Autonomous Decision Research Articles

How Do Nurses Decide on Missed Nursing Care? A Grounded Theory Study of Grassroots Arrangement of Nursing Care.

To explore the complete decision-making process and action logic of nurses making autonomous decisions that result in missed nursing care. The complex characteristics of patients in Intensive Care Units place higher demands on the allocation of nursing resources, as well as on the professional skills, resilience and ethics of nursing staff. Preventing missed nursing care is particularly crucial in Intensive Care Units. A theory construction qualitative study using grounded theory. Semistructured face-to-face interviews were conducted with 20 nurses, including three head nurses and 17 bedside nurses. Head nurses provided insights into counselling and management practices. The theoretical model of nurses' decision-making processes comprise four strategies: setting priorities, seeking help, delaying nursing care and omitting nursing care. The latter two constitute missed nursing care. Inadequate staffing, task urgency and negative emotions can lead to omitting nursing care. This study proposes an original concept: grassroots arrangement of nursing care (GANC). Grassroots arrangement of nursing care includes the autonomous and adaptive decision-making process used by bedside nurses to optimise workflow in busy environments. It includes specific strategies and quality implications, enabling a nuanced balance between limited nursing resources, increasing patient needs and maintaining the best possible quality of care. Nursing managers should consider the dual aspects of grassroots arrangement of nursing care, support nurses' grassroots autonomy and streamline decision-making processes. This study follows the Consolidated Criteria for Reporting Qualitative Studies (COREQ). No patient or public contribution.

Understanding barriers to young people’s utilisation of sexual and reproductive health services in Asia-Pacific countries: a qualitative systematic review and thematic synthesis

IntroductionBased on the United Nations’ sustainable development goals, universal access to sexual and reproductive health (SRH) services should be attained by 2030. Yet, large inequalities in adolescent SRH knowledge and...

The Effect of Offspring Gender Composition on Modern Contraceptive Uptake Among Married Women of Reproductive Age in Pakistan: A Facility-Based Cross-Sectional Study.

Introduction: Pakistan is confronted with the formidable challenge of high population growth, which is compounded by cultural norms that prioritize male offspring, leading to adverse implications for family planning efforts and demographic trends. Despite efforts to promote contraception, including a national family planning program, Pakistan continues to struggle with low and stagnant contraceptive prevalence rates among married women. The influence of gender composition on modern contraceptive uptake remains underexplored, necessitating research to elucidate its impact on reproductive behavior. Materials and methods: This study used the dataset of a facility-based cross-sectional survey conducted in six districts of the Sindh and Punjab provinces in Pakistan. A subset of 495 married women of reproductive age seeking health services from March to June 2019 was used for this study. Logistic regression analysis was employed to examine the association between the gender composition of children and modern contraceptive uptake, adjusting for covariates such as province, the age of the women, and the type of health facility. Results: The analysis revealed a significant association between the gender composition of children and modern contraceptive uptake among married women. As the number of daughters increased without sons, the likelihood of contraceptive uptake remained low (adjusted odds ratio [AOR]: 0.12; 95% CI: 0.04-0.34; p < 0.000), while having at least one son substantially increased the odds of contraceptive use (AOR: 19.91; 95% CI: 8.00-49.50; p < 0.000). Notably, the gender composition of having one daughter with two sons had the highest level of contraceptive uptake, potentially because of family composition preferences. Discussion: The findings highlight the pervasive influence of gender composition on reproductive decision-making in Pakistan, with a clear preference for sons driving modern contraceptive behavior. These results underscore the need for targeted interventions to address gender norms and biases while promoting equitable access to family planning services. Engaging men in family planning initiatives is crucial for challenging traditional gender norms and fostering informed decision-making regarding contraception. Conclusions: Gender preference influences modern contraceptive uptake among women in Pakistan, with the strong preference for sons driving reproductive behavior. Addressing gender norms and biases while promoting informed, self-determined choice is essential for enhancing modern contraceptive uptake and achieving sustainable population growth. Targeted interventions, including male engagement strategies, are needed to challenge societal gender norms and empower individuals to make autonomous decisions regarding family planning.

