Search Results (61)

Burnout syndrome is characterized mainly by three criteria (emotional exhaustion, depersonalization, and low personal accomplishment), and further exacerbated by night shift work, with profound implications for individual and societal well-being. The Maslach Burnout Inventory survey applied to 97 medical care professionals (with day and night work) revealed different scores for these criteria. Blood metabolic profiles were obtained by UHPLC-QTOF-ESI⁺-MS untargeted metabolomics and multivariate statistics using the Metaboanalyst 6.0 platform. The Partial Least Squares Discrimination scores and VIP values, Random Forest graphs, and Heatmaps, based on 99 identified metabolites, were complemented with Biomarker Analysis (AUC ranking) and Pathway Analysis of metabolic networks. The data obtained reflected the biochemical implications of night shift work and correlated with each criterion’s burnout scores. Four main metabolic pathways with important consequences in burnout were affected, namely lipid metabolism, especially steroid hormone synthesis and cortisol, the energetic mitochondrial metabolism involving acylated carnitines, fatty acids, and phospholipids as well polar metabolites’ metabolism, e.g., catecholamines (noradrenaline, acetyl serotonin), and some amino acids (tryptophan, tyrosine, aspartate, arginine, valine, lysine). These metabolic profiles suggest potential strategies for managing burnout levels in healthcare professionals, based on validated criteria, including night shift work management. Full article

Background: Occupational burnout and fatigue are critical issues affecting the health and performance of healthcare workers (HCWs) globally. These outcomes are often driven by complex and overlapping work-related stressors, which remain insufficiently understood in combination. Objective: To investigate the associations of multiple work-related stressors with occupational burnout and fatigue, and to identify distinct stress patterns and critical stressors among HCWs. Method: A cross-sectional survey was conducted using a self-administered electronic questionnaire among 2695 HCWs in Shanghai, China. Validated questionnaire scales were used to assess work-related stress (self-developed occupational stress scale for medical staff, CSSM), occupational burnout (Maslach Burnout Inventory–General Survey, MBI-GS), and fatigue (Fatigue Scale-14, FS-14). Latent profile analysis (LPA) was employed to identify distinct work-related stress patterns. Generalized linear models (GLMs) were used to explore the associations between individual stressors, stress patterns, and occupational burnout and fatigue. Additionally, weighted quantile sum (WQS) models were utilized to evaluate the combined effects of multiple stressors and identify the main contributors. Results: In this study, 77.0% and 71.2% of participants were classified as experiencing occupational burnout and fatigue, respectively. A strained doctor–patient relationship was the highest-rated work-related stressor. All work-related stressors, including career development, interpersonal relationships, work–life imbalance, physical environment, doctor–patient relationship, social environment, and workload, were significantly associated with burnout (β: 0.444~0.956, p < 0.001) and fatigue (β: 1.384~3.404, p < 0.001). WQS assigned higher weights to career development and workload for burnout, and to workload and work–life imbalance for fatigue. LPA identified two distinct occupational stress patterns. HCWs characterized by higher stress levels in physical environment, career development, workload, and interpersonal relationships exhibited significantly higher burnout scores (β = 0.325, 95% CI: 0.122, 0.528), particularly in the reduced personal accomplishment (PA) dimension (β = 1.003, 95% CI: 0.746, 1.259). Conclusions: This study highlighted the high prevalence of occupational burnout and fatigue among HCWs in Shanghai, China. Occupational stressors were associated with both burnout and fatigue, with higher workload, work–life imbalance, and poorer career development showing particularly significant contributions. These findings emphasized the urgent need for targeted interventions, including workload management, career development programs, and mental health support, to reduce occupational stress and mitigate its adverse effects on HCWs. Full article

