PROBLEMATIC BEHAVIOUR IN FOSTER CARE: INSIGHTS FROM FOSTER CARERS AND CARE CENTRE STAFF IN LITHUANIA
Bibliographic record
Abstract
Children’s problematic behaviour is a common issue in care that must be recognised and understood to be effectively addressed. This study explores how foster carers and care centre staff identify and manage internalising and externalising behaviour problems in children. A quantitative study was conducted in Lithuania using a questionnaire administered to 54 care centre staff and 67 foster carers. The results indicate that foster carers feel more capable of recognising problematic behaviour than care centre staff do, and that staff struggle more with decision-making in cases of internalising problematic behaviour. However, staff feel more capable of directly helping children than supporting foster carers. While foster carers can seek additional help for children, they are less likely to do so for themselves, despite knowing where to find it. The study highlights the need to strengthen staff’s ability to identify internalising behaviour, support foster carers, and determine necessary interventions. Additionally, foster carers should be encouraged to seek help for themselves when managing children’s behavioural challenges. It is anticipated that attention to these areas would enhance care quality and caregiver well-being.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".