Search Results (128)

Background/Objectives: Respectful maternity care involves privacy, dignity, and informed choice within the process of delivery as stipulated by the World Health Organization (WHO). Informed consent is a cornerstone of patient-centered care, representing not just a formal document, but an ongoing ethical and clinical process through which women are offered objective, understandable information to support autonomous, informed decision-making. Methods: This narrative review critically examines the literature on informed consent in maternity care, with particular attention to both obstetric-led and midwifery-led models of care. In addition to identifying institutional, cultural, and systemic obstacles to its successful implementation, the review examines the definition and application of informed consent in perinatal settings and evaluates its effects on women’s autonomy and satisfaction with care. Results: Important conclusions emphasize that improving women’s experiences and minimizing needless interventions require active decision-making participation, a positive provider–patient relationship, and ongoing support from medical professionals. However, significant gaps persist between legal mandates and actual practice due to provider attitudes, systemic constraints, and sociocultural influences. Women’s experiences of consent can be more effectively understood through the use of instruments such as the Mothers’ Respect (MOR) Index and the Mothers’ Autonomy in Decision Making (MADM) Scale. Conclusions: To promote genuinely informed and considerate maternity care, this review emphasizes the necessity of legislative reform and improved provider education in order to close the gap between policy and practice. Full article

Patient-generated health data (PGHD) enhance traditional healthcare by enabling continuous monitoring and supporting personalized care, yet concerns over privacy, security, and integration into existing systems hinder broader adoption. This study examined the perceptions, awareness, and concerns of patients and caregivers regarding PGHD and assessed their willingness to share such data for clinical, research, and commercial purposes. A cross-sectional survey was conducted from 6 to 12 November 2023, involving 400 individuals with experience using PGHD. Participants completed structured questionnaires addressing health information management, PGHD usage, and attitudes toward its application. PGHD was most commonly used by patients with chronic conditions and guardians of minors, with tethered personal health record apps frequently utilized. Respondents identified improved self-management and better access to information as key benefits. However, significant concerns about data privacy and security emerged, especially regarding non-clinical use. Younger adults, particularly those in their 20s, showed lower willingness to engage with PGHD due to heightened privacy concerns. These findings suggest that, while support for clinical use of PGHD is strong, barriers related to trust and consent remain. Addressing privacy concerns and simplifying consent processes will be essential to promote equitable and responsible PGHD utilization across diverse patient populations. Full article

Emotional difficulties are increasingly prevalent amongst young people, yet the use of AI technology for emotion regulation remains limited. This study aimed to identify young people’s attitudes toward AI technology for emotion regulation and to analyse the factors influencing their decision to use or not use AI technology. Forty participants from China, comprising twenty males and twenty females, with a mean age of twenty-five, took part in the study. Data were collected through semi-structured face-to-face interviews and were analysed using NVivo 11 software. Grounded theory techniques and a three-stage coding approach were used to categorise the data. The grounded theory model demonstrated that user behaviours are influenced by three contextual factors: personal, technological and environmental contexts. Key influencing factors for user behaviours include fulfilling utilitarian, hedonic and social value needs such as perceived usefulness, ease of use, trust, positive emotions, interest, social perception, high value, convenience and privacy protection. This study offered theoretical insights and practical recommendations for designing and developing AI technology aimed at emotion regulation in youth populations. Full article

