Student Theses, Dissertations and Capstones

Document Type

Dissertation - NSU Access Only

Degree Name

Doctor of Philosophy (PhD) in Nursing Education

Copyright Statement

All rights reserved. This publication is intended for use solely by faculty, students, and staff of Nova Southeastern University. No part of this publication may be reproduced, distributed, or transmitted in any form or by any means, now known or later developed, including but not limited to photocopying, recording, or other electronic or mechanical methods, without the prior written permission of the author or the publisher.

First Advisor

Chitra Paul Victor

Date of original Performance / Presentation

January 2025

Publication Date / Copyright Date

1-1-2025

Abstract

Abstract Background. Prelicensure nursing students (PNSs) often lack informatics competencies due to limited resources and educational opportunities. Preparing these students to utilize technology for patient-centered care is essential, particularly through Locsin’s technological competency as caring in nursing theory. Purpose. This study aimed to assess the psychometric properties and establish reliability of the English translation of the Technology Competency as Caring in Nursing Instrument–Revised (TCCNI-R). Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were used to evaluate factor structure, while structural equation modeling assessed validity, and reliability analysis evaluated reliability, determining the instrument’s applicability in U.S. prelicensure nursing education. Theoretical Framework. Locsin’s middle-range theory acted as a guide for the study, emphasizing the use of technology by PNSs to facilitate patient-centered nursing care. Methods. The proposed dissertation study utilized a cross-sectional survey design to address the research question. Systematic sampling recruited students via email through program directors of U.S. prelicensure nursing programs. Programs were aggregated and systematically arranged by the ten U.S. zip code regions. Results. EFA with Promax oblique rotation indicated a four-factor solution, with items 6 and 8 removed due to lack of salience. CFA did not support the four-factor model, likely due to mixed model fit indices and inadequate sample size. Cronbach’s alpha reflected acceptable internal consistency reliability, with values ranging from 0.71 to 0.88. Conclusions. Broader assessment of the TCCNI-R’s validity and reliability through factor analysis is needed to confirm its suitability for nursing education in the U.S.

Disciplines

Nursing

Keywords

health information technology; nursing informatics; Prelicensure nursing students; Rozzano Locsin; technological competency; technological competency as caring in nursing

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