Actual Use Research Articles (Page 1)

Purpose This study extends the technology acceptance model (TAM) to identify factors impacting the ongoing use of electronic payment (e-payment) systems in Bangladesh in order to create a cashless society. Design/methodology/approach Data were acquired from 442 Bangladeshi e-payment consumers. Structural equation modeling (SEM) and confirmatory factor analysis (CFA) were used to investigate the correlations between the suggested variables and user behavioral intentions. Findings Trust, security, individual mobility and conducive conditions all have a substantial impact on perceived utility and ease of use. Along with social impact, these impressions strongly predict consumers’ long-term desire to utilize e-payment systems, which then affects actual use. Furthermore, self-efficacy considerably modifies the link between continuous use intention and actual usage. Originality/value This study expands on existing e-payment work by incorporating more components into TAM, resulting in a more comprehensive understanding of behavioral drivers in developing nations. The findings provide practical insights for e-payment service providers looking to boost user confidence, bolster trust and security measures and increase adoption through increased user assistance and training.

An increasing number of women of childbearing age are treated for attention-deficit hyperactivity disorder (ADHD). Limited evidence exists on risk of pregnancy loss associated with ADHD medication use in early pregnancy. To assess whether ADHD medication use during pregnancy is associated with increased risk of miscarriage. We conducted a nationwide, register-based, case-control study, using linked Norwegian data from Medical Birth Registry of Norway, Norwegian Patient Registry, Norwegian Control and Payment of Health Reimbursements Database and Norwegian Prescription Database. Among pregnant women with ADHD, those with miscarriage (n = 2993 cases) were matched with up to four live births (n = 10 305 controls) by maternal age and year of conception. ADHD medication exposure during pregnancy was defined as any use (one or more filled prescriptions) and categorised into tertiles of total defined daily doses (DDDs) as a proxy for dose. The main outcome was miscarriage (pregnancy loss before 20 weeks). Conditional logistic regression was used to estimate adjusted odds ratios (aORs) with 95% confidence intervals, adjusting for psychiatric comorbidities, psychotropic and teratogenic medications, and maternal age at conception. Of 13 298 pregnancies, 1389 (10.5%) were exposed to ADHD medications. Any ADHD medication use was associated with increased miscarriage risk (aOR 1.60, 95% CI 1.41-1.83). Methylphenidate (aOR 1.55, 95% CI 1.35-1.79), lisdexamfetamine (aOR 1.81, 95% CI 1.06-3.10) and atomoxetine (aOR 2.34, 95% CI 1.41-3.89) were associated with increased risks. Higher levels of medication exposure, categorised by DDD tertiles, were associated with increased odds of miscarriage, increasing from 1.14 (95% CI 0.91-1.42) for the lowest tertile to 2.11 (95% CI 1.71-2.60) for the highest. ADHD medication use during pregnancy is associated with increased miscarriage risk. However, filled prescriptions may not reflect actual use. Further research is needed to clarify these associations and refine risk estimates.

Understanding how organisational support, perceived ease of use, and perceived usefulness influence the actual use of a High-Performance Computing (HPC) system sheds light on its adoption within a higher education institution. A quantitative approach with a descriptive design was employed, surveying 218 respondents, including Master's and PhD students and academic staff, using stratified and simple random sampling techniques. Data were collected through online self-administered questionnaires and analysed using SPSS version 29.0. The findings revealed strong positive correlations between organisational support, perceived ease of use, perceived usefulness, and actual use of the HPC system, supporting prior research on technology adoption (Davis, 1989; Venkatesh et al., 2003). A moderate positive correlation was found between organisational support and perceived ease of use and perceived usefulness. This suggests that users who feel supported by their institution are more likely to find the system easy to use and valuable. Furthermore, a moderate positive correlation was found between perceived ease of use and perceived usefulness, as well as between perceived ease of use and actual use, indicating that users who find the system simple to use are more likely to adopt it. Additionally, there was a moderate positive correlation between perceived usefulness and actual use, highlighting that users engage more with the system when they recognise its benefits. In conclusion, organisational support and user perceptions are key to successfully implementing and using new technologies.