Background/Objectives: Burnout and anger are prevalent among healthcare professionals in high-stress environments, particularly in addiction services. This study explores the relationship between burnout and anger among 124 operators working in public addiction services (SERD) in Calabria and Sicily. The objective is to assess how different anger dimensions contribute to burnout and identify protective factors that could inform targeted interventions. Methods: The sample consisted of 58 men and 66 women, with a mean age of 39.2 years (SD = 9.8), ranging from 25 to 59 years old. Burnout was measured using the Maslach Burnout Inventory (MBI), assessing emotional exhaustion, depersonalization, and personal accomplishment. Anger was evaluated through the State-Trait Anger Expression Inventory-2 (STAXI-2), examining trait anger, state anger, anger expression (anger-in, anger-out), and anger control. A cross-sectional design was used, with correlation and regression analyses controlling for gender and years of service. Results: High levels of burnout, particularly emotional exhaustion and depersonalization, were found. Emotional exhaustion correlated strongly with trait anger, indicating that individuals with a chronic predisposition to anger are more vulnerable to burnout. Suppression of anger (anger-in) significantly predicted depersonalization, exacerbating emotional disengagement from patients. Conversely, anger control acted as a protective factor, helping maintain a sense of personal accomplishment. Conclusions: These findings underscore the importance of emotional regulation in mitigating burnout among addiction service workers. Interventions such as emotional regulation training and anger management programs could help reduce psychological distress and promote resilience. Workplace strategies that support emotional well-being may improve both staff retention and patient care quality. Further research should explore longitudinal trends and intervention effectiveness. Full article

The application of Artificial Intelligence and Machine Learning in the supply chain fields is significantly changing the way businesses manage their operations, forecast their demand, manage their inventory, optimize their logistics, and increase their level of resilience. This research explores, through a bibliometric literature review, how the integration of these technologies can support the implementation of a demand-driven supply chain approach in the global healthcare and pharmaceutical supply chains, which are facing remarkable challenges in ensuring demand-driven operations, especially in light of sudden disruptions such as the COVID-19 pandemic. Full article

Introduction—Aim: Agitation and aggression are common symptoms in people with Alzheimer’s disease and other dementias. This systematic review outlines the current evidence for the effect of antidementia treatments on agitation and aggression in patients with Alzheimer’s disease. Methods: The literature search was performed by manually checking articles published since 2000 in the following databases: PubMed, ResearchGate, and Google Scholar, following the PRISMA guidelines. Results: Nineteen double blinded placebo-controlled trials were included. Treatment with galantamine seems to provide more credible evidence for treating or preventing agitation/aggression. Studies on memantine often presented with an improvement of the neuropsychiatric inventory but not specifically on agitation/aggression. The trials on donepezil and rivastigmine either did not include enough information on agitation/aggression or did not provide compelling results. The incidence of agitation as an adverse event was not higher in antidementia treatments compared to placebo. Conclusions: Agitation and aggression are common symptoms of Alzheimer’s disease and have a significant impact on the patient, caregiver, and the broader healthcare system. The current literature lacks robust evidence on which of the antidementia treatments could be used to manage or prevent agitation and aggression in Alzheimer’s disease. In most included studies, no specific scores that assess those symptoms were used. Future research that specifically focuses on different disease phenotypes and behavioral profiles to enhance and facilitate the management of these symptoms is needed. Full article

Background/Objectives: There is a significant gap in accessibility to mental healthcare in Canada. This study aims to examine the population of Canadian crisis hotline responders and investigate the variables that contributed to burnout and professional quality of life during COVID-19. Crisis hotline responders are hypothesized to be affected by burnout and poor professional quality of life, due to the inherent nature of the job and the widespread negative mental health effects of COVID-19, which are expected to continue even after the pandemic. Methods: An online, cross-sectional, mixed-methods survey assessed sociodemographic information, shift-related variables, burnout and related factors, and current support methods utilized by crisis hotline responders across Canada. The open-ended questions helped to more personally reflect participants’ experiences. Data were analyzed using chi-square tests, an analysis of variance, and a regression analysis. Results: The survey was completed by 136 participants (78.7% female) with an average age of 39.68. Participants reported relatively high levels of burnout/stress on both the Copenhagen Burnout Inventory and professional quality of life survey. Younger age, less work experience, and working overnight shifts emerged as possible predictors of worse mental wellbeing. Conclusions: Findings suggest that Canadian crisis hotline responders require greater support to manage workplace burnout/stress. Nevertheless, conducting comprehensive studies during times when there are no public health emergencies are warranted to understand the full scope of burnout in this population. We offer five recommendations to support the mental wellbeing of responders and improve access to this important public health resource. Full article

