An Easily Accessible, Semi-Automated Approach to Creating Personalized Normative Feedback and Risk Feedback Graphics
Year: 2024
Type: article
Abstract: OBJECTIVE: Personalized normative feedback interventions show efficacy in reducing health risk behaviors (e.g., alcohol use, sexual aggression). However, complex personalized normative feedback interventions may require manual methods of inputting participant data into graphics, which introduces error, and automated approaches require substantial technical costs and funding and may limit the types of feedback that can be provided. METHOD: To make personalized normative feedback more accessible, we outline a method of using easily accessible software programs, including IBM Statistical Package for the Social Sciences (SPSS), Microsoft Excel, and Microsoft PowerPoint, to create and display complex personalized normative feedback graphics. We also describe methods through which personalized normative feedback graphics can be created within a larger preventive intervention for alcohol and sexual assault in college men. RESULTS: We first provide step-by-step instructions for collecting data and then creating semi-automated syntax files within SPSS and Excel to merge participant data into complex personalized normative feedback graphics in Excel. To do so, we append annotated syntax in text and supplemental material. Next, we outline the process of creating risk feedback graphics, whereby individual items or the exact wording of items are displayed back to the participant. Finally, we provide guidance regarding the process of translating graphics from Excel for viewing via PowerPoint without having to manually update PowerPoint slides for each presentation. CONCLUSIONS: Via the described syntax and graphic generation, researchers are then able to create semi-automated personalized normative feedback and risk feedback graphics. This tutorial may help increase the dissemination of complex personalized normative feedback interventions.
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W4404743473