Perceived Parental Rearing Practices, Supportive School Environment, and Self-Reported Emotional and Behavioral Problems among Lithuanian Secondary School Students
Bibliographic record
Abstract
Previous research rarely addressed parental rearing practices, perceived safety at school, teachers’ support andschool climate in the same study. Most often those two contexts-home environment and school context-areanalyzed separately. Several authors have advocated the need for incorporating those two contexts in the study ofemotional and behavioral problems (Suldo et al., 2012). Thus, the main purpose of the study was to investigatethe relationship between the perceived parental practices (parents’ reactions to adolescents’ behavior, i.e., guiltinduction and emotional warmth) and supportive school environment (school attachment, school climate,perceived teacher support, and feelings of safety at school) with adolescents’ emotional and behavioral problems.The data used is from an ongoing longitudinal Positive Youth Development study (POSIDEV) that examines themechanisms and processes through which young people develop their competences. The sample comprised 2625Lithuanian students (1146 boys and 1479 girls, age 14-20 (M = 16.69; SD = 1.17)) from the ninth, tenth,eleventh and twelfth grades of 8 upper secondary schools. The results showed that parents’ emotional warmthwas negatively, and psychological control was positively related to students’ depressive symptoms anddelinquent behavior. Furthermore, perceived teacher support, feelings of safety at school were negativelyassociated with adolescents’ depressive symptoms and delinquent behavior, when students’ perceptions ofnegative school climate were positively associated with adolescents’ depressive symptoms and delinquentbehavior. After entering school context variables in the regression, demographic characteristics and mother’sguilt induction practice remained significant, but mother’s emotional warmth was no longer significant. Thissuggests the possibility that school context acts as a mediator between emotional warmth by mother anddelinquent behavior. This finding has important practical implications in terms of shedding some insight on howmultiple systems might be interlinked in influencing wellbeing in adolescents and confirms the importance ofintervening at the double platform of both the family and the school system.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".