Volume 14 | Issue 4

 Abstract

Background: Cancer-related pain is one of the most distressing symptoms experienced by patients and significantly affects quality of life. While pharmacological management remains the cornerstone of treatment, nonpharmacological interventions led by nurses have gained increasing attention as complementary strategies. Aim: To evaluate the effectiveness of nurse-led nonpharmacological interventions (NPIs) in reducing pain among patients with cancer. Methods: A systematic review and meta-analysis were conducted using databases such as PubMed, CINAHL, EMBASE, and Cochrane Library. Randomized controlled trials (RCTs) examining nurse-led NPIs for cancer pain were included. Data were analyzed using pooled effect sizes with a random-effects model. Results: The meta-analysis demonstrated that nurse-led NPIs significantly reduced pain intensity compared to usual care. Interventions such as massage, reflexology, aromatherapy, acupressure, and psychoeducational approaches showed both short-term and long-term effectiveness. The pooled effect size indicated moderate improvement in pain outcomes. Conclusion: Nurse-led nonpharmacological interventions are effective adjuncts to pharmacological therapy in managing cancer-related pain. These interventions should be integrated into routine oncology nursing practice.

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Keywords: Cancer pain, nonpharmacological interventions, nurse-led care, meta-analysis, oncology nursing

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Keywords: Neonatal resuscitation, infant mortality, nurses, training, effectiveness

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Keywords: Neonatal resuscitation, knowledge retention, skill retention, staff nurses, training program, neonatal care

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Abstract Background: Chemotherapy is a primary treatment modality for cancer, but it is often associated with multiple side effects such as nausea, vomiting, fatigue, alopecia, mucositis, and immunosuppression. These adverse effects frequently lead to poor treatment adherence, reduced quality of life, and compromised therapeutic outcomes. Nurse-led education has emerged as an effective intervention to improve patient understanding and adherence to chemotherapy regimens. Objective: To assess the effectiveness of nurse-led educational intervention on treatment adherence and management of chemotherapy side effects among cancer patients. Methods: A quasi-experimental pre-test and post-test design was adopted among 100 cancer patients receiving chemotherapy at a tertiary care hospital. A structured questionnaire was used to assess knowledge and adherence levels. The intervention included education on chemotherapy side effects, self-care practices, medication adherence, and lifestyle modifications. Data were analyzed using descriptive and inferential statistics. Results: The mean adherence score significantly improved from pre-test (Mean = 10.5, SD = 2.8) to post-test (Mean = 19.2, SD = 2.1), with a mean difference of 8.7 (t = 16.45, p < 0.05). Knowledge regarding side effect management also improved significantly. Patients reported better control of symptoms such as nausea and fatigue after the intervention. Conclusion: Nurse-led educational interventions significantly improve treatment adherence and enhance patients' ability to manage chemotherapy side effects effectively.

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Keywords: Chemotherapy, Nurse-led education, Treatment adherence, Side effects, Cancer care

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Keywords: Cancer pain, Non-pharmacological interventions, Pain management, Nursing care, Guided imagery, Music therapy

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Keywords: Ventilator-Associated Pneumonia, Nurse-led intervention, ICU care, Ventilator bundle, Patient safety

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Abstract Background: The theory-practice gap remains a significant challenge in nursing education, particularly in India, where disparities between classroom teaching and clinical practice affect the competence of nursing graduates. Bridging this gap is essential to ensure quality patient care and professional preparedness. Objectives: This study aimed to identify the factors contributing to the theory-practice gap, assess its impact on nursing students, and explore effective strategies to bridge the gap. Methodology: A quantitative descriptive approach was adopted with a sample size of 100 nursing students. Data were collected using a structured questionnaire focusing on contributing factors, impact areas, and strategies to reduce the theory-practice gap. Data were analyzed using descriptive statistics including frequency and percentage. Results: The findings revealed that limited use of simulation (88%), poor theory-practice integration (85%), and inadequate clinical exposure (82%) were the major contributing factors. The gap significantly affected students, with reduced confidence (84%) and increased stress levels (80%) being the most reported impacts. Among the strategies, simulation-based learning (90%), clinical mentorship (88%), and continuous skill assessment (87%) were identified as the most effective measures. Conclusion: The study concludes that the theory-practice gap is a multifactorial issue requiring comprehensive intervention. Strengthening clinical training, integrating simulation-based education, and enhancing mentorship programs can significantly reduce this gap and improve clinical competence among nursing students.

