“What Can I Cook with these Ingredients?” - Understanding Cooking-Related Information Needs in Conversational Search

As conversational search becomes more pervasive, it becomes increasingly important to understand the users’ underlying information needs when they converse with such systems in diverse domains. We conduct an in situ study to understand information needs arising in a home cooking context as well as how they are verbally communicated to an assistant. A human experimenter plays this role in our study. Based on the transcriptions of utterances, we derive a detailed hierarchical taxonomy of diverse information needs occurring in this context, which require different levels of assistance to be solved. The taxonomy shows that needs can be communicated through different linguistic means and require different amounts of context to be understood. In a second contribution, we perform classification experiments to determine the feasibility of predicting the type of information need a user has during a dialogue using the turn provided. For this multi-label classification problem, we achieve average F1 measures of 40% using BERT-based models. We demonstrate with examples which types of needs are difficult to predict and show why, concluding that models need to include more context information in order to improve both information need classification and assistance to make such systems usable.

Trichotillomania in an Autistic Spectum Disroder: Single Case Intervention

The following work addresses trichotillomania and dermatillomania, both symptoms of the impulses control, in a 11 years old girl, who courses the sixth grade in a private elementary school and with a diagnose of first degree autism spectrum disorder and Attention Deficit Hyperactivity Disorder (ADHD) as a comorbidity. The objective was to reduce the frequency of tearing her hair and the skin imperfections in the school context throughout an intervention based on cognitive behavioral techniques. Within the used methodology to analyze the case an exhaustive evaluation of the patient has been performed using grade observation records, before and during the intervention period in order to systematize the whole process. The intervention techniques used where Token Economy and self-instruction. The results show a progressive improvement of the symptoms, reflected in the diminish of frequency of the behaviors registered that were conducted. In spite of the limited time for the intervention for these kinds of behaviors and the base line phase, it was possible to get to know the girl well and establish bonds with her, in spite of her condition, which can be noted in a better adaptation on her school context. This work seeks to favor the increase of research on this disorder since there is information related on the etiological factors, but it still is not enough, likewise, the related information on these disorders and its possible comorbidities is useful to continue with the advance on the treatments in this area.

Predicting Patients' Satisfaction With Doctors in Online Medical Communities

Online medical communities have revolutionized the way patients obtain medical-related information and services. Investigating what factors might influence patients’ satisfaction with doctors and predicting their satisfaction can help patients narrow down their choices and increase their loyalty towards online medical communities. Considering the imbalanced feature of dataset collected from Good Doctor, we integrated XGBoost and SMOTE algorithm to examine what factors and these factors can be used to predict patient satisfaction. SMOTE algorithm addresses the imbalanced issue by oversampling imbalanced classification datasets. And XGBoost algorithm is an ensemble of decision trees algorithm where new trees fix errors of existing trees. The experimental results demonstrate that SMOTE and XGBoost algorithm can achieve better performance. We further analyzed the role of features played in satisfaction prediction from two levels: individual feature level and feature combination level.

Hybrid Analysis of the Decision-Making Factors for Software Upgrade Based on the Integration of AHP and DEMATEL

Software is a very important part to implement advanced information systems, such as AI and IoT based on the latest hardware equipment of the fourth Industrial Revolution. In particular, decision making for software upgrade is one of the essential processes that can solve problems for upgrading the information systems. However, most of the decision-making studies for this purpose have been conducted only from the perspective of the IT professional and management position. Moreover, software upgrade can be influenced by various layers of decision makers, so further research is needed. Therefore, it is necessary to conduct research on what factors are required and affect the decision making of software upgrade at various layers of organization. For this purpose, decision factors of software upgrade are identified by literature review in this study. Additionally, the priority, degree of influence and relationship between the factors are analyzed by using the AHP and DEMATEL techniques at the organizational level of users, managers and IT professionals. The results show that the priority, weight value, causal relationship of decision factors of users, managers and IT professionals who constitute the organizational level were very different. The managers first considered the benefits, such as ROI, for organization as a leader. The users tended to consider their work efficiency and changes due to the software upgrade first. Finally, the IT professionals considered ROI, budget and compatibility for the aspect of the managers and users. Therefore, the related information of each organizational level can be presented more clearly for the systematic and symmetrical decision making of software upgrade based on the results of this study.

