Understanding Of Intentions Research Articles

Archetypes and change in wildfire risk perceptions, behaviours and intentions among adults in Tasmania, Australia

Background Anthropogenic climate change globally increases wildfire risk. Understanding how wildfire threats impact community-wide risk perceptions and response options will critically inform resilience education strategies. Aim To gain an increased understanding of wildfire risk perceptions and self-evacuation intentions among residents in the wildfire-prone state of Tasmania, Australia. Methods We co-designed survey questions with stakeholders from emergency management, health and community recovery, using a computer-aided telephone interview to survey residents over 18 years of age. Numerical classification analysis, linear regression and descriptive statistics were used to analyse survey data. Results We identified four archetypes – the ‘immediate leaver’, ‘prepared stayer’, ‘unprepared leaver’ and ‘informed leaver’, each with distinct sociodemographic characteristics. Key variables were gender, age, location and income, with women most likely to leave and lower-income householders from rural areas most likely to stay. Previous wildfire experience and owning a home were significantly associated with increased preparedness actions. Compared to 2016, we found a significant increase in the proportion of residents intending to leave their property, with rural men least likely and urban women most likely to leave. Implications Recent education campaigns have likely driven increases in wildfire threat-related self-evacuation, yet the existence of distinct archetypes argues for more tailored messaging and education programs.

Expert and Novice Teachers’ Cognitive Neural Differences in Understanding Students’ Classroom Action Intentions

Objectives: Teachers’ intention understanding ability reflects their professional insight, which is the basis for effective classroom teaching activities. However, the cognitive process and brain mechanism of how teachers understand students’ action intention in class are still unclear. Methods: This study used event-related potential (ERP) technology to explore the cognitive neural differences in intention understanding ability among teachers with different levels of knowledge and experience. The experiment used the comic strips paradigm to examine the ability of expert and novice teachers to understand students’ normative and non-normative classroom actions under different text prompts (“how” and “why”). Results: The results revealed that in the late time window, expert teachers induced larger P300 and LPC amplitudes when they understood students’ classroom action intentions, while the N250 amplitudes induced by novice teachers in the early time window were significantly larger. In addition, for both types of teachers, when understanding the intentions behind students’ normative actions, the N250 amplitude was the most significant, while the P300 and LPC amplitudes were more significant for non-normative actions. Conclusions: This study found that teachers at varying professional development stages had different time processing processes in intention understanding ability, which supported teachers’ brain electrophysiological activities related to social ability.

Entrepreneurial Intention in Romanian Engineering Students: Expanding the Theory of Planned Behavior

This study analyzes the entrepreneurial intention of Romanian engineering students. We had a sample of 700 students (mean age = 23.14; SD = 2.92; 378 males and 322 females) who belonged to three technical universities and completed an online survey between October and December 2023. This research extends the theory of planned behavior (TPB) to explore the factors influencing students’ entrepreneurial intentions. In addition to base TPB components, such as attitude, normative and perceived behavioral control factors, we considered curiosity and well-being. Three structural equation models were used, one after the other, through the method of partial least squares (PLS-EM). The results show that attitude, perceived control behavior and curiosity have a positive impact on entrepreneurial intention, whereas subjectivenorms, surprisingly, have a negative impact on it. Psychological well-being expressed through autonomy is not associated with entrepreneurial intention in our sample of students. This article contributes to a better understanding of entrepreneurial intention in engineering students.

How Does Understanding of Social Situations and Other's Intention Contribute to Idiom and Irony Comprehension in Autism Spectrum Disorder?

