Search Results (31)

Background/Objectives: This retrospective study evaluated the effectiveness of a two-year online mindfulness program (five biweekly sessions) combined with a smartphone application for healthcare workers (HCWs) in Korean medicine (KM) institutions. Methods: Twenty-three participants, including KM University students, KM doctors, and nurses, completed a 9-week online mindfulness program in 2023 or 2024. The pre- and post-intervention surveys assessed subjective health status (SHS), knowledge of mind–body modalities (MBMs), hwa-byung (HB) symptoms, emotional labor (EL), burnout, and program satisfaction. Results: Participants showed significant improvements in SHS (p = 0.008) and MBM knowledge (p = 0.035). HB personality scores decreased significantly (p = 0.027), while the reduction in HB symptoms approached statistical significance (p = 0.052). The frequency of interactions among job-focused EL increased (p = 0.003). The subgroup analysis revealed significant reductions in HB personality traits (p = 0.017) and symptoms (p = 0.006) among practicing KM doctors and nurses. No significant changes were observed in burnout levels. Participants reported high satisfaction (median 8.00 [IQR 8.0–9.0]) and willingness to recommend the program (median 5.00 [IQR 4.0–5.0]). Conclusions: Analysis of the 2-year results suggests that the online mindfulness program effectively improved SHS, MBM knowledge, and HB-related symptoms among HCWs in KM institutions, particularly among practicing professionals. High satisfaction rates indicated the acceptability of the program. Future research should use larger sample sizes and randomized controlled designs to further validate these findings and explore long-term outcomes. This intervention shows promise as a tool to promote mental health in Korean healthcare settings. Full article

Background: Pain is a complex and challenging phenomenon. People have different pain experiences, but everyone has the right to effective pain management. Pain assessment and management are integral components of a nurse’s role. Aim: To assess the knowledge and attitudes of nurses in Qatar about adult post-operative patients’ pain assessment and management, and the factors that may be associated with such knowledge and attitudes. Methods: Post-operative registered nurses from all peri-operative areas at Hamad Medical Corporation participated in a cross-sectional online survey using a self-administered questionnaire. A knowledge and attitudes (K&A) score was calculated. Associations between K&A and potential explanatory variables were assessed using t-tests and one-way ANOVA. Results: A total of 151 post-operative nurses participated in the study. The mean knowledge and attitudes (K&A) score was 19.6 ± 4.5 out of 41 (48%), indicating a large deficit in nurses’ knowledge and attitudes about adult post-operative pain. There were no statistically significant differences in the mean K&A scores of participants based on gender, nationality, education level, marital status, workplace facility, current job designation, or hours of pain education. Conclusions: There is a significant deficit in post-operative nurses’ knowledge and attitudes about pain across the nursing workforce in post-operative care. Implications for nursing education and policy: Evidence-based, innovative nursing education courses are needed to improve nurses’ knowledge and attitudes about pain assessment and management. Health service policy is required to ensure that evidence-based in-service education on pain management is compulsory for all nurses. This study was not registered. Full article

In the continuously changing labor market, understanding the dynamics of online job postings is crucial for economic and workforce development. With the increasing reliance on Online Job Portals, analyzing online job postings has become an essential tool for capturing real-time labor-market trends. This paper presents a comprehensive methodology for processing online job postings to generate labor-market intelligence. The proposed methodology encompasses data source selection, data extraction, cleansing, normalization, and deduplication procedures. The final step involves information extraction based on employer industry, occupation, workplace, skills, and required experience. We address the key challenges that emerge at each step and discuss how they can be resolved. Our methodology is applied to two use cases: the first focuses on the analysis of the Greek labor market in the tourism industry during the COVID-19 pandemic, revealing shifts in job demands, skill requirements, and employment types. In the second use case, a data-driven ontology is employed to extract skills from job postings using machine learning. The findings highlight that the proposed methodology, utilizing NLP and machine-learning techniques instead of LLMs, can be applied to different labor market-analysis use cases and offer valuable insights for businesses, job seekers, and policymakers. Full article