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Keywords: Theory-practice gap, nursing education, clinical competence, simulation-based learning, India

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(???????? ??? "?????????? ?? ????? ??? ???? ??????????????? ??? ??????? ?????? ??????????? ?? ??????-????? ????????? ?? ????????? ??????" ???? ?????? ?? ??????? ??? ???????? ??? ??????????? ?? ????????? ?? ???? ??? ?? ?????????? ?????? ??? ?? ?????? ?? ????? ???????? ????? ??? ???? ??????????????? ??? ??????-????? ????????? ?? ?????? ?? ????????? ???????? ???? ??? ??? ??? ?????????? ??? ????????? ???????? ?????? ?? ????? ???? ??? ?????????? ??? ???????? ????? ?????? ?? ??????? ?? ??????? ???????? ???? ??? ??? ?????? ?? ??????? ?????????? ?? ????? ????? ?? 400 ??.??. ??????-??????????? ?? ????? ???? ???, ?????? ????? ??? ???? ??????????????? ?? ???? ???????????? ????????? ???? ???? ??????? ?? ???????? ???? ?????, ???? ????? ??? t-??????? ?? ?????? ???? ???? ???????? ?? ?????? ??? ?? ???? ??????????????? ??? ??????-????? ????????? ?? ??? ?????? (Mean = 3.85) ????? ??????????????? (Mean = 3.70) ?? ??????? ???? ?? ??? t-????? (2.10) ??? p-????? (0.03) ?? ???? ?? ?? ???? ?????????? ??? ?? ?????? ???? ???? ?????? ???? ?? ???? ?? ??? ?????????? ???? ???? ???? ???, ?????? ???????? ?????? ?? ???? ?? ?????? ??????? ????????? ???? ?????? ?? ?? ???????? ?????? ?? ?? ???? ??????????????? ??? ?????? ?????? ?????????, ?????? ???????? ??? ?????-???????? ????????? ?? ???? ??????? ????? ???? ?? ??? ??, ????? ????? ?? ???????? ??? ?????? ???? ??? ???? ??????, ????? ??????????????? ??? ???????? ????????? ?? ???????? ?? ???? ?????????? ?? ??????????? ???? ??? ?? ??????, ?????? ? ???? ????????? ?? ???????? ???? ??, ????? ?? ?? ????? ???? ?? ?? ???? ?????? ??? ???????? ????? ???? ??????, ?????? ?????? ??? ????-?????? ????? ?????? ?????? ???? ?? ??? ?????? ????-??????????, ????????? ??? ???????? ?? ??? ?????? ????-??????? ?????? ???? ???)

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????? ????: ??????-????? ?????????, ????? ?????????????, ???? ?????????????, ??????? ??????, ????????? ??????, ???? ??????, ?????-???????? ?????, ?????? ????????, ?????????? ????????, t-???????, ??????? ???????????, ??????????

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Keywords: Ventilator-Associated Pneumonia, Nurse-led Intervention, ICU, Infection Control, Prevention Protocol

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Abstract Background: Non-adherence to chemotherapy remains a major barrier to effective cancer treatment worldwide. Recent advancements emphasize the role of nurse-led educational interventions in improving adherence and patient outcomes. Objective: To evaluate the effectiveness of nurse-led education on treatment adherence, symptom management, and psychosocial outcomes among patients undergoing chemotherapy. Methods: A meta-analysis and systematic review of 19 studies involving 1,339 cancer patients undergoing chemotherapy was conducted. Studies included randomized controlled trials and quasi-experimental designs assessing nurse-led educational interventions. Outcomes measured included treatment adherence, symptom burden, self-efficacy, and quality of life. Results: The pooled standardized mean difference (SMD) was 0.89, indicating a significant improvement in adherence-related outcomes. The pooled odds ratio (OR) of 4.37 demonstrated that patients receiving nurse-led education were more than four times likely to adhere to treatment compared to controls. Conclusion: Nurse-led educational interventions significantly enhance chemotherapy adherence, improve symptom management, and promote better psychosocial outcomes. These interventions should be integrated into routine oncology care.

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Keywords: Nurse-led interventions, chemotherapy side effect management, treatment adherence, oncology nursing, patient education, cancer care, symptom management, quality of life, evidence-based practice, patient outcomes

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Cervical cancer is a malignant disease caused by uncontrolled abnormal growth of cells in the cervix and is a major public health problem among women, particularly in low-resource settings. Information, Education and Communication (IEC) modules are effective educational strategies for improving knowledge and promoting prevention. The present study was conducted to assess the effectiveness of an IEC module on knowledge regarding cervical cancer and its prevention among rural and urban women in a selected area of Gorakhpur. The objectives were to assess pre-test and post-test knowledge levels, evaluate and compare the effectiveness of the IEC module among rural and urban women, and determine the association between post-test knowledge and selected demographic variables. A quantitative quasi-experimental pre-test and post-test comparative design was adopted. Sixty women (30 from Khatripura and 30 from Omkar Nagar) were selected using purposive sampling, and data were collected using a structured knowledge questionnaire. The findings revealed a significant improvement in knowledge following the IEC module. The paired t-test showed significant improvement among rural women (t = 4.60) and urban women (t = 7.67) at p < 0.05. The unpaired t-test (t = 3.24) indicated greater effectiveness of IECM among urban women. The study concluded that the IEC module was effective in improving knowledge regarding cervical cancer and its prevention.