Background/Objectives: Figurative language is a central tool for enriching spoken and written languages, and it is important for building social relationships. Difficulties in figurative language understanding may impair social adjustment. Some studies have found more gaps in the understanding of irony and idioms among children with autism spectrum disorder (ASD) compared to those of their peers with typical development (TD). To date, no studies have examined the relationship between the ability to understand social situations (as a separate ability) and the ability to understand irony and idioms. The present study examined the roles of theory of mind (ToM) and social situation understanding in the comprehension of idioms and ironic criticism. Methods: The current study included 58 participants aged 8-11, including 28 children with high-functioning ASD and 30 children with TD matched by age, gender, and nonverbal intelligence. All the participants completed a ToM questionnaire that assesses their understanding of others' intentions, as well as a questionnaire pertaining to their comprehension of social situations, ironic criticism, and idioms. Results: TD children outperformed the autistic children in idiom and irony understanding, as well as in ToM and social situation understanding. Understanding social situations and ToM contributed to idiom and irony understanding, with ToM ability uniquely contributing to irony (but not to idiom) understanding. Path analysis revealed that social cognitive abilities mediated the link between group affiliation and vocabulary, affecting figurative language comprehension. Conclusions: The present study demonstrates that social cognition skills influence the ability to understand ironic criticism and idioms, mediating the association between vocabulary and figurative language comprehension.

Variable Admittance Control of High Compatibility Exoskeleton Based on Human–Robotic Interaction Force

The wearable exoskeleton system is a typical strongly coupled human–robotic system. Human–robotic is the environment for each other. The two support each other and compete with each other. Achieving high human–robotic compatibility is the most critical technology for wearable systems. Full structural compatibility can improve the intrinsic safety of the exoskeleton, and precise intention understanding and motion control can improve the comfort of the exoskeleton. This paper first designs a physiologically functional bionic lower limb exoskeleton based on the study of bone and joint functional anatomy and analyzes the drive mapping model of the dual closed-loop four-link knee joint. Secondly, an exoskeleton dual closed-loop controller composed of a position inner loop and a force outer loop is designed. The inner loop of the controller adopts the PID control algorithm, and the outer loop adopts the adaptive admittance control algorithm based on human–robot interaction force (HRI). The controller can adaptively adjust the admittance parameters according to the HRI to respond to dynamic changes in the mechanical and physical parameters of the human–robot system, thereby improving control compliance and the wearing comfort of the exoskeleton system. Finally, we built a joint simulation experiment platform based on SolidWorks/Simulink to conduct virtual prototype simulation experiments and recruited volunteers to wear rehabilitation exoskeletons to conduct related control experiments. Experimental results show that the designed physiologically functional bionic exoskeleton and adaptive admittance controller can significantly improve the accuracy of human–robotic joint motion tracking, effectively reducing human–machine interaction forces and improving the comfort and safety of the wearer. This paper proposes a dual-closed loop four-link knee joint exoskeleton and a variable admittance control method based on HRI, which provides a new method for the design and control of exoskeletons with high compatibility.

Using hope theory to understand changes from professional learning in inclusive education

AbstractProfessional learning for quality teaching is a lifelong enterprise. Nevertheless, it entails a considerable cost with varying outcomes. Drawing on Snyder's hope theory and Pantic's teacher agency, this paper aims to present a model aimed at deepening our understanding of teachers' intentions and competencies in inclusive education. The model formulates a professional learning cycle tailored to address their unique needs. This study draws on data from a larger qualitative dominant mixed‐methods study exploring 18 teachers' professional learning experience with the inclusionEd online platform. The process involved a pre‐training online survey and interviews and employed multiple strategies for data analysis. Descriptive statistics were used for pre‐training survey data to assess teacher‐participants' attitudes towards inclusion and efficacy levels in this area. Subsequently, using Snyder's hope theory and Pantic's teacher agency, we deductively analysed interview data. The quantitative results showed that teacher‐participants had positive beliefs about inclusive education with high efficacy. However, qualitative data analysis uncovered a misalignment between their stated beliefs and enacted beliefs, revealing diverse pathways to both success and challenges in their implementation of inclusive practices. The qualitative analysis, combined with the preliminary survey findings, unveiled the fluidity of hope and identified the influences on shifting hope and maintaining a positive stance. We offer an illustration of teacher professional learning pathways. Understanding how these pathways might be used to increase the value and outcomes of professional learning programmes is discussed. This study concludes with a discussion of theoretical and practical implications and directions for future research.

Residents' Cognition, Attitudes, and Intentions to Participate in Long-Term Care Insurance: Moderating Effect of Policy Support.

