UNASSIGNED: A Google Forms survey was designed, and the link was shared through various Jordanian social media platforms. Factor analysis and Rasch analysis were performed to validate the Jordanian version of the MHLS. Binary logistic regression was performed to assess variables associated with MHL.
UNASSIGNED: The Jordanian MHLS was administered to 974 participants (74.4% females; median age 27 years). The mean MHL score of the participants was 71.1% indicating average literacy levels. The factor analysis indicated that 27 items distributed across four factors had the best model fit. The Rasch analysis confirmed item separation reliability and person reliability. The regression showed a correlation between educational attainment, income, marital status and MHL level. These findings emphasize the role of educational attainment in MHL, pointing to the necessity of integrating mental health education into formal curricula to enhance MHL across all societal levels. Stigma and limited-service availability act as barriers to mental health service and access, which compound the challenge of improving MHL. Targeted educational interventions and policy reforms may help improve MHL, thereby contributing to improving mental health outcomes in Jordan and potentially other similar settings.
■设计了GoogleForms调查,该链接通过各种约旦社交媒体平台共享。进行因子分析和Rasch分析以验证MHLS的约旦版本。进行二元逻辑回归以评估与MHL相关的变量。
■对974名参与者(74.4%为女性;平均年龄27岁)进行了约旦MHLS治疗。参与者的平均MHL得分为71.1%,表明平均识字水平。因子分析表明,分布在四个因素中的27个项目具有最佳的模型拟合。Rasch分析确认了项目分离可靠性和人员可靠性。回归显示受教育程度之间存在相关性,收入,婚姻状况和MHL水平。这些发现强调了受教育程度在MHL中的作用,指出必须将心理健康教育纳入正式课程,以增强所有社会层面的MHL。污名化和有限的服务可用性是心理健康服务和获取的障碍,这增加了改善MHL的挑战。有针对性的教育干预和政策改革可能有助于改善MHL,从而有助于改善约旦和其他潜在类似环境的心理健康结果。