Legal Barriers and Ethical Challenges in HIV Prevention and Care: A Case Study on the Criminalization of Sex Workers and Clients Living With HIV in China.

The number older patients with cancer who are terminally ill is expected to increase with global population aging. However, reports on the actual use of opioids for pain relief in patients aged ≥ 90years with cancer at the end of life are limited. To investigate opioid use in older patients with cancer aged ≥ 90years who died in a palliative care unit. Patients with cancer who died in the palliative care unit between August 2020 to August 2024 and were aged ≥ 90years were included. We analyzed their data on opioid use, including opioid type and route of administration, and morphine equivalent daily dose (MEDD), at the time of death. Ninety-one patients with cancer were included in the study. Their median age was 92.0years (interquartile range [IQR] 91.0-93.0). Seventy-six patients (83.5%) were administered opioids at the time of death, and hydromorphone delivered via continuous subcutaneous injection was the most common (41 patients). The median MEDD at the time of death for the 76 patients was 19.6mg/day (IQR 12-42). Four patients were administered high doses of opioids (MEDD of > 120mg/day) at the time of death. Of the patients aged ≥ 90years with cancer who were terminally ill, more than 80% had used opioids. Their median MEDD tended to be low at 19.6mg/day. Future studies are required to help appropriately use opioids for patients aged ≥ 90years with cancer.

This study employs the Technology Acceptance Model (TAM) to examine factors influencing graduate students' acceptance and use of ChatGPT in academic writing. Despite ChatGPT's growing presence in higher education, limited evidence exists regarding its actual adoption. A modified TAM-based questionnaire was completed by 254 graduate students from four Saudi universities and analyzed using SPSS and JASP. Structural Equation Modeling assessed both direct and indirect effects within a mediation model. Results indicate that perceived ease of use and perceived usefulness significantly shape students' attitudes and behavioral intentions toward ChatGPT. However, ease of use only impacts attitudes when mediated by usefulness. Positive attitudes were linked to stronger intentions to use the tool, yet high intentions did not always lead to actual use. Barriers such as limited skills or concerns about academic integrity may hinder this transition.

Upper Extremity (UE) rehabilitation is crucial for stroke survivors, aiming to improve the use of the paretic UE in everyday activities. However, assessing the effectiveness of these treatments is challenging due to a lack of objective measurement tools. Traditional methods, such as clinician-rated motor ability or patient self-reports, often fail to measure UE performance in real-life settings accurately. Evidence suggests that currently used clinical assessments do not reliably capture actual UE use at home or in the community. This study investigates the application of Convolutional Neural Networks (CNNs) combined with Dense layers using accelerometry data from wrist-worn sensors to classify functional and non-functional UE movements of stroke survivors. Two types of models were developed: one trained on data from individual subjects (intrasubject model) and another trained on data across all subjects (intersubject model). The intrasubject model for the paretic UE achieved an average accuracy of 0.90 ± 0.05, while the intersubject model reached an accuracy of 0.79 ± 0.06. When incorporating signals from the non-paretic arm, the intersubject model’s accuracy improves to 0.88 ± 0.10. Notably, this method utilized raw accelerometry data, eliminating the need for manual feature extraction, which is commonly required in traditional machine learning, and yielded higher accuracy than previously reported methods. This proposed deep learning approach incorporates CNNs with Dense layers, offering a cost-effective and adaptable method for monitoring UE functionality in real-world settings. The results from this study have the potential to inform the development of personalized rehabilitation strategies for stroke survivors, offering valuable insights for clinical practice.

