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The emergence of mobile health (mHealth) products has created a capability of monitoring and managing the health of patients with chronic diseases. These mHealth technologies would not be beneficial unless they are adopted and used by their target users. This study identifies key factors affecting the usage of mHealth apps based on user usage data collected from an mHealth app.

Using a dataset collected from an mHealth app named mPower, developed for patients with Parkinson's disease (PD), this paper investigated the effects of disease diagnosis, disease progression and mHealth app difficulty level on app usage, while controlling for user information. App usage is measured by five different activity counts of the app.

The results across five measures of mHealth app usage vary slightly. On average, previous professional diagnosis and high user performance scores encourage user participation and engagement, while disease progression hinders app usage.

The findings potentially provide insights into better design and promotion of mHealth products and improve the capability of health management of patients with chronic diseases.

Studies on the mHealth app usage are critical but sparse because large-scale and reliable mHealth app usage data are limited. Unlike earlier works based solely on survey data, this research used a large user usage data collected from an mHealth app to study key factors affecting app usage. The methods presented in this study can serve as a pioneering work for the design and promotion of mHealth technologies.

The purpose of this paper is to describe a project undertaken at SUNY Cortland to develop a system that would collect electronic resource usage data in a consistent manner and allow SUNY Cortland to assess this data over several years.

The project used data gathered from EZProxy server log files to examine usage of the library's electronic resources.

Through examining the usage data the library discovered that users were utilizing particular types of resources, from specific physical locations, and accessing those resources from specific pages in the library's web site.

By examining usage data for electronic resources, libraries can learn more than which resources are being used. Usage data can give libraries insight into where, when, how, and possibly why their users are accessing electronic resources.

The aim of this paper is to know the cost of per use, to analyze the cost per use in different subjects, to analyze the most economical as well as expensive electronic database being subscribed by the University of Delhi, to identify the database(s) for cancellation and to highlight issues related to usage statistics.

Usage statistics have been collected from the publishers for the period under study of full-text databases in the counting online usage of networked electronic resource (COUNTER) JR1 excluding downloads from an archive and Indian databases not providing COUNTER compliance usage. Usages of foreign databases have been analyzed through different parameters like yearly average cost per down load, subject-wise average cost per down, most economical databases and most expensive databases have been identified. A total approximation cost has also been worked by adopting standards practice to know the saving of University of Delhi by subscribing these databases.

The study concludes that in case of foreign databases, the cost per use has increased by 41.77 per cent in the past 10 years and the cumulative average cost per use has been Rs.55.07 less than $1 if converted into US$. In case of subject, the cheapest cost per use has been from the databases providing statistical data (Rs.26.50) and the costliest cost per use has been from discipline social science (99–196.61), followed by management (Rs.37.33), general databases (Rs.40.58), science (Rs.41.66), humanities (Rs.48.73), technology (Rs.93.22) and computer science (Rs.102.09) per use. It has also been found that the Britannica Online has been the most economical database costing Rs.2.33 and World Intellectual Property Search as most expensive costing Rs.14,902.19 per use. The study concludes that University of Delhi have saved substantial amount by subscribing these databases instead of purchasing these article from open market. The study concluded that though the usage statistics is an important parameter for renewal or cancellation, it should not be the only criteria.

This study could not able to work out the cost per use of Indian databases, as they were not able to provide COUNTER statistics.

On the basis of the study, University of Delhi and institute may decide on renewal of these databases. The institute may take necessary action to promote these databases through information literacy program. On the basis of the study, University of Delhi and institute may decide on renewal of these databases. The institute may take necessary action to promote these databases through information literacy program.

This study is an empirical research based on original usage statistics provided by the publishers in COUNTER format. Earlier literature has also been studied and used. Proper citation and reference have been acknowledged. The study has been checked through plagiarism detecting software.

This paper is an interim report of a study under way in the USA with the goal of developing a core set of national statistics and performance measures that librarians,researchers, and policy‐makers can use to describe public library and library‐based state‐wide network use of the Internet and Web‐based services and resources. The paper summarises preliminary findings and key issues identified as of January 2000. It describes a number of models for developing such statistics and performance measures. The paper also offers a number of preliminary statistics and performance measures that are being field‐tested to describe information resources and services in the networked environment. The authors expect to have a final set of such statistics and performance measures by the summer of 2000.

This paper aims to share some experiences and practical activities related to the use and management of usage data in the Digital Resource Acquisition Alliance of Chinese Academic Libraries (DRAA) as a reference for library consortia engaged in providing usage statistics services of e-resources to member libraries.

A literature review and online survey are used to analyze the research and practice of e-resources usage statistics conducted internationally. The case of DRAA is introduced to present how DRAA develops usage statistics services and promotes the implementation of the Standardized Usage Statistics Harvesting Initiative (SUSHI) to deliver usage statistics to member libraries. Future developments and enhancements are also described.

