This study aimed to investigate the role of the five-factor model of personality (FFM) and the moderating role of gender and age in predicting medication adherence (MA) and self-care behaviors (SCB) ...among Iranian patients with type 2 diabetes mellitus (T2DM).
This study was conducted on 495 patients with T2DM (73.5% female; n = 364) from two major cities of Iran (Tehran and Qom) in 2019. Pearson's correlation coefficient, multiple regression analysis, and conditional process analysis were performed. P < .05 and P < .10 were considered significant for the relationships and moderation analysis, respectively.
Neuroticism indicated a negative association with MA and SCB. Positive associations were found between MA and personality traits, including extraversion, agreeableness, and conscientiousness, whereas extraversion showed a weak correlation with SCB. According to the covariate-adjusted regression model, neuroticism had a negative effect on MA and SCB. Agreeableness had a positive effect on MA and a negative effect on SCB. However, extraversion exerted a negative effect on MA and a positive effect on SCB. Also, the negative effect of neuroticism on MA was highlighted in women, indicating marginally significant moderation effect. The positive effects of extraversion and conscientiousness on MA were moderated by age. The effect of conscientiousness on SCB was positive in young patients and negative in old patients. No interaction effect was observed between age and gender.
This study indicated that neuroticism, extraversion, and agreeableness significantly contributed to MA, but not to SCB. However, the effects were conditioned by age for extraversion and conscientiousness to some extent.
•Personality traits affect the patients' engagement in healthcare practices•Neuroticism consistently hammers women; yet not moderated via gender•Extraversion and conscientiousness in older patients indicates higher MA•Agreeableness promotes MA, shadowing the effect of conscientiousness•Conscientiousness might act conversely on SCB for very young and very old patients
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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