Examining the Relationship Between Pediatric Behavioral Health and Parent Productivity Through a Parent-Reported Survey in the Time of COVID-19: Exploratory Study
Bibliographic record
Abstract
BACKGROUND: Pediatric behavioral health needs skyrocketed during the COVID-19 pandemic. Parents and caregivers lacked access to well-established tools to identify risk and protective factors while also experiencing decreased access to treatment options to meet their families' behavioral health needs. OBJECTIVE: The aim of this study is to investigate the associations of known pediatric behavioral health risk factors and parents' reports of workplace productivity. METHODS: A clinical research team at Brightline-a virtual, pediatric behavioral health solution-drew on standardized instruments to create a survey designed to understand pediatric behavioral health conditions, child stress, and family resilience and connection during the COVID-19 pandemic. Multivariable linear regression was used to characterize the relationship between these variables and parents' reports of workplace productivity. RESULTS: Participants (N=361) completed the survey between October 2020 and November 2021. In the multivariable model, higher pediatric stress and time spent managing children's behavioral health needs were associated with greater productivity loss among working parents, whereas higher family connection was associated with lower productivity loss. COVID-19 diagnoses among parents and dependents, financial impact of COVID-19 on households, and family resilience were not associated with parents' workplace productivity. CONCLUSIONS: This survey captured child stress, family connection, and productivity as reported by parents and caregivers during the COVID-19 pandemic. Exploratory studies are the first step in understanding the relationship between these variables. The results from this study can empower parents by providing insights to help manage their child's behavioral health concerns and identify pediatric behavioral health services to aid working parents who are caregivers.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".