The COVID-19 Family Stressor Scale: Validation and Measurement Invariance in Female and Male Caregivers
Bibliographic record
Abstract
The COVID-19 pandemic has raised significant concerns regarding the effect of social disruptions on parental mental health, family well-being, and children's adjustment. Due to the pace of the pandemic, measures of pandemic-related disruption have not been subject to rigorous empirical validation. To address this gap, a multi-national sample (United Kingdom, 76%; United States, 19%; Canada, 4%, and Australia, 1%) of 372 female caregivers and 158 male caregivers of 5–18-year-old children was recruited online. Participants completed a survey including a 25-item scale indexing disruption in finances, basic needs, personal and family welfare, career/education, household responsibilities, and family relationships related to the pandemic. An exploratory factor analysis yielded an optimal three-factor solution: factors included Income Stress (five items related to income, debt, and job loss; loadings ranged from 0.57 to 0.91), Family Stress (seven items related to family altercations and child management; loadings from 0.57 to 0.87), and Chaos Stress (four items related to access to supplies, crowded shopping areas, news coverage; loadings from 0.53 to 0.70). Multiple-group confirmatory factor analysis demonstrated measurement invariance of each factor across female and male caregivers, indicating that factor structure, loadings, and thresholds were equivalent across groups. Composites reflective of each factor were computed, and Mann-Whitney U tests indicated that female caregivers consistently scored higher than male caregivers on COVID-19 stressors related to income, family, and chaos. Finally, concurrent validity was demonstrated by significant bivariate correlations between each scale and caregiver, family, and child outcomes, respectively. This demonstrates the validity of the COVID-19 Family Stressor Scale for use with female and male caregivers in family-based research. The current sample was predominantly White-European, married/common-law, and had at least some post-secondary education. Additional sampling and validation efforts are required across diverse ethnic/racial and socioeconomic groups.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".