When daily challenges become too much during COVID-19: Implications of family and work demands for work–life balance among parents of children with special needs.
Bibliographic record
Abstract
Working parents of children with special needs (i.e., emotional, behavioral, and/or learning difficulties) face recurrent stressors that can make balancing work and family demands difficult. This strain has been magnified during the COVID-19 pandemic, as these parents often need to take on greater responsibility in supporting their children's remote learning, while still meeting their own job-related responsibilities. Accordingly, working parents of special needs children may be particularly vulnerable to adverse outcomes stemming from pandemic-induced changes to work (e.g., teleworking) and education (e.g., remote instruction). We sought to understand how daily family and work challenges influence satisfaction with work-life balance (WLB) in this priority population, with an emphasis on contextualizing this process through chronic job stress perceptions. Conducting a 10-day daily diary study in a sample of 47 working parents of special needs children during fall 2020, we observed family challenges to deplete positive affect from day-to-day, which undermined satisfaction with work-life balance. Furthermore, detrimental influences of daily family and work challenges on positive affect were magnified under chronic job stress, yielding diminished WLB satisfaction for more chronically stressed employees. We discuss how these findings can be harnessed to support particularly vulnerable employees during the COVID-19 pandemic and other chronic stress circumstances, while also drawing attention to how the pandemic may be exacerbating work-life inequities that some employees face. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".