Predictors of Mental Health Literacy in a Sample of Health Care Major Students: Pilot Evaluation Study

BackgroundThe numerous mental health awareness campaigns during the COVID-19 pandemic have shifted our understanding and perception of mental health. ObjectiveThe purpose of this study is to evaluate predictors of mental health literacy (MHL), that is, one’s knowledge and beliefs about mental disorders. We evaluate whether digital health literacy, empathy, and mentalizing contribute to MHL. MethodsOur sample consisted of 89 health care major students, aged between 17 and 32 years, studying at a university in Lebanon. The Mental Health Literacy Scale for Healthcare Students (MHLS-HS), the eHealth Literacy Questionnaire (eHLQ), the Basic Empathy Scale (BES), and the Reflective Functioning Questionnaire-8 (RFQ-8) were used. ResultsMultiple regression analyses revealed that the Engagement in Own Health subscale of digital health literacy constituted a predictor of MHL. While empathy and mentalizing did not directly predict MHL, they were found to predict components of MHL. ConclusionsThis is the first study to evaluate digital health literacy, empathy, and mentalizing as predictors of MHL in Lebanon, a country where mental health is still considered taboo. Moreover, this pilot study is the first to provide some support for the predictive role of some digital health literacy subscales on MHL in light of the rise of the digital era following the COVID-19 pandemic.