Abstract

Background
Evidence-based parenting programs effectively prevent the onset and escalation of child and adolescent behavioral health problems. When programs have been taken to scale, declines in the quality of implementation diminish intervention effects. Gold-standard methods of implementation monitoring are cost-prohibitive and impractical in resource-scarce delivery systems. Technological developments using computational linguistics and machine learning offer an opportunity to assess fidelity in a low burden, timely, and comprehensive manner.
Methods
In this study, we test two natural language processing (NLP) methods [i.e., Term Frequency-Inverse Document Frequency (TF-IDF) and Bidirectional Encoder Representations from Transformers (BERT)] to assess the delivery of the Family Check-Up 4 Health (FCU4Health) program in a type 2 hybrid effectiveness-implementation trial conducted in primary …

Date

January 1, 1970

Authors

Cady Berkel, Dillon C Knox, Nikolaos Flemotomos, Victor R Martinez, David C Atkins, Shrikanth S Narayanan, Lizeth Alonso Rodriguez, Carlos G Gallo, Justin D Smith

Journal

Implementation Research and Practice

Volume

4

Pages

26334895231187906

Publisher

SAGE Publications