The relationship between placement instability and mental health among care-experienced children and young people: UK systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Children in care who experience frequent placement changes face an increased risk of negative mental health outcomes. Emerging evidence suggests a bidirectional relationship, where placement instability can both predict and result from mental health difficulties. Understanding the strength and direction of this relationship is crucial for informing policy and practice, yet UK-based evidence remains unconsolidated. AIMS: To conduct the first systematic review and meta-analysis examining the relationship between placement instability and mental health in the UK care system. METHOD: This review was prospectively registered on the International Prospective Register of Systematic Reviews (PROSPERO; CRD42024493617). We searched five databases (up to August 2024) for peer-reviewed UK studies that included a care-experienced sample, measured placement (in)stability, measured mental health, and quantitatively examined the relationship between placement instability and mental health. A random-effects meta-analysis was conducted, and study quality was assessed using the Newcastle-Ottawa Scale. RESULTS: = 5536) contributing to the meta-analysis. Children with unstable placements were more than twice as likely to experience mental health difficulties compared to those with stable placements (odds ratio 2.07, 95% CI 1.65-2.59). However, evidence on the causal direction of this relationship was limited. CONCLUSION: Placement instability doubles the risk of mental health difficulties for care-experienced children, who already face elevated rates of mental disorders. Further research is urgently needed to clarify the bidirectional nature of this relationship and guide targeted intervention. Meanwhile, policymakers should prioritise collaborations between mental health services and local authorities to prevent the cycle of instability and mental health deterioration.
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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 | 0.018 | 0.058 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".