The Application Potential of Microelectronic Processing and Integrated Circuit in Mechanical Design

The rapid development of microelectronic processing has not only fostered its interdisciplinary fusion with mechanical design. With the introduction of microelectronic processing, the precise control capabilities of mechanical systems have been significantly bolstered, and the energy consumption of machinery and equipment was also optimized, which has led to an increasingly high degree of automation, allowing for the execution of complex tasks and autonomous decision-making. Additionally, as both technologies continue to evolve towards smaller scales, their application scope is expanding, including Micro Electro Mechanical System (MEMS), sensors, etc. This paper explores the application of microelectronic processing and integrated circuits in mechanical design, elucidating how advancements in microelectronics enhance the automation and intelligence of mechanical equipment. Furthermore, with the rise of nanotechnology, the paper discusses new applications of microelectronic processing in mechanical design fields such as automation control systems, sensors, and embedded systems. Meanwhile, the cost reduction and standardization of integrated circuits have boosted their popularity in a wider range of fields

Small firms’ motivations in offering apprenticeship training in Switzerland

ABSTRACT This paper aims to determine what motivates small firms to offer apprenticeship training. The current state of research provides various indications. While research focusing on the specificity of small firms identifies the important role of the owner and their personality, values, attitudes and experiences, economic research mainly refers to the explanatory factor of profitable cost-benefit relationships in apprenticeship training. Finally, research on the institutional embeddedness of firms points to the importance of institutional framework conditions. Our contribution links these three usually unrelated research perspectives and focuses on Switzerland as a collective skill formation system. We asked heads (owners, managers, or other collaborators) of small firms who make autonomous decisions regarding personnel and budget issues about their motivations in offering apprenticeship training using qualitative interviews. The results show that, at the individual, organisational, and societal levels, different motivations influence the provision of training positions. Furthermore, within small companies, we identified heterogeneous motivational configurations. In conclusion, if the participation of small firms in the provision of apprenticeship places is to be promoted, their heterogeneity and motivations in doing so must be addressed at various levels.

EXPRESS: Quality, Necessity, or Accessibility? Impact of Dockless Bike Sharing on Ineffective Use of Medical Resources

In recent years, patients have increasing autonomy in medical decision-making. With great autonomy in selecting medical institutions, patients with low-risk diseases (LRD) may opt for treatment in prestigious hospitals, which limits the access of patients with high-risk diseases (HRD) to these hospitals. Moreover, due to limited medical knowledge and a fear of uncertainty regarding diseases, patients with greater medical autonomy may request various unnecessary medical tests to alleviate their health-related anxiety. This study takes a novel patients’ perspective to investigate how dockless bike sharing, which addresses the “last-mile problem” and improves geographical accessibility to medical institutions, affects two types of ineffective use of medical resources: disease-institution mismatch and overuse of medical tests. By introducing the concept of quality-accessibility trade-off in patients’ decision-making processes, we shed light on the psychological mechanism underlying the effect of dockless bike sharing on patients’ medical institution choices. We also introduce a new concept, perceived necessity of medical tests, to explain how dockless bike sharing reduces unnecessary medical tests. In Study 1, we designed a quasi-experiment and applied a difference-in-differences model based on real-world electronic health record data to show that dockless bike sharing increased the likelihood of patients choosing hospitals over clinics and decreased the number of unnecessary medical tests. In Studies 2a, 2b, 3a, and 3b, four randomized controlled experiments were employed to replicate the findings and reveal the underlying mechanisms. In sum, we found that dockless bike sharing acted as a “double-edged sword” in terms of its impact on exacerbating disease-institution mismatch and alleviating the overuse of medical tests. This study makes significant theoretical contributions to the Operations Management (OM), sharing economy, and medical resource management literature. It also offers important managerial insights for governments, shared mobility platforms, and healthcare providers.

Understanding Agentic Frameworks in AI Development: A Technical Analysis

This technical article examines the evolution and implementation of agentic frameworks in artificial intelligence development, focusing on their transformative impact across multiple industries. The article explores the fundamental architectural components, implementation methodologies, and practical applications of these frameworks in manufacturing, financial services, and healthcare sectors. By investigating the core components, including perception systems and decision architectures, alongside the Belief-Desire-Intention model and advanced learning mechanisms, this article provides comprehensive insights into how agentic frameworks are revolutionizing autonomous decision-making capabilities. The article also addresses critical technical challenges in scalability and safety while offering potential solutions and future directions for development, highlighting the growing importance of these frameworks in shaping the future of AI technology.

