3 resultados para cognitive diagnostic model

em Digital Commons @ DU | University of Denver Research


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The purposes of this study were (1) to validate of the item-attribute matrix using two levels of attributes (Level 1 attributes and Level 2 sub-attributes), and (2) through retrofitting the diagnostic models to the mathematics test of the Trends in International Mathematics and Science Study (TIMSS), to evaluate the construct validity of TIMSS mathematics assessment by comparing the results of two assessment booklets. Item data were extracted from Booklets 2 and 3 for the 8th grade in TIMSS 2007, which included a total of 49 mathematics items and every student's response to every item. The study developed three categories of attributes at two levels: content, cognitive process (TIMSS or new), and comprehensive cognitive process (or IT) based on the TIMSS assessment framework, cognitive procedures, and item type. At level one, there were 4 content attributes (number, algebra, geometry, and data and chance), 3 TIMSS process attributes (knowing, applying, and reasoning), and 4 new process attributes (identifying, computing, judging, and reasoning). At level two, the level 1 attributes were further divided into 32 sub-attributes. There was only one level of IT attributes (multiple steps/responses, complexity, and constructed-response). Twelve Q-matrices (4 originally specified, 4 random, and 4 revised) were investigated with eleven Q-matrix models (QM1 ~ QM11) using multiple regression and the least squares distance method (LSDM). Comprehensive analyses indicated that the proposed Q-matrices explained most of the variance in item difficulty (i.e., 64% to 81%). The cognitive process attributes contributed to the item difficulties more than the content attributes, and the IT attributes contributed much more than both the content and process attributes. The new retrofitted process attributes explained the items better than the TIMSS process attributes. Results generated from the level 1 attributes and the level 2 attributes were consistent. Most attributes could be used to recover students' performance, but some attributes' probabilities showed unreasonable patterns. The analysis approaches could not demonstrate if the same construct validity was supported across booklets. The proposed attributes and Q-matrices explained the items of Booklet 2 better than the items of Booklet 3. The specified Q-matrices explained the items better than the random Q-matrices.

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Little is known about the developmental processes through which parenting factors may influence clinical depression among youth. This study investigated whether parenting influences the onset of clinical depression through the mediating mechanism of negative attributional style, particularly under conditions of high stress, in a community sample of children and adolescents (N = 289). Results supported a moderated mediation model in which low levels of observed parent positive regard and sensitivity to distress during a youth stressor task were indirectly associated with an increased likelihood of experiencing an episode of depression over an18 month period, through the mediating influence of youth negative attributional style, but only for youth who also experienced a high number of peer stressors. These findings elucidate mechanisms through which parenting may contribute to risk for depression during the transition into and across adolescence.

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Purpose: Breast cancer is the most frequently diagnosed cancer among women worldwide. While undergoing chemotherapy treatment for breast cancer, patients often report experiencing "chemobrain." Previous literature reports correlations between psychological distress and these perceived cognitive problems. The aim of the present study was to examine the strength of the association between affective disturbance and subjective cognitive dysfunction.Methods: This study included a meta-analysis of the literature reporting a correlation between mood and subjective cognitive dysfunction. Eight studies with 1344 breast cancer patients treated with chemotherapy were selected based on stringent study inclusion criteria. Studies reporting a correlation coefficient between mood and subjective cognitive dysfunction were included.Results: In these data, there was no significant correlation between affective disturbance and subjective cognitive dysfunction. A random effects model yielded an overall weighted mean effect size of 0.12.Conclusion: Although this meta-analysis did not confirm the correlation between mood and subjective cognitive dysfunction, there was a clear association between these factors in the original disaggregated analyses, and they are clearly impactful from the time of diagnosis through long-term after care. The clinical implications of the present study and future directions for research are discussed.