Information processing likelihood, eHealth literacy, and complexity of seeking strategies as predictors of health decision-making quality

Yaron Connelly, Nehama Lewis, Ilan Talmud, Giora Kaplan

Research output: Contribution to journalArticlepeer-review

Abstract

eHEALS is one of the most prevalent scales used to measure eHealth literacy. However, significant criticism toward its conceptualization had raised. This study tests the effects of eHEALS alongside constructs from the elaboration likelihood model and information seeking processes, within a multidimensional model to predict medical decision-making quality. We test this model using a sample of 56 participants who completed a 45-minute online simulation task, requiring them to offer recommendation for a hypothetical medical scenario. Findings revealed that neither eHealth literacy nor elaboration likelihood independently predicted decision quality. However, eHEALS was positively associated with higher decision quality, but only among participants who had greater motivation and ability to process health information, and who used more complex information seeking strategies. Findings suggest that the eHEALS measure can be examined using a multidimensional theoretical approach to illustrate the ways in which patients obtain and utilize health information to make informed decisions.

Original languageEnglish
JournalNew Media and Society
DOIs
StateAccepted/In press - 2023

Keywords

  • ELM
  • eHEALS
  • eHealth literacy
  • health decision-making
  • seeking strategies
  • simulations study

All Science Journal Classification (ASJC) codes

  • Communication
  • Sociology and Political Science

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