Augmented Reality Smart Glasses (ARSGs) allow users to engage in picture-taking and video recording, as well as real-time storage and sharing of pictures and videos through cloud services. Unlike smartphones, newer ARSGs resemble ordinary sunglasses, allowing for unobtrusive recording. As these devices become available on an international market, it is important to understand how different cultural attitudes towards privacy and the recording and sharing of images of bystanders could impact the acceptance and adoption of ARSGs. South Korea and the United States have vastly different culturally based perceptions of photography and recording in public. S. Korea has cultural and legal restrictions in place, while the U.S.’s values of freedom of expression and individual rights are reflected in limited restrictions. Accordingly, drawing upon the Technology Acceptance Model (TAM), this paper explored the impact of privacy concerns on key constructs of the TAM for U.S. and S. Korean participants. This paper examined how Americans’ (U.S. = 402) and S. Koreans’ (S. Korea = 898) perceived usefulness, perceived ease of use, attitude toward using, and behavioral intention to use ARSGs were impacted by privacy concerns. The results of this study found that S. Korean respondents had significantly greater privacy concerns about using ARSGs than U.S. respondents. However, they also had significantly more positive attitudes and greater behavioral intentions to use ARSGs. Path analyses examining ARSGs’ acceptance revealed that privacy concerns impacted attitudes towards ARSGs, but that these had a greater impact on U.S. participants than on Koreans. The results highlight the importance of considering nuanced cultural perspectives, specifically privacy concerns, in examining the development and adoption of new technologies. Raw data and scripts for this study are available to ensure reproducibility. Full article

Insider threats pose significant challenges to organizations, seriously endangering information security and privacy protection. These threats arise when employees with legitimate access to systems and databases misuse their privileges. Such individuals may alter, delete, or insert data into datasets, sell customer or client email addresses, leak strategic company plans, or transfer industrial and intellectual property information. These actions can severely damage a company’s reputation, result in revenue losses and loss of competitive advantage, and, in extreme cases, lead to bankruptcy. This study presents a novel solution that examines how organizational factors such as job satisfaction and security, organizational support, attachment, commitment, involvement in information security, and organizational norms influence employees’ attitudes and intentions, thereby mitigating insider threats. A key strength of this research is its integration of two foundational theories: the Social Bond Theory (SBT) and the Theory of Planned Behavior (TPB). The results reveal that job satisfaction and security, affective and normative commitment, information security training, and personal norms all contribute to reducing insider threats. Furthermore, the findings indicate that employees’ attitudes, perceived behavioral control, and subjective norms significantly influence their intentions to mitigate insider threats. However, organizational support and continuance commitment were not found to have a significant impact. Full article

As smart voice assistants (SVAs) become increasingly integrated into digital commerce, understanding the psychological factors driving their adoption or resistance is essential. While prior research has addressed the impact of privacy concerns, few studies have explored the competing forces that shape user decisions. This study investigates the dual role of privacy cynicism as a context-specific belief influencing both trust (reason-for) and perceived creepiness (reason-against)—which in turn affect attitudes, behavioral intentions, and resistance toward SVA usage, based on the Behavioral Reasoning Theory (BRT). The study used a convenience sampling method, gathering data from 250 Turkish consumers aged 18–35 through an online survey technique. The research model was analyzed using PLS-SEM. The findings revealed that perceived creepiness increases resistance intention but does not significantly affect attitudes toward using SVAs. Perceived cynicism was found to positively influence perceived trust, and perceived trust, in turn, increased both behavioral intentions and attitudes toward using SVAs. Furthermore, attitudes toward SVA usage decreased resistance intention but increased behavioral intention. The results emphasize consumer trust and skepticism in AI-driven marketing. The study offers both theoretical contributions by extending BRT with a novel dual-path conceptualization of privacy cynicism, and practical implications for developers aiming to boost SVA adoption through trust-building and privacy assurance strategies. Full article

The rapid development of autonomous driving technology has been a key driver for the emergence of driverless delivery vehicles. To promote wider adoption, it is essential to address consumers’ concerns about safety and reliability, leverage psychological factors, and implement supportive policies that encourage technology adoption while ensuring public safety and privacy. Therefore, it is necessary to explain and predict consumers’ behavior and intention to adopt driverless delivery vehicles. To this end, this study extends the Technology Acceptance Model (TAM) to include technological complexity and perceived trust. This study evaluates the model by applying necessary condition analysis (NCA) and partial least squares structural equation modeling (PLS-SEM) to analyze data from 579 respondents from Jiangsu Province, China. This study explores the sustainability implications of autonomous delivery vehicles, highlighting their potential to reduce environmental impact and promote a more sustainable transportation system. The outcomes indicate that perceived ease of use (PEU), attitude, perceived trust, technological complexity (TECOM), and perceived usefulness (PU) are significant determinants and necessary conditions of consumers’ intention to adopt driverless delivery vehicles. Perceived trust and TECOM had a significant and indirect influence on consumers’ intention to adopt driverless delivery vehicles via PU and PEU. Perceived trust and technological complexity had a substantial impact on consumers’ adoption intention of driverless delivery vehicles. The study recommends that managers work closely with regulators to ensure their technologies meet all local standards and regulations. It also recommends its potential to reduce carbon emissions, improve energy efficiency, and contribute to a more sustainable transportation system. Full article

