Self-efficacy in digital nursing education: a scoping review

Self-efficacy in digital nursing education: a scoping review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Self-efficacy in digital nursing education: a scoping review Tamal Joyti Roy, Broti Mondal Bonya This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9657971/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Self-efficacy is central to nursing education because it shapes learners’ confidence in acquiring clinical, academic, and technology-mediated competencies. The rapid expansion of digital learning after the COVID-19 pandemic has created diverse instructional contexts in which nursing students, nurses, faculty, and preceptors develop self-efficacy. However, evidence on how self-efficacy is conceptualized, measured, and strengthened in digital nursing education remains fragmented. This scoping review mapped the literature on self-efficacy in digital nursing education by addressing three questions: how self-efficacy is conceptualized and measured; which learner, faculty, contextual, and instructional factors are associated with self-efficacy; and which digital interventions improve, reduce, or show no effect on self-efficacy outcomes. Five databases were searched: MEDLINE, PsycINFO, CINAHL, Education Source, and Web of Science. After deduplication and eligibility screening, 69 unique studies published between 2018 and 2025 were included. Studies were conducted in 25 countries and primarily involved undergraduate nursing students, followed by graduate students, practicing nurses, and faculty or preceptors. Four self-efficacy domains were identified: domain-specific clinical self-efficacy, academic self-efficacy, computer or technology self-efficacy, and online learning self-efficacy. Measurement was highly heterogeneous, with more than 25 instruments and frequent use of ad hoc scales. Most studies reported positive self-efficacy outcomes, particularly for simulation, flipped classroom models, gamification, AI-assisted tools, and theory-grounded online modules. However, null and negative findings showed that digital delivery alone does not improve self-efficacy. Effective outcomes depend on instructional design, learner readiness, feedback, and structured opportunities for mastery. Nursing Educational Psychology digital learning nursing education nursing students online learning self-efficacy Figures Figure 1 Figure 2 Introduction Digital technologies are now embedded in nursing education rather than functioning as supplemental instructional tools. Undergraduate and graduate nursing programs increasingly use asynchronous online modules, synchronous virtual classrooms, virtual and mixed reality simulations, mobile applications, AI-assisted chatbots, gamified platforms, metaverse environments, and flipped classroom models to support clinical, academic, and professional learning. This shift was accelerated by the COVID-19 pandemic, which forced many nursing programs to adopt remote instruction rapidly, often without adequate preparation, infrastructure, or pedagogical redesign [ 1 , 2 ]. Evidence from this period is mixed. Some studies reported preserved or improved learning outcomes in digitally mediated environments [ 3 , 4 ], whereas others found declines in students’ confidence, engagement, academic performance, and perceived clinical readiness following emergency transitions to online learning [ 2 , 5 ]. Thus, the central issue is not whether digital technologies are used in nursing education, but under what instructional conditions they support or undermine learner development. Self-efficacy is a theoretically important construct for interpreting this literature. Derived from Bandura's social cognitive theory, self-efficacy refers to an individual's belief in their capacity to organize and execute the courses of action required to produce specific attainments [ 6 ]. It is domain-specific, task-referenced, and shaped by four sources: mastery experiences, vicarious learning, verbal or social persuasion, and physiological and affective states [ 6 ]. In nursing education, self-efficacy has been associated with clinical skill acquisition, academic performance, professional identity formation, persistence under adversity, and quality of patient care [ 7 , 8 ]. In digital contexts, self-efficacy is not a single construct. Some studies address beliefs about using digital tools (computer or technology self-efficacy), others address beliefs about succeeding as a learner in online environments (online learning self-efficacy), and others concern domain-specific clinical competence beliefs that happen to be measured within digitally delivered training. These are related but distinct constructs with different antecedents and implications for instructional design [ 9 , 10 ]. Despite a growing empirical literature spanning more than a decade, no comprehensive scoping review has mapped how self-efficacy is conceptualized, measured, associated with learner and contextual factors, and promoted through interventions