Child Abuse in Indonesia: A National Trend Analysis and Health Promotion Response (2016-2024)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Child abuse remains a critical issue in Indonesia. Cases have been tracked in real time through the Online Information System for the Protection of Women and Children ( SIMFONI-PPA ) since 2016; however, long-term trends have not been comprehensively analysed. This study examined national child abuse trends in Indonesia and explored health promotion strategies for prevention. Secondary data from SIMFONI-PPA were analysed to identify trends in abuse types, victim profiles, perpetrator profiles, and locations. A literature review was conducted to identify prevention strategies employing a health promotion framework grounded in the Ottawa Charter. Findings showed a steady increase in reported child abuse cases. Sexual violence was the most reported abuse, 2–3 times higher than physical or psychological violence and several times more than trafficking or exploitation. Adolescent girls (approximately 70% of victims), aged 13–17 (over 50% victims), were the most affected; about one-third of victims were attending junior high school. Perpetrators were known to the victims, such as lovers or peers (about a quarter of cases), and most incidents occurred at home (around half of reported cases). Indonesia has implemented several prevention strategies, including policy reform, education, and community-based efforts. The rising trend of child abuse in Indonesia underscores the urgent need for multisectoral, context-sensitive interventions focused on improving data collection, service access, and reducing stigma. Future research should explore socio-cultural factors and evaluate the effectiveness of existing prevention programs.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.001 | 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 it