Persuasion with Precision: Using Natural Language Processing to Improve Instrument Fidelity for Risk Communication Experimental Treatments

Autor: Ann Marie Reinhold, Eric D. Raile, Clemente Izurieta, Jamie McEvoy, Henry W. King, Geoffrey C. Poole, Richard C. Ready, Nicolas T. Bergmann, Elizabeth A. Shanahan
Rok vydání: 2022
Předmět:
Zdroj: Journal of Mixed Methods Research. :155868982210969
ISSN: 1558-6901
1558-6898
DOI: 10.1177/15586898221096934
Popis: Instrument fidelity in message testing research hinges upon how precisely messages operationalize treatment conditions. However, numerous message testing studies have unmitigated threats to validity and reliability because no established procedures exist to guide construction of message treatments. Their construction typically occurs in a black box, resulting in suspect inferential conclusions about treatment effects. Because a mixed methods approach is needed to enhance instrument fidelity in message testing research, this article contributes to the field of mixed methods research by presenting an integrated multistage procedure for constructing precise message treatments using an exploratory sequential mixed methods design. This work harnesses the power of integration through crossover analysis to improve instrument fidelity in message testing research through the use of natural language processing (NLP).
Databáze: OpenAIRE