Type of the article: Research ArticleAbstractThe ongoing process of digitalization presents both opportunities and challenges for small and medium-sized enterprises (SMEs), particularly when it comes to integrating corporate mobile applications into daily operations. This study examines the key factors that influence employees’ acceptance of, and their actual use of, employer-provided mobile applications.Primary data were collected via a structured questionnaire survey conducted between March and July 2024 in Hajdú-Bihar County, Hungary. The target population comprised employees of SMEs and micro-enterprises who had access to such applications. Non-probability purposive sampling was employed to ensure relevance, yielding a total of 161 valid responses. Quantitative data were analyzed using structural equation modelling via the partial least squares method.The results demonstrate that performance expectancy, facilitating conditions, hedonic motivation, and price value have a statistically significant positive impact on behavioral intention, which in turn is the strongest predictor of actual use. The model explains 69% of the variance in behavioral intention and 87.2% of the variance in actual use, which highlights the robustness of the findings. Conversely, social influence and effort expectancy played no meaningful role in this context, suggesting that adoption is shaped less by peer pressure or perceived ease of use and more by perceived benefits, organizational support, and motivational factors. From a management perspective, the findings emphasize the importance of investing in digital infrastructure, providing organizational support, and improving perceived value and user experience. Such measures are crucial for supporting effective implementation and fostering sustainable digital transformation in SMEs.AcknowledgmentSupported by the University of Debrecen Program for Scientific Publication.

CubeSats suffer from limitations in power and processing capacity, often leading developers with limited options in implementing data security measures thereby increasing the vulnerability to data breaches and unauthorized access. These attacks negatively affected CubeSat operations or caused losing control over CubeSats in orbit; therefore, recent missions have prioritized the implementation of security measures, with data encryption being the most common method to defend against eavesdropping, and authentication protocols to prevent unauthorized access. This study presents an application of a Fuzzy Logic-based Authentication module to enhance CubeSats' security with minimal strain on the processing power of the Command and Data Handling System (CDHS) and without the need of additional hardware, targeting missions with constrained budgets relying solely on Commercial Off-The-Shelf (COTS) hardware. The module addresses cyber-attacks by analyzing the typing pattern transmitted during the initial communication, in addition to the username and password, such that authenticated users are granted access to the CubeSat. The success criteria defined in this study were based on two primary elements: (1) granting access to authenticated users with accurate credentials and (2) denying access for any user attempting impersonation, regardless of providing correct credentials. During initial testing, the algorithm achieved a 97% success rate in authenticating legitimate users, while maintaining an average 95% success rate in detecting impersonation attempts. These results will be verified after the launch of the CubeSat, where the algorithm will undergo further testing in real-time operations, as its performance is influenced by operators’ behavior, which can vary significantly during actual use.

We are now living in a platform society, where platforms are widely acknowledged to exert significant control over users. But how can user agency exert power to influence the platform? To explore this question, the study conducts in-depth interviews with 21 Xiaohongshu users and analyzes their imagined affordances of this Chinese UGC platform. It finds that users creatively engage with and repurpose the platform based on their imagination, thereby transforming Xiaohongshu from a “developer-envisioned platform” into four distinct forms of the “platform in actual use.” These user agency-driven practices serve as ways of reshaping the platform’s meanings, functions, and values. By centering user agency, this research may offer platform studies a new perspective on power dynamics, shifting the current focus away from the dominance of platforms.

