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Recommended stages of cross-cultural adaption
Source publication
The use of robotic technology in healthcare is increasing. The aim was to explore attitudes toward the use of humanoid robots in healthcare among patients, relatives, care professionals, school actors and other relevant actors in healthcare and to analyze the associations between participants’ background variables and attitudes. The data were colle...
Citations
... Hybrid approaches that combine multiple learning techniques have also emerged, blending the strengths of each method to enhance detection accuracy and reduce false positives. The increasing adoption of deep learning techniques, including neural networks, autoencoders, and convolutional neural networks (CNNs), has further improved the capability of anomaly detection systems [4]. These models can analyze complex data types, such as medical images and time-series data from monitoring devices, enabling the identification of anomalies that might not be apparent through traditional analysis. ...
Anomaly detection in healthcare data is a crucial aspect of ensuring data quality, identifying unusual health conditions, and enhancing patient outcomes. Healthcare data is inherently complex, comprising diverse formats like medical records, imaging, and real-time monitoring data. This complexity, coupled with the sensitivity of medical information, presents unique challenges in anomaly detection, including handling noisy data, balancing false positives and false negatives, and dealing with imbalanced datasets. This paper explores the core challenges associated with anomaly detection in healthcare, focusing on the integration of advanced machine learning techniques to improve accuracy and efficiency. Innovations such as ensemble learning, deep learning models, and hybrid systems are discussed, highlighting their potential to enhance detection capabilities. These innovations aim to improve predictive accuracy while minimizing errors, thereby ensuring the reliability of healthcare systems and enabling early intervention in critical medical scenarios.
... Bias in robot algorithms presents another ethical challenge, as pre-programmed systems may inadvertently perpetuate existing inequalities in educational settings (Andtfolk et al., 2021;Papadopoulos et al., 2020). Continuous evaluation and an inclusivity-focused design approach are critical to mitigate these risks and ensure that robotic technologies serve all students equitably (Huijnen et al., 2017). ...
This study examines the factors influencing science teachers’ intentions to adopt humanoid robots in educational settings. It employs the Unified Theory of Acceptance and Use of Technology 2 (UTAUT-2) and the Technology-Organization-Environment (TOE) framework as guiding theoretical models. By integrating UTAUT-2, which emphasizes individual factors, and TOE, which addresses organizational and environmental influences, the study constructs a comprehensive model that explores both personal and contextual drivers of adoption. Utilizing structural equation modeling on a sample of 1,150 pre-service and in-service science teachers, the study reveals that the integrated model demonstrates superior predictive power compared to each framework individually. Results highlight the moderating role of professional experience in the adoption process, with significant differences identified between pre-service and in-service teachers. The findings reveal significant differences between pre-service and in-service teachers, illustrating the moderating role of professional experience in the adoption process. This study provides a deeper understanding of how motivational, organizational, and environmental factors interact to influence adoption intentions. These insights provide practical guidance for developing targeted training programs, promoting institutional readiness through well-crafted policy initiatives, and implementing pilot projects to support schools in the effective integration of humanoid robots into educational curricula. These findings provide actionable insights for educational policymakers and practitioners aiming to enhance teaching quality and student engagement through innovative technologies.
... Estos procesos e influencias se pueden observar ya, de manera empírica, en robots humanoides que, si bien no poseen en algunos casos piel, sí una figura humana. Andtfolk et al. (2021) destacan, por medio de análisis de datos, cómo existe una propensión generalizada en las personas (especialmente mujeres) que se encuentran en hospitales (pacientes, terapeutas, entre otras) a ver de forma amigable, con simpatía y con curiosidad las relaciones de alteridad que establecen con el robot Pepper. Para que la piel y la figura del androide alcancen estos niveles de compenetración con el ser humano, este realiza una proyección de sus sentimientos y convicciones en búsqueda de una confianza que le permita afirmar que este ente es un otro en toda su dimensión existencial. ...
This article studies the problem of otherness in human-robot interactions, especially in the figure of the android. Thinking of this entity as a “you” with its particularities brings with it a series of phenomenological and ethical problems that are strongly linked to the question about the place of human beings in the framework of future technological development. The appearance of this otherness can modify the current conceptions of society, life, feelings, among other characteristics. In this sense, the main premise of this article is to offer a study that provides answers, from a philosophical point of view, to the tensions that may emerge between this new social agent and the subjects.
... The experts involved in the translation process must be native speakers of both the original and the target language; moreover, the translation process must involve people with expertise in the technical language of the research subject concerned. A practical application of the cross-cultural adaptation processes in the field of robot studies is presented in the work of Andtfolk et al. [35] where the authors translated the RAS from the English language into both Finnish and Swedish. ...
... A convenience sample composed of 15 native Italian speakers (aged 18 years or over) recruited from the target and nontarget populations in which the instrument will be used were invited to answer the survey. The sample dimension is considered adequate according to the literature [32,35]. Participants were provided an online link where they could fill the questionnaire in. ...
