From experts' perspective, factors affecting the effectiveness of online educational programs in promoting the health literacy of MS patients: A grounded theory approach

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2025

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Haji Seyed Javadi, K.
Nouri, A.

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Journal article

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Patient Education and Counseling, 2025; 134:108673-1-108673-7

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Seyed Kian Haji seyed javadi, Aisan Nouri

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Abstract

Background Online educational programs have emerged as a promising tool for promoting health literacy (HL) among multiple sclerosis (MS) patients. However, identifying influencing factors is crucial for maximizing their effectiveness. Aim This study aimed to explain the factors affecting the effectiveness of online educational programs in promoting HL among MS patients in Iran. Methods A qualitative methodology based on Grounded Theory (GT) was employed and participants were recruited using snowball sampling. A total of 17 experts, including patient educators and HL experts, were interviewed until theoretical saturation was achieved. Participants were selected from patient rehabilitation centers in Tehran and members of the Iran MS Society. Results Analysis of the interview data revealed six contextual factors. These factors included socioeconomic status, healthcare infrastructure, technological accessibility and literacy, cultural and linguistic diversity, support networks and caregiver involvement, and health policy and regulatory environment. Conclusions Addressing socioeconomic disparities, improving technological access and literacy and fostering cultural sensitivity are essential steps to enhance the effectiveness and accessibility of these programs. Moreover, collaboration with caregivers and policymakers is crucial for creating an enabling environment that supports the successful integration of online health education initiatives into MS care. Practice implications Findings from this study can enhance the efficacy and productivity of online programs aimed at boosting HL among patients with specific conditions like MS

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© 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

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