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Health Information Avoidance and eHealth Literacy in Patients With Multiple Sclerosis: A Cross-Sectional
Leila Mobasher1, Maryam Shekofteh1, Maryam Kazerani1
1Department of Medical Library and Information Science, School of Allied Medical Sciences Shahid Beheshti University of Medical Sciences Tehran Iran.
Background And Aims:
Information avoidance refers to deliberately evading or delaying access to freely accessible but undesired information, and eHealth literacy refers to people's capability to comprehend, assess, find, and use health knowledge derived from electronic sources. The present study aims to investigate the health information avoidance and eHealth literacy levels in patients with multiple sclerosis (MS) in Fars Province, Iran, and their correlation with each other.
Methods:
The present research method was a cross-sectional correlational study. The studied population included all patients with MS in Fars Province, Iran, in 2023. The sampling method was convenience sampling with a sample size of 127 people. The data collection tools consist of the Health Information Avoidance Questionnaire and the eHEALS Questionnaire. Data analysis was performed using descriptive statistics, Pearson's correlation coefficient, t-test, ANOVA, and Bonferroni test with the help of the SPSS software version 21.
Results:
The average score for general health information avoidance was 9.06 out of 20 points, while the average score for MS health information avoidance was 20.52 out of 50, and the average patient eHealth literacy score was 26.28 out of 40 points. However, this analysis found no significant correlation between general health information or MS health information avoidance and eHealth literacy avoidance (p ≥ 0.05).
Conclusion:
Most patients show an above-average understanding of health information literacy and minimal health information avoidance. Nevertheless, micro-and macro-level strategies and policies are necessary to decrease this avoidance and enhance eHealth literacy optimally. However, because of the convenience sampling, the generalization to the broader population should be approached with caution.
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