specifically in digital nursing education. A scoping review is warranted because the evidence base is broad, methodologically heterogeneous, and still emerging conditions suited to evidence mapping rather than quantitative pooling [ 11 , 12 ]. Research questions (1) How is self-efficacy conceptualized and measured in digital nursing education? (2) What learner, faculty, contextual, and instructional factors are associated with self-efficacy in digital nursing education? (3) What digital interventions and strategies are reported to improve, reduce, or have no effect on self-efficacy outcomes? Methods Design and framework This scoping review followed Arksey and O'Malley's five-stage methodological framework [ 11 ], refined by Levac et al. [ 12 ], and reported in accordance with PRISMA-ScR [ 13 ]. A scoping review was selected over a systematic review because the aim was to map the breadth and nature of available evidence rather than to pool effect estimates or conduct a formal risk-of-bias appraisal. Population, concept, and context (PCC) framework Population Nursing students at all levels (undergraduate, graduate, post-licensure), nursing faculty, and nurse preceptors involved in teaching-learning activities in digital environments. Studies of faculty or preceptors were included when outcomes could be referenced to the nursing education context. Studies were excluded when participants had no substantive educational connection to nursing for instance, studies exclusively of fully licensed practicing nurses with no educational component, patient self-management studies, or health disciplines without a nursing population. Concept : Self-efficacy as defined or operationalized in any form: domain-specific clinical self-efficacy (e.g., confidence in infection control), academic self-efficacy (e.g., beliefs about learning performance), computer or technology self-efficacy (e.g., confidence in using digital platforms), or online learning self-efficacy. Adjacent constructs operationally equivalent to self-efficacy, perceived clinical competence, and self-assessed teaching efficacy were included when measured using validated SE instruments or described explicitly as SE constructs. Context Any technology-mediated or digitally enhanced nursing education context, including asynchronous online modules, synchronous virtual instruction, virtual or mixed reality simulation, mobile application-based learning, AI-assisted or chatbot-based tools, gamified platforms, metaverse environments, flipped classroom designs, blended or hybrid programs, and distance education. Studies conducted entirely in face-to-face settings without a digital component were excluded. Search strategy A structured search was conducted across five databases: MEDLINE, PsycINFO, CINAHL, Education Source, and Web of Science. Three Boolean strings were combined with AND: (1) digital and technology-mediated learning (e.g., "digital* learn*," "e-learning*," "virtual* teach*," "metaverse education*"); (2) nursing populations (e.g., "nursing student*," "nursing education*," "nurse preceptor*," "nursing faculty"); and (3) self-efficacy ("self efficacy" OR "self-efficacy"). All publications through December 31, 2025 were eligible. No language or design filters were applied. The full search strategy is in Appendix 1. The initial search yielded 800 citations: MEDLINE (n = 258), PsycINFO (n = 83), CINAHL (n = 160), Education Source (n = 131), and Web of Science (n = 168). Following deduplication, supplementary Google Scholar hand searching and backward/forward citation tracking were performed. The nursing-specific extraction table contained 72 rows; three exact duplicate entries were identified during data cleaning and removed. The final corpus comprised 69 unique studies. Data extraction and synthesis Data were extracted by the lead author into a structured 10-variable form: (1) author and year; (2) country and timeframe; (3) sample size and design; (4) sample characteristics; (5) sampling technique; (6) how self-efficacy was defined; (7) scales or instruments used; (8) interventions or strategies; (9) correlates or factors associated with SE; and (10) SE outcomes. The complete extraction table is presented in Table 1 . No formal risk-of-bias appraisal was conducted, consistent with scoping review methodology [ 11 , 12 ]. Narrative synthesis was adopted, with quantitative outcomes reported descriptively. Null and negative findings were identified and reported alongside positive findings. Table 1 Summary of the findings Author (Year) Country Sample & Design Population Sampling SE Defined As SE Instrument(s) Intervention / Strategy Correlates of SE SE Outcome Patton (2018) [ 43 ] USA 52 undergraduate and 22 graduate nursing students; pretest-posttest study Senior nursing students and first-year graduate students Convenience sampling Belief in one's ability to assess fall risk in older adults Self-efficacy survey Online fall prevention education and practical assessment Prior experience with fall risk assessment Increased self-efficacy in fall