Embedded Strategies in Mathematics Vocabulary Instruction: A Quasi-Experimental Study

Recent accountability requirements increase the emphasis on mathematics achievement for all students, including low-performing students and students with learning disabilities. However, these students progress very slowly, with weaknesses evident in computation and problem solving. These limitations affect their success in mathematics at lower grades and make earning a high school diploma difficult. It is imperative to isolate components of mathematics comprehension and identify methods to teach them in order to help these lower performing students be successful. Research indicates a strong relationship between vocabulary and mathematical comprehension, identifying vocabulary understanding as a key component in understanding the subject. Vocabulary instruction incorporating mnemonic strategies has consistently resulted in substantial increases in learning and retention for students with disabilities as well as nondisabled peers when compared with other approaches. The research reported here focused on the use of keyword mnemonics in mathematics vocabulary instruction. This mixed model multi-strand study with a quasi-experimental quantitative design tested for significant differences between groups on a vocabulary assessment and conducted a repeated measures analysis of variance was on two levels of instruction (direct instruction versus keyword mnemonic instruction) and across three measures (pretest, posttest, and follow-up). Although both groups did show significant improvements, the students who participated in the keyword mnemonic classes outperformed the students in the direct instruction classes as measured on the both the posttest and the follow-up test of the vocabulary assessment. There was no significant difference between the groups on overall mathematics achievement as measured by Curriculum-Based Measurement probes or on attitudes toward mathematics. The qualitative data identified a relationship between the use of elaboration techniques, level of performance, and conceptual misunderstandings. However, as always, the effective use of any retrieval technique is dependent on the accuracy of the information encoded

Does Postformal Thinking Facilitate Recovery From Grief and Promote Well-Being During Bereavement In Widows?

Widows were assessed on four measures relating to recovery from bereavement: postformal thinking (measured as dialectical thinking), recovery from grief (measured as past feelings and present feelings), well-being (measured by three subscales: autonomy, environmental mastery, and positive relations with others), and age at time of participation. Eighty participants completed and returned questionnaires. It was hypothesized that age of the participant and the development of postformal thinking would predict higher scores on recovery from grief and well-being. Analysis was performed using a Structural Equation Model with a comparative fit index (CFI) of .98. Results showed that age and postformal thinking did not predict recovery from grief or higher well-being scores. In addition no correlation was found between later age and postformal thinking, although there was a correlation between scores on recovery from grief and scores on well-being

Prescribable mHealth apps identified from an overview of systematic reviews

AbstractMobile health apps aimed towards patients are an emerging field of mHealth. Their potential for improving self-management of chronic conditions is significant. Here, we propose a concept of “prescribable” mHealth apps, defined as apps that are currently available, proven effective, and preferably stand-alone, i.e., that do not require dedicated central servers and continuous monitoring by medical professionals. Our objectives were to conduct an overview of systematic reviews to identify such apps, assess the evidence of their effectiveness, and to determine the gaps and limitations in mHealth app research. We searched four databases from 2008 onwards and the Journal of Medical Internet Research for systematic reviews of randomized controlled trials (RCTs) of stand-alone health apps. We identified 6 systematic reviews including 23 RCTs evaluating 22 available apps that mostly addressed diabetes, mental health and obesity. Most trials were pilots with small sample size and of short duration. Risk of bias of the included reviews and trials was high. Eleven of the 23 trials showed a meaningful effect on health or surrogate outcomes attributable to apps. In conclusion, we identified only a small number of currently available stand-alone apps that have been evaluated in RCTs. The overall low quality of the evidence of effectiveness greatly limits the prescribability of health apps. mHealth apps need to be evaluated by more robust RCTs that report between-group differences before becoming prescribable. Systematic reviews should incorporate sensitivity analysis of trials with high risk of bias to better summarize the evidence, and should adhere to the relevant reporting guideline.</jats:p

The decisions and processes involved in a systematic search strategy: a hierarchical framework

OBJECTIVE: The decisions and processes that may compose a systematic search strategy have not been formally identified and categorized. This study aimed to (1) identify all decisions that could be made and processes that could be used in a systematic search strategy and (2) create a hierarchical framework of those decisions and processes. METHODS: The literature was searched for documents or guides on conducting a literature search for a systematic review or other evidence synthesis. The decisions or processes for locating studies were extracted from eligible documents and categorized into a structured hierarchical framework. Feedback from experts was sought to revise the framework. The framework was revised iteratively and tested using recently published literature on systematic searching. RESULTS: Guidance documents were identified from expert organizations and a search of the literature and Internet. Data were extracted from 74 eligible documents to form the initial framework. The framework was revised based on feedback from 9 search experts and further review and testing by the authors. The hierarchical framework consists of 119 decisions or processes sorted into 17 categories and arranged under 5 topics. These topics are “Skill of the searcher,” “Selecting information to identify,” “Searching the literature electronically,” “Other ways to identify studies,” and “Updating the systematic review.” CONCLUSIONS: The work identifies and classifies the decisions and processes used in systematic searching. Future work can now focus on assessing and prioritizing research on the best methods for successfully identifying all eligible studies for a systematic review