This study took a comprehensive approach to considering residents' demands and investigated the intentions of residents in Hebei Province to participate in LTCI, exploring the potential for individual participation. By integrating the unique Chinese context and existing literature, this study established a theoretical framework for research hypotheses concerning the influencing factors of residents' participation intentions. Leveraging a sample of 516 survey responses, we employed structural equation modeling (SEM) and hierarchical regression analysis (HRA) for validation. The research revealed that the heterogeneity of resident attributes has a significant influence on their participation intentions, and a gap exists between residents' attitudes and intentions, leading to a scenario where attitudes are high but intentions are low. Moreover, perceived usefulness, risk perception, and perceived trust were found to directly affect residents' intentions and could indirectly affect intentions through the mediating effect of attitudes. Additionally, the moderating role of policy support is instrumental in facilitating the translation of attitudes into actual intentions, bridging the gap between attitudes and participation intentions. These findings will assist researchers in gaining a deeper understanding of Chinese residents' participation intentions and their underlying influencing factors, ultimately providing a solid foundation for government policy formulation and insurance companies' strategic adjustments.

Patient Experiences of using Wearable Health Monitors during Cancer Treatment: A Qualitative Study

IntroductionWearable health monitors (WHM) offer minimally invasive, ambulatory monitoring of physiological parameters and activity. WHMs are being used increasingly in healthcare but adoption for patients undergoing cancer treatment is limited in part due to a lack of understanding of patient intention as they receive treatment. The aim of this study explores the patient experience of using WHMs during their cancer pathway, including barriers and enablers of WHM use. MethodsA phenomenological qualitative approach was used with single semi-structured interviews conducted in the form of focus groups with individuals enrolled in the EMBRaCE-GM study, where WHMs were worn for up to six months prior to, during and after treatment of either colorectal, lung, or head & neck cancer, or leukaemia/lymphoma. ResultsWe identified three major themes: perceived patient benefits, barriers to the adoption of WHMs and the importance of treatment partnerships between patients and healthcare professionals. WHMs promoted positive behaviour change, prioritisation of own health and represented a form of “digital advocacy”. Potential barriers were aesthetic, experiential and technological. WHM introduction was time-sensitive, with patients finding their use acceptable at differing stages in their cancer pathway. Patients desired reciprocal interaction with WHMs and were less concerned with data accuracy. DiscussionThis study identifies factors influencing patient decisions to use WHMs as part of cancer treatment. Novel findings include the optimal time to start wearing WHMs and the validity of measurements perceived as less of a concern for patients (in contrast to clinicians) who use wearable data with their own experiences as part of a sense making exercise. Future work should focus on balancing patient and clinician expectations to provide guidance on the feasibility of WHM in routine clinical practice.

Sensorless Human–Robot Interaction: Real‐Time Estimation of Co‐Grasped Object Mass and Human Wrench for Compliant Interaction

Human–robot physical interaction in shared object manipulation can fully leverage the strengths of both humans and collaborative robots, achieving better interaction outcomes. However, in typical physical interactions, the inertia parameters of the object are either assumed to be known or ignored, simplifying the interaction to be directly between the human and the collaborative robot. This simplification can lead to inaccuracies in the robot's understanding of human intent due to deviations in object dynamics. This article presents a method that eliminates the need for a force sensor on the human side during human–robot collaboration. Using an extended Kalman filter, the method estimates object parameters online and applies a disturbance observer to determine human force. This approach reduces human effort and improves tracking performance compared to traditional methods. It also avoids the hassle of installing and removing sensors in complex scenarios. By estimating object mass and human force in real time, the robot can adjust its behavior to ensure safer and smoother interactions. Furthermore, the system can handle various objects without requiring specific programming for each case.