risk assessment after training Buthelezi (2020) [ 39 ] South Africa 60 postgraduate nursing students; exploratory quantitative study Postgraduate nursing students Purposive convenience sampling Confidence in using e-learning platforms for professional learning Self-reported questionnaire Training and technical support for using Moodle Proficiency in English, computer literacy, access to technology Higher self-efficacy in using e-learning after training Chang (2020) [ 57 ] Taiwan 36 nursing students; experimental study Nursing students in neonatal health care training Random assignment Belief in one's ability to handle neonatal health care cases RSI-based flipped classroom approach RSI-based flipped classroom model Critical thinking, decision-making skills Improved self-efficacy, learning satisfaction, and critical thinking Hampton (2020) [ 46 ] USA N/A (faculty study); survey-based study Nursing faculty in online education Self-efficacy in online teaching Self-efficacy and satisfaction survey Training and support for online teaching Experience with online teaching, institutional support Higher self-efficacy and satisfaction in online teaching after training Kim & Jeon (2020) [ 42 ] South Korea 205 nursing students; cross-sectional study Nursing students in two colleges Convenience sampling Self-efficacy in online education and digital literacy eHealth literacy scale, digital literacy scale Online learning and ICT integration in nursing education Academic level, digital literacy, access to ICT Higher eHealth literacy with improved digital literacy and self-efficacy Koca & Arkan (2020) [ 15 ] Turkey 127 experimental, 108 control; randomized controlled trial Third-year nursing students in disaster preparedness training Random assignment Self-efficacy in disaster response and management Disaster Response Self-Efficacy Scale (DRSES) Jennings Disaster Nursing Management Model-based training Previous exposure to disaster management training Increased disaster response self-efficacy and preparedness perceptions Lin (2020) [ 58 ] Taiwan 102 nursing students; quasi-experimental study Nursing students in an introductory computer science course Purposive sampling Self-efficacy in information security literacy Information security literacy pre/post-tests Blended assessment strategy using audience response system and online system Prior knowledge of information security, learning environment stimulation Higher self-efficacy, motivation, and learning outcomes in information security Mun & Hwang (2020) [ 55 ] South Korea 56 clinical nurses; randomized controlled trial Clinical nurses in oncology settings Randomized selection Self-efficacy in anticancer chemotherapy nursing Self-efficacy scale for chemotherapy nursing Web-based learning course for chemotherapy nursing Prior education and experience with chemotherapy nursing No significant difference in self-efficacy between web-based and lecture-based training Wu et al. (2020) [ 27 ] Singapore 150 nurse preceptors; quasi-experimental study Registered nurse preceptors in a clinical teaching blended learning program Convenience sampling Self-efficacy in clinical teaching and assessment Preceptor self-efficacy questionnaire Clinical Teaching Blended Learning (CTBL) with web-based pedagogy and case-based learning Prior teaching experience, attitudes toward online learning Increased clinical teaching competence and self-efficacy Beasley (2021) [ 17 ] USA 71 nurse practitioner and medical students; quasi-experimental study Medical and nurse practitioner students in antepartum depression screening training Convenience sampling Self-efficacy in antepartum depression screening and education Physician/Nurse Practitioner Student Teaching Self-Efficacy Questionnaire Online educational intervention using a virtual learning platform Motivation for maternal depression screening, prior mental health education Increased self-efficacy, knowledge, and motivation for antepartum depression screening Berga et al. (2021) [ 56 ] Canada 217 nursing students; quasi-experimental pre-post study Undergraduate nursing students in health assessment course Convenience sampling Self-efficacy in nursing health assessment training Self-efficacy scale for nursing assessment Blended learning versus face-to-face learning in health assessment Learning preferences, prior exposure to blended learning No significant difference in self-efficacy between blended and face-to-face learning groups Culp-Roche et al. (2021) [ 45 ] USA 84 nursing faculty; cross-sectional study Nursing faculty transitioning to online teaching during COVID-19 Convenience sampling Online teaching self-efficacy Michigan Nurse Educators Sense of Efficacy for Online Teaching (MNESEOT) Sudden transition to online teaching due to COVID-19 Prior online teaching experience, instructional support Higher online teaching self-efficacy in faculty with prior online teaching experience Fung et al. (2021) [ 3 ] Hong Kong 188 final-year undergraduate nursing students; pre-post study Final-year nursing students in a virtual simulation