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Updated: Jul 15, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
[Developing a decision tool: indicating care for mild intellectual disability]
Background:
Children and youth with an intellectual disability and psychiatric problems are a complex group. By identifying clients who require highly specialized mental health care at an early stage, it is expected that the provided care can be utilized more effectively, there will be less non-response and clients will more efficiently receive the most appropriate care.
Aim:
To develop a decision tool which can identify clients who need highly specialized care at an early stage.
Method:
A review of the literature and qualitative research methods were used, including a Delphi study to get consensus on criteria that could be used as indicators for highly specialized care. These criteria were included in a decision tool, followed by validation of these criteria by testing them on the population of the Banjaard, a mental health care setting for young people with intellectual disability and psychiatric problems.
Results:
Ten criteria emerged from the Delphi method that were seen to be predictive of the need for highly specialized care. After applying these criteria to the Banjaard population, it appeared that three or more criteria reliably identified clients needing highly specialized care (sensitivity 76.5% and specificity 75.6%).
Conclusion:
The decision tool developed in the current study is a reasonable instrument for identifying clients who could benefit from highly specialized mental health care.
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