Human Behavior Research Articles

Negative association between basal oxytocin and oxytocin changes after repetitive transcranial magnetic stimulation in patients with treatment-resistant depression

Repetitive transcranial magnetic stimulation (rTMS) is a neuromodulator effective for treating depressive symptoms in patients with treatment-resistant depression (TRD). One of the multiple mechanisms for its antidepressant effects proposed is related to the hypothalamus. Oxytocin is a neuropeptide synthesized in the hypothalamus that affects human behavior and psychology, including social and affiliative behaviors, stress regulation, and fear and emotion processing. There have been no reports on the relationship between rTMS and oxytocin for the treatment of TRD. Therefore, we aimed to investigate changes in salivary oxytocin concentrations in patients with TRD before and after 6 weeks of rTMS treatment. A total of 28 patients with TRD who received rTMS at Saga University Hospital between August 2013 and August 2020 were included. Although rTMS treatment significantly improved 24-item Hamilton Depression Rating Scale scores, rTMS treatment did not change mean salivary oxytocin after 6 weeks of treatment in patients with TRD. Multiple regression analysis revealed that the change in salivary oxytocin levels after rTMS treatment was negatively associated with basal oxytocin levels before rTMS treatment, suggesting that rTMS treatment tends to decrease oxytocin levels in patients with depression with high basal oxytocin levels while increasing them in those with low basal levels. These findings suggest that rTMS treatment improved depressive symptoms through mechanisms other than the modulatory effect on oxytocin levels in patients with TRD, while there is room for further studies to confirm these findings using a larger patient sample size and/or a sham rTMS procedure.

The role of human behaviour in activist content sharing on social media

PurposeSocial media (SM) platforms tempt individuals to communicate their perspectives in real-time, rousing engaging discussions on countless topics. People, besides using these platforms to put up their problems and solutions, also share activist content (AC). This study aims to understand why people participate in activist AC sharing on SM by investigating factors related to planned and unplanned human behaviour.Design/methodology/approachThe study adopted a quantitative approach and administered a close-ended structured questionnaire to gather data from 431 respondents who shared AC on Facebook. The data was analysed using hierarchical regression in SPSS.FindingsThe study found a significant influence of both planned (perceived social gains (PSGs) , altruism and perceived knowledge (PK)) and unplanned (extraversion and impulsiveness) human behaviour on activist content-sharing behaviour on SM. The moderating effect of enculturation and general public opinion (GPO) was also examined.Practical implicationsSharing AC on SM is not like sharing other forms of content such as holiday recommendations – the former can provoke consequences (sometimes undesirable) in some regions. Such content can easily leverage the firehose of deception, maximising the vulnerability of those involved. This work, by relating human behaviour to AC sharing on SM, offers significant insights to enable individuals to manage their shared content and waning probable consequences.Originality/valueThis work combined two opposite constructs of human behaviour: planned and unplanned to explain individual behaviour in a specific context of AC sharing on SM.

Unveiling Human Values: Analyzing Emotions behind Arguments.

Detecting the underlying human values within arguments is essential across various domains, ranging from social sciences to recent computational approaches. Identifying these values remains a significant challenge due to their vast numbers and implicit usage in discourse. This study explores the potential of emotion analysis as a key feature in improving the detection of human values and information extraction from this field. It aims to gain insights into human behavior by applying intensive analyses of different levels of human values. Additionally, we conduct experiments that integrate extracted emotion features to improve human value detection tasks. This approach holds the potential to provide fresh insights into the complex interactions between emotions and values within discussions, offering a deeper understanding of human behavior and decision making. Uncovering these emotions is crucial for comprehending the characteristics that underlie various values through data-driven analyses. Our experiment results show improvement in the performance of human value detection tasks in many categories.

Effect of payment for forest ecosystem services on forest conservation practices in Vietnam

Payment for forest ecosystem services (PFES) policy is a prevalent strategy designed to establish a marketplace where users compensate providers for forest ecosystem services. This research endeavours to scrutinise the impact of PFES on households’ perceptions of forest values and their behaviour towards forest conservation, in conjunction with their socio-economic circumstances and their communal involvement in forest management. By incorporating the social-ecological system framework and the theory of human behaviours in environmental conservation, this study employs a structural equations model to analyse the factors influencing individuals’ perceptions and behaviours towards forest conservation. The findings indicate that the payment of PFES significantly increases forest protection behaviour at the household level and has achieved partial success in activating community mechanisms to guide human behaviour towards forest conservation. Furthermore, it has effectively leveraged the role of state-led social organisations to alter local individuals’ perceptions and behaviours towards forest protection.

