Information Behavior Research Articles

What drives Chinese youth to use fitness-related health information on social media? An analysis of intrinsic needs, social media algorithms, and source credibility

IntroductionThe role of social media in providing fitness-related health information has been widely discussed; however, there is a notable lack of research on fitness-related health information behaviors among youth within the social media context. This study aims to address this gap by integrating Self-Determination Theory (SDT)-based internal factors and external factors (social media algorithms and source credibility).MethodsA voluntary sample of 600 participants, aged 15 to 29, was recruited. Data were analyzed using Partial Least Squares-Structural Equation Modeling (PLS-SEM) to examine the relationships between variables.ResultsThe analysis revealed that all three intrinsic needs—competence, autonomy, and relatedness—along with social media algorithms and source credibility, positively correlated with fitness-related health information use behaviors among youth. Additionally, social media algorithms moderated the relationship between the need for relatedness and fitness-related health information behavior.DiscussionThese findings provide new insights into developing health communication strategies on social media, particularly targeted toward the youth demographic, enhancing our understanding of effective health information dissemination in digital environments.

Optimization algorithm of power system line loss management using big data analytics

As global energy demand continues to rise and renewable energy sources develop rapidly, the operational efficiency and stability of power systems have emerged as primary challenges in energy management. Line loss within these systems is a critical factor for both energy efficiency and economic performance. This study leverages an electric energy data management platform that facilitates the sharing of archival information, the development of line loss calculation models, and the automated computation of electricity and line loss formulas. This ensures accurate and real-time calculations of line losses in the power grid, supporting multi-time scale analyses and providing timely, comprehensive data for effective line loss management. The platform utilizes theoretical line loss values to identify anomalies, which are categorized into five types: topological relationships, archival information, data collection, electricity metering, and consumption behavior. In response to the abnormal monthly power imbalance rate of 220 kV and 110 KV stations, and the − 3.684% exceeding the − 1% assessment limit, the designed line loss management system service layer does not need to go deep into the bottom layer of the power system. It hides the complexity of the power grid through middleware and provides data, application, and security services.

Teachers' information-seeking on accomplishments of academic tasks

Background of the study: Teachers have a vital role in education, which includes educating and guiding students, developing teaching materials, preparing lesson plans, and performing student evaluations. Therefore, individuals need information in order to complete their educational objectives. Purpose: This review aims to systematically examine the three constituent elements of information-seeking behavior, with a particular emphasis on their application within the teaching field. Method: The systematic literature evaluation in this study was guided by the PRISMA approach. The study's data collecting phase spanned a period of twenty years, specifically from 2003 to 2023. The study's results encompassed an extensive review of 25 research papers about the information-seeking behavior shown by educators. This review employed an inductive approach to data analysis. Findings: Teachers demonstrate a preference for selecting information sources that encompass digital, printed, and interpersonal types. Teachers prioritize information sources that are familiar, user-friendly, and have a well-designed interface. Teachers have several barriers when seeking information, which can be attributed to both internal and external constraints. Conclusion: This study draws on studies related to teachers' information behavior published in the last 20 years. Our goal is to comprehensively understand the information sources teachers use, their awareness of these sources of information, and the constraints they encounter when information-seeking.

The relationship between eWoM, security, quality of information and purchase behaviour at B2C e-commerce website: the moderating role of E-trustmarks

The relationship between eWoM, security, quality of information and purchase behaviour at B2C e-commerce website: the moderating role of E-trustmarks

Pengaruh Problem Solving Therapy terhadap Kecemasan Global pada Pasien Skizofrenia

