Distress Trajectories for Parents of Children With DSD: A Growth Mixture Model
Bibliographic record
Abstract
OBJECTIVE: This study identifies trajectories of parent depressive symptoms after having a child born with genital atypia due to a disorder/difference of sex development (DSD) or congenital adrenal hyperplasia (CAH) and across the first year postgenitoplasty (for parents who opted for surgery) or postbaseline (for parents who elected against surgery for their child). Hypotheses for four trajectory classes were guided by parent distress patterns previously identified among other medical conditions. METHODS: Participants included 70 mothers and 50 fathers of 71 children diagnosed with a DSD or CAH with reported moderate to high genital atypia. Parents were recruited from 11 US DSD specialty clinics within 2 years of the child's birth and prior to genitoplasty. A growth mixture model (GMM) was conducted to identify classes of parent depressive symptoms over time. RESULTS: The best fitting model was a five-class linear GMM with freely estimated intercept variance. The classes identified were termed "Resilient," "Recovery," "Chronic," "Escalating," and "Elevated Partial Recovery." Four classes have previously been identified for other pediatric illnesses; however, a fifth class was also identified. The majority of parents were classified in the "Resilient" class (67.6%). CONCLUSIONS: This study provides new knowledge about the trajectories of depressive symptoms for parents of children with DSD. Future studies are needed to identify developmental, medical, or familial predictors of these trajectories.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".