Defaults versus framing: Revisiting Default Effect and Framing Effect with replications and extensions of Johnson and Goldstein (2003) and Johnson, Bellman, and Lohse (2002)

People tend to stick with a default option instead of switching to another option. For instance, Johnson and Goldstein (2003) found a default effect in an organ donation scenario: if organ donation is the default option, people are more inclined to consent to it. Johnson et al. (2002) found a similar default effect in a health-survey scenarios: if receiving more information about your health is the default, people are more inclined to consent to it. Much of the highly cited, impactful work on these default effects, however, has not been replicated in well-powered samples. In two well-powered samples (N = 1920), we conducted a close replication of the default effect in Johnson and Goldstein (2003) and in Johnson, Bellman, and Lohse (2002). We successfully replicated Johnson and Goldstein (2003). In an extension of the original findings, we also show that default effects are unaffected by the permanence of these selections. We, however, failed to replicate the findings of Johnson, Bellman, and Lohse’s (2002) study; we did not find evidence for a default effect. We did, however, find a framing effect: participants who read a positively-framed scenario consented to receive health-related information at a higher rate than participants who read a negatively framed scenario. We also conducted a conceptual replication of Johnson et al. (2002) that was based on an organ-donation scenario, but this attempt failed to find a default effect. Our results suggest that default effects depend on framing and context. Materials, data, and code are available on: https://osf.io/8wd2b/.

HPV Vaccination: Polish-Language Facebook Discourse Analysis

Social media platforms are widely used for spreading vaccine-related information. The objectives of this paper are to characterize Polish-language human papillomavirus (HPV) vaccination discourse on Facebook and to trace the possible influence of the COVID-19 pandemic on changes in the HPV vaccination debate. A quantitative and qualitative analysis was carried out based on data collected with a tool for internet monitoring and social media analysis. We found that the discourse about HPV vaccination bearing negative sentiment is centralized. There are leaders whose posts generate the bulk of anti-vaccine traffic and who possess relatively greater capability to influence recipients’ opinions. At the beginning of the COVID-19 pandemic vaccination debate intensified, but there is no unequivocal evidence to suggest that interest in the HPV vaccination topic changed.

What Accounts for the Variation in COVID-19 Vaccine Hesitancy in Eastern, Southern and Western Europe?

Attitudes towards vaccination have proven to be a major factor determining the pace of national COVID-19 vaccination campaigns throughout 2021. In Europe, large differences in levels of vaccine hesitancy and refusal have emerged, which are highly correlated with actual vaccination levels. This article explores attitudes towards COVID-19 vaccination in 27 European countries based on data from Eurobarometer (May 2021). The statistical analyses show that demographic variables have complex effects on vaccine hesitancy and refusal. Trust in different sources of health-related information has significant effects as well, with people who trust the Internet, social networks and ‘people around’ in particular being much more likely to express vaccine skepticism. As expected, beliefs in the safety and effectiveness of vaccines have large predictive power, but – more interestingly – net of these two beliefs, the effects of trust in Internet, online social networks and people as sources of health information are significantly reduced. This study shows that the effects of demographic, belief-related and other individual-level factors on vaccine hesitancy and refusal are context-specific. Yet, explanations of the differences in vaccine hesitancy across Europe need to consider primarily different levels of trust and vaccine-relevant beliefs, and to a lesser extent their differential effects.

The System of Awarding Degrees in Higher Education of Iran and United Kingdom: A Descriptive-Comparative Study With Focusing on the Internationalization of Health Education

The main indicators of higher education (HE) internationalization in the field of awarding degrees are the international development of disciplines and interdisciplinary sciences, new educational and learning methods, new and updated curricula, and their correct ways of sharing. This study aimed to examine the system of awarding degrees in health HE of Iran and the United Kingdom. This descriptive-comparative study focused on the field of medical sciences and its related disciplines. The vital information about the variables was collected by visiting the official websites of the UK universities and related or joint organizations. The related information to the Kerman University of Medical Sciences as a sample of Iran medical universities was obtained from the university’s Farabar system. All data extraction steps were performed manually. There were differences in the mechanism of setting up a new discipline and the process of students’ admission, diversity of degrees’ titles and curriculums, stability of disciplines over the time, creativity in creating competition between different disciplines, the reason for establishing a discipline and the requirements for certification and awarding of degrees in health sciences disciplines in Iran and the United Kingdom were described. Propelling of medical education in the health sciences area towards standard awarding degree systems can be responsible for the requirements of internationalization of higher education.