Perceived child vulnerability and overprotective parenting in caregivers of twin children
Bibliographic record
Abstract
Caregivers may be more protective of children they perceive as vulnerable. As second-born twins have poorer health outcomes compared to first-born twins, it is theorised that caregivers will perceive second-born twins as more vulnerable and parent them more protectively. In this cross-sectional online study, 855 biological mothers of twins aged 2 to 9 years, living in Australia, Canada, Ireland, New Zealand, United Kingdom, and United States of America, completed the Child Vulnerability Scale (Forsyth et al., 1996) and Parent Protection Scale (Thomasgard, Metz, et al., 1995) for each twin. Compared to first-born twins, more second-born twins were considered highly vulnerable (p=.038) and parented in an overprotective manner (p=.005). Perceived child vulnerability was positively correlated with parent protection for both first- and second-born twins (rs=.22, p<.001 and rs =.25, p <.001, respectively). Mothers of younger children perceived them to be more vulnerable than mothers of older children (H(2)=11.28 p=.004; H(2)=9.76, p=.008), and parented them more protectively (H(2)=106.48, p<.001; H(2)=123.32, p<.001). More neonatal, child health and maternal risk factors were identified for greater perceived child vulnerability and parent protection for second-born twins than first-born twins. Findings highlight the importance of context-driven psychosocial interventions to improve outcomes for caregivers and their twin 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 | 0.008 |
| 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 | 0.000 | 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".