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Steve M. Esteban

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Review Open access 2026

Innovative Practices of Clinical Instructors and their Relationship with Student Performance: Basis for an Enhancement Program

This study determined the relationship between the innovative practices of clinical instructors and the student performance of nursing students at the University of La Salette as basis for a proposed Clinical Practice Enhancement Program. The study used a descriptive-correlational research design and involved third-year and fourth-year nursing students as respondents. A structured survey questionnaire was used to gather data on the respondents' profile, the level of innovative management practices of clinical instructors, and the level of student performance based on the Six-Dimension Scale of Nursing Performance. Frequency, percentage, weighted mean, Kruskal-Wallis H test, Mann-Whitney U test, and Pearson correlation coefficient were used to analyze the data. Findings revealed that the respondents were mostly within the 20-23 age range, predominantly female, and almost evenly distributed between third-year and fourth-year levels. The innovative management practices of clinical instructors were rated Very Highly Practiced, particularly in transformational leadership, support for professional development, creativity and change management, participative decision-making, and the use of technology and evidence-based practices. Student performance was rated Excellent across the six dimensions of nursing performance, with interpersonal relations as the strongest area and leadership as the area needing further strengthening. The findings also showed no significant differences in the students' evaluation of clinical instructors' innovative practices and student performance when grouped according to age, sex, and year level. However, a significant positive relationship was found between the innovative practices of clinical instructors and student performance. Thus, the null hypothesis on the relationship between the two variables was rejected. The study concluded that innovative, supportive, participative, and evidence-based clinical instruction contributed meaningfully to better student performance. Based on the findings, an Enhancement Program was proposed to sustain effective clinical teaching practices and further improve student leadership, feedback-seeking behavior, technology use, reflective learning, and professional development.

Hannah Kathrine B. Chiu, Steve M. Esteban · 0 citations
Open access Jul 2026

Acceptability and accountability on Artificial Intelligence among healthcare workers in selected hospitals in Isabela

An outright improvement in accuracy, clinical efficiency and patient-directed care has been attributed to the radical integration of Artificial Intelligence (AI) in the healthcare arena. This inquiry explored the accountability and acceptability of AI among selected hospitals in the Province of Isabela. The selected participants were assessed on ethics, potential judgments, man-over-machine roles, public confidence and dignity and inherent biases, formerly and perceived usefulness, ease of use, social influence, self-efficacy and facilitating conditions, on the latter. This study was qualitatively underpinned by the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology. Inherently, themes and subthemes were purposefully extracted from the viewpoints of the selected health workers. Thus, findings denoted that accountability is strongly linked to transparency and training, governance, regulation and ethical guidelines as it  underscore the importance of regulating human oversight while safeguarding equitable caring outcomes as algorithmic biases are addressed. Consequently, the participants recognized that AI aids in enhancing diagnostic accuracy, reduces clinical workload yielding to improved patient care in terms of Acceptability. Although trepidations were evident on data privacy, lack of trainings , unethical nuances and human-centered oversight, public confidence, on the other hand, was robustly linked to accuracy, transparency and data privacy. Hence, the study concluded that a successful AI-integration maintains a harmony among ethical principles, technological advancements and man-over-machine oversight. Recommendations are centered to dynamic trainings, proposed policy frameworks and ergonomic collaboration between healthcare professionals and AI developers.

Steve M. Esteban · 0 citations