Differences in Depression, Anxiety, and Stress Scores Across Workload Categories Among Nurses Working at Community Health Centers in Metro City, Lampung Province

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Background: Increasing workloads among nurses working at community health centers, driven by high service demands and limited staffing, may adversely affect mental health, particularly symptoms of depression, anxiety, and stress.

Objective: To examine differences in depression, anxiety, and stress scores across workload categories among nurses working at community health centers administered by the Metro City Health Office.

Methods: This cross-sectional study was conducted from November 2025 to July 2026 at 11 community health centers. A total of 55 nurses were recruited using purposive sampling. Workload was assessed using the National Aeronautics and Space Administration Task Load Index (NASA-TLX), whereas depression, anxiety, and stress were measured using the Depression Anxiety Stress Scale-21 (DASS-21). Data were analyzed using descriptive statistics and the Kruskal-Wallis test, with statistical significance set at p < 0.05.

Results: Most respondents had a high workload (60.0%). The largest proportions of respondents were classified as normal for depression (49.1%), anxiety (54.5%), and stress (83.6%). The Kruskal-Wallis test showed significant differences in depression (p = 0.006), anxiety (p = 0.001), and stress (p = 0.040) scores across workload categories. The high-workload group had the highest mean ranks for depression (33.27), anxiety (34.67), and stress (32.26).

Conclusion: Depression, anxiety, and stress scores differed significantly across workload categories, with the highest mean ranks observed among nurses in the high-workload category. Equitable workload distribution and accessible psychosocial support are needed to protect nurses’ mental health and maintain the quality of healthcare services.

Implementation of YOLOv8n-Based Liveness Detection to Enhance the Security of Facial Attendance Systems Against Real-Time Spoofing Attacks

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This research aims to develop an anti-spoofing security system based on liveness detection to address the vulnerabilities of facial attendance systems against identity manipulation using photos or videos. The methodology employed is quantitative experimental, utilizing the YOLOv8n (You Only Look Once) deep learning architecture. The research stages involved the independent collection of a dataset comprising 8,000 images, categorized into “real” and “fake” face classes. This dataset was processed using a distribution ratio of 70% for training, 20% for validation, and 10% for testing. The model training process was conducted over 50 epochs using the Google Colab platform supported by a Tesla T4 Graphics Processing Unit (GPU). The results indicate that the developed model achieves high performance, with a mean Average Precision (mAP50) of 99.4%, precision of 98.8%, and recall of 99.0%. Real-time testing demonstrated an average inference speed of 20 frames per second (FPS), ensuring system responsiveness in practical applications. Implementation on low-power hardware, specifically the NVIDIA Jetson Nano, confirmed the computational efficiency of the model for edge device deployment. The primary conclusion of this study is that the YOLOv8n-based liveness detection system is highly effective and viable for integration into automated organizational attendance systems due to its high accuracy and efficient power consumption.

Effect of Different Levels of Nitrogen on Growth and Yield of Flax under Kabul Agro-Ecological Conditions

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Flax is among the most significant industrial oilseed crops in the world, as well as in Afghanistan.  It is high in health-promoting fatty acids. However, its yield and quality are low owing to poor nitrogen fertilizer use and lack of improved cultivars in Afghanistan. Hence, a field trial was conducted at the Research Farm of the Agriculture Faculty of Kabul University during the main cropping season of 2025 to evaluate four nitrogen rates (0, 50, 100, and 150 kg/ha). The study was conducted using a randomized complete block design (RCBD) arrangement with four replications. The size of each experimental unit was 2 m × 2 m (4 m2), with six rows. Distances of 30 cm and 40 cm were left between plots and blocks, respectively. The spacing between rows was 30 cm, and the spacing between plants was 15 cm. Significant differences were observed in the different levels of nitrogen on plant height, number of capsules per plant, number of branches per plant, number of seeds per capsule, 1000-seed weight, length of roots, biological yield, grain yield, and straw yield. However, the results showed that the 100 kg N/ha fertilization level significantly outperformed in number of seeds per capsule, number of capsules per plant, 1000-seed weight, and seed yield. Meanwhile, the 150 kg N/ ha fertilization level excelled in plant height and number of branches per plant, biological yield, and straw yield.