Background: Schizophrenia is a serious mental disorder that is often encountered and hospitalized. Schizophrenia is a long-term and serious brain disease that results in psychotic behavior, concrete thinking, and difficulties in processing information, interpersonal relationships, and solving problems. One of the symptoms that arise from various types of disorders and symptoms of schizophrenia is anxiety which affects daily functional limitations, including the inability to solve problems. Therefore, non-pharmacological therapy with CBT is given to train the patient's problem-solving skills. Objectives: This study aims to determine the effect of problem-solving therapy on global anxiety in schizophrenia patients. Methods: This research uses a quantitative approach, with a pre-experimental research design type One group Pretest-posttest. The research sample consisted of 22 people, obtained through purposive sampling. The instrument used to measure the sample's anxiety was the Hamilton Anxiety Rating Scale (HARS). Hypothesis testing analysis uses a paired sample t-test. Results: The research sample was dominated by men (63.6%), aged 26-35 years (50%), had a history of high school/K education (50%), and a low socioeconomic level (81.8%). Hypothesis testing showed a p-value of 0.000 (p<0.05). Conclusion: Problem-solving therapy affects the global anxiety of schizophrenia patients at RSJD Dr. RM. Soedjarwadi Klaten. Bibliography: 74 (2009-2023) Keywords: Problem-Solving Therapy, Anxiety, Schizophrenia

Network structure and time delays shape synchronization patterns in brain network models.

In this paper, we investigate synchronization patterns and coherence for a network of delayed Wilson-Cowan nodes. To capture information processing across different brain regions, our model incorporates two distinct delays: an intra-nodal delay that reflects the time signals take to travel within a cortical region due to local circuitry and an inter-nodal delay representing the longer communication times associated with white matter connections between brain areas. To investigate the role of network topology, we consider a range of toy network structures as well as the known (macro-scale) cortical structure of the Macaque monkey. We examine how global network dynamics are shaped by a combination of network configuration, coupling strength, and time delays. Our focus lies on two dynamic measures: synchrony and metastability, the latter reflecting the temporal variation of the former, both crucial for the brain's real-time functionality. Our investigation identifies extensive regions within the system's parameter space where the synchronized state exhibits transverse instabilities. These instabilities give rise to diverse dynamical behaviors contingent upon the network architecture and the interplay between coupling strength and time delay. While similar complex partially synchronized states existed for all network topologies considered, the cortical network demonstrated time-dependent behaviors, such as phase cluster dynamics, which were absent in the toy network architectures, and which are considered crucial in its ability to orchestrate complex information processing and behavior. Additionally, we illustrate how delays can regulate a cortical network with chaotic local dynamics, thus emphasizing the potential importance of delays in suppressing pathological spreading dynamics.

Investigating the Impact of Health-Protective Behaviors on Morbidity and non-Morbidity COVID-19 among Workers in Oil Refining Industry Using Machine Learning algorithms

Introduction: The prevalence of COVID-19 has significantly impacted work environments and the workforce. Therefore, identifying the most important preventive and control strategies, as well as assessing their effectiveness, is of paramount importance. Various studies have shown that machine learning algorithms can be used to predict complex and nonlinear issues, including predicting the behavior of various diseases such as COVID-19 and the parameters affecting it, and can be beneficial. The purpose of this study has been to examine the importance of preventive measures and hygiene behaviors in preventing COVID-19 in the oil refining industry using various machine learning models. Material and Methods: For this purpose, demographic information and health behaviors of individuals were collected. Subsequently, a multi-layer perceptron (MLP), radial basis function (RBF), and support vector machine (SVM) models were compared to enhance the analysis of the effects of preventive measures on COVID-19 infection. Finally, the most influential factors affecting the likelihood of COVID-19 infection were determined using sensitivity analysis. Results: The results showed that the accuracies achieved in predicting the impact of preventive measures and health behaviors on COVID-19 in occupational settings were 78.1%, 81.2%, and 78.1% by MLP, RBF, and SVM respectively. The RBF model was identified as the most accurate model for predicting the impact of health behaviors on COVID-19 disease Additionally, the level of social distancing with customers, handwashing frequency and disinfection, the availability of cleansing and disinfecting agents for hands and surfaces in the workplace, and gatherings for eating meals and snacks were identified as the most significant health behaviors influencing the prevalence of COVID-19 in the workplace. Conclusion: Studies of this nature can underscore the importance of attention to preventive measures and health behaviors in unprecedented circumstances. Furthermore, the utilization of artificial intelligence models and tools such as DSS (Decision Support Systems) can serve as powerful tools for optimizing control measures in work environments.