Background: Unlike other chronic diseases, cancer patients undergo different types of treatments that affect their well-being, and as a result, they tend to have different experiences from those of other chronic disease sufferers. The purpose of this study was to assess the effects of cancer diagnosis and coping strategies on patients in Vhembe District hospitals in Limpopo Province. Methodology: The study design used was a quantitative descriptive cross-sectional survey. The target population included patients in the Vhembe District of Limpopo who had started treatment within the last year. Probability-stratified sampling was used to sample 207 patients from seven selected hospitals in Vhembe District. A self-administered questionnaire was used to collect data, and the data were analyzed using a software package for descriptive statistics (SPSS version 23). Tables were used to display the results visually, and chi-square tests were used to compare the variables. Ethical principles were considered for the participants’ privacy, anonymity, and informed consent. Findings: The findings revealed that the majority of patients 185 (89.4%) experienced a sense of psychosocial distress such as emotional pain; 142 (68.6%) participants experienced hopelessness and despair, 127 (61.3%) resorted to substance use, 160 (77.3%) did not have a positive attitude towards seeking the medical and other support resources available, only a minority resorted to spirituality, and 121 (63.2%) indicated seeking further clarity about the disease. The study recommends supporting cancer patients and their families through the cancer journey. Contributions: Clinicians should provide psychosocial support interventions to enhance mental health and quality of life in cancer patients, and decentralize oncology services by including primary care professionals in delivering chronic illness disease management strategies. Full article

The widespread deployment of service robots in industries such as hospitality has significantly transformed service delivery, influencing not only customers but also employees. This study examines the multi-dimensional impact of service robots on hotel employees, focusing on their attitudes, emotional responses, and willingness to collaborate, as shaped by perceived benefits (service reliability, process efficiency, and job crafting) and risks (inefficiency, insufficient intelligence, and privacy concerns). Data were collected from 471 hotel employees in South Korea with experience working alongside service robots, and Hayes’ Process Macro Model 4 was employed for hypothesis testing. The findings reveal that perceived benefits positively influence employees’ attitudes, emotions, and willingness to collaborate, while perceived risks exert a negative impact. Furthermore, attitudes and emotional responses mediate these relationships. These findings provide theoretical and practical insights for managers, policymakers, and service robot manufacturers to address employee concerns, improve human–robot collaboration, and promote sustainable technological integration within the service industry. Full article

Purpose: Assess mental health professionals’ attitudes regarding the timing and characteristics of therapeutic interventions for children whose parents have incurable cancer, and whether professionals would use artificial intelligence (AI) in these interventions. Methods: Professionals were surveyed about their therapeutic approaches to caring for children when parents have incurable cancer under different scenarios. Data from N = 294 (69% male, 72% white, 26% Latine, 56% rural or underserved communities) physicians, psychologists, social workers, hospital chaplains, community health workers, and others were analyzed. Attitudes surrounding the timing and characteristics of interventions across the parent’s cancer journey were compared, including how professionals believed interventions should attend to dimensions of the child or family, and if, how, and when AI technology could be introduced. Results: Across 10 dimensions of childhood, (1) the child’s premorbid exposure to traumatic events, (2) a surviving parent’s presence, and (3) the child’s age were important factors to consider when making mental health care decisions in this context. The professionals reported being more likely to introduce therapeutic resources as early as possible in the parent’s illness (i.e., upon diagnosis). Regarding the use of AI, 87% foresaw its role in supporting children’s mental health. While 93.2% agreed that a grieving child could be helped by interacting with an AI-generated likeness of the deceased parent, when AI’s use was contextualized in providing support for a child who lost a parent to cancer, only 49% believed AI was appropriate. The participants were conflicted over when AI could be first introduced, either upon a parent’s illness diagnosis (19.4%), during a parent’s treatment (19.0%), or as part of a parent’s hospice care (12.6%). None believed it to be appropriate following the loss of the parent to cancer. Conclusions: AI is increasingly present in children’s daily lives and quickly infiltrating health care with widely accessible mental health chatbots. Concerns about privacy, the accuracy of information, and the anthropomorphism of AI tools by children give professionals pause before introducing such technology. Proceeding with great caution is urged until more is known about the impact of AI on children’s mental health, grief, and psychological well-being in the context of parental cancer. Full article

