Head injury secondary to suspected child maltreatment: results of a prospective Canadian national surveillance program

Objective

We sought to determine the incidence, clinical features, and demographic profile of head injury secondary to suspected child maltreatment (abuse or neglect) in Canada to help inform the development and evaluation of prevention programs for abusive head injuries.

Methods

From March 1, 2005 to February 28, 2008, an average of 2,545 paediatricians and paediatric subspecialists were surveyed monthly through the established network of the Canadian Paediatric Surveillance Program. We calculated incidence rates using the number of confirmed cases over the product of the duration of the study (3 years) and population estimates by age group.

Results

There were 220 confirmed cases of head injury from suspected child maltreatment. The annual incidence rate was 14.1 per 100,000 for children less than 1 year of age and 1.4 per 100,000 for those less than 15 years. Seventy three percent (141) of cases involved infants less than 12 months of age and 52% (100) of cases involved infants less than 6 months of age. Seventy-five percent (165) of cases presented to the emergency room. With regard to outcome, 12% (27) of cases resulted in death and 45% (75) of survivors had neurological sequelae at discharge. Thirty percent (67) of all cases, as well as 30% (8) of deaths were previously known to child welfare authorities.

Conclusion

This study provides an estimate of the rate of head injury secondary to suspected child maltreatment in Canada. The young age and poor medical outcomes of those involved highlights the need for prevention efforts that are implemented early in life. Given that a significant percentage of injured infants and children were already known to child welfare authorities, the study also highlights the need to establish and evaluate additional preventive efforts for parents and caregivers already in the child welfare system.     

Face-to-face versus computer-mediated discussion of teaching cases: Impacts on preservice teachers’ engagement, critical analyses, and self-efficacy

Two frequently-used discussion protocols were investigated as part of a program to implement teaching cases in undergraduate educational psychology classes designed for preservice teachers. One protocol involved synchronous face-to-face (FTF) discussion of teaching cases, which occurred in class after students had individually completed written case analyses as homework outside of class. The other was asynchronous computer-mediated (CM) discussion taking place outside of class, simultaneous to students’ completion of their written case analyses. Six class offerings of an undergraduate child development course taught by two instructors (three classes by each instructor) were randomly assigned within instructor in a quasi-experimental design to one of the three discussion conditions: FTF, CM, or no discussion of the cases across the semester. Findings indicated that both CM and FTF discussion conditions were associated with positive outcomes relative to the control condition. Both CM and FTF discussion related to higher cognitive–affective engagement with the cases than the control condition; and the CM discussion condition was associated with higher cognitive–affective engagement than FTF discussion. In contrast, FTF discussion, but not CM discussion, was associated with higher-than-control-condition case analysis ability at the end of the semester. Potential explanations for these findings and directions for future research are discussed.     

Rapid Prototyping a Collections-based Mobile Wayfinding Application

This research presents the results of a project that investigated how students use a library developed mobile app to locate books in the library. The study employed a methodology of formative evaluation so that the development of the mobile app would be informed by user preferences for next generation wayfinding systems. A key finding is the importance of gathering ongoing user feedback for designing useful and used mobile academic library applications. Elements and data points to include in future mobile interfaces are discussed.     

面向个性化推荐的快速关联规则挖掘算法

关联规则挖掘是解决电子商务推荐问题的重要方法之一.针对传统关联规则挖掘算法在解决移动电子商务环境个性化推荐问题时反复扫描数据库,频繁项挖掘效率低,关联规则挖掘准确率低以及规则大量冗余等不足,提出一个基于事务矩阵和用户兴趣度的关联规则挖掘算法(Matrix-and-Interestingness-based Association Rules Mining,MIbARM).该算法仅需扫描一次数据库,并在挖掘过程中不断缩小算法搜索空间以避免生成冗余候选项,同时避免了冗余规则挖掘,从而提高了挖掘效率.最后,在四组人工数据和160种参数组合的数值实验环境下,引入Apriori、CBAR 及BitTableFI算法对MIbARM进行对比验证.结果表明,在不减少有趣规则的前提下,MIbARM不但可有效避免冗余候选项集的产生,而且大幅减少了冗余规则数量,极大提高了算法的搜索效率,同时提升了个性化推荐的质量,更适用于移动电子商务环境下的个性化推荐问题.