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63 articles for “Instrumentation”
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A Study to Assess the Effectiveness of Self-Instructional Module Regarding Common Psychological Problems of Postpartum Psychosis and Its Management Among Trained Staff Nurses of Netaji Subhash Chandra Bose Medical College, Jabalpur
Abstract: A quasi-experimental study employing a one-group pretest and posttest design was undertaken to evaluate the impact of a self-instructional module on staff nurses’ knowledge of postpartum psychosis and its management. The research was conducted at Netaji Subhash Chandra Bose Medical College Hospital and included 60 trained staff nurses selected through a non-probability convenience sampling technique. Data were collected through a structured questionnaire designed to assess knowledge levels. The reliability of …
Published in International Journal of Women's Health Nursing And Practices · Vol. 4, Issue 1, 2026 · pp. 24–28 Read article
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Predicting Student Placement Readiness: A Machine Learning Approach Using Coding Activities and Multi-Dimensional Performance Indicators
Abstract: In the modern information-driven academic world, identifying student employability and placement preparedness has predicted. be made a part and parcel of academic planning and career. development. This study provides a machine learning-based. structure to evaluate and forecast student placement pre-paredness by combining various performance aspects-academic achieve- ment, coding activity, aptitude and behavioral engage-ment metrics. Multi-source was gathered and preprocessed in the study. student information, such as student records (CGPA, attendance), …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article
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Passive Digital Phenotyping for Longitudinal Burnout and Occupational Mental Health Surveillance: A Transformer-Based Explainable Deep Learning Approach Using Smartphone Behavioral Streams
Abstract: Occupational burnout constitutes a pervasive yet chronically under-surveilled public health threat, its insidious temporal evolution rendering episodic self-report instruments structurally inadequate for early detection. This paper introduces BurnoutSense, a passive digital phenotyping framework that continuously harvests eight heterogeneous smartphone behavioral data streams encompassing application usage ecology, communication metadata, geospatial mobility, screen interaction dynamics, inferred sleep rhythmicity, keystroke kinematics, ambient noise exposure, and battery/charging cadence to construct individualized multivariate behavioral signatures …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 2, 2026 · pp. 44–53 Read article