education program Convenience sampling Self-efficacy in clinical competence and decision-making Self-efficacy scale for clinical competence Virtual simulation combined with facilitated debriefing Prior clinical exposure, familiarity with virtual learning Improved self-efficacy in clinical competence and decision-making Gulley et al. (2021) [ 2 ] USA 44 nursing students; pilot study Associate degree nursing students transitioning to online learning Volunteer sampling Self-efficacy in passing NCLEX-RN and clinical skill competence General Self-Efficacy Scale Transition to online learning due to COVID-19 pandemic Confidence in NCLEX-RN preparation, adaptation to online learning Perceived self-efficacy declined due to online transition, impacting NCLEX-RN confidence Lin et al. (2021) [ 4 ] Taiwan Nurse practitioner students; experimental study Nurse practitioners in online interactive peer-review training Random assignment Self-efficacy in critical thinking and decision-making Self-efficacy scale for nursing decision-making Interactive peer-review approach in flipped learning Prior experience with peer review, learning engagement Higher critical thinking, self-efficacy, and reflection in interactive peer-review group Maenhout et al. (2021) [ 30 ] Belgium 71 nurses and midwives; quasi-experimental study Nurses and midwives in a neonatal intensive care unit (NICU) Convenience sampling Self-efficacy in handling acute patient deterioration events Clinical Decision-Making Self-Confidence Scale (CDMSCS) Repeated high-fidelity in situ simulation-based training Years of NICU experience, exposure to high-risk scenarios Improved self-efficacy and leadership abilities, no significant change in team performance Rohmani & Andriani (2021) [ 7 ] Indonesia 69 first-year nursing students; correlational study Nursing students in distance learning during COVID-19 Convenience sampling Academic self-efficacy in distance learning Academic Self-Efficacy Questionnaire [ 69 ] Online learning during the pandemic Self-directed learning ability, academic workload, burnout levels Higher self-efficacy correlated with lower burnout; moderate self-efficacy linked to severe burnout Smith et al. (2021) [ 53 ] USA 17 nursing students and 15 faculty; qualitative study Undergraduate and graduate nursing students and faculty Purposive sampling Self-efficacy in online learning and teaching effectiveness Focus group interviews with open-ended questions Exploring factors influencing online teaching effectiveness Technology skills, faculty engagement, course structure Higher self-efficacy in students linked to instructor presence and interactive learning experiences Vance et al. (2021) [ 29 ] USA 43 medical trainees; mixed-methods study Fourth-year medical students, pediatrics interns, psychiatry interns, and nurse practitioners Convenience sampling Self-efficacy in gender-affirming communication with transgender youth Pre- and post-self-efficacy assessment Standardized patient encounters combined with e-learning modules Prior experience working with transgender patients Improved self-efficacy and communication skills in gender-affirming care Beck (2022) [ 69 ] USA 17 oncology nurses; quasi-experimental mixed-methods study Oncology nurses participating in an online communication intervention Purposive sampling Self-efficacy in conducting spiritual histories for cancer patients Pre- and post-Spiritual History Self-Efficacy assessment Lift the Spirit educational communication intervention Practice opportunities, confidence in spiritual discussions Increased self-efficacy and confidence in conducting spiritual histories Can et al. (2022) [ 44 ] Turkey 60 nursing students; randomized controlled study First-year nursing students Random assignment Self-efficacy in communication skills and self-regulated learning General Self-Efficacy Scale (GSE), Effective Communication Skills Scale (ECSS) Online communication skills training Training exposure, self-regulation skills No significant impact on self-efficacy despite improved communication skills Najafi et al. (2024) [ 60 ] Iran n = 68 nursing students; quasi-/semi-experimental study with control and intervention groups Sixth-semester undergraduate nursing students Convenience sampling with random allocation to groups (dice method) Educational self-efficacy: belief in one’s capability to perform learning tasks and acquire knowledge (Bandura-based framing) Self-Efficacy Questionnaire (SEQ) (17 items; Likert 1–5; score range 17–85) Online gamification-based learning using Storyline platform + Kahoot (puzzles, clinical scenarios, competitions, progressive difficulty); 3 sessions (2 hours each) Not primary focus; intervention-based change (gamification vs lecture) Significant increase in self-efficacy in intervention group (Post: 65.29 ± 3.97 vs control 48.18 ± 5.36, p = 0.006; paired t-test p = 0.023); no significant change in control group Chang et al. (2022) [ 59 ] Taiwan 45 first-year nursing students; quasi-experimental study Nursing students in sputum suction skill training Random