The current labor market is characterized by drastic changes linked to the use of information and communication technologies (ICT) and post-COVID-19 transformations, which have decreased job security and job stability. As a result, the feeling of losing one’s job has become even more common among European workers. In this study, we aimed to investigate whether and how job insecurity would be related to work–family conflict during the pandemic. Online self-report questionnaires assessing job insecurity, working excessively, techno-overload, and work-to-family conflict were completed by 266 workers from Italy. Descriptive analyses, confirmatory factor analyses, and structural equation mediation models were conducted. Job insecurity was positively associated with work-to-family conflict, both directly and indirectly, as mediated by techno-overload and a tendency to work excessively. This study advances the literature, as it is the first to identify techno-overload and working excessively as parallel psychological mechanisms linking job insecurity to work–family conflict among Italian workers during the pandemic. Workers could benefit from technological workload monitoring programs, techno effectiveness, and time management training programs. Companies could also consider implementing family-friendly and digital disconnection practices. Full article

This study aims to determine the factors influencing the career preparation behavior of nursing students in the post-COVID-19 era and to provide a basis for preparation strategies to enhance nursing students’ nursing professionalism and career preparation behaviors. This is a descriptive cross-sectional study that measures major satisfaction, self-efficacy, nursing image, nursing professionalism, nursing image and intuition, and career preparation to identify factors influencing nursing students’ career preparation behavior in the post-COVID-19 era. An online survey was conducted to collect the data. The data were analyzed using descriptive statistics, Pearson’s correlation, and multiple regression analysis using the SPSS/WIN 25.0 program. A total of 240 students were included; most of them were female (86.3%) and between 21 and 25 years old (80%). The level of motivation to pursue nursing (F = 12.34, p < 0.001) and clinical practice satisfaction (F = 11.37, p < 0.001) showed statistically significant differences in career preparation behavior. Self-efficacy (r = 0.32), major satisfaction (r = 0.32), nursing image (r = 0.32), and nursing professionalism (r = 0.32) were positively correlated with career preparation behavior and significant (p < 0.001). According to the findings, nursing professionalism and image can be enhanced by providing career planning and counseling based on the student’s degree of comprehension and cognitive behaviors to nurture the professional and positive attitudes that are essential for a successful nursing career. Nursing schools need to incorporate a job portal, facilities, and a mentorship program to help nursing students prepare for their careers. Full article

Our cross-sectional study, conducted from October 2022 to January 2023, aims to assess post-COVID job satisfaction, crucial work dimensions, and self-reported factors influencing nursing retention. Using an online survey, we surveyed 2572 nurses in different working fields in Bavaria, Germany. We employed a quantitative analysis, including a multivariable regression, to assess key influence factors on nursing retention. In addition, we evaluated open-ended questions via a template analysis to use in a joint display. In the status quo, 43.2% of nurses were not committed to staying in the profession over the next 12 months. A total of 66.7% of our surveyed nurses were found to be dissatisfied with the (i) time for direct patient care. Sources of dissatisfaction above 50% include (ii) service organization, (iii) documentation, (iv) codetermination, and (v) payment. The qualitative data underline necessary improvements in these areas. Regarding retention factors, we identified that nurses with (i) older age, (ii) living alone, (iii) not working in elder care, (iv) satisfactory working hours, (v) satisfactory career choice, (vi) career opportunities, (vii) satisfactory payment, and (viii) adequate working and rest times are more likely to remain in the profession. Conversely, dissatisfaction in (ix) supporting people makes nurses more likely to leave their profession and show emotional constraints. We uncovered a dichotomy where nurses have strong empathy for their profession but yearn for improvements due to unmet expectations. Policy implications should include measures for younger nurses and those in elderly care. Nevertheless, there is a need for further research, because our research is limited by potential bias from convenience sampling, and digitalization will soon show up as a potential solution to improve, e.g., documentation and enhanced time for direct patient time. Full article