Maritime Autonomous Surface Ships: Architecture for Autonomous Navigation Systems

The development of Maritime Autonomous Surface Ships (MASS) has seen significant advancements in recent years, yet there remains a lack of comprehensive studies that holistically address the architecture of autonomous navigation systems and explain the complexity of their individual elements. This paper aims to bridge this gap by conducting a literature review that consolidates key research in the field and presents a detailed architecture of autonomous navigation systems. The results of this study identify several major clusters essential to MASS navigation architecture, including (1) autonomous navigation architecture, (2) decision-making and action-taking system, (3) situational awareness and associated technologies, (4) sensor fusion technology, (5) collision avoidance subsystems, (6) motion control and path following, and (7) mooring and unmooring. Each cluster is further dissected into sub-clusters, highlighting the intricate and interdependent nature of the components that facilitate autonomous navigation. The implications of this study are vital for multiple stakeholders. Ship captains and seafarers must be prepared for new navigation technologies, while managers and practitioners can use this architecture to better understand and implement these systems. Researchers will find a foundation for future investigations, particularly in filling knowledge gaps related to autonomous ship operations. This study makes a substantial contribution by filling a critical gap in the maritime literature, offering a detailed explanation of the elements within autonomous navigation systems.

Human autonomy with AI in the loop

ABSTRACT In the wake of recent advancements in the field of AI, this paper investigates the impact of recommender systems and generative models on human decisional and creative autonomy. For this purpose, we adopt Dennett’s conception of autonomy as self-control. We show that recommender systems can play a double role in relation to decisional autonomy: as information filter, they can augment self-control in decision-making, but also act as mechanisms of remote control that clamp degrees of freedom. As for generative models in AI, we show that they can be seen as a powerful system of selection and suggestion (similar to standard recommender systems) but also as an instrument for information production. We suggest that the latter perspective opens new possibilities in terms of creative autonomy. Additionally, for both systems we propose a distinction between “extrinsic” and “intrinsic” mechanisms and effects. Through Dennett’s theory of self-control, this paper offers new insights into the relation between AI and human autonomy by framing it in terms of remote or self-control and by addressing the impact of generative models on creative autonomy.

Truth-telling, and ethical considerations in terminal care: an Eastern perspective.

Truth-telling for terminally ill patients is a challenging ethical and social issue for Chinese health care professionals. However, despite the existence of ethical and moral standards for nurses, they frequently encounter moral dilemmas when making decisions about truth-telling to patients with end-stage diseases in China. This article aims to provide ethical strategies for clinical nurses in China regarding truth-telling decisions for terminally ill patients on the basis of their individual autonomy. This article first presents a common case scenario in China and then critically discusses ethical issues related to ethical principles and philosophical theories. The aim is to provide the much needed strategy for truth-telling for nurses who are terminally ill rather than to focus on attitudes toward disclosure. This article focuses on nursing morality, ethics, norms, and philosophy in health care and discusses countermeasures taken by nurses in truth-telling decision-making in combination with Chinese Confucian culture. The analysis identifies key ethical strategies tailored to Chinese nurses' practices, emphasizing individual autonomy, cultural sensitivity, and family dynamics in truth-telling decisions. The complexity of end-of-life illness requires Chinese nurses to strengthen the communication training needed to deliver bad news, as well as critical and autonomous thinking and good communication skills when implementing patient- and family-centered care, to achieve true delivery of bad news, thereby increasing patient autonomy and promoting more successful collaboration among patients, families, and providers. To improve the quality of care. Chinese nurses should integrate ethical principles with Confucian values to enhance patient-centered communication, respecting autonomy while adapting to cultural nuances in end-of-life care.