A speech enhancement model based on noise component decomposition: Inspired by human cognitive behavior

In multimedia intelligent systems, speech enhancement is commonly employed to improve the quality of speech signals, making them clearer and more natural. Current deep learning-based speech enhancement models typically treat noise as a unified entity and aim to separate it from the target speech. In this paper, inspired by the cognitive behavior of the human brain when observing noisy speech spectrograms, we decompose the spectral energy of noise into regular and random components. We propose an auxiliary-model-based speech enhancement framework that better suppresses noise components closely resembling speech features. Firstly, we introduce a voiceprint segmentation network (VSnet) that partitions noisy speech into voiceprint and non-voiceprint regions. Subsequently, we present a noise reconstruction network (NRnet) that utilizes noise information from non-voiceprint regions to reconstruct and suppress the regular noise components within the voiceprint region. Finally, we construct a combination of a model dedicated to suppressing random components (RANnet) and a speech enhancement model (SEnet), and train them synchronously. By sharing encoder parameters, SEnet is compelled to reduce the extraction of regular noise features from the original noisy speech, contributing to improving speech quality generated through the decoder. Experimental results on public Voickbank-DEMAND and DNS-challenge 2020 datasets demonstrate that our approach achieves state-of-the-art performance.

Holocene utopias and dystopias: Views of the Holocene in the Anthropocene and their impact on defining the Anthropocene

In delineating the Anthropocene, the Holocene is being redefined as the formative epoch of human development leading to the Anthropocene. This has led to a diversity of views of the Holocene and Holocene humanity in the Anthropocene, the extremes of which may be described as “Holocene utopianism” and “Holocene dystopianism.” The former views the Holocene as a solution to the predicament of the Anthropocene, as an idealized past of human activities and stable climate that must be aspired to. The latter perceives the Holocene and Holocene humanity as the root cause of the ills of the Anthropocene that must be avoided in the future. These views reflect a gross simplification of human activities and the environment of the Holocene. Human activity in the Holocene is characterized by diverse human behaviors that can be perceived as both destructive and sustaining to the earth’s ecological systems, and in many cases, emerged as a response to fluctuations in the Holocene climate. The Holocene does not provide an escape from the Anthropocene, as a solution or as a cautionary tale. Nonetheless, future human endeavors must necessarily draw from the diversity of human activities and systems of organization observed in the Holocene, but do so carefully.

Research on human behavior recognition algorithm based on HRNet and LSTM with model lightweight

This paper proposes a lightweight human action recognition algorithm for pedestrian behavior recognition. First, the skeleton feature information is input into the HRNet network model. In order to selectively enhance more details containing the target features and suppress irrelevant or weak features, an external attention mechanism is added to the HRN child model. Secondly, in order to extract the temporal characteristics of the target feature vector and ensure the continuity of actions in human behavior recognition, a dual-stream network based on HRNet and Long Short-Term Memory (LSTM) is constructed; finally, due to the huge model, it cannot be well transplanted to embedded. Therefore, this paper uses depthwise separable convolution to lightweight the network model. The experimental results show that in terms of human behavior recognition, the method in this paper has better recognition accuracy than Two-stream, Multi-streamCNN, Cov3DJ, ConvNets, JTM, ASM-3, RF+SW, hd-CNN and TPSMMs.

Principal’s Leadership Style of SDN 3 Ujung Tanjung Banyuasin III Sub-District, Banyuasin Regency

The purpose of this study is to describe the leadership style of the Principal of SDN 3 Ujung Tanjung, Banyuasin III District, Banyuasin Regency, from 2015 until now. The research method that researchers use is a qualitative descriptive research method with case study research procedures. Case study research is a form of qualitative research that examines human behavior or objects at a certain time to reveal their behavior or actions. The behavior, actions, and events he did were obtained from the opinions of others based on his behavior and understanding, and he had collaborated with the perpetrator on an object. The results of this study show that during the period 2015–now the principal’s leadership style applied by the principal of SDN 3 Ujung Tanjung, Banyuasin III District, Banyuasin Regency is a democratic leadership style.

Prolonged HPA axis dysregulation in postpartum depression associated with adverse early life experiences: A cross-species translational study.

