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Abstract: Aims and Objective: The aim of this study was to explore the feasibility, usability and acceptance of integrating Clinical Decision Support Systems with Socially Assistive Robots into hospital grand rounds. Background: Adopting Clinical Decision Support Systems in healthcare faces challenges such as complexity, poor integration with workflows, and concerns about data privacy and quality. Issues such as too many alerts, confusing errors, and difficulty using the technology in front of patients make adoption challenging and prevent it from fitting into daily workflows. Making Clinical Decision Support System simple, intuitive and user-friendly is essential to enable its use in daily practice to improve patient care and decision-making. Methods: This six-month pilot study had two participant groups, with total of 40 participants: a longitudinal intervention group (n =8) and a single-session evaluation group (n=32). Participants were medical doctors at the University Clinical Center Maribor. The intervention involved implementing a Clinical Decision Support System delivered via a Socially Assistive Robot during hospital grand rounds. We developed a system that employed the HL7 FHIR standard for integrating data from hospital monitors, electronic health records, and patient-reported outcomes into a single dashboard. A Pepper-based SAR provided patient specific recommendations through a voice and SAR tablet enabled interface. Key evaluation metrics were assessed using the System Usability Scale (SUS) and the Unified Theory of Acceptance, Use of Technology (UTAUT2) questionnaire, including Effort Expectancy, Performance Expectancy and open ended questions. The longitudinal group used the system for 6 months and completed the assessments twice, after one week and at the end of the study. The single-session group completed the assessment once, immediately after the experiment. Qualitative data were gathered through open-ended questions. Data analysis included descriptive statistics, paired t-tests, and thematic analysis. Results: System usability was rated highly across both groups, with the longitudinal group reporting consistently excellent scores (M =82.08 at final evaluation) compared to the acceptable scores of the single-session group (M =68.96). Extended exposure improved user engagement, reflected in significant increases in Effort Expectancy and Habit over time. Participants found the system enjoyable to use, and while no significant changes were seen in Performance Expectancy, feedback emphasized its efficiency in saving time and improving access to clinical data, supporting its feasibility and acceptability. Conclusions: This research supports the potential of robotic technologies to transform CDSS into more interactive, efficient, and user-friendly tools for healthcare professionals. The paper also suggests further research directions and technical improvements to maximize the impact of innovative technologies in healthcare.
Keywords: clinical decision support systems, clinical decision-making, hospital grand rounds, patient data integration, perceived quality of care, socially assistive robots, usability and familiarity, user experience questionnaire, workload reduction
Published in DKUM: 30.05.2025; Views: 0; Downloads: 2
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Abstract: In pig farming, knowing the exact weight of each animal is critical for the owner. Such information can help determine the amount and type of feed that needs to be fed to a specific fattening pig. Weighing pigs has always been problematic, because it is highly time consuming, and herding the pigs on the scale is extremely cumbersome. Moreover, it causes stress to the animals. The aim of our study was to build an RGB-based system that could estimate the daily weight of pigs and individual animal weight. The study was set up in a 100-day rotation in a commercial pig farm where we monitored 32 pigs. We developed a system to identify the features of the pigs, more particularly the head, shoulder, belly, and rump part. Three different models were tested, and their main differences were linked to image processing and training data. Using these models, we received higher than 97% accuracy between the predicted and the manually recorded weight of the animals. This system allows owners to manage and monitor their pigs using our web interface, allowing them to make crucial decisions during the farming process.
Keywords: image processing, pig size, decision support system, precision livestock farming
Published in DKUM: 25.04.2025; Views: 0; Downloads: 1
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Abstract: The world economy and society are in a complex process of transition characterized by a high degree of uncertainty. Therefore, further development and management of the transition will largely depend on the quality of the decisions made and, accordingly, on the decision-making process itself. The main goal of this study is to analyze the reliability of International Energy Security Risk Index as a tool to support the process of energy and economy transition decision making, as closely related and highly interdependent phenomena. The index is composed of 29 aggregated variables (grouped into eight categories), and the research is conducted on a research sample of 25 countries over a period of 36 years. The reliability assessment is performed by using Multiple Regression Analysis. Multicollinearity test, plus Multicollinearity test with Variance Inflation Factors, is used for methodological verification. The test results indicate a high degree of unreliability of the Index, as is concluded based on the observed errors in its methodological settings. These errors primarily relate to a high degree of multicollinearity in all 29 variables, whereby independent variables lose their independence and thus jeopardize reliability of the total Index. Out of the eight groups of variables, the fuel imports group is the only one that does not show big methodological errors. The paper presents a recommendation for the improvement of the observed Index (review of the role of individual variables found to be particularly methodologically indicative), as well as a recommendation for different distribution of weighting coefficients.
Keywords: energy and economy transition, decision making, international energy security risk index, multiple regression analysis, multicollinearity test, multicollinearity test with variance inflation factors
Published in DKUM: 04.02.2025; Views: 0; Downloads: 7
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Abstract: This thesis explores the impact of foreign language on moral decision making by analyzing the occurrence called Foreign Language Effect (FLE) among Slovenian primary, secondary, and university students. Students were presented with two moral dilemmas (the trolley dilemma and the footbridge dilemma) and presumed that the students would decide on the utilitarian choice in higher number when said dilemmas are presented in foreign language (English) than when they are presented in their native language (Slovene). The study dealt with three separate groups divided by educational level of students that were further split into a control group and a test group. Participants also varied by age, gender, and proficiency in the foreign language. A total of 184 of students participated in the study, responding to moral dilemmas presented in their native language (Slovene) and English. Results indicate that FLE exists as an occurrence among Slovene students across all levels of education but to various degrees. The highest impact of the FLE was viewed among primary school students who are poorer in fluency in the foreign language than both secondary and university students. FLE was more pronounced in the footbridge dilemma than in the trolley dilemma across all educational levels. Gender differences were also noted, with male students showing higher levels of FLE than females. These findings expand our understanding of FLE and add another language group onto the spectrum of foreign language effect research while also highlighting the importance of age, gender, and proficiency in the foreign language on the decision-making process.
Keywords: Foreign Language Effect (FLE), Slovene students, moral decision making, dilemma, utilitarianism
Published in DKUM: 09.01.2025; Views: 0; Downloads: 27
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Abstract: A new approach for spatial modelling of transport mode choice is presented in the paper. The approach tackles the problem by considering the trade-off between subjective and objective factors. To obtain mode Preference Rates (PRs) based on subjective factors, the Analytic Hierarchy Process (AHP) method is applied. The objective factors are expressed with the journey time from any point in the map to destination according to the available transport mode choice on the specific connection. The results are presented as PRs of individual transport modes. The model is validated on the con-ducted the survey, with students of Vienna University of Economics and Business (WU) as a target audience. Members of different target groups (age, national, employment) decide differently regarding the transport choice, so it is better to analyse them separately. The presented model can be used for the city transport planning in any urban area. It can help promote the sustainable modes of transport in the areas that are less adjusted in sustainable manner.
Keywords: transport mode choice, passenger transport, spatial modelling, city transport planning, city mobility, urban logistics, ergonomics, AHP, decision-making policy, GIS, students, objective and subjective factors, transport management
Published in DKUM: 10.12.2024; Views: 0; Downloads: 7
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