Exploring Socio-Cultural Determinants of Female Suicides: A Qualitative Study of Gahkuch, Gilgit-Baltistan

This qualitative ethnographic study investigates the socio-cultural determinants of female suicides in Gahkuch, District Ghizer, Gilgit-Baltistan, where alarming rates of such incidents have been reported. The research aims to uncover the perceptions of the community, and affected families regarding the underlying causes of female suicides, while exploring the broader socio-cultural and psychological contexts. Data were collected through purposive sampling, employing in-depth interviews with diverse participants, including relatives of victims, community members, land alongside direct observations. Thematic analysis of the data reveals that patriarchal norms, restricted decision-making autonomy for women, domestic violence, forced marriages, and societal rejection of personal choices are pivotal factors driving women toward suicide. Additional determinants include the unavailability of ideal life partners, marital conflicts, societal pressure to conform to traditional roles, and the stigma attached to non-conventional behavior, such as pursuing love marriages or modern lifestyles. The study also identifies cases of honor killings misrepresented as suicides due to societal taboos around disclosing the true causes of death. Psychological stressors, compounded by inadequate acknowledgment of women’s contributions to households and society, were found to exacerbate vulnerabilities. Unique local factors, such as the misuse of technology, excessive salt consumption linked to aggressive behavior, and limited mental health support, were also highlighted as contributing elements. The study concludes that Gahkuch’s traditional and patriarchal social structure, despite progress in education and empowerment, perpetuates systemic inequalities and cultural restrictions that leave women vulnerable. To address these issues, the research emphasizes the need for societal reforms, enhanced religious and mental health awareness, and initiatives promoting gender equality and female empowerment. It further advocates for targeted interventions, including community-based awareness campaigns, institutional mechanisms for addressing domestic violence, and the inclusion of women in decision-making processes, to mitigate the factors leading to female suicides and create a more inclusive and supportive environment for women in the region.

Managing complexity in cross-cohort classrooms: strategies for effective implementation of real-life projects

IntroductionReal-life project-based courses aim to enhance student learning by integrating authentic projects into the curriculum. However, the complexity of these projects, due to their VUCA (Volatile, Uncertain, Complex, and Ambiguous) nature, can pose significant challenges, especially for students new to the concepts and skills being taught. This study addresses the overarching question: “How can a systematic model be developed and implemented to effectively manage teaching and learning through developing a real-life project in a hybrid cross-cohort environment?”.MethodsThe study was conducted within an Instructional Systems Design (ISD) course in a hybrid cross-cohort class structure. A diverse class of 27 students with varying backgrounds participated in the course. Data were collected through surveys, interviews, and instructor observations. The implementation process involved multiple student cohorts, primary stakeholders of the project, subject matter experts, and instructors.ResultsThe study resulted in the development of the proposed 3 Square model to manage hybrid cross-cohort learning environments. Students engaged in developing a real-life project—a public awareness website for Persons with Disabilities (PwD) in a university environment. They navigated the complexities of coordinating within a cross-cohort classroom and developed critical skills such as autonomous decision-making and effective communication. Outcomes included efficient time management, achievement of project objectives, and tangible learning outcomes such as mastering ISD topics, using new tools, and working collaboratively in a group.DiscussionThe findings highlight the importance of leveraging diverse student knowledge and experience to manage challenges in cross-cohort classrooms for complex projects. Practical implications are discussed for instructional design and teaching strategies in diverse educational settings, emphasizing the need for systematic approaches to facilitate real-life problem-based learning tasks.ConclusionThis study provides a retrospective evolution of a systematic model for hybrid cross-cohort learning environments. It identifies teaching-learning challenges, determines appropriate instructional strategies, and evaluates the effectiveness of solutions in facilitating real-life project-based learning. The insights gained contribute to managing diverse educational settings and enhancing instructional design practices.

Decoding fertility behaviour of married women in Zambia: A multipronged analysis of bio-demographic, socio-economic and intermediate factors.

