The purpose of this review is to synthesize the evidence and determine the efficacy of interventions based on family systems theory in diabetes-related family conflict, self-management, and glycemic control among adolescents with type 1 diabetes. A systematic search of five English databases was conducted. Interventions based on family systems theory in adolescents with type 1 diabetes that reported diabetes-related family conflict, self-management, and glycemic control as outcome variables were included. A total of 14 articles from ten interventions were included. Meta-analysis results revealed that, compared to adolescents who received usual care, adolescents who received family systems theory interventions reported fewer diabetes-related family conflicts with a medium effect size of 0.32 (p?<?0.05), but there was no significant improvement on self-management or glycemic control (p?>?0.05). Family systems theory interventions appear to have beneficial effect on reducing diabetes-related family conflicts for adolescents with type 1 diabetes. Adolescents who have type 1 diabetes and their families may need multidimensional psychosocial programs accompanied by diabetes education to improve glycemic control.
In a cognitive diagnostic assessment (CDA), attributes refer to fine-grained knowledge points or skills. The Q -matrix is a central component of CDA, which specifies the relationship between items and attributes. Oftentimes, attributes and Q -matrix are defined by subject-matter experts, and assumed to be appropriate without any misspecifications. However, this assumption does not always hold in real applications. To address this concern, this paper proposes a residual-based statistic for validating the Q -matrix. Its performance is evaluated in a simulation study and compared against that of an existing method proposed in Liu, Xu and Ying (2012, Applied Psychological Measurement, 36, 548). Simulation results indicate that the proposed method leads to a higher recovery rate of the Q -matrix and is computationally more efficient. The advantage in computational efficiency is particularly pronounced when the number of attributes measured by the test reaches five or more. Results also suggest that the two methods have different tendencies in estimating the attribute vector for each item. In cases where the methods fail to recover the correct Q -matrix, the method in Liu et al. (2012, Applied Psychological Measurement, 36, 548) tends to overestimate the number of attributes measured by the items, whereas our method does not show that bias. 相似文献