Barcode technology plays a crucial role in automatic identification and data acquisition systems, with extensive applications in retail, warehousing, healthcare, and industrial automation. However, barcode images often suffer from blurriness due to lighting conditions, camera quality, motion blur, and noise, adversely affecting their readability and system performance. This paper proposes a multi-scale real-time deblurring method based on edge feature guidance. Our designed multi-scale deblurring network integrates an edge feature fusion module (EFFM) to restore image edges better. Additionally, we introduce a feature filtering mechanism (FFM), which effectively suppresses noise interference by precisely filtering and enhancing critical signal features. Moreover, by incorporating wavelet reconstruction loss, the method significantly improves the restoration of details and textures. Extensive experiments on various barcode datasets demonstrate that our method significantly enhances barcode clarity and scanning accuracy, especially in noisy environments. Furthermore, our algorithm ensures robustness and real-time performance. The research results indicate that our method holds significant promise for enhancing barcode image processing, with potential applications in retail, logistics, inventory management, and industrial automation. Full article

Healthcare professionals in pediatric oncology are at a high risk of burnout. Art therapy is being increasingly recognized as a potential tool for reducing stress and improving emotional well-being. The Art-Out pilot project aimed at nursing staff was initiated in a pediatric oncology unit. The staff members participating in the project were guided in a team-building course integrated with art and clay therapy, aiming to reduce burnout levels, improve emotional climate, and strengthen resilience. Methods: Burnout levels were assessed through the Maslach Burnout Inventory (MBI), alexithymia was measured with the Toronto Alexithymia Scale (TAS-20), and emotional regulation difficulties were evaluated through the Difficulties in Emotion Regulation Scale (DERS); these tests were assessed before (T0) and after (T1) the team-building course (Art-Out project). Results: Data analysis showed a significant reduction in burnout, alexithymia, and emotional dysregulation, highlighting the positive impact of this approach in improving team dynamics and emotional management. Conclusions: Our study confirms the high risk of burnout, alexithymia, and emotional dysregulation among pediatric oncology healthcare workers, underscoring the need for targeted interventions to prevent and mitigate these risks. Full article

Background/Objectives: The integration of Artificial Intelligence (AI) and Machine Learning (ML) in pharmaceutical research and development is transforming the industry by improving efficiency and effectiveness across drug discovery, development, and healthcare delivery. This review explores the diverse applications of AI and ML, emphasizing their role in predictive modeling, drug repurposing, lead optimization, and clinical trials. Additionally, the review highlights AI’s contributions to regulatory compliance, pharmacovigilance, and personalized medicine while addressing ethical and regulatory considerations. Methods: A comprehensive literature review was conducted to assess the impact of AI and ML in various pharmaceutical domains. Research articles, case studies, and industry reports were analyzed to examine AI-driven advancements in predictive modeling, computational chemistry, clinical trials, drug safety, and supply chain management. Results: AI and ML have demonstrated significant advancements in pharmaceutical research, including improved target identification, accelerated drug discovery through generative models, and enhanced structure-based drug design via molecular docking and QSAR modeling. In clinical trials, AI streamlines patient recruitment, predicts trial outcomes, and enables real-time monitoring. AI-driven predictive maintenance, process optimization, and inventory management have enhanced efficiency in pharmaceutical manufacturing and supply chains. Furthermore, AI has revolutionized personalized medicine by enabling precise treatment strategies through genomic data analysis, biomarker discovery, and AI-driven diagnostics. Conclusions: AI and ML are reshaping pharmaceutical research, offering innovative solutions across drug discovery, regulatory compliance, and patient care. The integration of AI enhances treatment outcomes and operational efficiencies while raising ethical and regulatory challenges that require transparent, accountable applications. Future advancements in AI will rely on collaborative efforts to ensure its responsible implementation, ultimately driving the continued transformation of the pharmaceutical sector. Full article