Background Precision medicine aims to facilitate a more individualized treatment selection and a more accurate diagnosis. While there is broad ranging research on precision psychiatry and the corresponding computational tools, its concepts and implementation are underway, little is known about the attitudes towards the actual use of precision psychiatry tools in the management of major psychiatric disorders, such as Major Depressive Disorder (MDD). This study aims to investigate the attitudes of depressive patients, professionals (physicians, psychologists and scientists) and the general population towards a novel, multimodal precision medicine algorithm designed to predict antidepressant treatment response. Methods 5490 participants from 21 European countries, consisting of three groups of stakeholders, patients with depression (n= 421), professionals (n = 367) and the general population (n = 4702), were polled with a newly developed cross-sectional survey. A hypothetical decision scenario was used to examine the participants’ attitudes, in which they were asked for their approval or disapproval for the application of a multimodal precision medicine algorithm to predict treatment response in antidepressant-treatment.3 Results The general population had an acceptance rate of 78.8%. Overall, 74.6% of patients with MDD would agree to undergo testing using the multimodal algorithm in their current situation and 80.2% reported they would have done so at the time of their first diagnosis. In contrast, the psychiatrist’s acceptance rates towards a multimodal algorithm were higher when patients had been in treatment for some time (79.3%) compared to those who had only recently been diagnosed (55.2%). This pattern was present across all other specialties within the professionals group. A considerable number of participants wished to receive more information before deciding, but few declined its application altogether. All groups indicated an openness towards personalized treatment options in general. Conclusion Overall, participants indicated a large degree of acceptance towards the application of a multimodal precision medicine algorithm. Although limited by the hypothetical nature of the decision scenario, this study provides valuable perspectives from different stakeholders. Future research should move beyond attitudes and address further implementation hurdles that need to be overcome for the successful implementation of novel precision psychiatry approaches in psychiatric care.

Recent studies in Nordic and European architectural- and urban history have emphasized the importance of commercial modernism in the making of European welfare societies. However, as this research has predominantly approached architecture from a planning and design angle, we know little about the actual use of these spaces and their socio-spatial flexibility and capacity in negotiating welfare on an everyday scale. Focusing on four shops located in Grantoften Shopping Center, this article introduces the concept of ‘more-than-mercantile relations’ to capture the multifaceted negotiations and exchanges through which local actors mobilize the spatiality of Grantoften Shopping Center into forms of everyday welfare. Combining archival studies and ethnographic data, the article examines how welfare at a local level is negotiated through specific temporal entwinements of spatial locations and everyday practices of care. By reimagining shopping centers as spaces of care and community interaction, this article contributes to research discussions on the geography of care, emphasizing the capacity of everyday commercial spaces to shape and be shaped by welfare practices.

This study explores Moroccan teachers’ perspectives on ChatGPT-Assisted Language Teaching in higher education. It examines the various factors and barriers influencing the integration of ChatGPT into teaching practices. This study is framed within Technology Acceptance Model (Davis,1989). TAM encompasses the constructs that this study aims at exploring: Perceived usefulness (PU), perceived ease of use (PEU), perceived risk (PR), attitude and actual use (ChatGPT practices). An online questionnaire was administered to 50 professors in different Moroccan universities. Descriptive statistics show that most professors hold favorable perceptions of integrating ChatGPT in teaching practices. Notably, key barriers to ChatGPT adoption include ethical concerns, lack of training, and insufficient AI knowledge. Correlational analysis shows that PU and PEU significantly influence the actual use of ChatGPT. In contrast, there is no significant correlation between perceived risk and use. This study suggests that offering AI-training programs could enhance the integration of ChatGPT in Moroccan academia.

Evaluation of Entrustable Professional Activities Implemented in Australian General Surgical Training: Perspectives of Surgeons and Trainees.

Performance and mechanism of double S-scheme FeOOH/TiO2/g-C3N4 heterojunction for acetochlor degradation under visible-light-driven photo-Fenton.

A Novel Radiation Shield for Interventional Echocardiographers With Application During Structural Heart Disease Procedures.

The increasing rate of home ownership in Indonesia has created a growing demand for construction services that are transparent, efficient, and reliable, posing challenges for consumers in finding skilled workers. This study formulates the problem of how perceived usefulness and perceived ease of use, facilitated by Machine Learning-based features, influence user acceptance of the Kanggo application. The objective is to analyze the effects of Perceived Ease of Use and Perceived Usefulness on attitude, intention, and actual use within the framework of the Technology Acceptance Model (TAM). A quantitative method employing Partial Least Squares Structural Equation Modeling (PLS-SEM) was applied to survey data from Kanggo users. The findings reveal that all hypotheses are supported, with significant relationships among latent variables, confirming that ease of use and perceived benefits drive user intention and actual application usage. Recommendations include strengthening recommendation and price prediction features to enhance user adoption.

