ParkinSong Online: protocol for a telehealth feasibility study of therapeutic group singing for people with Parkinson’s disease

IntroductionParkinson’s disease can be associated with speech deterioration and low communication confidence which in turn compromises social interaction. Therapeutic singing is an engaging method for combatting speech decline; however, face-to-face delivery can limit access to group singing. The aim of this study is to test the feasibility and acceptability of an online mode of delivery for a Parkinson’s singing intervention (ParkinSong) as well as remote data collection procedures.Methods and analysisThis ParkinSong Online feasibility trial is a single-arm, pre–post study of online singing delivery and remote data collection for 30 people living with Parkinson’s. The primary outcome measure is feasibility: recruitment, retention, attendance, safety, intervention fidelity, acceptability and associated costs. Secondary outcomes are speech (loudness, intelligibility, quality, communication-related quality of life) and wellbeing (apathy, depression, anxiety, stress, health-related quality of life). This mode of delivery aims to increase the accessibility of singing interventions.Ethics and disseminationEthics approval was obtained from The University of Melbourne Human Research Ethics Committee (2021-14465-16053-3) and the trial has been prospectively registered. Results will be presented at national and international conferences, published in a peer-reviewed journal, and disseminated to the Parkinson’s community, researchers and policymakers.Trial registration numberACTRN12621000940875.

Considerations for conducting and reporting digitally supported cognitive interviews with children and adults

Background Cognitive interviewing is a well-established qualitative method used to develop and refine PRO measures. A range of digital technologies including phone, web conferencing, and electronic survey platforms can be leveraged to support the conduct of cognitive interviewing in both children and adults. These technologies offer a potential solution to enrolling underrepresented populations, including those with rare conditions, functional limitations and geographic or socioeconomic barriers. In the aftermath of the COVID-19 pandemic, the use of digital technologies for qualitative interviewing will remain essential. However, there is limited guidance about adapting cognitive interviewing procedures to allow for remote data capture, especially with children. Methods Synthesizing the literature and our research experiences during the COVID-19 pandemic, we examine considerations for implementing digitally supported cognitive interviews with children, adolescents, and adults. We offer recommendations to optimize data quality and empirical rigor and illustrate the application of these recommendations in an ongoing cognitive interviewing study to develop and refine a new pediatric PRO measure. Results Good research practices must address participant and researcher preparation for study-related procedures and should anticipate and pre-emptively manage technological barriers. Field notes should detail interview context, audio/video cues, and any impact of technological difficulties on data quality. The approaches we recommend have been tested in an ongoing cognitive interviewing study that is enrolling children/adolescents with cGVHD ages 5–17 and their caregivers [NCT 04044365]. The combined use of telephone and videoconferencing to conduct cognitive interviews remotely is feasible and acceptable and yields meaningful data to improve the content validity of our new PRO measure of cGVHD symptom bother. Conclusion Digitally supported cognitive interviewing procedures will be increasingly employed. Remote data collection can accelerate accrual, particularly in multi-site studies, and may allow for interviewer personnel and data management to be centralized within a coordinating center, thus conserving resources. Research is needed to further test and refine techniques for remote cognitive interviewing, particularly in traditionally underrepresented populations, including children and non-English speakers. Expansion of international standards to address digitally supported remote qualitative data capture appears warranted.

The Application of Wireless Network in the Process of Remote Data Collection

The use of wireless network for remote data collection can provide a fast and reliable wireless data transmission channel for those monitoring points involving a wide area and scattered equipment layout with the help of its large coverage and high communication quality. This article analyzes the characteristics and advantages of wireless networks, and then discusses the networking scheme for remote data collection using wireless networks, and analyzes the reliability of network transmission. Finally, some program fragments on the server side are given.

Performance Evaluation of NVMe-over-TCP Using Journaling File Systems in International WAN

Distributing Big Data for science is pushing the capabilities of networks and computing systems. However, the fundamental concept of copying data from one machine to another has not been challenged in collaborative science. As recent storage system development uses modern fabrics to provide faster remote data access with lower overhead, traditional data movement using Data Transfer Nodes must cope with the paradigm shift from a store-and-forward model to streaming data with direct storage access over the networks. This study evaluates NVMe-over-TCP (NVMe-TCP) in a long-distance network using different file systems and configurations to characterize remote NVMe file system access performance in MAN and WAN data moving scenarios. We found that NVMe-TCP is more suitable for remote data read than remote data write over the networks, and using RAID0 can significantly improve performance in a long-distance network. Additionally, a fine-tuning file system can improve remote write performance in DTNs with a long-distance network.

Advances in Behavioral Remote Data Collection in the Home Setting: Assessing the Mother-Infant Relationship and Infant’s Adaptive Behavior via Virtual Visits

Psychological science is struggling with moving forward in the midst of the COVID-19 pandemic, especially due to the halting of behavioral data collection in the laboratory. Safety barriers to assessing psychological behavior in person increased the need for remote data collection in natural settings. In response to these challenges, researchers, including our team, have utilized this time to advance remote behavioral methodology. In this article, we provide an overview of our group’s strategies for remote data collection methodology and examples from our research in collecting behavioral data in the context of psychological functioning. Then, we describe the design and development of our strategies for remote data collection of mother-infant interactions, with the goal being to assess maternal sensitivity and intrusiveness, as well as infants’ adaptive behaviors in several developmental domains. During these virtual visits over Zoom, mother-infant dyads watched a book-reading video and were asked to participate in peek-a-boo, toy play, and toy removal tasks. After the behavioral tasks, a semi-structured interview (Vineland Adaptive Behavior Scale – VABS III) was conducted to assess the infant’s adaptive behavior in communication, socialization, daily living skills, and motor domains. We delineate the specific strategies we applied to integrate laboratory tasks and a semi-structured interview into remote data collection in home settings with mothers and infants. We also elaborate on issues encountered during remote data collection and how we resolved these challenges. Lastly, to inform protocols for future remote data collection, we address considerations and recommendations, as well as benefits and future directions for behavioral researchers in developmental psychology research.

Remote Data Possession Checking Scheme with Supporting Efficient Group User Authority Management for Shared Cloud Data

Under the shared big data environment, most of the existing data auditing schemes rarely consider the authorization management of group users. Meanwhile, how to deal with the shared data integrity is a problem that needs to be pondered. Thus, in this paper, we propose a novel remote data checking possession scheme which achieves group authority management while completing the public auditing. To perform authority management work, we introduce a trusted entity – group manager. We formalize a new algebraic structure operator named authorization invisible authenticator (AIA). Meanwhile, we provide two versions of AIA scheme: basic AIA scheme and standard AIA scheme. The standard AIA scheme is constructed based on the basic AIA scheme and user information table (UIT), with advanced security and wider applicable scenarios. By virtue of standard AIA scheme, the group manager can perfectly and easily carry out authority management, including enrolling, revoking, updating. On the basis of the above, we further design a public auditing scheme for non-revoked users’ shared data. The scheme is based on identity-based encryption (IBE), which greatly reduce the necessary certificate management cost. Furthermore, the detailed security analysis and performance evaluation demonstrate that the scheme is safe and feasible.