Development an assessment tool of treatment adherence in patients with multiple sclerosis based on theory of planned behavior

Document Type : Original Article

Authors

1 Department of Health Education and Health Promotion, Faculty of Health, Arak University of Medical Sciences, Arak, Iran

2 MS Research Center , Tehran University of Medical Sciences, Tehran, Iran

3 Department of Epidemiology, Faculty of Health, Arak University of Medical Sciences, Arak, Iran

Abstract

Background and Objective: Multiple sclerosis is the most common neurological disease in the world and third cause of disability in chronic disease. One of the dimension to treatment of MS is adherence drugs that need development of an instrument.  This study aimed to evaluate the reliability and validity of treatment adherence drugs tool in patient with multiple sclerosis (MS) based on the theory of planned behavior.
Materials and Methods: This cross-sectional study in 2021-2022 that was carried out on 269 patients with MS were referred to Sina Hospital in Tehran city with a random sample.  Through quantitative and qualitative face validity, content validity index, with a 10-member panel of experts examined to judge the quality and reliability by determining the internal agreement (Cronbach's alpha coefficient) and was approved estimates.
Results: The mean age of patients was 35.04±9.63 years and mean age of morbidity was 32.48±9.6 years. After reviewing the results validity, content validity index less than limit the questions to be revised and the necessary changes were made in the narrative process is repeated until the desired amount of content validity index of more than 0.62 reliability content was more than 0.79. Test-retest and reliability with more than 0.7 was confirmed. The mean of Cronbach's alpha coefficient was 0.87.
Conclusion: The results of this study provided good evidence of valid and reliable tools to assess treatment adherence drugs in patients with MS based on the theory of planned behavior.

Keywords

References

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Daneshvar Medicine
Volume 31, Issue 1 - Serial Number 164
May and June 2023
Pages 23-33

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