Despite national efforts and a decrease in total fertility rate, Zambia's fertility remains high compared to global and regional averages. While previous research has examined the influence of bio-demographic and socio-economic factors, it has neglected the role of overlooked intermediate variables such as age at first marriage, contraception use, and abortion. This study investigated the influence of these variables, while controlling for bio-demographic and socio-economic factors, on women's fertility behaviour in Zambia. The study drew upon data from three cross-sectional Zambia Demographic Health Surveys (2007, 2013-14, 2018) to investigate fertility behaviour among 18,299 married women, measured by the number of children ever born (CEB). Descriptive and inferential statistical analyses, including Analysis of Variance and Negative Binomial regression, were conducted using Stata 14.2 to identify factors associated with women's fertility behaviour. The regression results are presented as adjusted incidence rate ratios with confidence intervals. Married Zambian women's fertility behaviours, as measured by CEB are concerning, and exhibit patterns influenced by intermediate factors like age at first marriage and abortion. Early marriage, specifically before the age of 18, is associated with higher likelihood of having more CEB than those who married at 18 years or above (AIRR = 1.10, 95% CI: 1.07-1.14 in 2007; AIRR = 1.10, 95% CI: 1.10-1.12 in 2013; and AIRR = 1.07, 95% CI: 1.05-1.10). Conversely, married women who reported having had an abortion were more likely to have fewer CEB. In 2018, women with a history of abortion had lower likelihood of higher CEB compared to those without (AIRR = 0.94, 95% CI: 0.91-0.97). Besides, demographic and socio-economic factors such as age, education level, geographic location, and decision-making autonomy were found to significantly impact women's fertility behaviour. This study shows that the two intermediate variables of age at first marriage and a history of prior abortion are more influential on women fertility behaviour than contraception among married women in Zambia. To effectively address stalled fertility and improve women's reproductive health, policies should address early marriage, enhance access to sexual reproductive healthcare, and empower women to enable them make informed reproductive decision-making.

Parametric modeling of under-5 children survival among 30 African countries: Lognormal accelerated failure time gamma shared frailty model.

Under-five mortality continues to be a serious public health concern in low-and middle-income countries, particularly in Africa. This study investigates the probability of under-five survival and its predictors of mortality in the African continent using a recent demographic health survey from 2014-2022. This study utilized recent Demographic and Health Survey data from 30 African countries, encompassing 226,862 live births. This study employed a multivariable lognormal accelerated failure time gamma shared frailty parametric survival regression analysis to identify the predictors of time-to-death among under-five children in these African nations. The overall under-five child mortality rate in Africa was 37.55 per 1,000 live births (95% CI: 37.35, 37.74. In this study, children born in Western Africa; children born in Eastern Africa; children born to mothers aged 15-19 years; maternal educational status; maternal decision autonomy; being female; place of delivery; number of ANC visits; children born among mothers who delivered by Cesarean section; mothers who have multiple birth outcome; children who were second birth order; and third birth order and third birth order; children who were small in size at birth; children who were born from a community with a low women education; having poor wealth index; respondents working; mothers delivered at the age between 20-35 were significant predictors of survival time to event of under-five children in Africa. This study found that the overall under-five mortality rates remain high across Africa. In this study country region, maternal age, maternal education status, maternal age at first birth, respondent's employment status, birth outcome, wealth index, birth order, place of delivery, mode of delivery, women's autonomy in healthcare decision-making, number of antenatal care visits, child's size at birth, sex of the neonate, and community-level women's education were found to be significant predictors of survival time to death of under-five children. Addressing these multilevel factors is crucial for developing targeted interventions to reduce under-five mortality further and improve child survival in African countries.

Reproductive health care seeking behavior in Bangladesh: Asystematic literature review.

Maternal health, in terms of pregnancy and childbirth, is an important aspect of women's reproductive health and remains a public health concern in underdeveloped countries of the world. Reproductive health care seeking behavior (RHSB), in both men and women in society, is influenced by a variety of social and environmental factors that needs to be summarized. This review aims to enhance understanding and perception of services in relation to RHSBs in several domains such as antenatal care (ANC), delivery care, postnatal care (PNC), and family planning (FP) services, for married women of reproductive age in Bangladesh. In major databases, for example, Medline, Ovid, PubMed, Web of Science, ProQuest and Google Scholar following keywords, timeline set as 2010 up to December 30, 2022. Articles that included discussion on married women of reproductive age, and their type of care seeking behavior for reproductive health. A systematic literature search was carried out and expected outcome was health care seeking behavior in the aspects of ANC, delivery care, PNC, and FP services. A data extraction form and quality appraisal form were used for data on RHSB of married women of the reproductive age group in Bangladesh and associated factors. A total of 245 articles were retrieved from databases; stepwise screening was done and finally 23 full-text articles were included for analysis. Descriptive statistics were used based on the included articles for narrative synthesis. In the selected articles, 17 (73.91%) were cross-sectional studies and more than half discussed both urban and rural women. Ante- and postnatal visits have proven to have positively influenced overall RHSB, as seen in Bangladesh. Grass root level workers play a major role in upgrading RHSB in women. Many factors limit rural access to mother and child health services including distance of the health facility and cost of the health service. In particular, education level, women's autonomy in family decision making and distance from health service can be considered as factors influencing RHSBs in Bangladesh. Exposure to mass media and TV watching are likely to positively impact RHSB patterns for women in Bangladesh.