Citizen engagement in urban planning is vital for democratic governance and sustainable development. While technologies such as e-governance platforms and mobile applications have facilitated participatory processes, their success ultimately hinges on citizen acceptance. This study investigates the factors influencing female citizens’ acceptance of a participatory urban planning application, employing a theoretical model based on the technology acceptance model (TAM) and its associated hypotheses. Data were collected through a survey of 390 women and analyzed using partial least squares structural equation modeling (PLS-SEM) via SmartPLS_3.2.8. The results demonstrate that perceived usefulness (β = 0.634, p < 0.001) and perceived ease of use (β = 0.321, p < 0.001) significantly predict intention to use, whereas perceived privacy risk exerts a negative influence (β = −0.190, p < 0.001). Environmental attitude (β = 0.396, p < 0.001) and attitude toward participation (β = 0.315, p < 0.001) also enhance perceived usefulness. Due to the impact of the environmental and participatory attitudes of citizens and their social environment on their acceptance of these apps, there is an urgent need to increase the level of citizen awareness and knowledge through targeted education. These findings offer valuable insights for both theoretical advancement and practical policy development in regards to urban governance. Full article

Background/Objectives: Wearable activity trackers (WATs) are increasingly used by individuals to monitor physical activity, sleep, and other health behaviors. Integrating WAT data into clinical care may offer a cost-effective strategy to support health behavior change. However, little is known about users’ willingness to share their WAT data with healthcare providers. This study aimed to explore attitudes and experiences of WAT users regarding the sharing of WAT data with healthcare providers and to examine how these vary according to user characteristics. Methods: An international online cross-sectional survey was conducted on adults who had used a WAT within the past three years. The survey assessed user demographics, usage patterns, experiences of sharing data with healthcare providers, and willingness or concerns regarding data sharing. Multivariate logistic regression was used to examine associations between user characteristics and data-sharing experiences or attitudes. Results: 447 participants completed the survey (60.0% female; 83.9% < 45 years; 60.0% from the United States). Most (94%) participants expressed willingness to share WAT data with healthcare providers, 47% had discussed it, and 43% had shared WAT data in clinical settings. Privacy was the most commonly reported concern, cited by 10% of participants. Participants with chronic health conditions were more likely to have shared or discussed WAT data, but also more likely to report concerns. Geographic differences were also observed, with Australian participants less likely to have shared or discussed their WAT data with providers, and US participants reporting fewer privacy concerns. Conclusions: The high willingness to share WAT data suggests that there is a possibility for integrating patient-owned WATs into clinical care. Addressing privacy concerns and equipping healthcare professionals with the skills to use WAT data will be essential to fully realize this opportunity. These findings highlight the need for further development of secure WAT systems, clinician training, and expanded evidence on WATs’ clinical utility. Full article

