Collection of Ego-Centered Network Data with Computer-Assisted Interviews

Methodology ◽  
2006 ◽  
Vol 2 (1) ◽  
pp. 7-15 ◽  
Author(s):  
Joachim Gerich ◽  
Roland Lehner

Although ego-centered network data provide information that is limited in various ways as compared with full network data, an ego-centered design can be used without the need for a priori and researcher-defined network borders. Moreover, ego-centered network data can be obtained with traditional survey methods. However, due to the dynamic structure of the questionnaires involved, a great effort is required on the part of either respondents (with self-administration) or interviewers (with face-to-face interviews). As an alternative, we will show the advantages of using CASI (computer-assisted self-administered interview) methods for the collection of ego-centered network data as applied in a study on the role of social networks in substance use among college students.

2015 ◽  
Vol 31 (1) ◽  
pp. 119-132 ◽  
Author(s):  
Michaele L. Morrow ◽  
Shane R. Stinson

ABSTRACT In this case, students assume the role of new accounting staff tasked with the preparation of a personal income tax return and supporting documentation for a client of their firm. Students are provided prior year work papers and client communications, a copy of the prior year's tax return, as well as a letter and supporting documents from the client for the current year. To complete the case, students generate questions based on the initial information provided, meet face-to-face with the client, and roll forward a set of electronic work papers before submitting a complete current year engagement file for senior review. This case adds work papers and client interaction to the traditional tax compliance case to reinforce both the technical and communication skills valued in professional practice. The formulation of questions for the client also allows students to practice discussing technical topics in a non-technical manner and underscores the required balance between attitudes of client advocacy stressed in professional tax practice and legal requirements for “good-faith” tax return reporting. This case is appropriate for an individual income tax course at either the undergraduate or graduate level, and can be easily adapted to increase or decrease difficulty.


2021 ◽  
pp. 216770262095934
Author(s):  
Julia M. Sheffield ◽  
Holger Mohr ◽  
Hannes Ruge ◽  
Deanna M. Barch

Rapid instructed task learning (RITL) is the uniquely human ability to transform task information into goal-directed behavior without relying on trial-and-error learning. RITL is a core cognitive process supported by functional brain networks. In patients with schizophrenia, RITL ability is impaired, but the role of functional network connectivity in these RITL deficits is unknown. We investigated task-based connectivity of eight a priori network pairs in participants with schizophrenia ( n = 29) and control participants ( n = 31) during the performance of an RITL task. Multivariate pattern analysis was used to determine which network connectivity patterns predicted diagnostic group. Of all network pairs, only the connectivity between the cingulo-opercular network (CON) and salience network (SAN) during learning classified patients and control participants with significant accuracy (80%). CON-SAN connectivity during learning was significantly associated with task performance in participants with schizophrenia. These findings suggest that impaired interactions between identification of salient stimuli and maintenance of task goals contributes to RITL deficits in participants with schizophrenia.


Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3327
Author(s):  
Vicente Román ◽  
Luis Payá ◽  
Adrián Peidró ◽  
Mónica Ballesta ◽  
Oscar Reinoso

Over the last few years, mobile robotics has experienced a great development thanks to the wide variety of problems that can be solved with this technology. An autonomous mobile robot must be able to operate in a priori unknown environments, planning its trajectory and navigating to the required target points. With this aim, it is crucial solving the mapping and localization problems with accuracy and acceptable computational cost. The use of omnidirectional vision systems has emerged as a robust choice thanks to the big quantity of information they can extract from the environment. The images must be processed to obtain relevant information that permits solving robustly the mapping and localization problems. The classical frameworks to address this problem are based on the extraction, description and tracking of local features or landmarks. However, more recently, a new family of methods has emerged as a robust alternative in mobile robotics. It consists of describing each image as a whole, what leads to conceptually simpler algorithms. While methods based on local features have been extensively studied and compared in the literature, those based on global appearance still merit a deep study to uncover their performance. In this work, a comparative evaluation of six global-appearance description techniques in localization tasks is carried out, both in terms of accuracy and computational cost. Some sets of images captured in a real environment are used with this aim, including some typical phenomena such as changes in lighting conditions, visual aliasing, partial occlusions and noise.


2021 ◽  
pp. 107385842110366
Author(s):  
Emilia Giannella ◽  
Valentino Notarangelo ◽  
Caterina Motta ◽  
Giulia Sancesario

Biobanking has emerged as a strategic challenge to promote knowledge on neurological diseases, by the application of translational research. Due to the inaccessibility of the central nervous system, the advent of biobanks, as structure collecting biospecimens and associated data, are essential to turn experimental results into clinical practice. Findings from basic research, omics sciences, and in silico studies, definitely require validation in clinically well-defined cohorts of patients, even more valuable when longitudinal, or including preclinical and asymptomatic individuals. Finally, collecting biological samples requires a great effort to guarantee respect for transparency and protection of sensitive data of patients and donors. Since the European General Data Protection Regulation 2016/679 has been approved, concerns about the use of data in biomedical research have emerged. In this narrative review, we focus on the essential role of biobanking for translational research on neurodegenerative diseases. Moreover, we address considerations for biological samples and data collection, the importance of standardization in the preanalytical phase, data protection (ethical and legal) and the role of donors in improving research in this field.


