The influence of memory for and affective response to health messages on self-care behavioral intentions
Metadatos
Afficher la notice complèteAuteur
Ferreira Leitão Azevedo, Renato; García Retamero Imedio, María Del Rocío; Morrow, Daniel G.; Hasegawa Johnson, Mark; Kuangxiao, GuEditorial
Elsevier
Materia
Cognition Affective responses Health behavior change
Date
2023-11-08Referencia bibliográfica
R.F.L. Azevedo et al. The influence of memory for and affective response to health messages on self-care behavioral intentions. Human Factors in Healthcare 4 (2023) 100058. [https://doi.org/10.1016/j.hfh.2023.100058]
Patrocinador
Agency for Healthcare Research and Quality (R21HS022948), the Jump Applied Research for Community Health through Engineering and Simulation (ARCHES) program and the Ministry of Economics, Industry and Competitivity, Spanish Government.Résumé
Clinical test results are often presented in digital health solutions (e.g., patient portals, mobile phone apps) with limited context to help patients understand implications of this numeric information. Guided by a framework that integrates cognitive and health behavior theories, we identified processes involved in understanding and responding to health messages as a basis for designing more effective digital health solutions that include clinical test results. This framework emphasizes the importance of presenting numeric information in ways that support memory, decision making, and action. In previous studies we measured memory for and affective response to messages about cholesterol and diabetes screening test results, perceived risk associated with these test results, as well as attitudes toward and intention to perform behaviors that address these risks (e.g., adherence to exercise recommendations). The focus of the present paper is to analyze direct and indirect relationships among these health decision making and behavioral variables through multivariate path analyses. Consistent with previous findings, we found that memory for messages was only indirectly related to behavioral attitudes and intentions.
Affective responses to risk-related information, on the other hand, directly related to these variables, perhaps
because behavioral attitudes and intentions are often based on information organized around affective/evaluative dimensions. These results suggest appropriate affective response may not only directly support risk perception, but attitudes toward behavior addressing this risk. We discuss implications for human factors and ergonomics researchers and practitioners to the design, implementation and evaluation of digital health solutions.