Intention of healthcare providers to use video-communication in terminal care: a cross-sectional study. Richard M. H. Evering, Marloes G. Postel, Harmieke van Os-Medendorp, Marloes Bults and Marjolein E. M. den Ouden BMC Palliative Care volume 21, Article number: 213 (2022) Cite this articleAbstractBackgroundInterdisciplinary collaboration between healthcare providers with regard to consultation, transfer and advice in terminal care is both important and challenging. The use of video communication in terminal care is low while in first-line healthcare it has the potential to improve quality of care, as it allows healthcare providers to assess the clinical situation in real time and determine collectively what care is needed. The aim of the present study is to explore the intention to use video communication by healthcare providers in interprofessional terminal care and predictors herein.MethodsIn this cross-sectional study, an online survey was used to explore the intention to use video communication. The survey was sent to first-line healthcare providers involved in terminal care (at home, in hospices and/ or nursing homes) and consisted of 39 questions regarding demographics, experience with video communication and constructs of intention to use (i.e. Outcome expectancy, Effort expectancy, Attitude, Social influence, Facilitating conditions, Anxiety, Self-efficacy and Personal innovativeness) based on the Unified Theory of Acceptance and Use of Technology and Diffusion of Innovation Theory. Descriptive statistics were used to analyze demographics and experiences with video communication. A multiple linear regression analysis was performed to give insight in the intention to use video communication and predictors herein.Results90 respondents were included in the analysis.65 (72%) respondents had experience with video communication within their profession, although only 15 respondents (17%) used it in terminal care. In general, healthcare providers intended to use video communication in terminal care (Mean (M) = 3.6; Standard Deviation (SD) = .88). The regression model was significant and explained 44% of the variance in intention to use video communication, with ‘Outcome expectancy’ and ‘Social influence’ as significant predictors.ConclusionsHealthcare providers have in general the intention to use video communication in interprofessional terminal care. However, their actual use in terminal care is low. ‘Outcome expectancy’ and ‘Social influence’ seem to be important predictors for intention to use video communication. This implicates the importance of informing healthcare providers, and their colleagues and significant others, about the usefulness and efficiency of video communication.
MULTIFILE
In dit artikel wordt gekeken naar de relatie tussen het gebruik van mobiele applicaties en fysieke activiteit en gezonde leefstijl. Dit is gedaan op basis van een vragenlijst onder deelnemers aan een hardloopevenement, de Dam tot Damloop. Er werden aparte analyses gedaan voor 8km lopers en 16 km lopers. Een positieve relatie werd gevonden tussen app gebruik en meer bewegen en zich gezonder voelen. App gebruik was ook positief gerelateerd aan beter voelen over zichzelf, je voelen als een atleet, anderen motiveren om te gaan hardlopen en afvallen. Voor de 16 km lopers was app gebruik gerelateerd aan gezonder eten, zich meer energieker voelen en een hogere kans om het sportgedrag vol te houden. De resultaten van dit onderzoek laten zien dat app gebruik mogelijk een ondersteunende rol kunnen hebben in de voorbereiding op een hardloopevenemen, aangezien het gezondheid en fysieke activiteit stimuleert.
DOCUMENT
BackgroundThe challenge of combining professional work and breastfeeding is a key reason why women choose not to breastfeed or to stop breastfeeding early. We posited that having access to a high-quality lactation room at the workplace could influence working mothers’ satisfaction and perceptions related to expressing breast milk at work, which could have important longer term consequences for the duration of breastfeeding. Specifically, we aimed to (1) develop a checklist for assessing the quality of lactation rooms and (2) explore how lactation room quality affects lactating mothers’ satisfaction and perceptions. Drawing on social ecological insights, we hypothesized that the quality of lactation rooms (operationalized as any space used for expressing milk at work) would be positively related to mothers’ satisfaction with the room, perceived ease of, and perceived support for milk expression at work.MethodsWe conducted two studies. In Study 1 we developed a lactation room quality checklist (LRQC) and assessed its reliability twice, using samples of 33 lactation rooms (Study 1a) and 31 lactation rooms (Study 1b). Data were collected in the Northern part of the Netherlands (between December 2016 and April 2017). Study 2 comprised a cross-sectional survey of 511 lactating mothers, working in a variety of Dutch organizations. The mothers were recruited through the Facebook page of a popular Dutch breastfeeding website. They completed online questionnaires containing the LRQC and measures aimed at assessing their satisfaction and perceptions related to milk expression at work (in June and July 2017).ResultsThe LRQC was deemed reliable and easy to apply in practice. As predicted, we found that objectively assessed higher-quality lactation rooms were associated with increased levels of satisfaction with the lactation rooms, perceived ease of milk expression at work, and perceived support from supervisors and co-workers for expressing milk in the workplace.ConclusionsThe availability of a high-quality lactation room could influence mothers’ decisions regarding breast milk expression at work and the commencement and/or continuation of breastfeeding. Future studies should explore whether and how lactation room quality affects breastfeeding choices, and which aspects are most important to include in lactation rooms.
DOCUMENT
Despite the benefits of the widespread deployment of diverse Internet-enabled devices such as IP cameras and smart home appliances - the so-called Internet of Things (IoT) has amplified the attack surface that is being leveraged by cyber criminals. While manufacturers and vendors keep deploying new products, infected devices can be counted in the millions and spreading at an alarming rate all over consumer and business networks. The objective of this project is twofold: (i) to explain the causes behind these infections and the inherent insecurity of the IoT paradigm by exploring innovative data analytics as applied to raw cyber security data; and (ii) to promote effective remediation mechanisms that mitigate the threat of the currently vulnerable and infected IoT devices. By performing large-scale passive and active measurements, this project will allow the characterization and attribution of compromise IoT devices. Understanding the type of devices that are getting compromised and the reasons behind the attacker’s intention is essential to design effective countermeasures. This project will build on the state of the art in information theoretic data mining (e.g., using the minimum description length and maximum entropy principles), statistical pattern mining, and interactive data exploration and analytics to create a casual model that allows explaining the attacker’s tactics and techniques. The project will research formal correlation methods rooted in stochastic data assemblies between IoT-relevant measurements and IoT malware binaries as captured by an IoT-specific honeypot to aid in the attribution and thus the remediation objective. Research outcomes of this project will benefit society in addressing important IoT security problems before manufacturers saturate the market with ostensibly useful and innovative gadgets that lack sufficient security features, thus being vulnerable to attacks and malware infestations, which can turn them into rogue agents. However, the insights gained will not be limited to the attacker behavior and attribution, but also to the remediation of the infected devices. Based on a casual model and output of the correlation analyses, this project will follow an innovative approach to understand the remediation impact of malware notifications by conducting a longitudinal quasi-experimental analysis. The quasi-experimental analyses will examine remediation rates of infected/vulnerable IoT devices in order to make better inferences about the impact of the characteristics of the notification and infected user’s reaction. The research will provide new perspectives, information, insights, and approaches to vulnerability and malware notifications that differ from the previous reliance on models calibrated with cross-sectional analysis. This project will enable more robust use of longitudinal estimates based on documented remediation change. Project results and methods will enhance the capacity of Internet intermediaries (e.g., ISPs and hosting providers) to better handle abuse/vulnerability reporting which in turn will serve as a preemptive countermeasure. The data and methods will allow to investigate the behavior of infected individuals and firms at a microscopic scale and reveal the causal relations among infections, human factor and remediation.