Integrating artificial intelligence (AI) into pharmacy operations and drug discovery represents a groundbreaking milestone in healthcare, offering unparalleled opportunities to revolutionize medication management, accelerate drug development, and deliver truly personalized patient care. This review examines the pivotal impact of AI in critical domains, including drug discovery and development, drug repurposing, clinical trials, and pharmaceutical productivity enhancement. By significantly reducing human workload, improving precision, and shortening timelines, AI empowers the pharmaceutical industry to achieve ambitious objectives efficiently. This study delves into tools and methodologies enabling AI implementation, addressing ongoing challenges such as data privacy, algorithmic transparency, and ethical considerations while proposing actionable strategies to overcome these barriers. Furthermore, it offers insights into the future of AI in pharmacy, highlighting its potential to foster innovation, enhance efficiency, and improve patient outcomes. This research is grounded in a rigorous methodology, employing advanced data collection techniques. A comprehensive literature review was conducted using platforms such as PubMed, Semantic Scholar, and multidisciplinary databases, with AI-driven algorithms refining the retrieval of relevant and up-to-date studies. Systematic data scoping incorporated diverse perspectives from medical, pharmaceutical, and computer science domains, leveraging natural language processing for trend analysis and thematic content coding to identify patterns, challenges, and emerging applications. Modern visualization tools synthesized the findings into explicit graphical representations, offering a comprehensive view of the key role of AI in shaping the future of pharmacy and healthcare. Full article

Chronic pain (CP) is a complex and debilitating condition that significantly impairs quality of life and imposes a high burden on healthcare systems. This study aims to evaluate the impact of telemedicine on chronic pain management in cancer survivors with complex CP. Our multicenter retrospective investigation of cancer survivors with complex CP included 100 patients (median age 65 years, 62% female). Pain, disability, and self-perceived health status were assessed using the Numeric Rating Scale (NRS), Brief Pain Inventory (BPI), Oswestry Disability Index (ODI), and the EuroQolfive-dimension five-level (EQ-5D-5L) questionnaire. The most common diagnoses were neuropathic pain (54%) and complex chronic pain (32%). Significant clinical improvements were observed after six months of telemedicine intervention (all p < 0.001). NRS scores improved by more than four points in 77% of patients, BPI Worst Pain Scores decreased by four points in 52% and by five points in 28% of patients. All patients’ disability levels improved from severe (median ODI score of 52) to moderate (median ODI score of 30). Self-perceived health status improved from 40 to 60 on the EQ-5D-5L scale. Telemedicine interventions significantly reduced pain intensity, decreased disability levels, and enhanced quality of life in chronic pain patients. These findings underscore the transformative potential of telemedicine in chronic pain management and support its broader integration into medical practice. Full article

Background: This study introduces a novel supply chain management (SCM) model tailored for the hospital industry in Thailand. The model emphasises the integration of third-party logistics (3PL) providers to streamline supply-processing-distribution (SPD) functions. By outsourcing non-core activities like SPD to 3PL providers, hospitals can enhance their operational efficiency, allowing healthcare professionals to focus on core tasks and ultimately improving service delivery. Methods: This research employed a dual methodology, combining an analytic hierarchy process (AHP) with a Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS). These approaches evaluated various SCM models based on multiple hospital logistics performance attributes. Results: The AHP results highlighted on-time delivery, patient safety, utilisation rate, and emergency procurement as critical criteria for selecting the optimal model. Fuzzy TOPSIS analysis identified the SCIII: W-G-H model as the most suitable for implementation in Thai hospitals. This model incorporates a centralised warehouse for negotiation leverage, a Group Purchasing Organisation (GPO) for cost efficiency, and regional SPD hubs for effective inventory management and rapid responses to demand fluctuations or emergencies. Conclusions: Adopting this SCM model is expected to significantly enhance supply chain performance, reduce operational costs, and improve the quality and safety of patient care in Thai hospitals. Full article

Acute care provided in the hospital’s emergency department (ED) is a key component of the healthcare system that serves as an essential bridge between outpatient and inpatient care. However, due to the emergency-driven nature of presenting problems and the urgency of care required, the ED is more prone to unintended medication regimen changes than other departments. Ensuring quality use of medicines (QUM), defined as “choosing suitable medicines and using them safely and effectively”, remains a challenge in the ED and hence requires special attention. The role of pharmacists in the ED has evolved considerably, transitioning from traditional inventory management to delivering comprehensive clinical pharmacy services, such as medication reconciliation and review. Emerging roles for ED pharmacists now include medication charting and prescribing and active participation in resuscitation efforts. Additionally, ED pharmacists are involved in research and educational initiatives. However, the ED setting is still facing heightened service demands in terms of the number of patients presenting to EDs and longer ED stays. Addressing these challenges necessitates innovation and reform in ED care to effectively manage the complex, rising demand for ED care and to meet government-imposed service quality indicators. An example is redesigning the medication use process, which could necessitate a shift in skill mix or an expansion of the roles of ED pharmacists, particularly in areas such as medication charting and prescribing. Collaborative efforts between pharmacists and physicians have demonstrated positive outcomes and should thus be adopted as the standard practice in improving the quality use of medicines in the ED. Full article

