Dataset Information

Cohort analysis of child abuse and neglect cases treated during the initial 2 years of a programme to support hospital-based child protection work in Austria.

ABSTRACT:

Objective

To describe characteristics of suspected child abuse and neglect (CAN) cases associated with the decision of paediatric departments (PDs) in Vienna, Austria, to involve services of a regional tertiary child protection service programme (Forensische Kinder- und JugendUntersuchungsStelle, FOKUS).

Design

Retrospective cohort analysis of a regional data collection of CAN cases over the first 2 years of FOKUS's operational period (1 July 2015-30 June 2017).

Setting

All CAN cases reported to the PDs of six public hospitals in Vienna. Five of these public hospitals were secondary heath care centres and one was a tertiary healthcare centre.

Results

Overall, 231 cases (59.1%) were treated without and 160 (40.9%) with additional involvement of the FOKUS service programme. The odds of a case to be treated without FOKUS involvement were higher if neglect was suspected (OR 3.233, 95% CI 2.024 to 5.279). In contrast, when sexual abuse was suspected, the odds for involvement with FOKUS were significantly higher (OR 7.577, 95% CI 4.580 to 12.879). The odds of being managed with FOKUS services nearly doubled when multiple forms of abuse were suspected (OR 1.926, 95% CI 1.136 to 3.285). The odds for additional FOKUS involvement were significantly lower for patients treated as inpatients (OR 0.239, 95% CI 0.151 to 0.373). CAN patients managed with FOKUS involvement were significantly more often reported to law enforcement (LE) (OR 3.234, 95% CI 2.078 to 5.002). Concurrently, suspected sexual abuse cases and cases reported to LE were more frequently treated in the PD of the tertiary centre than in other PDs (χ² p<0.001).

Conclusion

CAN case characteristics significantly influenced if PDs involved a tertiary child protection programme. Suspected sexual abuse, if more than one form of CAN was suspected and cases reported to LE required additional specialist expertise. For suspected neglect involvement of tertiary services seemed less important.

SUBMITTER: Mora-Theuer EA

PROVIDER: S-EPMC10351272 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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Cohort analysis of child abuse and neglect cases treated during the initial 2 years of a programme to support hospital-based child protection work in Austria.

Mora-Theuer Eva Anna EA Klomfar Sophie S Ramazanova Dariga D Grylli Chryssa C Kletecka-Pulker Maria M Völkl-Kernstock Sabine S Otterman Gabriel G Simon Judit J Greber-Platzer Susanne S

BMJ open 20230714 7

<h4>Objective</h4>To describe characteristics of suspected child abuse and neglect (CAN) cases associated with the decision of paediatric departments (PDs) in Vienna, Austria, to involve services of a regional tertiary child protection service programme (Forensische Kinder- und JugendUntersuchungsStelle, FOKUS).<h4>Design</h4>Retrospective cohort analysis of a regional data collection of CAN cases over the first 2 years of FOKUS's operational period (1 July 2015-30 June 2017).<h4>Setting</h4>All ...[more]

PMID: 37451739

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Project description:BackgroundChild abuse and neglect (CAN) is prevalent, associated with long-term adversities, and often undetected. Primary care settings offer a unique opportunity to identify CAN and facilitate referrals, when warranted. Electronic health records (EHR) contain extensive information to support healthcare decisions, yet time constraints preclude most providers from thorough EHR reviews that could indicate CAN. Strategies that summarize EHR data to identify CAN and convey this to providers has potential to mitigate CAN-related sequelae. This study used expert review/consensus and Natural Language Processing (NLP) to develop and test a lexicon to characterize children who have experienced or are at risk for CAN and compared machine learning methods to the lexicon + NLP approach to determine the algorithm's performance for identifying CAN.MethodsStudy investigators identified 90 CAN terms and invited an interdisciplinary group of child abuse experts for review and validation. We then used NLP to develop pipelines to finalize the CAN lexicon. Data for pipeline development and refinement were drawn from a randomly selected sample of EHR from patients seen at pediatric primary care clinics within a U.S. academic health center. To explore a machine learning approach for CAN identification, we used Support Vector Machine algorithms.ResultsThe investigator-generated list of 90 CAN terms were reviewed and validated by 25 invited experts, resulting in a final pool of 133 terms. NLP utilized a randomly selected sample of 14,393 clinical notes from 153 patients to test the lexicon, and .03% of notes were identified as CAN positive. CAN identification varied by clinical note type, with few differences found by provider type (physicians versus nurses, social workers, etc.). An evaluation of the final NLP pipelines indicated 93.8% positive CAN rate for the training set and 71.4% for the test set, with decreased precision attributed primarily to false positives. For the machine learning approach, SVM pipeline performance was 92% for CAN + and 100% for non-CAN, indicating higher sensitivity than specificity.ConclusionsThe NLP algorithm's development and refinement suggest that innovative tools can identify youth at risk for CAN. The next key step is to refine the NLP algorithm to eventually funnel this information to care providers to guide clinical decision making.

Project description:ImportancePoverty has long been associated with a higher risk for child maltreatment, and recent research suggests that income support policies are associated with reduced child abuse and neglect. However, income supports tied to employment cannot separate the associations of income from those of employment.ObjectiveTo estimate the short-term association of universal and unconditional income payments to parents with child abuse and neglect.Design, setting, and participantsIn this cross-sectional study, variation in the timing of the 2021 expanded child tax credit (CTC) advance payments was used to determine whether receiving unconditional income is associated with child abuse and neglect. A fixed-effects approach was used to compare child abuse and neglect before and after payments were made in 2021. The study compared 2021 trends with the same period in 2018 and 2019, during which no CTC payments were made. Participants were pediatric emergency department (ED) patients identified as experiencing child abuse or neglect at a level I pediatric hospital system in the Southeastern US from July through December 2021. Data were analyzed from July to August 2022.ExposuresTiming in the disbursement of the expanded CTC advance payments.Main outcomes and measuresDaily child abuse and neglect-related ED visits.ResultsDuring the study period, there were 3169 ED visits related to child abuse or neglect. The 2021 advance payments of the expanded CTC were associated with fewer child abuse and neglect-related ED visits. There was a decrease in these ED visits in the 4 days following the advance CTC payments, although the reduction was not significant (point estimate, -0.22; 95% CI, -0.45 to 0.01; P = .06). There were significant reductions in such ED visits among male children (point estimate, -0.40; 95% CI, -0.75 to -0.06; P = .02) and non-Hispanic White children (point estimate, -0.69; 95% CI, -1.22 to -0.17; P = .01). These reductions did not persist, however.Conclusions and relevanceThese findings suggest that federal income supports to parents are associated with immediate reductions in child abuse and neglect-related ED visits. These results are important for discussions of making the temporary expansion of the CTC permanent and are applicable to income support policies more broadly.

Dataset Information

Cohort analysis of child abuse and neglect cases treated during the initial 2 years of a programme to support hospital-based child protection work in Austria.

Objective

Design

Setting

Results

Conclusion

Publications

Cohort analysis of child abuse and neglect cases treated during the initial 2 years of a programme to support hospital-based child protection work in Austria.

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