assignment Self-efficacy in clinical nursing skills Pre-post self-efficacy assessments Online game-based learning with the watch-summarize-question strategy Learning engagement, teaching strategy effectiveness Higher self-efficacy, learning satisfaction, and engagement Enyan et al. (2022) [ 38 ] Ghana 45 nurse preceptors; mixed-methods interventional study Nurse preceptors in clinical training Non-randomized convenience sampling Self-efficacy in using digital technology for preceptorship Technology acceptance model questionnaire Training intervention on digital technology for clinical teaching Perceived ease of use, perceived usefulness, institutional constraints Increased self-efficacy, improved intention to use technology Fadaeinia et al. (2022) [ 24 ] Iran 80 postgraduate nursing students; quasi-experimental study Postgraduate nursing students Random assignment Self-efficacy in cultural competence and multicultural care Cultural Self-Efficacy Scale (CSES) Online cultural care training program Cultural awareness, knowledge of cultural patterns Higher self-efficacy and competence in cultural care Garber & Gustin (2022) [ 26 ] USA Advanced practice nurses; quasi-experimental study Advanced practice registered nurses (APRNs) Convenience sampling Self-efficacy in telehealth education and adoption Pre- and post-telehealth self-efficacy assessment Online telehealth education program Previous experience with telehealth, institutional support Increased self-efficacy and confidence in using telehealth Han et al. (2022) [ 50 ] USA 113 ESL nursing students; path analysis study Undergraduate ESL nursing students Convenience sampling Academic self-efficacy in online learning Self-efficacy Formative Questionnaire Analysis of factors influencing self-efficacy (perfectionism, acculturative stress) Perfectionistic concerns, acculturative stress, e-learning stress Lower self-efficacy associated with higher acculturative stress and perfectionism Hidayati et al. (2022) [ 41 ] Indonesia 298 nursing students; cross-sectional study Nursing students in online learning during COVID-19 Consecutive sampling Self-efficacy and anxiety correlation in online learning General Self-Efficacy Questionnaire (GSE), Hamilton Anxiety Rating Scale (HARS) Assessment of anxiety and self-efficacy in online learning Psychological stress, learning format adaptation Higher self-efficacy correlated with lower anxiety Hwang et al. (2022) [ 76 ] Taiwan 40 senior nursing students; quasi-experimental study Senior nursing students in a virtual patient-based social learning program Random assignment Self-efficacy in clinical judgment and communication Pre- and post-self-efficacy assessments Virtual patient-based social learning approach Learning engagement, interaction with digital patients Improved self-efficacy in communication and clinical judgment Jeon & Kim (2022) [ 49 ] South Korea 259 nursing students; cross-sectional study Undergraduate nursing students in online learning Convenience sampling Self-efficacy in digital literacy and eHealth literacy Self-efficacy for online education scale Analysis of the mediating role of self-efficacy in eHealth literacy Attitudes toward online learning, digital literacy Higher self-efficacy in digital literacy linked to improved eHealth literacy Liaw et al. (2023) [ 28 ] Singapore 59 nurse preceptors; mixed-methods study Nurse preceptors in an online telesimulation training program Convenience sampling Self-efficacy in nurse preceptorship and clinical teaching Preceptor Self-Efficacy Questionnaire (PSEQ) Telesimulation-based online preceptor training Collaboration with academic institutions, digital teaching strategies Improved self-efficacy and preparedness for clinical preceptorship Naciri et al. (2022) [ 54 ] Morocco 20 nursing students; pre-experimental study Nursing students in a flipped classroom intervention Convenience sampling Self-efficacy for learning and performance Motivated Strategies for Learning Questionnaire (MSLQ) Comparison of traditional vs. flipped classroom teaching Extrinsic motivation, self-regulation Higher self-efficacy and performance in flipped classroom group Park & Seo (2022) [ 35 ] South Korea 245 nursing students; mixed-methods study Undergraduate nursing students during COVID-19 Convenience sampling Self-efficacy in clinical practice during online learning Stepwise multiple regression analysis Virtual clinical training and self-regulated learning interventions Learning motivation, lecture type (recorded vs. live) Higher self-efficacy linked to improved learning flow and motivation Warshawski (2022) [ 8 ] Israel 222 first-year nursing students; cross-sectional study Nursing students in online learning during COVID-19 Convenience sampling Academic self-efficacy in online environments Survey using resilience and social support scales Assessment of social support and resilience factors Gender, cultural background, perceived difficulty in studies Resilience and social support positively correlated with self-efficacy Yang and Kim (2022) [ 70 ] South Korea 55 