Machine Learning in Drones for Enhancing Autonomous Flight and Decision-Making

Machine Learning in Drones for Enhancing Autonomous Flight and Decision-Making

Protection of the elderly patient and preservation of decision-making autonomy at the end of life in Belgian law

Protection of the elderly patient and preservation of decision-making autonomy at the end of life in Belgian law

The ethics of using artificial intelligence in medical research

The integration of artificial intelligence (AI) technologies into medical research introduces significant ethical challenges that necessitate the strengthening of ethical frameworks. This review highlights the issues of privacy, bias, accountability, informed consent, and regulatory compliance as central concerns. AI systems, particularly in medical research, may compromise patient data privacy, perpetuate biases if they are trained on nondiverse datasets, and obscure accountability owing to their “black box” nature. Furthermore, the complexity of the role of AI may affect patients’ informed consent, as they may not fully grasp the extent of AI involvement in their care. Compliance with regulations such as the Health Insurance Portability and Accountability Act and General Data Protection Regulation is essential, as they address liability in cases of AI errors. This review advocates a balanced approach to AI autonomy in clinical decisions, the rigorous validation of AI systems, ongoing monitoring, and robust data governance. Engaging diverse stakeholders is crucial for aligning AI development with ethical norms and addressing practical clinical needs. Ultimately, the proactive management of AI’s ethical implications is vital to ensure that its integration into healthcare improves patient outcomes without compromising ethical integrity.

Artificial Intelligence and Machine Learning Driven Adaptive Control Applications

This article explores the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in enhancing adaptive control systems across various industries. Adaptive control systems adjust their parameters in real-time to maintain optimal performance in dynamic environments, and the integration of AI and ML significantly improves their effectiveness. AI enables these systems to learn, recognize patterns, and make autonomous decisions, while ML algorithms allow adaptive controllers to generalize from data, enhancing performance through techniques such as supervised, reinforcement, and unsupervised learning. Applications in autonomous vehicles, industrial process control, and aerospace illustrate the impact of AI and ML on adaptive control. Despite challenges such as computational demands, safety concerns, and regulatory hurdles, the future of adaptive control will be shaped by advances in AI and ML technologies, driving innovations in automation, precision, and reliability across diverse sectors.

Advancements in mobile AI: A machine learning-driven approach to enhance user experience and functionality

Artificial intelligence (AI) and mobile technology have synergized to achieve remarkable advancements across various sectors, transforming user interactions and significantly boosting mobile device performance. This study examines how integrating machine learning (ML) techniques into mobile applications enhances user satisfaction, productivity, and security. By deploying predictive models and real-time analysis directly on mobile devices, our approach reduces latency and personalizes experiences to better adapt to user behavior. Key findings reveal that the Hybrid CNN-LSTM model achieves superior accuracy (93.8%), precision (92.1%), and F1-score (91.5%) compared to standalone CNN or LSTM models, with a manageable latency of 140 ms, making it optimal for tasks requiring both image and sequential data processing. Additionally, applying optimization techniques like knowledge distillation reduces model size by 40% and latency by 25%, enhancing device efficiency without compromising performance. This study confirms that mobile-based AI equipped with advanced, autonomous decision-making capabilities enhances user-centric services and application responsiveness. Through experimental evaluations, this paper underscores the transformative impact of ML on mobile technology and proposes strategies to further integrate AI into the mobile ecosystem.