Social robots and Artificial Intelligence (AI) are two technologies currently benefitting from significant scientific advancements. By consequence, the development of social robots equipped with AI is also progressing fast, and their presence and relevance in our lives are set to increase considerably. Thus, in view of a context characterized by the spread of the humanoid robots, the development of scales which measure peoples’ attitudes towards social robots is of great importance and value. The aim of this paper was to translate and validate in the Italian language the English version of the General Attitudes Towards Robots Scale (GAToRS). GAToRS measures individual and social dimensions, considering both positive and negative attitudes towards robots. We compiled a questionnaire incorporating the GAToRS and sociodemographic items and administered it to a non-probabilistic sample composed of 302 Italian citizens working in the health care sector. To identify the latent underlying dimensions, we applied exploratory factor analysis to the set of the twenty GAToRS items. We used confirmatory factor analysis to investigate the factorial structure validity of the scale and Cronbach’s alpha to measure the internal consistency. The results obtained for the Italian context suggest a version of the GAToRS which excludes the item related to the need to monitor robot technology.
... Studies conducted on healthcare providers are scarce and inconclusive, but overall suggest that the relationship between age and acceptance may be different than in the general population (Mlakar et al., 2024). Andtfolk et al. (2021), employed a mixed sample of healthcare providers and patients, and found that older individuals are more likely to favour the use of cobots in healthcare than younger individuals. Similarly. ...
This article explores the complexities and benefits of leading collaborative robots, particularly in terms of intergenerational and technological oversight. It looks at the challenges that companies face and the potential benefits that can emerge from such situations. The aim is to guide how to effectively maneuver through these different scenarios. The primary objective is to examine the hurdles that organizations must overcome, identify the available opportunities, and formulate successful strategies not only for survival but also for prosperity in this complex environment. Therefore, we support the opinion that knowledge transfer between different generations is a bidirectional process where both younger and older employees are part of knowledge sharing and knowledge receiving activities within the organization.
... [6] This also was reported by another article as higher scores were reported among women and low-educated participants. [30] Comparative research must be conducted to understand how different cultural contexts and health systems influence nations' views on AI in health care. ...
Objectives:
Artificial intelligence (AI) holds the promise to revolutionize the field of medicine and enhance the well-being of countless patients. Its capabilities span various areas, including disease prevention, accurate diagnosis, and the development of innovative treatments. Moreover, AI has the potential to streamline health-care delivery and lower expenses. The community should be aware of the potential applications of AI in health care, so that they can advocate for its development and adoption. Hence, the objective of this study is to assess the community’s perspectives regarding the utilization of AI in health care.
Methods:
A cross-sectional, questionnaire-based study was conducted in Saudi Arabia during the period of June to October 2023. The questionnaire was distributed to people on various social media platforms using a convenience sampling method. The collected data were analyzed using Statistical Package for the Social Sciences.
Results:
The study included 771 individuals, with 42.5% having a positive outlook on the use of AI in health care, 31.8% having a neutral view, and 7.5% having a negative view. The only factor associated with a positive opinion was regional differences (P = 0.006). Moreover, participants who used medical apps or programs (P = 0.026), wearables (P = 0.027), felt more confident in using technology (P < 0.001), enjoyed using technology (P < 0.001), found it easier to familiarize themselves with new devices or programs (P < 0.001), and had more knowledge about AI (P < 0.001) had more positive opinions regarding the use of AI in health care.
Conclusions:
The study found that most Saudis, especially those who were familiar with the use of technology, support the use of AI in health care, with a positive or neutral view. Yet, targeted campaigns in certain regions are needed to educate the entire community about AI’s potential benefits.
... Interestingly, while relatives showed a high willingness to share health-related data, elderly individuals expressed a preference for sharing such information with both relatives and doctors. As studied in [20], it is necessary to understand the negative attitude of people towards assistive robots for the elderly. The support for such a study could be drawn from the question of buying the robot (Figure 7), where, compared to other questions, it has a higher percentage of negative opinions. ...
Purpose:
Assistive technology for elderly are advancing, and this study aimed to analyse the Indian perspective on utilising assistive robot technology for aiding elderly individuals.
Materials and methods:
A population-based survey was undertaken to collect data from three perspectives: Relatives of the elderly, Healthcare professionals and Elderly individuals. The survey gathered 389 responses. The responses are statistically analysed, and data is visualised with different plots for better understanding.
Results:
It is observed that the older people rate with less conviction on the use of technology when compared to the relatives and healthcare professionals. Out of the three target groups, the elderly individuals had the most correlating attributes to purchasing the robot. Also, healthcare personnel, relatives, and older people gave 82%, 63% and 55% affirmatives to the question on purchasing the robot, respectively. And the cost of the robot is preferred to be under 6 lakh rupees.
Conclusions:
Though the younger generation has more orientation towards technology, older people are skeptical about handling computer gadgets or robots. However, there are significant expectations and concerns expressed by three target groups such as conversational, navigational, reminder features, security and malfunction concerns.
... Robots are also perceived positively in the hospital environment (Andtfolk et al., 2022), but there is no lack of ambivalence on the part of patients, as many of them would prefer to be cared for by humans (Vallès-Peris et al., 2021). In the case of care for the elderly, positive attitudes are also generally observed, but only if robots are cast in appropriate roles (Niemelä & Melkas, 2019). ...