Background: Anxiety is one of the most frequent disorders during the perinatal stage that is associated with adverse health effects in women and their babies. In spite of this, preventive interventions during this stage are scarce. A long-distance intervention carried out during pregnancy can be an effective and accessible resource to help improve women’s emotional state. The objective of this study is to present and assess the effectiveness of a telepsychology cognitive–behavioral preventive intervention during pregnancy to manage anxiety. Methods: A random clinical trial will be carried out among pregnant women in Spain. The psychological intervention will take place via videoconference in seven weekly sessions, lasting one hour each, with groups of 6–8 pregnant women. Study outcomes will be collected via online questionnaires at five points in time: pre-intervention (baseline: t0), post-intervention (baseline: t1), follow-up at 1 month (t2), follow-up at 3 months (t3) and follow-up at 6 months (t4). The control group will receive usual pregnancy care (attendance at pregnancy follow-up consultations and information and answers to frequently asked questions provided by the midwife). Our primary hypothesis is that the intervention will decrease the frequency of women who present anxious symptomatology during pregnancy. The second objective is to analyze the effectiveness of this intervention to prevent depressive symptomatology during pregnancy, as well as postpartum anxiety and depressive symptomatology. The primary outcome measure is the difference in the mean anxiety score between the intervention and control groups assessed by the Edinburgh Depression Scale-Anxiety Subscale (EDS-3A), the State–Trait Anxiety Inventory (STAI) and Generalized Anxiety Disorder Screener (GAD-7) at the end of the intervention and at 1, 3 and 6 months postpartum. Generalized anxiety disorder (GAD) will be evaluated with the SCID clinical interview at the same time points. The secondary outcome will be determined by using the EPDS at the same time points. Conclusions: The results will determine whether a cognitive behavioral therapy applied via videoconference is well accepted by pregnant women, and if it is effective in preventing anxiety and emotional symptoms during the perinatal stage. If this intervention is an effective and useful resource among pregnant women, it can be implemented as a tool in Spanish healthcare. Full article

Background: Innovation is a crucial issue in healthcare services since it can affect job-related variables such as productivity, satisfaction, and burnout. The aim of our study was to examine the impact of innovation support on quiet quitting, innovative behavior, and innovation outputs among nurses. Methods: We conducted a cross-sectional study in Greece during April 2024. We employed a convenience sample of nurses. We followed the reporting of observational studies in epidemiology (STROBE). We used the following instruments: (a) the innovation support inventory (ISI) to measure innovation support; (b) the quiet quitting scale (QQS) to measure quiet quitting; (c) the innovative behavior inventory (IBI) to measure innovative behavior; and (d) the innovation outputs (IO) scale to measure innovation outputs. Our study questionnaire was anonymous, and nurses gave their informed consent to participate. The Ethics Committee of the Faculty of Nursing, National and Kapodistrian University of Athens, approved our study protocol, while we followed the guidelines of the Declaration of Helsinki. Results: Our study population included 328 nurses with a mean age of 42.3 years (standard deviation: 9.7). Among them, 89.9% were females. Our multivariable analysis identified a negative relationship between innovation support and quiet quitting. Moreover, we found that managerial support and cultural support improved several aspects of innovative behavior, such as idea generation, idea search, idea communication, implementation starting activities, involving others, and overcoming obstacles. Additionally, managerial support improved innovation outputs. Conclusions: Our findings suggested the positive impact of innovation support on quiet quitting, innovative behavior, and innovation outputs among nurses. Organizations and nurses’ managers should establish an innovative working environment to improve nurses’ passion, motives, and productivity. Full article