BIM IMPLEMENTATION FOR HERITAGE RENOVATION THROUGHOUT PROJECT LIFECYCLE: CURRENT USE, BENEFITS, AND BARRIERS

Introduction: Building Information Modeling (BIM) has garnered significant attention due to advancements in sophisticated technologies and methods. However, a comprehensive review of the existing literature indicates a lack of research exploring the application of BIM in managing the entire intervention design and renovation processes from a broader system perspective. The purpose of the study was to fill this gap by identifying and evaluating the current utilization, benefits, and barriers associated with implementing BIM in the lifecycle of renovation projects. The study methodology is based on conducting 31 structured interviews with experienced professionals who have employed BIM in their project deliveries. The results reveal that the primary benefits of BIM adoption, in descending order of importance, pertain to improved collective understanding of design intent, lower risk and better predictability of outcomes, better-designed and performing buildings, more accurate project documentation, and increased accuracy of the cost estimate. However, there are several prominent barriers: project budget, complexity of modeling historic structures, cost to hire BIM professionals, and the lack of BIM knowledge. The findings will advance BIM adoption for heritage renovation and enable project stakeholders to focus on realizing the benefits and potential uses of lifecycle BIM, while also addressing the critical challenges discussed in this study.

Second language writing anxiety and ChatGPT adoption as an automated writing evaluation tool

PurposeThis study examines the relationship between the writing anxiety experienced by English second language learners and their intention to employ ChatGPT for their academic writing as an automated writing evaluation tool. This research integrates writing anxiety as an additional variable to understand how much writing anxiety affects the perceived usefulness of ChatGPT as an automated writing evaluation tool, perceived ease of use of ChatGPT, and attitude towards using ChatGPT as an automated writing evaluation tool for their academic writing with the technology acceptance model (TAM) as a theoretical framework.Design/methodology/approachThis is a cross-sectional study, with SEM PLS to analysis data collected from 639 undergraduate students.FindingsThis study found that writing anxiety significantly affects perceived ease of use of ChatGPT as an automated writing evaluation tool, and attitude towards using ChatGPT. Altogether they both influence students’ intention to use the ChatGPT as an automated writing evaluation tool.Originality/valueThis study contributes to the understanding of students intention to use ChatGPT as an automated writing evaluation tool when they suffer from writing anxiety.

Human–robot collaborative handling of curtain walls using dynamic motion primitives and real-time human intention recognition

Human–robot collaboration fully leverages the strengths of both humans and robots, which is crucial for handling large, heavy objects at construction sites. To address the challenges of human–machine cooperation in handling large-scale, heavy objects — specifically building curtain walls — a human–robot collaboration system was designed based on the concept of “human–centered with machine support”. This system allows the handling of curtain walls according to different human intentions. First, a robot trajectory learning and generalization model based on dynamic motion primitives was developed. The operator’s motion intent was then characterized by their speed, force, and torque, with the force impulse introduced to define the operator’s intentions for acceleration and deceleration. Finally, a collaborative experiment was conducted on an experimental platform to validate the robot’s understanding of human handling intentions and to verify its ability to handle curtain wall. Collaboration between humans and robots ensured a smooth and labor-saving handling process.

Factors influencing farmers' intention to participate in the voluntary carbon market: An extended theory of planned behavior

Carbon sequestration in agricultural soils is essential for sustainable agriculture, contributing to the achievement of the Sustainable Development Goals and combating climate change. The Voluntary Carbon Market (VCM), designed to encourage farmers to implement sequestration practices, is a recent innovation in Europe, in contrast to the well-established American system. Consequently, there is limited understanding of farmers' intentions to participate. The study analyzes farmers' willingness to participate in VCM and the influencing factors through the Extended Theory of Planned Behavior (ETPB). For this purpose, data were collected from 241 Italian farmers located in the Sicily region and the partial least squares structural equation model (PLS-SEM) was applied. The results show that Attitude, Perceived Behavioral Control and Knowledge of VCM have a statistically significant influence on farmers' intention to participate in VCM. In contrast, Subjective Norms and Perceived Environmental Risk do not have a statistically significant influence. Our findings suggest that farmers' intention is strongly influenced by confidence in their capabilities and knowledge of the topic. This should guide policymakers and practitioners to offer extension services and technical assistance, helping farmers understand the potential of the VCM. Indeed, limited knowledge is a major barrier to participation in this initiative.

