Guidelines for support to mothers of sexually abused children in North-West province
Bibliographic record
Abstract
BACKGROUND: South Africa is reported to have the highest rate of sexual assault in the world with over 40% of cases occurring among children. Children who are sexually abused have support programmes and policies to assist them in coping, but there are no support programmes for mothers or caretakers. Caretakers need support for themselves and assisting them will incrementally benefit children under their care. Often mothers of these children experience shock, anger, disbelief and suffer secondary trauma such as depression and post-traumatic stress disorder (PTSD) following their children's sexual abuse disclosure and yet there are no guidelines for support to these mothers within North-West province (NWP)Objectives: The study seeks to develop guidelines for support to mothers of sexually abused children in NWP. METHODS: Concurrent convergence triangulation mixed method design was employed in this study. The population consisted of mothers of sexually abused children (SAC) (n = 17 participants for the qualitative component and n = 180 participants for the quantitative component). A sample of mothers of SAC was purposely selected. RESULTS: The participants indicated significant levels of depression because of lack of support by stakeholders. Guidelines for support to assist mothers cope with their secondary trauma were developed based on the literature review, study findings as well as an ecological model of the impact of sexual assault on women's mental health. The results also showed extreme PTSD (47.8%), little support (38.8%), not coping (76.1%) and depression (36.1%). CONCLUSION: The stakeholders should consider a positive approach to support mothers whose children are sexually abused.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".