Childhood and adolescent stress increase the risk of postpartum depression (PPD), often providing an increased probability of treatment refractoriness. Nevertheless, the mechanisms linking childhood/adolescent stress to PPD remain unclear. Our study investigated the longitudinal effects of adolescent stress on the hypothalamic-pituitary-adrenal (HPA) axis and postpartum behaviors in mice and humans. Adolescent social isolation prolonged glucocorticoid elevation, leading to long-lasting postpartum behavioral changes in female mice. These changes were unresponsive to current PPD treatments but improved with post-delivery glucocorticoid receptor antagonist treatment. Childhood/adolescent stress significantly impacted HPA axis dysregulation and PPD in human females. Repurposing glucocorticoid receptor antagonists for some cases of treatment-resistant PPD may be considered.

Never-Ending Learning for Explainable Brain Computing.

Exploring the nature of human intelligence and behavior is a longstanding pursuit in cognitive neuroscience, driven by the accumulation of knowledge, information, and data across various studies. However, achieving a unified and transparent interpretation of findings presents formidable challenges. In response, an explainable brain computing framework is proposed that employs the never-ending learning paradigm, integrating evidence combination and fusion computing within a Knowledge-Information-Data (KID) architecture. The framework supports continuous brain cognition investigation, utilizing joint knowledge-driven forward inference and data-driven reverse inference, bolstered by the pre-trained language modeling techniques and the human-in-the-loop mechanisms. In particular, it incorporates internal evidence learning through multi-task functional neuroimaging analyses and external evidence learning via topic modeling of published neuroimaging studies, all of which involve human interactions at different stages. Based on two case studies, the intricate uncertainty surrounding brain localization in human reasoning is revealed. The present study also highlights the potential of systematization to advance explainable brain computing, offering a finer-grained understanding of brain activity patterns related to human intelligence.

The Intention of Young Muslim Generation to Use the Islamic E-Wallet Services in Indonesia

Research Originality: Technological developments have changed human behavior in economic activities, including payment methods that use e-wallets. On the other hand, consumers also need an e-wallet that complies with Sharia principles. The COVID-19 pandemic forced consumers to use digital payment methods. However, the number of studies related to the continued usage of Islamic e-wallets in Indonesia remains limited.Research Objectives: Hence, our study examines the factors influencing a person's intention to use an Islamic e-wallet.Research Method: The theoretical framework used in this study is the Technology Acceptance Model. The analysis technique employed is multiple regression analysis using 371 respondents.Result: Empirical results indicate that the factors influencing a person's intention to use an Islamic e-wallet are usability, ease of use, trustworthiness, and religiosity. However, the risk variable does not significantly affect a person's intention to use an Islamic e-wallet. Implication: These results imply that companies must improve the features and services of Islamic e-wallet applications.JEL Classification: D10, G29How to Cite:Risza, H. (2024). The Intention of Young Muslim Generation Using the Islamic E-wallet Services in Indonesia. Etikonomi, 23(1), 219 – 232. https://doi.org/10.15408/etk.v23i1.37452.

Towards a definition of ‘empathic understanding’ in industrial design practice

Empathy is often not well defined, particularly in design. While the practice of designers developing a deep understanding of the people who use their products is recommended, the details of how to do this are limited. This problem of vagueness about empathy in design makes it difficult for product designers to take suitable actions to produce best results for the users. Through a strategic examination of a body of literature, across seven databases relevant to design, the systematic literature review adds to a discussion on empathy within the designing process. Study limitations included the complex nature of empathy itself, and multiple uses of the terms design and product. Findings indicate a contradiction of internal and external factors affecting empathy in design, and are considerably more complex than just an ‘accepted’ part of the design process. Shifting towards user-centred design in industrial design means that a considerably more nuanced understanding of empathy is needed, for implementation in design practice. By better understanding the concept of empathy as a duality, all stakeholders can manage expectations around empathy ‘behaviour’, and empathy as part of the design process. Empathy needs to be recognised as a complex phenomenological relationship between process (external) and person (internal) within industrial design. Practical, theoretical and societal implications of this concept are discussed.Transdisciplinary contribution: Empathy in product design practice represents several fields, related to human behaviour and interactions. This review’s contribution is to confirm areas for further research and the importance of developing theory to address the complexity of design practice.

