Measuring COVID-19 Related Anxiety in Parents: Psychometric Comparison of Four Different Inventories
Bibliographic record
Abstract
BACKGROUND: The COVID-19 outbreak and the measures to contain the global pandemic can have an impact on the well-being and mental health status of individuals. Parents of young children are particularly at risk for high levels of parental stress due to the current public health crisis, which can impact parenting behaviors and children's well-being. Although different initial scales have been developed to measure COVID-19-related anxiety, they have not yet been tested sufficiently in parent samples. A brief measure of COVID-19-related anxiety is necessary for both quick assessment in practice and in larger epidemiological studies of parents. OBJECTIVE: The purpose of this study is to compare the distributions, validities, and reliabilities of four different COVID-19 anxiety scales: Fear of COVID-19 Scale, Coronavirus Anxiety Scale, Pandemic Anxiety Scale, and one subscale of the COVID Stress Scales. Based on the psychometric properties of these scales, we aim to provide recommendations for a brief unidimensional inventory to assess COVID-19-related anxiety among parents. METHODS: A cross-sectional web-based survey of 515 German-speaking parents (465 mothers, 90.3%) with at least one child aged 0-6 years was conducted during a 6-week period (June 29 to August 9, 2020). Half of the parents were recruited via Facebook parenting groups, while the other half were recruited through childcare centers. We psychometrically tested 25 items on COVID-19-related anxiety using the framework of classical test theory, including item analysis, correlational analysis of family variables, and exploratory factor analysis. Moreover, an item response theory approach was applied to estimate item discriminations and item difficulties. RESULTS: =-0.79, P=.42). CONCLUSIONS: Factor analysis suggests that existing COVID-19-related anxiety scales measure different latent constructs of anxiety. Furthermore, all scales showed only small to moderate correlations with trait health anxiety, suggesting that COVID-19-related anxiety is distinct from general health anxiety. The adapted "disease anxiety" subscale of the Pandemic Anxiety Scale is an economical measure for assessing COVID-19-related anxiety in parents. Directions for future research are outlined.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".