Maternal Mental Health after Custody Loss and Death of a Child: A Retrospective Cohort Study Using Linkable Administrative Data
Bibliographic record
Abstract
OBJECTIVE: The objective was to compare mental illness diagnoses and treatment use among mothers who lost custody of their child through involvement with child protection services and those seen in mothers dealing with the death of a child. METHODS: We studied mental health outcomes of a cohort of women whose first child was born in Manitoba, Canada between 1 April 1997 and 31 March 2015. Of these women, 5,792 had a child taken into care, and 1,143 mothers experienced the death of a child (<18 y old) before 31 March 2015. Adjusted relative rates (ARR) of 3 mental health diagnoses and 3 mental health treatment use outcomes between these 2 groups were examined. RESULTS: Mothers with a child taken into care had significantly greater ARR of depression (ARR = 1.90; 95% CI, 1.82 to 1.98), anxiety (ARR = 2.51; 95% CI, 2.40 to 2.63), substance use (ARR = 8.54; 95% CI, 7.49 to 9.74), physician visits for mental illness (ARR = 3.01; 95% CI, 2.91 to 3.12), and psychotropic medication use (ARR = 4.95; 95% CI, 4.85 to 5.06) in the years after custody loss compared with mothers who experienced the death of a child. CONCLUSION: Losing custody of a child to child protection services is associated with significantly worse maternal mental health than experiencing the death of a child. Greater acknowledgement and supportive services should be provided to mothers experiencing the loss of a child through the involvement of child protection services.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".