The main actions taken by DRAA to develop usage statistics services are as follows: development of the DRAA Usage Statistics Portal to provide a single point of access to usage statistics from participating publishers on behalf of member libraries; development of a SUSHI client, taking the lead in promoting SUSHI implementation to automatically obtain usage statistics in Chinese academic libraries; establishment of a working group on usage statistics and the China Academic Library and Information System/DRAA Standards and Recommended Practices Research Task Group to form a long-term mechanism for monitoring and gathering usage statistics; and strengthening of the understanding and application of standards and best practices for libraries and vendors in China. Scheduled enhancements in the future include a deep analysis and utilization of usage statistics, the promotion of Counting Online Usage of NeTworked Electronic Resources and SUSHI to Chinese academic resource publishers and raising awareness about normalizing usage statistics.

This paper has pertinence and wider implications for library consortia engaged in providing e-resources usage statistics services to member libraries.

This paper aims to identify patterns, trends and potential implications related to post-checkout non-usage (material that is checked out by a user, but subsequently never opened and/or downloaded) of library digital content.

A large urban Canadian public library’s data (2013-2017) from Rakuten OverDrive was analyzed. Pending items (items that are checked out, but neither opened nor downloaded) were compared with total checkouts to determine post-checkout non-usage rates.

Checkouts and overall rates of post-checkout non-usage of e-books and e-audiobooks have risen significantly and consistently. Juvenile and non-fiction e-books demonstrate higher post-checkout non-usage rates than adult and fiction e-books, respectively. The library spends up to US$10,700 per year on metered access e-books that are never opened by users. This number has grown significantly over the years.

E-materials in libraries have been growing rapidly, but their current lending models are still largely a direct application of concepts in traditional library services that have developed based on physical materials, such as checkouts, due dates, renewals, holds and wait times. However, e-materials do not have the limitation of physical materials that prevents other users from accessing a checked-out item, which makes many of the traditional concepts no longer applicable. New concepts and lending models should be developed that allow users to access any library e-materials at any time, and are financially functional and sustainable for both libraries and e-content providers.

The purpose of this paper is to examine the relationship between electronic journal downloads and citations and whether online electronic resource usage can be adopted as an alternative to citation for evaluation of scholarly discourse.

A consolidated 16 publishers’ COUNTER usage data of UGC-Infonet members was collected from INFLIBNET Centre. The usage was meticulously filtered from UGC-subscribed journals and institutional subscriptions. The quantitative data were analysed to establish the relationship between download, impact factor (IF) and price. Multiple regression analysis was used to assess the influence of price and IF on usage and to predict the usage when they are known and the threshold for significance was set at p < 0.05.

There exists a relationship between IF and downloads of journals in UGC-Infonet. Journal IF and price significantly influence usage, where journal IF plays an important role in the intensity of the use. Also, the top 25 hottest downloaded papers were journals with IF; hence, no journal without IF featured in the top 25 most downloaded journals in the consortia. The relationship between the top 25 IF journals in the consortia and download is strong (r = 0.368537).

The only account that reports on the relationship between journal IFs and downloads for UGC-Infonet consortia. Also, the influence of usage behaviour with respect to citation and price of a journal.

In the era of artificial intelligence (AI), algorithms have gained unprecedented importance. Scientific studies have shown that algorithms are frequently mentioned in papers, making mention frequency a classical indicator of their popularity and influence. However, contemporary methods for evaluating influence tend to focus solely on individual algorithms, disregarding the collective impact resulting from the interconnectedness of these algorithms, which can provide a new way to reveal their roles and importance within algorithm clusters. This paper aims to build the co-occurrence network of algorithms in the natural language processing field based on the full-text content of academic papers and analyze the academic influence of algorithms in the group based on the features of the network.

We use deep learning models to extract algorithm entities from articles and construct the whole, cumulative and annual co-occurrence networks. We first analyze the characteristics of algorithm networks and then use various centrality metrics to obtain the score and ranking of group influence for each algorithm in the whole domain and each year. Finally, we analyze the influence evolution of different representative algorithms.

The results indicate that algorithm networks also have the characteristics of complex networks, with tight connections between nodes developing over approximately four decades. For different algorithms, algorithms that are classic, high-performing and appear at the junctions of different eras can possess high popularity, control, central position and balanced influence in the network. As an algorithm gradually diminishes its sway within the group, it typically loses its core position first, followed by a dwindling association with other algorithms.

To the best of the authors’ knowledge, this paper is the first large-scale analysis of algorithm networks. The extensive temporal coverage, spanning over four decades of academic publications, ensures the depth and integrity of the network. Our results serve as a cornerstone for constructing multifaceted networks interlinking algorithms, scholars and tasks, facilitating future exploration of their scientific roles and semantic relations.