Author(s):  
Alicja Niedźwiecka

AbstractEye contact is a crucial aspect of social interactions that may enhance an individual’s cognitive performance (i.e. the eye contact effect) or hinder it (i.e. face-to-face interference effect). In this paper, I focus on the influence of eye contact on cognitive performance in tasks engaging executive functions. I present a hypothesis as to why some individuals benefit from eye contact while others do not. I propose that the relations between eye contact and executive functioning are modulated by an individual’s autonomic regulation and reactivity and self-regulation of attention. In particular, I propose that individuals with more optimal autonomic regulation and reactivity, and more effective self-regulation of attention benefit from eye contact. Individuals who are less well regulated and over- or under-reactive and who do not employ effective strategies of self-regulation of attention may not benefit from eye contact and may perform better when eye contact is absent. I present some studies that justify the proposed hypothesis and point to a method that could be employed to test them. This approach could help to better understand the complex mechanisms underlying the individual differences in participant’s cognitive performance during tasks engaging executive functions.


Author(s):  
Julia Eberle ◽  
Karsten Stegmann ◽  
Alain Barrat ◽  
Frank Fischer ◽  
Kristine Lund

AbstractCollaborations are essential in research, especially in answering increasingly complex questions that require integrating knowledge from different disciplines and that engage multiple stakeholders. Fostering such collaboration between newcomers and established researchers helps keep scientific communities alive while opening the way to innovation. But this is a challenge for scientific communities, especially as little is known about the onset of such collaborations. Prior social network research suggests that face-to-face interaction at scientific events as well as both network-driven selection patterns (reciprocity and transitivity) and patterns of active selection of specific others (homophily / heterophily) may be important. Learning science research implies, moreover, that selecting appropriate collaboration partners may require group awareness. In a field study at two scientific events on technology-enhanced learning (Alpine Rendez-Vous 2011 and 2013) including N = 5736 relations between 287 researchers, we investigated how researchers selected future collaboration partners, looking specifically at the role of career level, disciplinary background, and selection patterns. Face-to-face contact was measured using RFID devices. Additionally, a group awareness intervention was experimentally varied. Data was analyzed using RSiena and meta-analyses. The results showed that transitivity, reciprocity and contact duration are relevant for the identification of new potential collaboration partners. PhD students were less often chosen as new potential collaboration partners, and researchers with a background in Information Technology selected fewer new potential collaboration partners. However, group awareness support balanced this disciplinary difference. Theoretical, methodological, and practical implications of these findings are discussed.


2016 ◽  
Vol 23 (3) ◽  
pp. 600 ◽  
Author(s):  
Uba Backonja ◽  
Nai-Ching Chi ◽  
Yong Choi ◽  
Amanda K Hall ◽  
Thai Le ◽  
...  

Background: Health technologies have the potential to support the growing number of older adults who are aging in place. Many tools include visualizations (data visualizations, visualizations of physical representations). However, the role of visualizations in supporting aging in place remains largely unexplored.Objective: To synthesize and identify gaps in the literature evaluating visualizations (data visualizations and visualizations of physical representations), for informatics tools to support healthy aging.Methods: We conducted a search in CINAHL, Embase, Engineering Village, PsycINFO, PubMed, and Web of Science using a priori defined terms for publications in English describing community-based studies evaluating visualizations used by adults aged ≥65 years.Results: Six out of the identified 251 publications were eligible. Most studies were user studies and varied methodological quality. Three visualizations of virtual representations supported performing at-home exercises. Participants found visual representations either (a) helpful, motivational, and supported their understanding of their health behaviors or (b) not an improvement over alternatives. Three data visualizations supported understanding of one’s health. Participants were able to interpret data visualizations that used precise data and encodings that were more concrete better than those that did not provide precision or were abstract. Participants found data visualizations helpful in understanding their overall health and granular data.Conclusions: Studies we identified used visualizations to promote engagement in exercises or understandings of one’s health. Future research could overcome methodological limitations of studies we identified to develop visualizations that older adults could use with ease and accuracy to support their health behaviors and decision-making.


2021 ◽  
Vol 13 (9) ◽  
pp. 4902
Author(s):  
Zia Ullah ◽  
Rana Tahir Naveed ◽  
Atta Ur Rehman ◽  
Naveed Ahmad ◽  
Miklas Scholz ◽  
...  

The literature on sustainable tourism is scant, particularly in the least developed countries. Very few studies touch upon the concept and no holistic theoretical or conceptual frameworks around the idea of sustainable tourism have been formulated. This study aims at exploring the role of tour operators in developing sustainable tourism in Pakistan and how the tour operators (TOs) conceive their role in this regard. TOs were reached through phone calls, emails, and virtual sources as face-to-face interviews were not possible due to COVID-19 pandemic and restrictions on travel by the government. In-depth interviews were conducted to gather data. Results suggest that the TOs although realize the importance of social, environmental, and economic dimensions of tourism on the communities but have no management systems in place to cater accordingly. There are no incentives in place by the government facilitate TOs to design and implement such systems. The TOs do not select a destination based on Global Sustainable Tourism Council criterion, but rather the selection of destination is mostly demand-based and profit-oriented. The study suggests that corporate profit motive is the sole criterion for decision making and is one of the major causes impeding sustainable tourism in Pakistan. The role of TOs in developing sustainable tourism is vague as the TOs do not have any systems in place to implement sustainable models. The study recommends that efforts need to be put in place to incentivize sustainable tourism in Pakistan and proper laws should be set forth by the authorities to comply by the TOs. The role of TOs is important and understood, however, there is a need to put proper systems in place.


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