Children of chronically ill parents: Relationship between parental multiple sclerosis and childhood developmental health
Bibliographic record
Abstract
BACKGROUND: Exposure to parental chronic illness is associated with adverse developmental outcomes. OBJECTIVE: We examined the association between parental multiple sclerosis (MS) and parental MS-related clinical factors on developmental health. METHODS: We conducted a population-based cohort study in British Columbia, Canada, using linked health databases. The outcome was childhood development at 5 years of age, expressed as vulnerability on the Early Development Instrument (EDI). Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were estimated using conditional logistic regression. RESULTS: MS-affected parents (n = 783) were older, more likely to be English speakers, and had higher rates of mental health morbidity (39.6% vs 22.2%, p < 0.001) than unaffected parents (n = 2988). In the adjusted models, children of mothers with MS (aOR = 0.62, 95% CI = 0.44-0.87), but not children of the fathers with MS, had a lower risk of vulnerability on the social development domain of the EDI. However, mental health comorbidity (aOR = 1.62, 95% CI = 1.05-2.50) and physical comorbidity (aOR = 1.67, 95% CI = 1.05-2.64) among mothers with MS were associated with increased vulnerability on the EDI. CONCLUSION: Maternal MS, but not paternal MS, was associated with lower rates of developmental vulnerability on the social development domain. However, mental and physical comorbidity among MS-affected mothers were associated with increased developmental vulnerability in children.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".