Purpose: This study analyzes the acceptance of telehealth among health workers at Gondangrejo Community Health Center, Indonesia, and at Sentro De Saude Becora Timor Leste, as a digital health strategy. Methods: This study employed an analytical observational research design with a cross-sectional approach using the Technology Acceptance Model questionnaire. The sample in this study comprised 30 health workers from the Gondangrejo Health Center in Indonesia and the Sentro De Saude Becora in Timor Leste. Data analysis and statistical tests used Pearson correlation. Results: There was a positive and significant relationship between perceived ease of use and perceived usefulness (p-value < 0.001; r=0.972), perceived usefulness and attitude toward using (p-value=0.015; r=0.359), perceived ease of use and attitude toward using (p-value=0.042; r=0.305), attitude toward using and behavioral intention to use (p-value < 0.001; r = 0.888), perceived usefulness and behavioral intention to use (p-value < 0.016; r=0.356), behavioral intention to use and actual system use (p-value < 0.022; r=0.342). Conclusion: Acceptance of telehealth by healthcare workers is influenced by perceived usefulness, perceived ease of use, attitude toward using, behavioral intention to use, and actual system use.

Background In Nepal, sexual relationships outside of the traditional arranged marital system are increasingly common. Despite the availability of modern sexual health care, research on how to effectively deliver sexual health services to unmarried young adults in Nepal is limited. Objective This study examined key theoretical correlates between Andersen's Behavioral Model of Health Service Use and actual sexual health service use among unmarried young adults (aged 18 to 25) in Kathmandu, Nepal. Methods Unmarried young adults between 18 and 25 were recruited from colleges and universities in the Kathmandu area. A total of 110 women and 93 men completed the survey ( n = 203). Using a cross-sectional correlational design, the analysis involved descriptive statistics, bivariate analysis, and logistic regression. Findings and conclusions Approximately 37% of participants reported engaging in sexual intercourse, with 55.7% reporting condom use during most recent intercourse. Less than half (39.1%) were aware of available sexual health services, and less than one-third (26.6%) were aware of Human Papillomavirus (HPV). Over a third of participants (40.9%) reported experiencing unwanted sexual contact, and 5.9% had a history of forced sexual intercourse. The actual reported sexual health service use within the past 12 months was 13.9%. Logistic regression analyses showed higher perceived youth friendliness of the health system (OR: 1.19; CI: 1.01–1.39; p < .05), sexual attraction to the same or both sexes (OR: 2.91; 95%; CI: 1.54–5.50; p < .01), higher perceived sexual risk (OR: 1.33; 95%; CI: 1.11–1.59; p < .01), as well as prior health awareness and behaviors (e.g., cigarette consumption, dating app use), were statistically significant correlates of sexual health service use. These findings indicate a need for further research to understand the experiences of Nepalese young adults with sexual healthcare and essential elements of youth-friendly health systems.

The use of Islamic mobile banking apps is still not optimal, even though people’s interest in digital finance is growing. This study examines how social influence, enjoyment (hedonic motivation), and user habits shape people’s intention to use these apps, and how that intention affects actual usage. It also tests whether word of mouth (WOM) strengthens the link between intention and behavior. Using a quantitative approach, the study surveyed 105 active BYOND BSI users in Padang City through purposive sampling. Data were analyzed with the PLS-SEM method using SmartPLS 4.0 and bootstrapping with 5,000 samples to ensure reliable results. The findings show that enjoyment and habit strongly affect intention, and intention significantly impacts actual use. However, social influence has no significant effect on intention, and WOM does not moderate the relationship between intention and use. Moreover, intention mediates the effects of enjoyment and habit on use but not that of social influence. Overall, the results highlight that users’ positive experiences and consistent habits are key drivers behind their intention and actual use of Islamic mobile banking services.