Emerging New Psychiatric Symptoms and the Worsening of Pre-existing Mental Disorders during the COVID-19 Pandemic: A Canadian Multisite Study: Nouveaux symptômes psychiatriques émergents et détérioration des troubles mentaux préexistants durant la pandémie de la COVID-19: une étude canadienne multisite
Bibliographic record
Abstract
BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has caused global disruptions with serious psychological impacts. This study investigated the emergence of new psychiatric symptoms and the worsening of pre-existing mental disorders during the COVID-19 pandemic, identified factors associated with psychological worsening, and assessed changes in mental health service use. METHODS: An online survey was circulated between April 3 and June 23, 2020. Respondents were asked to complete mental health questionnaires based on 2 time referents: currently (i.e., during the outbreak) and in the month preceding the outbreak. A total of 4,294 Canadians between 16 and 99 years of age were subdivided based on the presence of self-reported psychiatric diagnoses. RESULTS: The proportion of respondents without prior psychiatric history who screened positive for generalized anxiety disorder and depression increased by 12% and 29%, respectively, during the outbreak. Occurrences of clinically important worsening in anxiety, depression, and suicidal ideation symptoms relative to pre-outbreak estimates were significantly higher in those with psychiatric diagnoses. Furthermore, 15% to 19% of respondents reported increased alcohol or cannabis use. Worse psychological changes relative to pre-outbreak estimate were associated with female sex, younger age, lower income, poorer coping skills, multiple psychiatric comorbidities, previous trauma exposure, deteriorating physical health, poorer family relationships, and lower exercising. Reductions in mental health care were associated with increased suicidal ideation. CONCLUSION: The worsening in mental health symptoms and the decline in access to care call for the urgent development of adapted interventions targeting both new mental disorders and pre-existing psychiatric conditions affected by the COVID-19 pandemic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".