Indian Journal of Surgical Nursing

Background: Alopecia is a common dermatological condition characterized by hair loss that affects individuals physically, emotionally, and socially. Young adults increasingly experience early-onset alopecia due to stress, poor dietary habits, chemical hair treatments, and improper scalp hygiene. Educational interventions led by nurses may help reduce the severity of alopecia. This study evaluated the effectiveness of a structured scalp-care education program in improving hair density and reducing hair-fall among young adults.

Methods: A quasi-experimental pretest–posttest control group design was used among 120 young adults aged 18–35 years diagnosed with Grade I–II alopecia. The experimental group received structured scalp-care education covering scalp hygiene, nutrition, stress management, and safe hair-care practices. Hair Density Score (HDS) and standardized Hair Fall Count Test were used for data collection.

Results: The experimental group showed a significant improvement in HDS (mean increase +0.96) compared to the control group (mean increase +0.18). Daily hair-fall reduced by 25.3 strands/day in the experimental group compared to 6.4 strands/day in the control group.

Conclusion: The structured scalp-care educational program effectively reduced alopecia severity and daily hair shedding. Nurse-led interventions are costeffective strategies to promote scalp health among young adults.

Background: This study examined the effectiveness of a structured teaching programme (STP) on the prevention of dengue fever among patients admitted to a medical ward in Coimbatore.

Material and methods: Convenience sampling was adopted and A quasiexperimental one-group pre-test and post-test design was used, involving patients aged 20–50 years. Data were collected using a structured knowledge questionnaire.

Conclusion: Results revealed a significant improvement in post-test knowledge scores compared to pre-test scores (t = 45.1, p < 0.001), indicating that the STP was effective in enhancing awareness and preventive knowledge regarding dengue fever. Implementing such educational interventions within healthcare institutions can contribute to controlling the spread of dengue and other vector-borne diseases.

Background: Gamma Knife radiosurgery is a non-invasive brain, Lesion, nerve disorder such as trigeminal Neuralgia etc. treatment by use of the high beam focused gamma ray from Cobalt-60 sources.

Aim: 1. To assess pre-test level of knowledge regarding Gamma Knife surgery among B.Sc Nursing Students. 2. To re-assess post-test level of knowledge regarding Gamma Knife surgery among B.Sc Nursing Students. 3. To find out of the effectiveness of Video assisted teaching program me of knowledge regarding Gamma Knife surgery among B.Sc Nursing student’s. 4. To find out the relationship between knowledge regarding Gamma Knife Surgery among B.Sc Nursing student’s.

Method & Material: Evaluative research approach & Quasi Experimental research design was adopted. 60 Sample of Undergraduate B.Sc Nursing students Apex Nursing College Varanasi was selected by the Simple random sampling Techniques by the table method. The semi structured constructed knowledge questionnaire regarding Gamma Knife Surgery among students.

Results: The finding of this study, Pre-test knowledge towards Gamma knife Surgery in undergraduate Nursing Student’s that Poor 81.67% (49),Average 15%(09) & Good knowledge 3.33% (2) but Post-test Nursing student’s that Poor 11.66%(7), Average 53.33% (32) & Good 35% (21). The Pre-test Mean ±S.D. 7.43±2.91 but after the video assisted Teaching Program me Mean ±S.D.11.82±3.42. The effectiveness of Video assisted teaching Program me Mean ±S.D 4.39 ±0.51. The relationship between Pre-test knowledge score with selected socio-demographical variables such as Age (Year’s), Gender, Types of Family, Monthly Income of the family Member’s, Any History of Brain Cancer/Lesions, Previous knowledge about Gamma Knife surgery are not significant but others demographical variables Year’s of course, Family occupation are significant at the level of P>0.05.

Conclusion: The B.Sc Nursing Students have enhanced the knowledge after the video assisted teaching programme regarding Gamma Knife Surgery & that Video assisted teaching programme was very effective.

Bionic eyes, or visual prostheses, represent a transformative advancement in restorative medicine for the millions worldwide suffering from blindness. Unlike cosmetic prosthetic eyes, these functional implants use micro-electrodes to stimulate surviving neurons in the retina, optic nerve, or visual cortex, bypassing damaged tissue. Currently, recipients perceive a “flashing mosaic” of light spots known as phosphenes, which requires specialized training to interpret. While existing models such as the Argus II and Bionic Vision Australia devices provide enough functional vision for basic navigation and object localization, they remain limited by low electrode density and a lack of color perception. Future developments focusing on higher-resolution electrode arrays and cortical stimulation (like the Orion system) aim to broaden eligibility to patients with glaucoma or optic nerve trauma, ultimately striving to more closely replicate natural sight.

