Research into the relationship between digital health literacy and healthy lifestyle behaviors: an intergenerational comparison

A Study of the Psychometric Properties of the Persian Version of the Online Gambling Symptom Assessment Scale in the Iranian Population

Background

The primary objective of the current paper was to assess the psychometric attributes of the Persian version of the Online Gambling Symptom Assessment Scale (P-OGSAS) within the Iranian population.

Methods

The current study was conducted through a convenient sampling method between September and November 2021, involving 187 participants who had experienced online gambling at least once a month for the last 3 months. OGSAS was translated from English into Persian using the forward-backward translation method. Cronbach's alpha coefficient and principal component analysis (PCA) were employed to evaluate the reliability and validity of the scale, respectively. Participants were administered a battery of assessments, including P-OGSAS, Persian Gambling Disorder Screening Questionnaire (GDSQ-P), Patient Health Questionnaire-9 Items (PHQ-9), and Generalized Anxiety Disorder Questionnaire (GADQ-7), to assess validity and reliability.

Findings

The results showed that the 3-factor model of this scale provides the highest level of predictability. The 3-factor model accounts for 54.8% of the square load. With a Cronbach's alpha coefficient of 0.807, P-OGSAS demonstrated satisfactory reliability. Finally, OGSAS has a significant correlation with other scales, and as a result, this scale has suitable convergent validity.

Conclusion

P-OGSAS can adequately assess the symptoms and severity of online gambling. Therefore, clinicians could use this scale to evaluate the problems related to online gambling in the Iranian population.

Understanding university students' attitudes and preferences for internet-based mental health interventions

Internet-based interventions are recognised as a practical approach to address mental health issues. The acceptance and utilisation of such interventions are closely linked to user attitudes and preferences. This study aims to examine the predictors of university students' attitudes towards internet-based interventions. Additionally, it seeks to elucidate students' preferences regarding crucial features of these interventions, such as the format, delivery mode, content type, and structural components, to understand better what makes these interventions appealing and practical for university students. A total of 273 university students (comprising 68 % females and 32 % males) participated in the study. The data collection instruments employed were the Personal Information Form, Internet-Based Intervention Preference Survey, E-therapy Attitude Measure (ETAM), Digital Literacy Scale, Patient Health Questionnaire-9, and the Generalized Anxiety Disorder-7 (GAD-7). The data were analysed utilising descriptive statistics, Pearson correlation analysis, and multiple linear regression analysis. The multiple regression analysis revealed digital literacy as a predictive factor for attitudes towards internet-based interventions. Demographic variables, such as age and gender, and psychological variables, such as depression and anxiety levels, were found not to be associated with attitudes towards these interventions. While students are actively seeking mental health information online, a significant majority remain unaware of internet-based interventions. They show a preference for interventions offering greater human interaction, including face-to-face guidance and video content featuring people. Participants favour completing one or two sessions of the intervention weekly. Desired features of internet-based interventions include self-assessment scales, relatable characters, voice relaxation exercises, practical daily life activity tasks, and weekly reminders throughout the process. In conclusion, initiatives aimed at enhancing digital literacy levels could foster more positive attitudes towards internet-based interventions among students. Developers creating Internet-Based Interventions (IBI) for university students should consider these preferences.