Mapping Agricultural, Forestry, And Fisheries Products In Indonesia: The Input-Output Approach

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Economic growth is a goal of economic development. To achieve strong growth, sound planning is essential. Accordingly, product mapping is crucial. Production activities in the agriculture, forestry, and fisheries sectors are part of the economy that produces both food and non-food products needed by humans. Input-output (I-O) analysis is used as a tool for mapping sectors and products. The data used are the 17×17 I-O table for 2020 and the 185×185 I-O table for 2020. The analysis results indicate that the agriculture, forestry, and fisheries sector is not a key sector but rather a sector with weak attractiveness and strong driving power. The sector lacks superior products, possessing only nine products with a strong sensitivity index (SEI).

The Effectiveness of Gamification Tools (Quizlet and Wayground) in Teaching English Vocabulary to Young Learners: Evidence from a Vietnamese English Education Center

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This article examined the effectiveness of two gamification tools, Quizlet and Wayground, in teaching English vocabulary to young learners at an English education center in Ho Chi Minh City, Vietnam. Employing an explanatory sequential mixed-methods design, the article addressed three research questions concerning the benefits of Quizlet and Wayground, their capacity to engage students’ motivation and interest and their effect on young learners’ memory of vocabulary meaning. Thirty students aged 10 to 11, enrolled in a Cambridge Flyers preparation course, were divided into an experimental group taught using Quizlet and Wayground and a control group taught using traditional methods over a six-week period. Data were collected through a vocabulary pre-test and post-test, twelve periods of classroom observation and semi-structured interviews with five English teachers. Quantitative data were analyzed using independent-samples and paired-samples t-tests, while qualitative data were analyzed thematically. The results indicated that teachers perceived Quizlet and Wayground as beneficial for presenting, practicing and reviewing vocabulary through varied game modes. Both interview and observation data showed that the tools substantially increased students’ motivation and interest in the classroom. Furthermore, although the two groups did not differ significantly on the pre-test (p = .653), the experimental group significantly outperformed the control group on the post-test (p = .035), and only the experimental group showed a statistically significant pre-to-post-test improvement (p < .001) with mean scores rising from 6.940 to 7.920. These findings suggest that gamification tools such as Quizlet and Wayground can meaningfully enhance vocabulary retention and classroom engagement among young EFL learners, offering practical implications for vocabulary instruction in similar educational contexts.

The Relationship between Teacher Support and First-Year EFL Students’ Attitudes toward Autonomous Learning: Evidence from a Vietnamese University

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Learner autonomy is widely regarded as a central goal of foreign language education, yet first-year students in Vietnamese higher education frequently enter university with strong habits of teacher dependency formed during exam-oriented secondary schooling. Grounded in Self-Determination Theory, this article examined the relationship between perceived teacher support and attitudes toward autonomous learning among first-year English as a Foreign Language (EFL) students at Industrial University of Ho Chi Minh City (IUH). Using an explanatory sequential mixed-methods design, quantitative data were collected from 202 first-year students through a questionnaire measuring three dimensions of attitude (cognitive, affective, behavioral) and three dimensions of teacher support (autonomy support, structure, involvement), followed by semi-structured interviews with 10 participants. Results indicated that students held moderately positive attitudes toward autonomous learning and perceived moderate levels of teacher support, with a strong, statistically significant positive correlation between the two constructs (r = .766, p < .001). Teacher support correlated most strongly with behavioral attitudes (r = .598), followed by affective (r = .565) and cognitive attitudes (r = .546). Qualitative findings converged with the quantitative results, showing that students associated supportive teaching with guided self-discovery rather than direct answers, while consistently identifying the need for more explicit instruction in learning strategies. The findings suggest that teacher support and learner autonomy are complementary rather than opposing forces, and that first-year EFL programs would benefit from embedding explicit strategy instruction within teacher-supportive pedagogy. Implications for EFL pedagogy, teacher training, and future research in non-English-major contexts are discussed.

Students’ Perceptions of Note-taking as a Listening Comprehension Strategy: A Mixed-methods Study of Vietnamese EFL Majors

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Note-taking is widely regarded as a critical strategy for supporting second-language listening comprehension, yet little is known about how Vietnamese English-major students themselves perceive its value and difficulty. This article investigated the perceptions of 150 third-year English majors at the Industrial University of Ho Chi Minh City (IUH) regarding the benefits and challenges of note-taking during English listening tasks. A mixed-methods design that combined a structured questionnaire with semi-structured interviews with 5 students was used thoroughly. Descriptive statistics showed that note-taking is a near-universal habit (83% of students reported taking notes “always” or “often”), predominantly practised with pen and paper (62%) rather than digital devices. Students overwhelmingly perceived note-taking as beneficial for comprehension, memory retention, information organisation, inferencing, test performance and sustained attention with agreement rates ranging from 84% to 93% across the measured benefits. At the same time, a substantial minority reported difficulties related to fast speech rate, unfamiliar vocabulary, divided attention and messy handwriting, particularly regarding missing subsequent information (29% agreement) and message overload at high speech rates (31% agreement). Interview data illuminated the cognitive and strategic mechanisms behind these patterns including code-switching, selective attention to discourse markers and compensatory strategies such as momentarily abandoning notes to preserve comprehension. The findings are interpreted through established learning theories, and practical implications for explicit note-taking instruction in EFL listening classrooms are discussed.