Privacy and political online microtargeting during the German Federal Election 2021*

ABSTRACT In the context of Federal Elections, political parties frequently engage in targeting social media users with tailored content. To facilitate this, personal data must be collected and processed, often without the users’ explicit awareness. Many users view political online microtargeting as an intrusion upon their privacy. In a longitudinal time-based sampling study shortly before, during, and after the German Federal Election in 2021, we surveyed social media users (N = 126) about their perception of political online microtargeting and individual privacy. In particular, we evaluated participants’ perception of being targeted, perceived social media affordances (anonymity, association), availability of privacy mechanisms (control, trust, norms, communication), and their subjective experience of privacy (experienced level of access, privacy perception). Furthermore, we evaluated how these variables influence users’ privacy regulation behaviours (interdependent or egocentric), political self-efficacy, future political information behaviour, and voting behaviour in the light of political online microtargeting. Multilevel analyses revealed that it is difficult for users to detect targeted ads, but that they feel more private and self-efficacious in their political and future political information behaviour if they believe they can rely on privacy mechanisms such as trust and control.

BGP anomaly detection as a group dynamics problem

Understanding group information and collective behaviors is an ongoing area of research, encompassing natural phenomena and human dynamics. Quantifying interactions and interdependencies at the group level can be valuable for understanding complex and dynamical systems. The Border Gateway Protocol (BGP), the default inter-domain routing protocol for the Internet, operates within a large, complex, and dynamic system vulnerable to security threats. Traditional BGP anomaly detection focuses on single observables from individual Autonomous Systems (ASes), which inadequately addresses the multidimensional, multi-viewpoint nature of the Internet and interdomain routing. This paper introduces a novel approach for quantifying group AS-level information and dynamics. We present the first ever application of Multidimensional Recurrence Quantification Analysis (MdRQA) to any computer system, offering a robust BGP anomaly detection technique that identifies anomalies earlier than traditional single-AS observable methods. This research marks a significant advancement in BGP anomaly detection, treating it as a group dynamics problem within the Internet’s complex and distributed system.

2019 개정 누리과정 현장지원자료의 디지털 시민성 분석: 디지털 놀이 사례를 중심으로

Objectives This study aims to analyze the On-site Support Data created to support the implementation of the 2019 revised Nuri Curriculum to explore the direction of fostering digital citizenship in early childhood. Methods To achieve this, 37 cases of young children's digital play, sourced from the ‘On-site Support Data’ on the I-Nuri portal site where national curriculum and information integration services are provided by the Ministry of Education, were analyzed using the content analysis method based on UNESCO's (2019) digital citizenship classification. Results The study results showed that in the digital play cases, which were the main focus of analysis, young children primarily demonstrated ‘digital literacy’ as a key component of digital citizenship. This emphasizes their ability to navigate and utilize content using various digital devices. In some play cases, key elements of digital citizenship, such as responsible behavior, ethical conduct, and critical evaluation of information in online environments, were also observed. However, there were cases where elements of digital citizenship were less evident, particularly with a lack of focus on ‘digital safety and resilience.’ Conclusions It is considered that the findings of this study can serve as a foundation for various educational practices aimed at helping young children grow to be responsible citizens in the digital world.

Enhancing Movie Recommendation Systems Through CNN-Based Feature Extraction and Optimized Collaborative Filtering

Abstract. This paper presents the design and implementation of a movie recommendation model that combines collaborative filtering with Convolutional Neural Networks (CNNs) to tackle the challenge of information overload in extensive movie databases. The primary objective is to enhance the user experience by developing an efficient and personalized recommendation system. The proposed model integrates CNNs to extract detailed image features from movie posters, enriching the movie representations used in the recommendation process. This feature extraction is coupled with an optimized collaborative filtering algorithm to deliver more accurate and tailored movie suggestions. The study is based on a dataset that includes movie information, user ratings, and user behavior data. Experimental results demonstrate that the proposed model significantly improves the accuracy and personalization of movie recommendations, thereby offering users a superior selection experience. The practical implications of this research are substantial, as it has the potential to boost user satisfaction and engagement on movie recommendation platforms. Future work will focus on further enhancing the model by incorporating long-term user behavior patterns and integrating multi-modal data sources for even more precise recommendations.