Deep vein thrombosis (DVT) is a significant vascular condition characterized by the formation of blood clots within the deep venous system, most commonly affecting the lower extremities. It represents a major public health concern due to its association with morbidity, mortality, and long-term complications such as pulmonary embolism and post-thrombotic syndrome. Nursing professionals play a pivotal role in prevention, early recognition, patient education, and management of DVT. This review provides an in-depth exploration of epidemiology, risk factors, pathophysiology, clinical manifestations, diagnostic approaches, and management strategies, with a particular focus on the implications for nursing education and practice. By synthesizing current evidence and highlighting emerging trends, this article aims to strengthen nursing faculty’s knowledge base, support clinical decision-making, and enhances teaching effectiveness in preparing future nurses to manage patients at risk for or affected by DVT.

Capgras Syndrome (CS) is a rare delusional misidentification syndrome (DMS) characterized by the irrational belief that a familiar person, such as a spouse or parent, has been replaced by an identical-looking impostor. First described by Jean Marie Joseph Capgras in 1923, the condition involves a disconnection between visual recognition and emotional response, often resulting from organic brain injuries, neurodegenerative diseases like Alzheimer’s, or psychiatric conditions such as Schizophrenia. Etiological theories range from psychodynamic conflicts (Oedipus/Electra complexes) to neurological dysfunction in the right hemisphere. Clinical manifestations include anxiety, hallucinations, and social withdrawal. Management requires a multimodal approach, combining pharmacotherapy (antipsychotics and SSRIs) with behavioral psychotherapy techniques that emphasize emotional connection and reality validation rather than direct confrontation of the delusion.

The integration of artificial intelligence (AI) into virtual simulation has transformed nursing education by enabling immersive, adaptive, and learner-centered clinical training environments.1,2 AI-driven virtual simulations offer personalized learning pathways, real-time feedback, and data-informed performance assessment, addressing limitations of traditional clinical education.3,4 Clinical competence in nursing involves the integration of cognitive, psychomotor, and affective domains, all of which can be supported through intelligent simulation technologies.5 This narrative review synthesizes existing literature on AI-driven virtual simulation and its impact on clinical competence in nursing education. Key areas reviewed include theoretical foundations, AI technologies used in virtual simulation, effects on competence domains, learner and faculty perspectives, and implementation challenges. Evidence suggests that AI-driven virtual simulation enhances clinical reasoning, procedural confidence, communication skills, and learner engagement.6-8 Strategic integration of AI-enabled virtual simulation may strengthen competency-based nursing education while ensuring patient safety and educational consistency.

Artificial Intelligence (AI) defined as the capacity of computational systems to perform tasks requiring human-like reasoning, perception, and problem-solving is fundamentally transforming the healthcare landscape. In high-pressure environments like the Intensive Care Unit (ICU), where nurses must process vast streams of time-sensitive data, AI serves as a vital tool for enhancing clinical decision-making and improving patient outcomes. This paper explores the current innovations, clinical benefits, and inherent challenges of integrating AI into critical care nursing. Recent innovations have introduced sophisticated robotic systems such as the Da Vinci Xi for surgery, RoBear for patient mobilization, and specialized nursing assistants like TRINA and the humanoid GRACE. Beyond physical robotics, AI’s primary value in the ICU lies in predictive analytics and real-time monitoring. These systems excel at early deterioration detection, identifying subtle physiological shifts that precede sepsis, cardiac events, or respiratory failure. By providing higher sensitivity in risk stratification and forecasting resource needs such as ventilation requirements and length of stay AI optimizes both clinical safety and operational efficiency. Furthermore, AI enhances the utility of Electronic Medical Records (EMRs) through expert knowledge based systems that offer diagnostic prompts and treatment recommendations. However, widespread adoption faces significant hurdles, including the “black box” nature of complex algorithms, the need for standardized data security, and the requirement for rigorous regulatory validation. Despite these technological advancements, the human element remains central to critical care. While AI can process data with unmatched speed, it lacks the common sense, empathy, creativity, and ethical judgment inherent to professional nursing. Ultimately, AI is positioned not as a replacement, but as an augmentative force that empowers nurses by reducing documentation burdens and providing actionable insights, ensuring that the future of the ICU is both technologically advanced and human-centered.