Relative Importance of Well-Being Determinants in Atlantic Canadian Families During the Pandemic
Bibliographic record
Abstract
Framed by the socio-ecological model of well-being, we examined the relative importance of factors contributing to three dimensions of well-being (child, parent, and family) during the COVID-19 pandemic. A sample of 536 participants from the Atlantic provinces of Canada answered a cross-sectional survey in 2021, covering experiences during the pandemic (eg, changes in family life and well-being). Well-being was assessed with 3 single-item measures on positive change in the life of children, parents, and families during the pandemic. This study involved 21 predictor variables (eg, change in time spent on various family activities). Using multiple regression and measures of relative importance based on the Lindeman, Merenda and Gold (lmg) method, we identified the variables most important to predicting well-being. Twenty-one predictors accounted for 21% of the variance in child well-being, 25% in parent well-being, and 36% in family well-being. Well-being at all 3 levels (child, parent, and family) shared the same top predictor (family closeness). The top 6 predictors of well-being at each level were related to leisure (eg, play) and time-use (eg, to prepare meals, engage in self-care, and rest). The effect sizes were smaller for child well-being than at the parent or family level, suggesting there may be important predictors of child well-being not accounted for in these analyses. This study may inform family-level programing and policy that seeks to promote well-being for children and their families.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".