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Assess, Effectiveness, IEC module, knowledge, Cervical cancer, prevention, rural area, urban area, women.

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Smart shoes for blind people using ultrasonic sensors and voice guidance are an innovative assistive technology designed to enhance independent mobility and safety for visually impaired individuals. The system integrates ultrasonic sensors into footwear to continuously detect obstacles in the user's path. These sensors measure the distance between the shoe and surrounding objects by emitting ultrasonic waves and analyzing the reflected signals. When an obstacle is detected within a predefined range, the system processes the data using a microcontroller and determines the appropriate alert to provide to the user.

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Smart shoe, Ultrasonic Sensor, Voice Guidance, Assistive Technology, Blind Navigation.

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Educational institutions frequently struggle with outdated methods for recording attendance, gauging classroom participation, and overseeing student whereabouts on campus. This study outlines a comprehensive monitoring platform built for Silver Oak University that tackles these persistent issues through a trio of interconnected capabilities. The first component employs the Local Binary Patterns Histograms (LBPH) technique via OpenCV to perform contactless, camera-based roll calls. The second leverages MediaPipe's dense facial landmark mesh--comprising 468 tracked points--to continuously assess whether learners are attentive, drowsy, using mobile devices, or looking away. The third capability uses a network of Android handsets repurposed as wireless IP cameras to flag students who leave designated areas during class hours. A Python-based Flask server connects these modules to a PostgreSQL data store, while a React.js interface delivers tailored views for administrators, faculty, and students. Testing across controlled scenarios yielded 97% precision in identity matching under well-lit conditions, 92% correctness in classifying attentive behavior, and dependable movement alerts governed by a five-minute suppression window to avoid redundant notifications.

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Face Recognition, LBPH, OpenCV, MediaPipe, Student Engagement, Attendance Automation, Roaming Detection

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Keywords: Simulation, clinical competence, nursing education, training effectiveness

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As educational systems worldwide undergo rapid transformations, the teaching profession faces increasing pressure from modern work demands. This study examines the impact of contemporary workplace challenges which includes technological integration, administrative burdens, and heightened accountability--on teacher stress and burnout. Drawing on the Transactional Model of Stress and the Job Demands-Resources (JD-R) framework, the research utilized a quantitative, cross-sectional design with a sample of 120 teachers. Results from one-sample t-tests indicated that teachers experience significant levels of both stress (M = 19.80) and burnout (M = 60.13), with extremely large effect sizes (d = 3.62 and 3.82, respectively). A key finding was that burnout levels were substantially higher than stress levels, supporting the theoretical understanding of burnout as a long-term consequence of chronic, unmanaged occupational stress.

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teacher stress, burnout, modern work demands, Job Demands-Resources model, educational quality, Maslach Burnout Inventory.

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Human suspicious activity detection is an important application in intelligent surveillance systems. Traditional monitoring methods require continuous human observation and may fail to detect suspicious behavior accurately. This research proposes a deep learning-based approach using the YOLO model for detecting suspicious human activities such as fighting, running, theft, intrusion, and unusual movement patterns in CCTV footage. The system is implemented using Google Colab with Python, OpenCV, and the Ultralytics YOLO framework. Experimental results show that the proposed model can detect suspicious activities in real time with high accuracy and reduced processing time.

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Suspicious Activity Detection ,YOLO ,Anomaly Detection ,Real-Time Surveillance ,Deep Learning , Google Colab , Computer Vision

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In today's fast-paced lifestyle, maintaining proper fitness and nutrition has become a challenge for many individuals. This paper presents an AI-powered Virtual Fitness Trainer designed to assist users with real-time exercise guidance and personalized diet recommendations. The system uses computer vision techniques with MediaPipe and OpenCV to monitor body movements and analyze posture during exercises such as push-ups, bicep curls, and yoga poses. It provides instant feedback to help users correct their form and improve workout effectiveness. In addition to exercise tracking, the system includes a diet recommendation module that analyzes nutritional intake based on user inputs like calories, protein, and fat. A machine learning model is used to evaluate diet quality and suggest improvements according to the user's fitness goals. The system also supports natural language input, allowing users to enter their daily food intake in a simple and intuitive way for automatic nutritional analysis. The application is developed using a Flask-based backend with an interactive web interface, making it accessible and easy to use. The results show that the system can effectively guide users in both exercise and diet management, offering a convenient and affordable solution for maintaining a healthy lifestyle. This work demonstrates how AI can be practically applied to enhance personal fitness and wellness.

