Examining the Relationship Between Screening for Postpartum Depression and Associated Child Health Service Utilization and Costs: A Study Using the All Our Families Cohort and Administrative Data
Bibliographic record
Abstract
INTRODUCTION: Despite a recognized association between maternal postpartum depression (PPD) and adverse child health outcomes, evidence examining the relationship between PPD symptoms and associated child health service utilization and costs remains unclear. In addition, there is a paucity of evidence describing the relationship between early identification of maternal PPD and associated health service utilization and costs for children. This study aims to address this gap by describing the secondary associations of screening for maternal PPD and annual health service utilization and costs for children over their first five years of life. METHODS: Mothers and children enrolled in the prospective All Our Families cohort were linked to provincial administrative data in Alberta, Canada. Multivariable generalized linear models were used to estimate the average annual inpatient, outpatient, physician, and total health service utilization and costs from a public health system perspective for children of mothers screened high risk for PPD, low/moderate risk for PPD, or unscreened. RESULTS: Total mean costs were greatest for children during their first year of life than other years. Those whose mothers were not screened had significantly lower costs compared to those whose mothers were screened low/moderate risk, despite equivalent health service utilization. DISCUSSION: Findings from this study describe the secondary associations of screening for maternal PPD using a public health system perspective. More research is required to fully understand variations in health costs for children across maternal PPD screening categories.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| 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".