Background: It is difficult to assess whether community-dwelling frail older adults may remain pre-frail status or improve into a robust state without being directly checked by health care professionals. The health information perceived by older adults is considered to be one of best sources of potential concerns in older adult population. An online measurement system combined with item response theory (IRT) and computer adaptive testing (CAT) methods is likely to become a realistic approach to remotely monitor physical activity status of frail older adults. Objects: This article suggests an approach to provide a precise and efficient means of measuring physical activity levels of community-dwelling frail older adults. Methods: Article reviews were reviewed and summarized. Results: In comparison to the classical test theory (CTT), the IRT method is empirically aimed to focus on the psychometric properties of individual test items in lieu of the test as a whole. These properties allow creating a large item pool that can capture the broad range of physical activity levels. The CAT method administers test items by an algorithm that select items matched to the physical activity levels of the older adults. Conclusion: An online measurement system combined with these two methods would allow adequate physical activity measurement that may be useful to remotely monitor the activity level of community-dwelling frail older adults.

The purpose of cooperation is to obtain mutual benefit. The basic process on cooperation is exchanging something that an individual cannot product. It means that cooperation can be decomposed into two processes: give and take. So, social network combined with give and take process becomes a complex system that represents cooperation. However, there was no method to measure cooperation numerically based on the complex system model before. Online messenger is an appropriate tool because it works on social network. With the number of messages sent or received on messenger, cooperative score is measurable in real time. To do it, the following three elements should be considered. First, cooperation means that both give and take need to be equally distributed among people in an organization. This measurement is available from entropy in information theory. However, without the amount of activity in give and take process, the equal distribution is not enough to present cooperative score. Last, the biased activity with a large amount of activity must be inhibited. Without the third element, only competition is led for selfish benefit. The example in the paper shows that cooperative score equation is proper to be applied if there are countable information in give and take process. With this cooperative scoring system, organizations could easily detect cooperativeness among teams and employee in real time.