Understanding hepatitis E vaccination intention among women of childbearing-age: A theory-based cross-sectional study

ObjectivesThe purpose of this study was to investigate the HEV vaccination intention, its determinants, and overall influence mechanisms among childbearing-age women. MethodThe current study was cross-sectional and conducted online from June 25, 2023 to September 25, 2023 in Nanjing, China. Logistic regression models were constructed to identify the intention-associated background factors. Technology Acceptance Model (TAM) and Theory of Planned Behavior (TPB) were integrated and expanded as TAM-TPB model to further investigate the determinants and overall influence mechanism of HEV vaccination intention among this population using structural equation modeling. ResultsA total of 423 eligible participants were included in this study. High general HEV knowledge was independently associated with an increased intention to get HEV vaccination (OR = 1.97, 95 % CI: 1.11–3.58, P = 0.023). All the hypotheses proposed in the theoretical TAM-TPB model were supported, with perceived ease of use, perceived usefulness, attitude, subjective norm, and perceived behavioral control positively affecting the intention of HEV vaccination (all P values <0.05), while perceived risk (P = 0.003) exhibited an inverse association with HEV vaccination intention. The model achieved an acceptable fit, and the total explained variance of HEV vaccination intention was as high as 86.20 %. Moreover, no significant common method bias was observed. ConclusionThis is the first theory-based study that explored the HEV vaccination intention, its determinants, and overall influence mechanism among childbearing-age women. The results of the current study are of great importance for improving the understanding of the HEV vaccination intention among females of childbearing age.

Investigating the determinants of turnover intention among the big 4 public accounting firms in Indonesia

This study examines the factors influencing turnover intention among staff auditors in the Big 4 public accounting firms in Indonesia specifically focusing on pay satisfaction, work overload, work stress, external work opportunities, work satisfaction and organizational commitment. Data from 144 participants employed by Big 4, namely PricewaterhouseCoopers (PwC), Ernst &amp; Young (EY), Deloitte and Klynveld Peat Marwick Goerdeler (KPMG) was collected through a Google Form questionnaire and analyzed using SMART Partial Least Square (PLS) 4.0. The outcomes show that work overload positively affects work satisfaction while pay satisfaction significantly contributes to turnover intention. The study also tested for mediation effects and found no significant mediating effect of work satisfaction and organizational commitment on the relationship between pay satisfaction, work overload, work stress and turnover intention. These findings enhance our understanding of turnover intention among auditors in Indonesia and suggest avenues for future research. However, the study's limitations such as its exclusive focus on turnover intention in the Big 4 public accounting firms in Indonesia should be acknowledged. Future research could broaden the scope to include additional factors influencing turnover intention or other samplings such as family businesses or the private sectors.

Enhancing conversational ai with the Rasa framework: intent understanding and NLU pipeline optimization

Implementing the Rasa NLU pipeline allowed intent detection and entity recognition, particularly in complex scenarios with multi-intent queries. Communication within the Rasa NLU pipeline was effectively managed, ensuring seamless data flow between components, which preserved context and enhanced interpretability. The voice assistant developed with STT and TTS capabilities demonstrated robust real-time natural language processing, handling spoken queries efficiently. This confirmed the practical viability of using the Rasa framework for scalable and customizable conversational AI applications. Discussing: The findings underscore the robustness of the Rasa NLU pipeline in handling diverse conversational demands and the flexibility of its components to adapt to different linguistic contexts. The research discusses the potential of integrating sophisticated NLU techniques to create more intuitive and responsive conversational agents, highlighting the critical role of context-aware processing in improving user interaction with AI systems.

Multimodal Massage Localization Algorithm for Human Acupoints

As the aging population issue worsens, people are experiencing increasing life pressures, and the elderly are unable to receive sufficient care, intensifying the demand for home-based intelligent massage healthcare robots. Addressing the challenges faced by users in expressing preferences for specific areas like the back through gestures or voice during the use of massage robots, and the issue of elderly individuals expressing imprecisely, which hinders effective communication of the desired massage target location to the robot, this paper proposes a new human-machine interaction mode for massage robots. The main innovations include: achieving precise control of the massage area through the representation of a virtual human body on the screen; proposing a virtual-to-real mapping algorithm based on human acupoints to address the consistency issue in human virtual-to-real mapping; introducing a multimodal intent understanding algorithm based on dynamic information entropy to address the current limitations of a single interaction mode and low intent comprehension rates in massage robot interactions. Experimental results demonstrate that the proposed multimodal massage localization algorithm achieves good massage intent recognition effects. By combining natural human-machine interaction with intent understanding, it not only accurately captures user massage intentions and assists in completing massage tasks but also reduces user psychological and cognitive loads, leading to more desirable interaction outcomes.

