A prevalence-based approach to societal costs occurring in consequence of child abuse and neglect
Bibliographic record
Abstract
BACKGROUND: Traumatization in childhood can result in lifelong health impairment and may have a negative impact on other areas of life such as education, social contacts and employment as well. Despite the frequent occurrence of traumatization, which is reflected in a 14.5 percent prevalence rate of severe child abuse and neglect, the economic burden of the consequences is hardly known. The objective of this prevalence-based cost-of-illness study is to show how impairment of the individual is reflected in economic trauma follow-up costs borne by society as a whole in Germany and to compare the results with other countries' costs. METHODS: From a societal perspective trauma follow-up costs were estimated using a bottom-up approach. The literature-based prevalence rate includes emotional, physical and sexual abuse as well as physical and emotional neglect in Germany. Costs are derived from individual case scenarios of child endangerment presented in a German cost-benefit-analysis. A comparison with trauma follow-up costs in Australia, Canada and the USA is based on purchasing power parity. RESULTS: The annual trauma follow-up costs total to a margin of EUR 11.1 billion for the lower bound and to EUR 29.8 billion for the upper bound. This equals EUR 134.84 and EUR 363.58, respectively, per capita for the German population. These results conform to the ones obtained from cost studies conducted in Australia (lower bound) and Canada (upper bound), whereas the result for the United States is much lower. CONCLUSION: Child abuse and neglect result in trauma follow-up costs of economically relevant magnitude for the German society. Although the result is well in line with other countries' costs, the general lack of data should be fought in order to enable more detailed future studies. Creating a reliable cost data basis in the first place can pave the way for long-term cost savings.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".