The purpose of the study is to assess attitudes toward robots among a Polish sample (N = 1044) using a series of questions focused on their perceptions within the labor market. Based on previous research, higher concerns toward and lower acceptance of robots were predicted for women, people performing manual and manual work, and people who are not familiar with robotics. The hypotheses were only partially confirmed. Orientation in the field of robotics is conducive to greater acceptance of the presence of robots in trust works professions. Unexpectedly, it turned out that people who declared performing physical work, compared to people performing other types of tasks, have a more affirmative attitude to the participation of robots in customer service occupations and to accept the autonomy of the robot to a higher degree. The results also showed that women are more concerned about the increased presence of robots in the labour market and less accepting of the replacement of humans by robots and the greater autonomy of intelligent machines. In addition, the analysis revealed that people with more knowledge in the field of robotics declare greater acceptance of the autonomous work of robots and in terms of replacing people with robots in the work environment, they also have fewer concerns about the market situation compared to those who do not consider themselves knowledgeable in this area.
... However, they expressed greater anxiety in turns of job displacement by HRs and slightly more than females regarding the fear that HRs could control humans. The more positive attitudes of males were found in previous studies (Andtfolk et al., 2021;Nomura, 2016), while other research found no significant differences regarding gender (Alemi et al., 2021;Kamide et al., 2012;Riek et al., 2010). Hypotheses 3 and 4 examined attitudes toward HRs by Employment Status and Ethnic Grouping, respectively. ...
... However, younger persons did have a greater fear of job replacement by HRs than older persons. Differentials in receptivity of HRs by Age is found in previous studies (Andtfolk et al., 2021;Kamide & Arai, 2017;Nomura et al., 2015) in reference to job displacement but not fear of losing control to HRS or being controlled by them, which this study found to increase with age. Finally, regarding the ethnicity of the respondents, the results indicated that five occupations varied significantly in their mean rankings of these replacements. ...
The phenomenon of job displacement by robots, in general, and potentially by humanoid robots has generated a growing body of academic literature as well as studies from business-funded think tanks. Because of the infancy of its development as a technology, much of the literature on humanoid robotics is speculative, focusing mostly on psychometric factors regarding receptivity and not on workers'perception of job displacement or human-robot interaction in future workplaces. This economics study regarding future employment trends is an original, pioneering effort in examining the perceptions of job displacement and future human-robot work interaction in Thailand. It surveyed students in an English-medium MBA program at an international university in Bangkok, Thailand. Perceptions of job displacement were examined using the demographic variables of gender, age, employment status, and ethnic background. The study found partial support regarding all fourof the demographic variables studied, with more significant differences regarding gender and ethnicity. Abdul Rasyid and Ghee-Thean Lim, On the Priorities of Indonesia's Agricultural Trade • 69
... Similarly, Turja and colleagues (2018) report that younger age predicted a lower level of robot acceptance at work among HCPs. On the other hand, previous studies conducted among healthcare providers and other populations suggest rather uniformly that higher education is associated with greater acceptance of SAHRs [73][74][75]. Besides age and education, the occupation of HCPs may also be important. ...
... Lastly, patients' demographic factors, particularly age and education level, may also be important. While studies among this population group are rare, studies conducted in other contexts generally suggest that older individuals are less likely to accept SAHRs [72,75], while individuals with higher education are more likely to accept SAHRs [73]. ...
... In fact, even on the correlational level, age was only observed to be weakly associated with the general acceptance of SAHR among HCPs. This observation partially contradicts the findings in related research, where it was observed that age, especially among the patient population, represents a key predictor, and that acceptance of SAHRs decreases with age [47,70,71,73]. ...
Healthcare systems around the world are currently witnessing various challenges, including population aging and workforce shortages. As a result, the existing, overworked staff are struggling to meet the ever-increasing demands and provide the desired quality of care. One of the promising technological solutions that could complement the human workforce and alleviate some of their workload, are socially assistive humanoid robots. However, despite their potential, the implementation of socially assistive humanoid robots is often challenging due to low acceptance among key stakeholders, namely, patients and healthcare professionals. Hence, the present study first investigated the extent to which these stakeholders accept the use of socially assistive humanoid robots in nursing and care routine, and second, explored the characteristics that contribute to higher/lower acceptance within these groups, with a particular emphasis on demographic variables, technology expectations, ethical acceptability, and negative attitudes. In study 1, conducted on a sample of 490 healthcare professionals, the results of structural equation modeling showed that acceptance is driven primarily by aspects of ethical acceptability, although education and technology expectations also exert an indirect effect. In study 2, conducted on a sample of 371 patients, expectations regarding capabilities and attitudes towards the social influence of robots emerged as important predictors of acceptance. Moreover, although acceptance rates differed between tasks, both studies show a relatively high acceptance of socially assistive humanoid robots. Despite certain limitations, the study findings provide essential knowledge that enhances our understanding of stakeholders' perceptions and acceptance of socially assistive humanoid robots in hospital environments, and may guide their deployment.
