iLookOut Micro-learning to Improve Knowledge Retention

Summary

This project investigates whether a multi-faceted strategy involving iLookOut's evidence-based Core Training plus an innovative follow-up Micro-Learning can promote knowledge retention and change behavior among early childhood professionals (ECPs) with regard to child abuse and its reporting. Additionally, this study will evaluate if non-ECPs experience similar improvements and retention of knowledge and changes in behavior as do ECPs.

Detailed Description

The primary purpose of this study is to understand the optimal timing to administer iLookOut Micro-Learning to boost ECPs waning knowledge and preparedness to protect children from abuse. Additionally, this study will conduct a randomized controlled trial to examine how interactive, gamified micro-learning promotes knowledge retention and fosters behavior change with regard to child abuse and its reporting, and to establish that implementation of this intervention is feasible. All components of the learning module being studied are online, and will be accessed by participants through a secure website. Once they complete the Core Training, participants who identify as ECPs will receive an email indicating which randomization arm they are in (regarding access to the advanced training) - immediate, 3 months, 6 months, or 9 months. Non-ECPs will be able to complete the advanced training as soon as they complete the Core Training. All non-ECPs will be used as a comparison group to determine if the iLookOut trainings are effective for improving and retaining knowledge, and changing behavior among Non-ECPs compared to the ECP participants. Separate mixed-effects linear regression model will be applied to assess (1) the knowledge decay effect based on the data collected at different time-points and (2) the behavior change between the various time-points and how it is correlated to the knowledge score, after controlling for participants' baseline characteristics and work setting. In addition, the regression model will adjust effects for allocation blocks and the factors for stratification in the analysis to reduce group variability.

Eligibility Criteria

Interventions