Household composition and anxiety symptoms during the COVID-19 pandemic: A population-based study
Bibliographic record
Abstract
INTRODUCTION: Household composition may be an important factor associated with anxiety during the COVID-19 pandemic as people spend more time at home due to physical distancing and lockdown restrictions. Adults living with children-especially women-may be particularly vulnerable to anxiety as they balance additional childcare responsibilities and homeschooling with work. The objective of this study was to examine the association between household composition and anxiety symptoms during the COVID-19 pandemic and explore gender as an effect modifier. METHODS: Data were derived from seven waves of a national online survey of Canadian adults aged 18+ years from May 2020 to March 2021, which used quota sampling by age, gender, and region proportional to the English-speaking Canadian population (n = 7,021). Multivariable logistic and modified least-squares regression models were used. RESULTS: Compared to those living alone, significantly greater odds of anxiety symptoms were observed among single parents/guardians (aOR = 2.00; 95%CI: 1.41-2.84), those living with adult(s) and child(ren) (aOR = 1.39; 95%CI: 1.10-1.76), and those living with adult(s) only (aOR = 1.22; 95%CI: 1.00-1.49). Gender was a significant effect modifier on the additive scale (p = 0.0487) such that the association between living with child(ren) and anxiety symptoms was stronger among men than women. CONCLUSION: Additional tailored supports are needed to address anxiety among adults living with children-especially men-during the COVID-19 pandemic and future infectious disease events.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".