This article presents a study on the multi-class classification of job postings using machine learning algorithms. With the growth of online job platforms, there has been an influx of labor market data. Machine learning, particularly NLP, is increasingly used to analyze and classify job postings. However, the effectiveness of these algorithms largely hinges on the quality and volume of the training data. In our study, we propose a multi-class classification methodology for job postings, drawing on AI models such as text-davinci-003 and the quantized versions of Falcon 7b (Falcon), Wizardlm 7B (Wizardlm), and Vicuna 7B (Vicuna) to generate synthetic datasets. These synthetic data are employed in two use-case scenarios: (a) exclusively as training datasets composed of synthetic job postings (situations where no real data is available) and (b) as an augmentation method to bolster underrepresented job title categories. To evaluate our proposed method, we relied on two well-established approaches: the feedforward neural network (FFNN) and the BERT model. Both the use cases and training methods were assessed against a genuine job posting dataset to gauge classification accuracy. Our experiments substantiated the benefits of using synthetic data to enhance job posting classification. In the first scenario, the models’ performance matched, and occasionally exceeded, that of the real data. In the second scenario, the augmented classes consistently outperformed in most instances. This research confirms that AI-generated datasets can enhance the efficacy of NLP algorithms, especially in the domain of multi-class classification job postings. While data augmentation can boost model generalization, its impact varies. It is especially beneficial for simpler models like FNN. BERT, due to its context-aware architecture, also benefits from augmentation but sees limited improvement. Selecting the right type and amount of augmentation is essential. Full article

The COVID-19 pandemic that hit the world in early 2020 has had major impacts on social and economic life in every country, including Malaysia. Many socio-economic activities have been globally disrupted, leading to the closure of companies and the suspension of work activities, which have drastically increased the unemployment rate and narrowed employment opportunities. This study used a qualitative method to explore the initiatives taken by the Malaysian Ministry of Higher Education and University Malaysia Sabah to improve the sustainability of graduate employability in the post-COVID-19 era. The study sample comprised ten officers who are experienced and responsible for organising initiatives for university graduate employability programmes and ten students who participated in these programmes. The study showed that the Short-Term Training and Placement Programme (MySTEP), Career Advancement Programme (Penjana CAP), Professional Certification Programme (Penjana PACE), and Career Advancement Programme at State (Penjana KPT-CAP @ State) were the major initiatives taken by the Malaysian Ministry of Higher Education to improve graduate employability in the post-COVID-19 era. The findings also revealed that the university undertook initiatives regarding upskilling and reskilling, the gig economy, entrepreneurship, finishing school programmes, and online career fairs to improve graduate employability rates in the post-COVID-19 era. Interviews with student respondents showed that these initiatives have given them the opportunity to learn and improve on new skills that are necessary to find new job opportunities in the post-COVID-19 era. The main contribution of this study is that upskilling and reskilling programmes are essential to improving the sustainability of graduate employability in the post-COVID-19 era. Full article

(1) Background: COVID-19 caused the worst international public health crisis, accompanied by major global economic downturns and mass-scale job losses, which impacted the psychosocial wellbeing of the worldwide population, including Saudi Arabia. Evidence of the high-risk groups impacted by the pandemic has been non-existent in Saudi Arabia. Therefore, this study examined factors associated with psychosocial distress, fear of COVID-19 and coping strategies among the general population in Saudi Arabia. (2) Methods: A cross-sectional study was conducted in healthcare and community settings in the Saudi Arabia using an anonymous online questionnaire. The Kessler Psychological Distress Scale (K-10), Fear of COVID-19 Scale (FCV-19S) and Brief Resilient Coping Scale (BRCS) were used to assess psychological distress, fear and coping strategies, respectively. Multivariate logistic regressions were used, and an Adjusted Odds Ratio (AOR) with 95% Confidence Intervals (CIs) was reported. (3) Results: Among 803 participants, 70% (n = 556) were females, and the median age was 27 years; 35% (n = 278) were frontline or essential service workers; and 24% (n = 195) reported comorbid conditions including mental health illness. Of the respondents, 175 (21.8%) and 207 (25.8%) reported high and very high psychological distress, respectively. Factors associated with moderate to high levels of psychological distress were: youth, females, non-Saudi nationals, those experiencing a change in employment or a negative financial impact, having comorbidities, and current smoking. A high level of fear was reported by 89 participants (11.1%), and this was associated with being ex-smokers (3.72, 1.14–12.14, 0.029) and changes in employment (3.42, 1.91–6.11, 0.000). A high resilience was reported by 115 participants (14.3%), and 333 participants (41.5%) had medium resilience. Financial impact and contact with known/suspected cases (1.63, 1.12–2.38, 0.011) were associated with low, medium, to high resilient coping. (4) Conclusions: People in Saudi Arabia were at a higher risk of psychosocial distress along with medium-high resilience during the COVID-19 pandemic, warranting urgent attention from healthcare providers and policymakers to provide specific mental health support strategies for their current wellbeing and to avoid a post-pandemic mental health crisis. Full article

