, Megan Bale-Nick, Ananya Banerjee, Michelle Barton, Darcy Beer, Simon Berthelot, Julie A. Bettinger, Maala Bhatt, Melanie Buba, Francine Buchanan, Jared Bullard, Brett Burstein, Catherine Burton, Rahul Chanchlani, Michaël Chassé, Karen Choong, Evelyn Constantin, Carrie Costello, Tammie Dewan, Tanya Di Genova, Olivier Drouin, Karen Dryden‐Palmer, Geneviève Du Pont- Thibodeau, Marc-André Dugas, Raven Dumont-Maurice, Guillaume Émériaud, Jason G. Emsley, Mark A. Ferro, Karen Forbes, Isabel Fortier, Jennifer Foster, Jessica Foulds, Stephen B. Freedman, Gabrielle Freire, Eleni Galanis, P. Grantley Gill, Jocelyn Gravel, Emily Gruenwoldt, Gonzalo Garcia Guerra, Astrid Guttman, Betty Jean Hancock, Robyn Harrison, Joanna Holland, Ari R. Joffe, Fatima Kakkar, April Kam, James D. Kellner, Lisa Knisley, Thierry Lacaze‐Masmonteil, Saptharishi Lalgudi Ganesan, Marc- André Langlois, Nicole Le Saux, Laurie Lee, Kirk Leifso, Patricia Li, Andrea Linares, Sanjay Mahant, Isabelle Marc, Ahmed Mater, James McNally, Garth Meckler, Shaun Morris, Haifa Mtaweh, Srinivas Murthy, Fiona Muttalib, Leigh Anne Newhook, Jessica Nicoll, Nathalie Orr-Gaucher, Joseph S. Pagano, Anna Pangilinan, Jeffrey M. Pernica, Naveen Poonai, Élodie Portales-Casamar, Robert Porter, Rupeena Purewal, Paula Robeson, Joan Robinson, Marina Salvadori, Susan Samuel, Shannon D. Scott, Anupam Sehgal, Tatiana Sotindjo, Carla Southward, Taylor Stoesz, Robert Strang, Shazeen Suleman, Péter Szatmári, Sepi Taheri, Jennifer Tam, Roseline Thibeault, Karina A. Top, Krystel Toulouse, SzeMan Tse, Anupma Wadhwa, Sam Wong, Bruce Wright, Rae S. M. Yeung

Bibliographic record

VenueJAMA Network Open · 2024
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversity of ManitobaChildren's Hospital Research Institute of ManitobaMcGill UniversityCentre Hospitalier Universitaire Sainte-JustineWomen and Children’s Health Research InstituteMontreal Children's HospitalBC Children's HospitalUniversity of British ColumbiaUniversity of AlbertaUniversité de MontréalInstitut National d'Excellence en Santé et en Services SociauxMcMaster UniversityMcMaster Children's Hospital
FundersCanadian Institutes of Health ResearchSanofi PasteurNational Institutes of HealthMcGill UniversitySanofiSeqirusFonds de Recherche du Québec - SantéModernaNational Institute of Allergy and Infectious DiseasesPfizer
KeywordsMedicineMental healthPublic healthPopulationDemographyAnxietyPandemicIncidence (geometry)Young adultPsychiatryEnvironmental healthGerontologyCoronavirus disease 2019 (COVID-19)Disease

Abstract

fetched live from OpenAlex

Importance: The COVID-19 pandemic resulted in multiple socially restrictive public health measures and reported negative mental health impacts in youths. Few studies have evaluated incidence rates by sex, region, and social determinants across an entire population. Objective: To estimate the incidence of hospitalizations for mental health conditions, stratified by sex, region, and social determinants, in children and adolescents (hereinafter referred to as youths) and young adults comparing the prepandemic and pandemic-prevalent periods. Design, Setting, and Participants: This Canadian population-based repeated ecological cross-sectional study used health administrative data, extending from April 1, 2016, to March 31, 2023. All youths and young adults from 6 to 20 years of age in each of the Canadian provinces and territories were included. Data were provided by the Canadian Institute for Health Information for all provinces except Quebec; the Institut National d'Excellence en Santé et en Services Sociaux provided aggregate data for Quebec. Exposures: The COVID-19-prevalent period, defined as April 1, 2020, to March 31, 2023. Main Outcomes and Measures: The main outcome measures were the prepandemic and COVID-19-prevalent incidence rates of hospitalizations for anxiety, mood disorders, eating disorders, schizophrenia or psychosis, personality disorders, substance-related disorders, and self-harm. Secondary measures included hospitalization differences by sex, age group, and deprivation as well as emergency department visits for the same mental health conditions. Results: Among Canadian youths and young adults during the study period, there were 218 101 hospitalizations for mental health conditions (ages 6 to 11 years: 5.8%, 12 to 17 years: 66.9%, and 18 to 20 years: 27.3%; 66.0% female). The rate of mental health hospitalizations decreased from 51.6 to 47.9 per 10 000 person-years between the prepandemic and COVID-19-prevalent years. However, the pandemic was associated with a rise in hospitalizations for anxiety (incidence rate ratio [IRR], 1.11; 95% CI, 1.08-1.14), personality disorders (IRR, 1.21; 95% CI, 1.16-1.25), suicide and self-harm (IRR, 1.10; 95% CI, 1.07-1.13), and eating disorders (IRR, 1.66; 95% CI, 1.60-1.73) in females and for eating disorders (IRR, 1.47; 95% CI, 1.31-1.67) in males. In both sexes, there was a decrease in hospitalizations for mood disorders (IRR, 0.84; 95% CI, 0.83-0.86), substance-related disorders (IRR, 0.83; 95% CI, 0.81-0.86), and other mental health disorders (IRR, 0.78; 95% CI, 0.76-0.79). Conclusions and Relevance: This cross-sectional study of Canadian youths and young adults found a rise in anxiety, personality disorders, and suicidality in females and a rise in eating disorders in both sexes in the COVID-19-prevalent period. These results suggest that in future pandemics, policymakers should support youths and young adults who are particularly vulnerable to deterioration in mental health conditions during public health restrictions, including eating disorders, anxiety, and suicidality.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.384
Teacher spread0.353 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations21
Published2024
Admission routes3
Has abstractyes

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