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Artificial Intelligence, Computer Vision, Pose Estimation, MediaPipe, Fitness Trainer, Exercise Detection, Real-Time Tracking, Diet Recommendation System, BMI Calculation, Machine Learning

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This study analyzes consumer perception and brand awareness in the EdTech sector and their impact on user adoption. With the increasing use of digital learning platforms, understanding consumer behaviour has become important. The research is based on primary data collected through a structured questionnaire among college students, supported by secondary data from relevant studies. Key factors such as brand awareness, perceived quality, ease of use, and social influence were considered. The findings show that brand awareness significantly influences consumer perception and the adoption of EdTech platforms. The study concludes that improving brand visibility and maintaining positive perception are essential for success in the EdTech market.

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Consumer Perception, Brand Awareness, EdTech, Consumer Behaviour

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The heavy engineering sector is a critical pillar of India's industrial and infrastructure growth. In an increasingly competitive landscape, companies must build strong brand associations to differentiate themselves and foster long-term customer relationships. This study evaluates the brand association of RK Heavy Engineering Pvt. Limited and examines customer perception of its products and services. The main objective is to analyse how brand attributes such as quality, reliability, innovation, and service excellence shape customer preference and loyalty. Primary data were collected from 200 respondents comprising engineers, managers, contractors, and suppliers, using a structured questionnaire. Statistical tools including Percentage Analysis, Chi-Square tests, and One-Way ANOVA were employed for analysis. Key findings reveal that 87% of respondents recommend the company to others, 42% rate it as excellent, and brand association is significantly influenced by age, residence, educational qualification, occupation, and monthly income. The study concludes that RK Heavy Engineering Pvt. Limited has established meaningful brand associations rooted in product quality and reliability, with scope for further growth through increased digital presence, customer engagement, and innovation.

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Brand Association, Customer Perception, Heavy Engineering, Brand Awareness, Brand Loyalty, RK Heavy Engineering, B2B Marketing.

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Apprentice Arm is a 6-Degree-of-Freedom, hand-gesture controlled, real-time. (6-DOF) robotic arm system based on the use of computer vision, machine learning, and embedded systems to allow contactless, intuitive robotic manipulation. The system will live video on a regular USB webcam, and will extract 21 three sided video. dimensional hand landmarks with MediaPipe Hands deep-learning of Google. pipeline, and maps the spatial geometry of the hand of the user into six. independent servo motor angles Base rotation,Shoulder lift, Elbow bend, Wrist Pitch, Wrist Roll and Gripper open/close-in real time. The software layer is developed using a Python Flask back-end which integrates. Hand tracking using MediaPipe, Exponential Moving Average (EMA) signal. deadband filtering, smoothing and serial communication into one. cohesive application. The backend is annotated MJPEG video which is being streamed to a modern. web dashboard (HTML5/CSS3/JavaScript) that features a live camera feed, an interactive Three.js 3D digital twin of the robotic arm, six manual override. sliders, a complete task recorder and player engine and an ML-based Smart. Presets module which opts K-Means clustering (scikit-learn) to automatically. find and propose the most common arm positions based on recorded. task history. Hardware On the hardware side, an Arduino UNO microcontroller receives commands regarding the angles. over a 9600-baud UART serial connection and drives a 16 channel I2C PWM, the PCA9685. servo driver. The Base, Shoulder, and have three MG996R high-torque servos. Elbow joints: There are three SG90 micro-servos that drive the Wrist Pitch, Wrist. Roll, and Gripper. The servos use two 3.7 V lithium-ion as a power source. batteries (in series) (~7.4 V), reduced to a regulated (~5.5 V). with an LM2695 DC-to-DC buck converter and then to the V+ of PCA9685. servo power rail. The Apprentice Arm has a gesture to servo end-to-end latency of. around 60 ms, a hand-tracking frequency of 30 FPS, a refresh of the dashboard. frequency of 12.5 Hz, and 3D frame rate of over 60 FPS. The system is developed to be modular, reproducible and extensible, which is why it is suitable. in the case of academic research, educational demonstrations, and hobbyist robotics. HRI projects.

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Keywords: Hand Gesture Recognition, 6-DOF Robotic Arm, Human-Robot Interaction (HRI), MediaPipe Hands, Computer Vision, Machine Learning, K-Means Clustering, Smart Presets, Exponential Moving Average (EMA), Deadband Filtering, Arduino UNO, PCA9685 Servo Driver, Real-Time Control System, Flask Web Application, Three.js Visualization.

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