Post-traumatic growth (PTG) and specific traumatic events have been poorly explored in the literature focusing on post-traumatic stress disorder (PTSD) among healthcare workers (HWs) tackling the COVID-19 pandemic. In a large sample of Italian HWs, we investigated the kinds of traumatic events and whether PTG affects the risk of PTSD, along with its prevalence and features, during the first COVID-19 wave. COVID-19-related stressful events, Impact of Event Scale-Revised (IES-R) and PTG Inventory-Short Form (PTGI-SF) scores were collected through an online survey. Out of 930 HWs included in the final sample, 257 (27.6%) received a provisional PTSD diagnosis based on IES-R scores. Events referring to the overall pandemic (40%) and to a threat to a family member (31%) were reported as the most stressful events. Female sex, previous mental disorders, job seniority, unusual exposure to sufferance and experiencing a threat to one’s family significantly increased the provisional PTSD diagnosis’ risk, while being a physician, the availability of personal protective equipment and moderate/greater scores on the PTGI-SF spiritual change domain were found to be protective factors. Full article

In this study, big data analysis on Korea’s “online tour”, which emerged as an alternative to satisfy tourism needs after COVID-19, was conducted. After extracting keywords through text mining for 24,073 posts from the top three most frequently visited social media platforms, Naver, Daum, and Google, to gather tour information in Korea, frequency analysis and TF-IDF analysis were run. In addition, network analyses, such as centrality and convergence of iteration correlation (CONCOR) analyses, were performed. The results showed: First, the sense of presence via local live streaming is crucial. It is vital to prepare a suitable video environment where tourists can immerse themselves in the tour. Second, the interaction between travel agencies, local guides, and tourists is important because it can expand tourists’ travel experiences. Third, the importance of online tour program content was revealed. It is necessary to increase the demand by designing various programs tailored to the audience. Fourth, new possibilities for local travel that had been neglected were uncovered. Fifth, the importance of online tourism production support was highlighted. The role of the government must be expanded to reinforce the digital capabilities of small- and medium-sized enterprises (SMEs) and to create jobs. Although the scope of this study is limited to Korea, it can definitely be used as a regional strategy. Full article

Teaching is amongst the six professions with the highest stress levels and lowest job satisfaction, leading to a high turnover rate and teacher shortages. During the pandemic, teachers and school principals were confronted with new regulations and teaching methods. This study aims to examine post-pandemic stress levels, as well as resilience factors to proactively cope with stress and thoughts of leaving the profession among teachers and school principals. We used a cross-sectional online survey. The validated instruments Perceived Stress Scale (PSS-10) and Proactive Coping Subscale (PCI) were used. We included 471 teachers and 113 school principals in the analysis. Overall, respondents had a moderate stress level. During the pandemic, every fourth teacher (27.2%) and every third principal (32.7%) had serious thoughts of leaving the profession. More perceived helplessness (OR = 1.2, p < 0.001), less self-efficacy (OR = 0.8, p = 0.002), and poorer coping skills (OR = 0.96, p = 0.044) were associated with a higher likelihood of thoughts of leaving the profession for teachers, whereas for school principals, only higher perceived helplessness (OR = 1.2, p = 0.008) contributed significantly. To prevent further teacher attrition, teachers and school principals need support to decrease stress and increase their ability to cope. Full article