Information seeking behaviour of informal caregivers at the premier tertiary teaching hospital in Nigeria

This study was conducted to examine the information behaviour of informal caregivers in a university college hospital in Ibadan, Nigeria. Informal caregivers in the teaching hospitals constitute critical pubic health care players whose information behaviours have not been studied. Data was collected from 208 caregivers using a questionnaire that consisted of structured and open-ended questions. The study found that healthcare providers were the primary source of health for caregivers, with 34.1% actively seeking information from them. The caregivers seldom utilised sources like the internet, community organizations, books, family, and friends. The preference for healthcare providers as sources is due to their accessibility and ability to provide prompt and accurate answers. Caregivers have diverse information needs, including medication-related information, first aid techniques, nutrition, exercise, mental health, and lifestyle choices. They seek this knowledge to make informed decisions that improve their loved ones’ well-being. The study also revealed that caregivers heavily rely on information technology for health information due to its accessibility and reliability. The study highlights the need for ongoing training and proactive information sharing by healthcare providers to better support informal caregivers in Nigeria, emphasizing the importance of integrated support systems within healthcare facilities. To meet diverse information needs, healthcare institutions should diversify dissemination strategies, including culturally sensitive materials and digital literacy programs, while developing tailored mobile applications and online support communities for caregivers. Policymakers must focus on creating supportive healthcare policies, funding caregiver programs, and expanding insurance coverage to alleviate financial burdens, ensuring that caregivers have access to necessary resources and information.

Effects and Mechanisms of TikTok Use on Self-Rated Health of Older Adults in China During the COVID-19 Pandemic: A Mediation Analysis.

During the COVID-19 pandemic, TikTok emerged as a significant app for entertainment and information acquisition for the general public, gradually extending its reach to the older population. Digital technology, exemplified by TikTok, has become an indispensable part of older adults' lives. However, while prior studies have extensively focused on the impact of internet use on older adults' health, research on the impact of TikTok during the COVID-19 pandemic remains insufficient. Utilizing data from the China Family Panel Studies (CFPS) 2020, this study explored the impact of TikTok use on older adults' self-rated health and its underlying mechanisms through multiple regression and mediation analysis. The study found that (1) TikTok use had a significant positive effect on the self-rated health of older adults; (2) while TikTok use increased the exercise frequency of older adults, exercise frequency did not affect their self-rated health; and (3) TikTok use boosted older adults' protein intake, contributing substantially to their self-rated health, accounting for 38.7% of the total effect. It is advisable to actively promote the popularity of short video apps such as TikTok among older adults, as they serve as an effective tool for disseminating health information and encouraging healthier lifestyles and behaviors.

Data, not documents: Moving beyond theories of information‐seeking behavior to advance data discovery

AbstractMany theories of human information behavior (HIB) assume that information objects are in text document format. This paper argues four important HIB theories are insufficient for describing users' search strategies for data because of assumptions about the attributes of objects that users seek. We first review and compare four HIB theories: Bates' berrypicking, Marchionni's electronic information search, Dervin's sense‐making, and Meho and Tibbo's social scientist information‐seeking. All four theories assume that information‐seekers search for text documents. Next, we compare these theories to search behavior by analyzing Google Analytics data from the Inter‐university Consortium for Political and Social Research (ICPSR). Users took direct, scenic, and orienting paths when searching for data. We also interviewed ICPSR users (n = 20), and they said they needed dataset documentation and contextual information to find data. However, Dervin's sense‐making alone cannot explain the information‐seeking behaviors that we observed. Instead, what mattered most were object attributes determined by the type of information that users sought (i.e., data, not documents). We conclude by suggesting an alternative frame for building user‐centered data discovery tools.

AI-integrated network for RNA complex structure and dynamic prediction.

