Development and validation of MIX: comprehensive free software for meta-analysis of causal research data

BACKGROUND: Meta-analysis has become a well-known method for synthesis of quantitative data from previously conducted research in applied health sciences. So far, meta-analysis has been particularly useful in evaluating and comparing therapies and in assessing causes of disease. Consequently, the number of software packages that can perform meta-analysis has increased over the years. Unfortunately, it can take a substantial amount of time to get acquainted with some of these programs and most contain little or no interactive educational material. We set out to create and validate an easy-to-use and comprehensive meta-analysis package that would be simple enough programming-wise to remain available as a free download. We specifically aimed at students and researchers who are new to meta-analysis, with important parts of the development oriented towards creating internal interactive tutoring tools and designing features that would facilitate usage of the software as a companion to existing books on meta-analysis. RESULTS: We took an unconventional approach and created a program that uses Excel as a calculation and programming platform. The main programming language was Visual Basic, as implemented in Visual Basic 6 and Visual Basic for Applications in Excel 2000 and higher. The development took approximately two years and resulted in the 'MIX' program, which can be downloaded from the program's website free of charge. Next, we set out to validate the MIX output with two major software packages as reference standards, namely STATA (metan, metabias, and metatrim) and Comprehensive Meta-Analysis Version 2. Eight meta-analyses that had been published in major journals were used as data sources. All numerical and graphical results from analyses with MIX were identical to their counterparts in STATA and CMA. The MIX program distinguishes itself from most other programs by the extensive graphical output, the click-and-go (Excel) interface, and the educational features. CONCLUSION: The MIX program is a valid tool for performing meta-analysis and may be particularly useful in educational environments. It can be downloaded free of charge via or

Analysis of Medical Equipment Management in Relation to the Mandatory Medical Equipment Safety Manager (MESM) in Japan

Half a decade has passed since the fifth revision of the medical law and mandatory appointment of a medical equipment safety manager (MESM) in hospitals in Japan. During this period, circumstances have changed regarding maintenance of medical equipment (ME). We conducted a survey to examine these changes and the current situation in ME management. Maintenance of ME and related work were found to have increased in many hospitals, but the number of clinical engineering technologists (CETs) has only slightly increased. The appointed MESM was a CET or physician in most hospitals. In hospitals where physicians were appointed as the MESM, 81% had operation managers. Many respondents commented that it was difficult for one person to cover all the tasks required by the MESM, due to a lack of knowledge, too much work, or other reasons. This suggests the importance of an operation manager for ME to work under the MESM

Factors associated with follow-up difficulty in longitudinal studies involving community-dwelling older adults.

This study aims to clarify the factors associated with the gradual withdrawal from society in older adults. We defined the stages of follow-up difficulty based on four follow-up surveys on non-respondents of longitudinal mail surveys in community-dwelling older adults to examine the main factors associated with the stages of follow-up difficulty. We conducted a follow-up mail survey (FL1) with respondents of a baseline survey, and three more follow-up surveys with the non-respondents of each previous survey: simplified mail (FL2), postcard (FL3), and home visit surveys (FL4). The respondents of each follow-up survey were defined as a stage of follow-up difficulty; their characteristics concerning social participation and interaction at baseline in each stage were analyzed. The number of respondents in the FL1, FL2, FL3, and FL4 stages and non-respondents (NR) were as follows: 2,361; 462; 234; 84; and 101, respectively. Participation in hobby groups in FL2 and FL3, sports groups in FL4, and neighborhood association and social isolation in NR were significantly associated with the stage of follow-up difficulty. Based on these results, we conclude that the following factors are associated with each stage of follow-up difficulty: 1) a decline in instrumental activities of daily living in the FL2 and FL3 stages, 2) dislike for participating in physical activity such as sports in the FL4 stage, and 3) social isolation, not even belonging to a neighborhood association due to low social interaction in the NR group