For more than ten years, online job boards have provided their services to both job seekers and employers who want to hire potential candidates. The provided services are generally based on traditional information retrieval techniques, which may not be appropriate for both job seekers and employers. The reason is that the number of produced results for job seekers may be enormous. Therefore, they are required to spend time reading and reviewing their finding criteria. Reciprocally, recruitment is a crucial process for every organization. Identifying potential candidates and matching them with job offers requires a wide range of expertise and knowledge. This article proposes a reciprocal recommendation based on bi-directional correspondence as a way to support both recruiters’ and job seekers’ work. Recruiters can find the best-fit candidates for every job position in their job postings, and job seekers can find the best-match jobs to match their resumes. We show how machine learning can solve problems in natural language processing of text content and similarity scores depending on job offers in major Saudi cities scraped from Indeed. For bi-directional matching, a similarity calculation based on the integration of explicit and implicit job information from two sides (recruiters and job seekers) has been used. The proposed system is evaluated using a resume/job offer dataset. The performance of generated recommendations is evaluated using decision support measures. Obtained results confirm that the proposed system can not only solve the problem of bi-directional recommendation, but also improve the prediction accuracy. Full article

The impacts of the COVID-19 pandemic have led to global reports of hazards to mental health. However, reports regarding lifestyle changes due to the COVID-19 pandemic are lacking. Using a convergent mixed methods design, we conducted individual interviews with twelve occupational therapy students and interpreted the results by content analysis. We completed a survey of Thai Sensory Patterns Assessment (TSPA) concerning perspectives from occupational therapy students (n = 99). They identified two major themes: (i) adaptive responses were consistent with areas of occupation during the COVID-19 pandemic; (ii) multidimensional challenges were related to sensory patterns of purposeful and meaningful activities. The participants reported both positive and negative impacts of the COVID-19 pandemic on their lives. It had both positive and negative effects on the lifestyle of students affected by the COVID-19 pandemic. The positive effect was that most students learned better ways to protect and care for themselves. During the COVID-19 pandemic, occupational therapy students were most concerned about their online learning activities, economic problems, isolation from society, and lifestyle. The negative effects of this include stress, anxiety, loneliness, frustration, boredom, and exhaustion for occupational therapy students. As an impact of the COVID-19 pandemic, occupational therapy students adapted to new lifestyles and experienced mental health issues related to their studies, families, friends, economics, social climate, and future job opportunities. Educators may use the findings of this study to prevent negative impacts on mental health and promote academic achievement in the future, as well as general well-being, efficacy, and empowerment of students in the new normal post-COVID-19 pandemic era. Full article

(1) Background: The purpose of this study was to evaluate the radiation awareness level of the public in Taiwan. (2) Methods: This study designed an online survey form to investigate the radiation awareness level with six topics: basic knowledge of radiation, environmental radiation, medical radiation, radiation protection, and university/corporate social responsibility. The score of respondents were converted into knowledge and responsibility indexes for the quantitative evaluation. Logistic regression was used to assess the correlation between the knowledge index and individual factors. Paired t-test was used to assess the significant difference in knowledge index between pre-training and post-training. (3) Results: The knowledge index of each job category reflected the proportion of radiation awareness of the job. The logistic regression result indicated that radiation-related people could get higher knowledge index. The paired t-test indicated that the knowledge index before and after class had significant differences in all question topics. (4) Conclusions: The public’s awareness of medical radiation was the topic that needed to be strengthened the most—the responses with high knowledge index significantly correlated with their experience in radiation education training or radiation-related jobs. It significantly increased the knowledge index of radiation if the public received radiation education training. Full article