Environmental and Public Health Impact Assessment if Solid Waste Management Practices in Ovia North East, Edo State, Nigeria

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Improper solid waste management has become a growing environmental and public health concern in many developing communities due to population growth, urban expansion, and inadequate waste management systems. This study assessed the environmental and health impacts associated with solid waste management practices in Okada, Usen and Iguomon communities in Edo State. The research was conducted to examine the environmental conditions and public health effects linked to prevailing waste management practices and identify differences among the selected communities. Primary data were collected through the administration of questionnaires distributed randomly among households, schools, stores, etc. This study utilised Section C of the questionnaire, which focused on environmental and health impacts of solid waste management practices. The data collected were processed using descriptive statistical techniques. Results indicated that ineffective waste management practices had substantial adverse effects on environmental conditions within the communities. The environmental impacts identified included bad odour, air pollution, water pollution, flooding, soil contamination, and an increase in pests. Okada recorded higher environmental pressures due to greater waste generation and population concentration, while Usen and Iguomon experienced moderate environmental impacts. Health challenges associated with poor waste management included malaria, diarrhoea, cholera, and skin infections. Most respondents indicated that open dumping negatively affected environmental aesthetics. The study concluded that existing solid waste management practices within the study area pose considerable environmental and public health risks. It is recommended that improved waste management infrastructure, regular environmental monitoring, public awareness programmes, and strengthened sanitation policies be implemented to promote environmental sustainability and healthier communities.

Anthropology Beyond the Walls of the Discipline: A Critical Reading of “Why the World Needs Anthropologists”

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This paper offers a critical review of the second edition of Why the World Needs Anthropologists, edited by Dan Podjed and Carla Guerrón Montero (Routledge, 2026), a thirteen-chapter collective volume that revisits, in new terms, the long-standing question of anthropology’s relevance to the contemporary world. The review argues that the book’s central contribution lies in repositioning anthropology from a detached observer of social life into an interventionist form of knowledge capable of understanding, mediating, and translating between disparate institutional and epistemic worlds. Drawing on chapters devoted to environmental anthropology, energy transitions, professional collaboration, and career preparation, the review traces how the volume grounds its theoretical claims in concrete applied experience. It also raises three critical points: the book’s tendency to soften the political tensions inherent in applied engagement, its persistent grounding in North Atlantic institutional contexts, and the latent risk of disciplinary self-centeredness embedded in its very title. The review concludes that, despite these limitations, the volume stands as one of the most successful recent collective attempts to reintroduce anthropology as a living form of knowledge, capable of combining theoretical depth with sustained practical relevance across a wide range of institutional and professional settings.

Artificial Intelligence and Mechanical Engineering in Greek Vocational High Schools: Educational Perspectives and Institutional Barriers

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This scoping review investigates the potential and challenges of integrating Generative Artificial Intelligence (GenAI) into Vocational Education and Training, with a specific focus on the Mechanical Engineering sector of Greek Vocational High Schools (EPA.L.). The purpose of this study is to analyze how AI can transform the teaching of mechanical engineering courses, bridging the gap between theoretical knowledge and laboratory practice in the context of Industry 4.0. The methodology involved a literature review of 26 scientific sources (2016-2026), utilizing thematic analysis guided by theoretical frameworks such as the Technology Acceptance Model (TAM) and teacher self-efficacy. Key findings indicate that the use of specialized, knowledge-enhanced Large Language Models (LLMs) significantly improves the structural integrity and technical accuracy of instructional materials, effectively reducing teacher preparation time. However, despite a high perceived usefulness, the adoption of AI by educators in public schools is severely hindered by the lack of adequate laboratory infrastructure, the absence of discipline-specific training, and heightened AI anxiety regarding ethical risks. In conclusion, the transition to an AI-enhanced school laboratory necessitates immediate upgrades to equipment and a shift from general ICT training to targeted, specialty-specific professional development programs, ultimately empowering teachers to become designers of digital learning experiences.