The rapid advancements in artificial intelligence (AI) have significantly transformed various domains, including education, by introducing innovative tools that reshape teaching and learning processes. This research investigates the perceptions and attitudes of students towards the use of AI tools in their academic activities, focusing on constructs such as perceived usefulness, the perceived ease of use, security and privacy concerns, and both positive and negative attitudes towards AI. On the basis of Technology Acceptance Model (TAM) and the General Attitudes towards Artificial Intelligence Scale (GAAIS), this research seeks to identify the factors influencing students’ behavioral intentions and actual adoption of AI tools in educational settings. A structured survey was administered to students at Multimedia University, Malaysia, capturing their experiences and opinions on widely used AI tools such as ChatGPT, Quillbot, Grammarly, and Perplexity. Hypothesis testing was used to evaluate the statistical significance of relationships between the constructs and behavioral intention and actual use of the AI tools. The findings reveal a high level of engagement with AI tools among University students, primarily driven by their perceived benefits in enhancing academic performance, improving efficiency, and facilitating personalized learning experiences. The findings also uncover significant concerns related to data security, privacy, and the potential over-reliance on AI tools, which may hinder the development of critical thinking and problem-solving skills. Full article

Background: The integration of artificial intelligence (AI) into mental health care is reshaping psychological support systems, particularly for digitally literate populations such as nursing students. Given the high prevalence of anxiety and depression in this group, understanding their perceptions of AI-driven mental health support is critical for effective implementation. Objectives: to evaluate nursing students’ perceptions toward AI-driven mental health support and examine its relationship with anxiety, depression, and their attitudes to seeking professional psychological help. Methods: A cross-sectional survey was conducted among 176 undergraduate nursing students in northern Jordan. Results: Students reported moderately positive perceptions toward AI-driven mental health support (mean score: 36.70 ± 4.80). Multiple linear regression revealed that prior use of AI tools (β = 0.44, p < 0.0001), positive help-seeking attitudes (β = 0.41, p < 0.0001), and higher levels of psychological distress encompassing both anxiety (β = 0.29, p = 0.005) and depression (β = 0.24, p = 0.007) significantly predicted more positive perceptions. Daily AI usage was not a significant predictor (β = 0.15, p = 0.174). Logistic regression analysis further indicated that psychological distress, reflected by elevated anxiety (OR = 1.42, p = 0.002) and depression scores (OR = 1.32, p = 0.003), along with stronger help-seeking attitudes (OR = 1.35, p = 0.011), significantly increased the likelihood of using AI-based mental health support. Conclusions: AI-driven mental health tools hold promises as adjuncts to traditional counseling, particularly for nursing students experiencing psychological distress. Despite growing acceptance, concerns regarding data privacy, bias, and lack of human empathy remain. Ethical integration and blended care models are essential for effective mental health support. Full article

Background and Objectives: The rapid advancement of Artificial Intelligence (AI) has driven the expansion of telemedicine solutions worldwide, enabling remote diagnosis, patient monitoring, and treatment support. This study aimed to explore medical students’ perceptions of AI in telemedicine, focusing on how these future physicians view AI’s potential, benefits, and challenges. Methods: A cross-sectional survey was conducted among 161 Romanian medical students spanning Years 1 through 6. Participants completed a 15-item questionnaire covering demographic factors, prior exposure to AI, attitudes toward telemedicine, perceived benefits, and concerns related to ethical and data privacy issues. A questionnaire on digital health acceptance was conceived and integrated into the survey instrument. Results: Out of 161 respondents, 70 (43.5%) reported prior telemedicine use, and 66 (41.0%) indicated high familiarity (Likert scores ≥ 4) with AI-based tools. Fifth- and sixth-year students showed significantly greater acceptance of AI-driven telemedicine compared to first- and second-year students (p = 0.014). A moderate positive correlation (r = 0.44, p < 0.001) emerged between AI familiarity and telemedicine confidence, while higher data privacy concerns negatively affected acceptance (β = −0.20, p = 0.038). Gender differences were noted but did not reach consistent statistical significance in multivariate models. Conclusions: Overall, Romanian medical students view AI-enhanced telemedicine favorably, particularly those in advanced academic years. Familiarity with AI technologies is a key driver of acceptance, though privacy and ethical considerations remain barriers. These findings underline the need for targeted curricular interventions to bolster AI literacy and address concerns regarding data security and clinical responsibility. By proactively integrating AI-related competencies, medical faculties can better prepare students for a healthcare landscape increasingly shaped by telemedicine. Full article