RNA complexes are essential components in many cellular processes. The functions of these complexes are linked to their tertiary structures, which are shaped by detailed interface information, such as binding sites, interface contact, and dynamic conformational changes. Network-based approaches have been widely used to analyze RNA complex structures. With their roots in the graph theory, these methods have a long history of providing insight into the static and dynamic properties of RNA molecules. These approaches have been effective in identifying functional binding sites and analyzing the dynamic behavior of RNA complexes. Recently, the advent of artificial intelligence (AI) has brought transformative changes to the field. These technologies have been increasingly applied to studying RNA complex structures, providing new avenues for understanding the complex interactions within RNA complexes. By integrating AI with traditional network analysis methods, researchers can build more accurate models of RNA complex structures, predict their dynamic behaviors, and even design RNA-based inhibitors. In this review, we introduce the integration of network-based methodologies with AI techniques to enhance the understanding of RNA complex structures. We examine how these advanced computational tools can be used to model and analyze the detailed interface information and dynamic behaviors of RNA molecules. Additionally, we explore the potential future directions of how AI-integrated networks can aid in the modeling and analyzing RNA complex structures.

Providing Information or Support Based on Cancer Worry Can Decrease Psychological Distress Among Daughters of Women with Breast Cancer

Cancer Worry (CW) can shape the responses and behaviors of information or support-seeking of daughters of women with breast cancer. This study aims to explore the roles of Cancer Worry (CW) as a moderator and mediator in the relationship between information needs, support needs, and psychological distress. A cross-sectional and correlational design was used in conjunction with a convenience sampling strategy. Daughters of mothers with breast cancer were requested to complete the questionnaires Impact of Event Scale Chinese version (IES-C), Cancer Worry Scale for Genetic Counseling (CWS-GC), and Information and Support Needs Questionnaire (ISNQ). Hayes' PROCESS macro using SPSS for Windows were used to examine the mediator and moderator role of CW. A total of 194 daughters provided data. Cancer worry was significantly correlated with total IES (r = 0.352, P < .01), intrusion-IES (r = 0.353, P < .01), avoidance-IES (r = 0.313, P < .01), unmet support needs (r = 0.226, P < .01), and unmet information needs (r = 0.17, P < .05). Cancer worry mediated the relationship between unmet support needs and total IES (β = 0.089, 95% CI: 0.026, 0.171) and moderated the relationship between unmet information needs and total IES (β = -0.395, P = .018, 95% CI: -0.723, -0.066). The role of cancer worry should be paid attention to when clinicians deliver information and provide support as well as tailoring psychological intervention for ameliorating distress in daughters of women with breast cancer. Providing personalized information and support is essential to address the unmet needs of daughters of women with breast cancer. Healthcare professionals providing interventions to reduce distress and improve overall care should consider individual CW. This research looks at how worrying about cancer affects daughters of women who have breast cancer. It focuses on the degree of cancer worry changes the way they feel when they don't get the information and support. Researchers used surveys to gather data from these daughters, examining how their level of cancer worry influenced their needs for information and support and their psychological distress. They found that greater unmet support needs will intensify worry about cancer and then increase psychological stress. However, too much or too little worry about cancer will also heighten their psychological distress due to limited information. The findings suggest that healthcare providers, including nurses, should consider the level of worry about cancer when offering support and information to these individuals to help reduce their stress.

Representing the Needs of Rural Caregivers of People Living with Alzheimer’s Disease and Related Dementias through User Personas

Abstract Background and Objectives Rural caregivers of people living with Alzheimer’s disease and related dementias (ADRD) face unique caregiving challenges. Current interventions do not address many of the systemic barriers experienced by rural ADRD caregivers, including barriers related to geography, healthcare services access, and financial insecurity. The objective of this study was to gain a deeper understanding of rural ADRD caregivers’ needs, strengths, and strategies in obtaining caregiving support, and to represent these attributes in the form of personas that can be used to design interventions for rural ADRD caregivers. Research Design and Methods In this qualitative user-centered design study, we conducted semi-structured interviews with self-identified caregivers of people living with ADRD in rural areas. Interview data was copied to a virtual whiteboard, and affinity diagramming was used to confirm a priori attributes and yield inductive attributes relevant to rural ADRD caregivers. Attributes were assigned to personas, which were then validated through team-based discussion, consultation with a study advisory board, and review by rural caregivers and community partners. Results Analyses of N=19 interviews yielded seven inductive attributes relevant to rural ADRD caregivers of persons living with ADRD and five distinct personas: Capable Christine, Connected Connie, Isolated Irene, Learning Larry, and Discerning Dan. Personas differed on inductive attributes including financial security, subjective rurality, attitudes, connectedness, and information behavior, including preferences for traditional versus technology-based information seeking. Discussion and Implications The personas identified in the present study can be used as tools to represent and efficiently communicate the intersection and interaction of attributes relevant to designing interventions and technologies to meet the support needs of rural ADRD caregivers.