Exploring Entrepreneurial Intentions among Vocational High School Graduates: The Impact of Entrepreneurial Knowledge and Attitude

This research addresses the significant issue of unemployment among vocational school graduates in Indonesia and the low level of entrepreneurship among them. While previous studies have predominantly focused on the entrepreneurial intentions of high school and university student samples, there isthere needs to be more understanding of the entrepreneurial intentions of vocational school graduates. Bridging the gap, this study explores the determinants of entrepreneurial intentions among vocational school graduates, particularly examining the roles of entrepreneurial knowledge and attitude toward entrepreneurship. Additionally, this research explores attitude toward entrepreneurship as a mediating variable. The study employs a survey method with data from 305 vocational school graduates in Indonesia as participants. D ta analysis uses partial least squares structural equation modelling (PLS-SEM) with SmartPLS 4.0 software. The findings indicate that entrepreneurial Knowledge has a significant positive relationship with attitude toward entrepreneurship and entrepreneurial intention. Furthermore, this research finds that attitude toward entrepreneurship exhibits a complementary partial mediation effect between entrepreneurial Knowledge and entrepreneurial intention. The study also suggests that interest in entrepreneurship and professional experience can enhance the entrepreneurial intentions of vocational high school graduates. These insights offer valuable guidance for policymakers and educators in designing strategies to promote entrepreneurship among vocational school graduates, ultimately addressing unemployment challenges in Indonesia.

Atypical and variable attention patterns reveal reduced contextual priors in children with autism spectrum disorder.

Accumulating evidence suggests that individuals with autism spectrum disorder (ASD) show impairments in using contextual priors to predict others' actions and make intention inference. Yet less is known about whether and how children with ASD acquire contextual priors during action observation and how contextual priors relate to their action prediction and intention inference. To form proper contextual priors, individuals need to observe the social scenes in a reliable manner and focus on socially relevant information. By employing a data-driven scan path method and areas of interest (AOI)-based analysis, the current study investigated how contextual priors would relate to action prediction and intention understanding in 4-to-9-year-old children with ASD (N = 56) and typically developing (TD) children (N = 50) during free viewing of dynamic social scenes with different intentions. Results showed that children with ASD exhibited higher intra-subject variability when scanning social scenes and reduced attention to socially relevant areas. Moreover, children with high-level action prediction and intention understanding showed lower intra-subject variability and increased attention to socially relevant areas. These findings suggest that altered fixation patterns might restrain children with ASD from acquiring proper contextual priors, which has cascading downstream effects on their action prediction and intention understanding.

Purchase intention of brands with corporate social responsibility among generations Y and Z consumers in Chile

AbstractBrands around the world are recognizing the importance of committing to sustainable development through corporate social responsibility (CSR) initiatives. However, the literature shows scant empirical understanding of the purchase intention of younger consumers of Generations Y and Z regarding brands that engage in CSR initiatives. Drawing on the theory of planned behavior (TPB), the objective of this study is to develop and test an extended model of purchase intention for brands with CSR initiatives among the segment of Gen Y and Z consumers. The model is tested using an online survey applied to Chilean consumers and statistically analyzed using the structural equation modeling (SEM) technique. The findings show that attitude, subjective norms, and perceived behavioral control are significantly and directly related to the consumer's intention to purchase brands that demonstrate CSR initiatives. Further, consumer involvement and trust in brands' CSR initiatives have an indirect but significant effect on purchase intention through their impact on attitude. This research contributes to the literature on CSR and branding by addressing the role of consumers in supporting brands, which contribute to sustainable consumption. Findings can help brand managers and policymakers implement strategies to encourage consumer support for CSR initiatives.