Personality Traits and the Growth of Emotional Intelligence. A Systematic Evaluation

Emotional intelligence (EI) and personality traits are inherent factors that shape individuals' perception, cognitive processing, and behavioral responses to emotional stimuli. This study examines the complex interplay between personality traits and emotional intelligence (EI), investigating how certain personality traits can impact the formation and expression of EI. By employing a blend of empirical investigation and theoretical examination, we evaluate the correlation between fundamental aspects of an individual's personality, namely openness, conscientiousness, extraversion, agreeableness, and neuroticism, and their emotional intelligence (EI) capacities, including self-awareness, self-regulation, motivation, empathy, and social skills. This study utilized fourteen articles acquired through a systematic search using the keywords "emotional intelligence and personality" in the Scopus and PubMed databases. An individual's personality plays a significant role in shaping their emotional intelligence, which in turn has a profound impact on multiple domains of human endeavor. Initial findings indicate that specific personality traits may facilitate developing emotional intelligence (EI), whereas others may pose obstacles that necessitate focused interventions. Acknowledging the interaction between personality and emotional intelligence (EI) presents novel opportunities for comprehensive personal growth, emphasizing the significance of customized approaches encompassing both aspects. This study emphasizes the need for a comprehensive comprehension of human behavior, advocating for approaches that accommodate the distinct interplay between an individual's personality and emotional intelligence. These strategies aim to enhance personal and interpersonal outcomes to their fullest potential.

Addressing Plastic Concern: Behavioral Insights into Recycled Plastic Products and Packaging in a Circular Economy

AbstractThe excessive production and use of new plastic materials pose a critical environmental challenge, and reducing its consumption has emerged as a major global hurdle. Understanding human behavior is thus essential for creating a circular economy for plastics. The study aims to gain insights into consumers' buying habits concerning recycled plastic, which has received relatively little attention in prior research on the subject of environmentally friendly consumer behavior. This study draws on the Theory of Planned Behavior to analyze the factors influencing consumer behavior regarding products and packaging made from recycled plastic. To this end, we employed a questionnaire, which was administered to 511 consumers in Italy. Results support that concerns about plastics and perceived efficacy exert a direct influence on attitudes. Additionally, our findings demonstrate that social norms, attitudes, and perceived behavioral control significantly shape purchasing behaviors concerning recycled plastic. The research contributes to extending the Theory of Planned Behavior model in predicting environmental-friendly behavior by adding new empirical evidence and provides valuable suggestions for companies to develop effective communication strategies and policies to redirect plastic consumption behavior towards less-impacting use of plastic.

A Comprehensive Review of Behavior Change Techniques in Wearables and IoT: Implications for Health and Well-Being.

This research paper delves into the effectiveness and impact of behavior change techniques fostered by information technologies, particularly wearables and Internet of Things (IoT) devices, within the realms of engineering and computer science. By conducting a comprehensive review of the relevant literature sourced from the Scopus database, this study aims to elucidate the mechanisms and strategies employed by these technologies to facilitate behavior change and their potential benefits to individuals and society. Through statistical measurements and related works, our work explores the trends over a span of two decades, from 2000 to 2023, to understand the evolving landscape of behavior change techniques in wearable and IoT technologies. A specific focus is placed on a case study examining the application of behavior change techniques (BCTs) for monitoring vital signs using wearables, underscoring the relevance and urgency of further investigation in this critical intersection of technology and human behavior. The findings shed light on the promising role of wearables and IoT devices for promoting positive behavior modifications and improving individuals' overall well-being and highlighting the need for continued research and development in this area to harness the full potential of technology for societal benefit.

How music-induced emotions affect sexual attraction: evolutionary implications.

More than a century ago, Darwin proposed a putative role for music in sexual attraction (i.e., sex appeal), a hypothesis that has recently gained traction in the field of music psychology. In his writings, Darwin particularly emphasized the charming aspects of music. Across a broad range of cultures, music has a profound impact on humans' feelings, thoughts and behavior. Human mate choice is determined by the interplay of several factors. A number of studies have shown that music and musicality (i.e., the ability to produce and enjoy music) exert a positive influence on the evaluation of potential sexual partners. Here, we critically review the latest empirical literature on how and why music and musicality affect sexual attraction by considering the role of music-induced emotion and arousal in listeners as well as other socio-biological mechanisms. Following a short overview of current theories about the origins of musicality, we present studies that examine the impact of music and musicality on sexual attraction in different social settings. We differentiate between emotion-based influences related to the subjective experience of music as sound and effects associated with perceived musical ability or creativity in a potential partner. By integrating studies using various behavioral methods, we link current research strands that investigate how music influences sexual attraction and suggest promising avenues for future research.