Risky Reproductive Health Behavior and Information Access on Adolescents: Qualitative and Quantitative Analysis

Adolescence is a vital period of development marked by confusion, a range of emotions, and an understanding of adult behavior, the environment, enthusiasm, and an inclination to explore, particularly with drugs, alcohol, and sex. This study outlines adolescents' knowledge, attitude, access to information and risky behaviors related to reproductive health. This study employed a concurrent triangulation design, using mixed methodologies. The chi-square test was used to examine this form of quantitative study. The focus groups and in-depth interviews with teenagers in several agencies, along with the accompanying teachers and parents, provided qualitative information for this study. Adolescents had greater access to knowledge about reproductive health issues, but the majority were unable to make effective use of this information. Numerous risky habits, including drug use, also set off unsafe sexual behaviors. In contrast to their parents or professors, teenagers increasingly feel more at the ease of sharing stories with their friends. It is intended that parents and educators will act in a peer-like manner by imitating teenagers’ social cues. Quantitative analysis revealed relationships among information access, attitude, knowledge, and reproductive behavior. Teenagers typically have higher knowledge of their reproductive health. However, the majority of them struggle to put this knowledge into practice, and as a result, many engage in risky sexual behavior out of curiosity.

Promoting health information and healthy behaviors: Results from a qualitative study

Abstract Background and aim Healthy living behaviors can prevent many chronic diseases. This study aimed to explore qualitative perceptions and behaviors about healthy lifestyles in a district’s residents. Methods This qualitative research was conducted through in-depth interviews with 24 participants aged 28 to 63 in Türkiye. Results Of the 24 participants, six were men. The themes were daily routines; health information-seeking behavior, beliefs, motivation for healthy living, dietary habits, daily movement, psychological relaxation, unhealthy behaviors, facilitators, and barriers. Individuals’ daily routines were shaped by caregiving duties or work. Health information was preferred from professionals, TV, family health history, and the Internet. Male participants lacked the need to seek health information. Also, some participants believed that diseases are unavoidable and incurable. People with growing children or a family member with a serious illness like cancer often report practicing healthy behaviors. Participants have different healthy eating patterns, including organic eating, home cooking, regular meals, more fruits and vegetables, increased water intake, avoiding late-night eating, and steering clear of packaged foods, salt, and sugar. Many participants walked regularly for physical and mental health; they also expressed avoiding negative people and engaging in hobbies and social activities to maintain psychological well-being. Smoking participants had attempted to quit smoking. Some participants said that adding salt to their food before tasting. Factors cited as hindering healthy behaviors included lack of time, financial constraints, and cultural reasons. Conclusions Despite awareness of healthy living, many participants struggle to implement it due to lack of motivation, busy work schedules, social and physical environments, and economic factors. Multisectoral collaboration to create environments that support healthy behaviors can improve public health.

New Urban Tourism: an On-Site Analysis of City Tourism’s New Trend in Selected Spots in the Destination of Munich, Germany

Abstract A shift in travel behavior is taking place within urban tourism. Experienced repeat visitors want to discover cities away from tourist centers and traditional attractions. They want to gain insights into everyday life in the city and explore it off the beaten track. This phenomenon is called New Urban Tourism (NUT). This paper aims to determine whether NUT is a noteworthy phenomenon in Munich. For this purpose, three research questions were formulated. A qualitative content analysis of travel blog entries about insider tips in Munich was conducted to answer the research questions. The goal was to identify the two insider tips that were most often mentioned. Here, face-to-face interviews with tourists and residents were conducted. The tourists were asked questions about their travel and information behavior to determine whether they could be classified as New Urban Tourists. The residents, in contrast, were asked to indicate whether they notice the presence of tourists and how this influences their perception of the neighborhood. NUT can be described as a notable phenomenon in the city of Munich. Recommendations for future research include examining the impact of NUT on Munich and identifying the specific aspects of urban ordinariness that New Urban Tourists deem worth experiencing.