Department of Occupational Therapy, School of Health Sciences, Fukushima Medical University.
Department of Rehabilitation Medicine, Fukushima Medical University.
Fukushima J Med Sci. 2024 Jul 24;70(3):153-162. doi: 10.5387/fms.23-00010. Epub 2024 Jul 13.
We constructed a hypothetical model of the knowledge of autism spectrum disorder (ASD) and self-perception of support of staff working in after-school day services to clarify structural relationships.
A questionnaire survey was conducted at 194 facilities providing after-school day services in Fukushima Prefecture (October 2020), including a basic attributes questionnaire, the Literacy Scale of Characteristics of Autistic Spectrum Disorder (LS-ASD), and a staff questionnaire. We developed a hypothetical model of the relationship between self-perception and LS-ASD total scores of after-school service staff. To obtain latent variables for structural equation modeling (SEM) to confirm factor extraction and the interrelationships among variables, exploratory factor analysis was performed. SEM was used to examine the fit of the hypothetical model to the data and the relationships among variables.
The study included 302 staff members from 58 of 194 facilities. Four factors (Factor 1, motivation; 2, self-perception of knowledge; 3, information sharing; 4, self-confidence) were extracted. The final model showed that Factor 2 had a positive direct effect (path coefficient = 0.64) and Factor 4 had a negative direct effect (path coefficient = -0.22) on LS-ASD scores. The model goodness of fit was acceptable (Goodness-of-Fit Index = 0.890; Comparative Fit Index = 0.912; Root Mean Square Error of Approximation = 0.086; Akaike's Information Criterion = 392.7).
Self-perception of knowledge contributes greatly to knowledge acquisition, while excessive confidence may hinder knowledge retention.
我们构建了一个关于自闭症谱系障碍(ASD)知识和工作人员自我感知支持的假设模型,以阐明结构关系。
在福岛县提供课后日服务的 194 个设施中进行了问卷调查(2020 年 10 月),包括基本属性问卷、自闭症谱系障碍特征的读写能力量表(LS-ASD)和工作人员问卷。我们开发了一个关于课后服务工作人员自我感知与 LS-ASD 总分之间关系的假设模型。为了获得结构方程建模(SEM)的潜在变量以确认因子提取和变量之间的相互关系,进行了探索性因子分析。SEM 用于检查假设模型与数据的拟合度以及变量之间的关系。
该研究包括来自 194 个设施中的 58 个设施的 302 名工作人员。提取了四个因素(因素 1,动机;2,自我感知的知识;3,信息共享;4,自信心)。最终模型表明,因素 2 对 LS-ASD 分数有正向直接影响(路径系数=0.64),因素 4 有负向直接影响(路径系数=-0.22)。模型拟合度良好(Goodness-of-Fit Index = 0.890;比较拟合指数=0.912;均方根误差近似值=0.086;Akaike 信息准则=392.7)。
自我感知的知识对知识获取有很大贡献,而过度自信可能会阻碍知识的保留。