The Hyperreality of Virtual Influencer Lentari Pagi on Instagram

Rapid developments in the 4.0 era of industry have created technology with capabilities similar to humans, namely artificial intelligence. One example is virtual influencers, which result from progress made by real human influencers supported by technological development. The presence of virtual influencers has become an interesting phenomenon in the contemporary social media ecosystem. Lentari Pagi is a digital representation designed to imitate human behavior and interact with its followers through visual and narrative content shared online. This research aims to understand hyperreality in the appearance and interactions of virtual influencer Lentari Pagi on Instagram and analyze the impact of artificial intelligence technology on the perception and participation of social media users. The qualitative research method was used, with interviews and observation as data collection techniques. The results of this research show that Lentari Pagi succeeded in creating an emotional connection with its followers, conveying promotional messages, and forming a unique self-image in the minds of its audience. In conclusion, this hyperreality phenomenon reflects the complex dynamics between technology, culture, and identity in the current digital era.

The Role of Nyakyusa Proverbs in Behavioural Development

This article examines the role of sayings in developing human behaviour in the Nyakyusa community in Tanzania. The primary data for this article were obtained by interview method in Luteba (Ipuguso), Kandete (Ipelo) and Mpombo (Lulasi) wards in Rungwe district, Mbeya region. Those areas met the data requirements presented in this article. The Sociological Theory was used in the analysis and discussion of data by looking at literature as a special unit that reflects both the science and culture of the society. Selected community sayings were examined as a special link to social relations. This article has revealed that the sayings of the selected community are a special link of social relations considering its history, philosophy, culture and economy. The sayings serve as a specific reference library for social issues, and a strong indigenous link that builds a system to train, strengthen and keep the community together in the foundations of culture and the whole philosophy of life from tradition until now. This article concludes that sayings are used as a special warehouse for reference to social issues that keep the community together in the foundations of culture and the whole philosophy of life from ancient times until now.

Парадоксы доброты в контексте просоциального поведения: анализ современных концепций

<p style="text-align: justify;"><strong>Objective. </strong>Analysis of the modern concepts of kindness as a moral and ethical construct and a predictor of prosocial human behavior, to identify paradoxes of kindness, indicating the multidimensionality and multidirectionality of the content of kindness, the ambivalence of the consequences of manifestation and the ambiguity of interpretation by the subjects of interaction. <br><strong>Background. </strong>In the modern information technology world, the problem of preserving the human in man and his moral cultural code is clearly identified, which is clearly intensifying in an era of uncertainty, instability and global risks. Kindness as a virtue and value, a personal quality and one of the predictors of prosocial behavior, having an interdisciplinary status, is studied in sufficient detail by various researchers, but not all of their results are presented in the domestic literature, and therefore their consolidation and clarification of the “kindness” construct in within the framework of social psychology. <br><strong>Conclusions. </strong>Main conclusions. The concept of “kindness” is clarified as an ethical construct of the individual and a predictor of prosocial behavior, as well as a social norm that regulates interpersonal interactions, strengthens trust and ensures social connections. “Paradoxes” of kindness have been identified, containing multidirectional psychological orientations – care for the Other and care for oneself, ambivalent consequences of showing kindness and its ambiguous interpretation by the subjects of interaction. The prospects for empirical research aimed at studying subjective ideas about kindness, diagnosing its modes, and identifying socio-psychological mediators and moderators are identified.</p>

Ten Years of Gamification-Based Learning: A Bibliometric Analysis and Systematic Review

Gamification-based learning is a recent trend that has received increasing attention in the last few years due to digital development. Gamification has emerged as a vital aspect of the educational setting, with gamified elements playing a crucial role in e-learning environments. The current study is motivated by the need to address a gap in the existing research on the utilization of gamification in education. This gap exists due to a lack of studies that monitor the developments and effects of gamification in the educational environment. It is important to conduct such studies to provide guidance for future research in the field of gamification. A bibliometric analysis and systematic literature review were conducted to understand and describe gamification and its potential for learning. The results of the bibliometric analysis revealed that the most frequently used keywords in the studies were gamification, game-based learning (GBL), motivation, and engagement. The majority of research published in this field was conducted in the United States, followed by Spain and Britain. The Journal of Computers in Human Behavior and the Journal of Computers and Education were the two journals that focused primarily on the field of GBL. The most famous authors in this field are Hamari, Juho, Patel, Mitesh S., Landers, and Richard N. The field is experiencing significant growth, with the number of studies increasing from 7 in 2012 to 917 in 2021. The systematic review has found that undergraduates are the most frequent participants in gambling activities. The game elements that are most utilized are points, leaderboards, and badges, while the learning outcomes most addressed are achievement, engagement, and motivation. The primary objective of this paper is to provide a comprehensive guide to scholars and research institutes, outlining the key areas of emphasis related to the subject of gamification. The systematic research also identified the key components of gamification that instructors and e-learning designers may rely on most frequently.