The Relationship Between Mothers' Mental Health and Violence Against Their Children
Bibliographic record
Abstract
Background: The negative life experiences and mental state of the mothers cause them to be inadequate to meet the needs of their children and to show negligent-abusive behavior towards their children. Objectives: The aim of this study was to investigate the relationship between mothers' mental health status and neglect/emotional-physical violence behavior towards their children. Methods: This was a cross-sectional quantitative study. The population of the study consists of women who had children aged 0-11 years who applied to a public hospital in Istanbul in the first quarter of 2016. In the study, Self-Reporting Questionnaire-SRQ was used to measure the mental health of mothers, and violence questionnaire was used to measure the violent behaviors of mothers towards their children. SPSS 20.0 program was used for statistical analysis. Results: It was found that almost half of the mothers had high psychological / psychiatric problems (above the threshold). It was found that the rates of high level of emotional violence, low and high level of physical violence against the children of mothers with a Self-Reporting Questionnaire-SRQ above the threshold were higher. In addition, a statistically significant difference was found between traumatic life experiences and mothers' neglect behavior towards the child and this difference was not found in the abuse types. Conclusions: In families with traumatic events, negligent behaviors of mothers towards their children are observed more frequently. In families with high traumatic life experiences, negligent behaviors of mothers towards their children are seen at a higher rate than families with low traumatic life experiences.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".