nursing students; quasi-experimental study Final-year nursing students in communication training Random assignment Self-efficacy in nonviolent communication skills Pre- and post-self-efficacy assessment Online nonviolent communication training Empathy, workplace stress management Improved self-efficacy in communication, empathy, and teamwork Youngwanichsetha (2022) [ 71 ] Thailand 80 nursing students; quasi-experimental study Third-year nursing students in maternal-newborn care Systematic random sampling Self-efficacy in nursing care for pregnant women with diabetes Pre- and post-self-efficacy survey Online computer-assisted instruction (CAI) Engagement in digital learning, teaching strategy effectiveness Higher self-efficacy and knowledge retention with Cai Yu & Yang (2022) [ 19 ] South Korea 50 nursing students; quasi-experimental study Nursing students in infection control training Random assignment Self-efficacy in infection control procedures Pre- and post-self-efficacy assessment Virtual reality infection control simulation (VRICS) Immersion level, previous clinical exposure Improved self-efficacy, infection control performance, and learning satisfaction Zarshenas et al. (2022) [ 72 ] Iran 46 nursing students; quasi-experimental study Nursing students in clinical education Random assignment Self-efficacy in clinical learning Pre- and post-self-efficacy evaluation Micro-learning-based e-learning intervention Multimedia learning strategies, student engagement Higher self-efficacy and improved clinical learning outcomes Chiu & Liu (2022) [ 64 ] Taiwan 80 nurses; quasi-experimental study Nursing personnel in non-pharmacological pain management training Convenience sampling Self-efficacy in aromatherapy-based pain management Self-efficacy and knowledge assessment Flipped teaching intervention with video-based pre-learning Pre-class preparation, interactive learning Significant improvement in self-efficacy and knowledge compared to traditional teaching DeFusco et al. (2023) [ 21 ] USA 40 critical care nurses; quasi-experimental study Critical care nurses receiving online palliative care training Convenience sampling Self-efficacy in providing palliative care Palliative Care Self-Efficacy Scale Online palliative care education using VitalTalk resources Previous palliative care experience, training accessibility Improved self-efficacy in psychosocial support and symptom management Fitriawan et al. (2023) [ 10 ] Indonesia 500 nursing students: Cross-sectional Nursing students from three universities Consecutive sampling Online learning self-efficacy Online Learning Self-Efficacy Scale (OLSES) Online learning training, technical assistance, psychological support Psychological distress (negative correlation), online learning readiness (positive correlation) Improved online learning readiness García-Pazo et al. (2023) [ 67 ] Spain 111 nursing students: Cross-sectional Third-year nursing students, no prior ICU experience Not mentioned Confidence in performing nursing assessments in ICUs Self-efficacy perception questionnaire Virtual reality-based training Immersion in virtual reality, exposure to ICU environment Enhanced skill acquisition, increased confidence Hwang et al. (2023) [ 23 ] Taiwan 38 nursing students: Experimental Two groups: one using DRI approach, one using conventional tech-assisted approach Not mentioned Competence in making correct judgments on real cases Not explicitly mentioned Technology-supported Decision, Reflection, and Interaction (DRI) approach Decision-making, reflection, interaction Improved learning achievement and self-efficacy Ibrahim & Aldawsari (2023) [ 51 ] UAE, Egypt 200 nursing students: Cross-sectional, correlational Nursing students from two universities Not mentioned Confidence in digital learning and academic performance General Self-Efficacy Scale Improving digital capabilities Digital capabilities Improved academic performance Jiang et al. (2023) [ 14 ] China 3733 nursing and midwifery students: Cross-sectional Students from seven provinces Not mentioned Belief in ability to engage in home-based e-learning General Self-Efficacy Scale Not explicitly mentioned Self-control, province, grade level, health status Better home-based e-learning behavior Kasar (2023) [ 22 ] Turkey 46 nursing students: Quasi-experimental 4th-year nursing students, majority female Not mentioned Self-efficacy in palliative care General Self-Efficacy Scale, Palliative Care Self-Reported Practices Scale Online palliative care course Not explicitly mentioned Improved self-efficacy in palliative care practices Thangam et al. (2023) [ 40 ] Saudi Arabia 250 undergraduate students: Cross-sectional Nursing students, majority female Not mentioned Confidence in e-learning during emergent transitions Self-Efficacy Questionnaire for Online Learning (SeQoL) Not explicitly mentioned Device used, previous online exposure, hours of online learning Mixed levels of online learning self-efficacy Wada et al. (2023) [ 48 ] USA Healthcare students: Experimental Social work, nursing, medical students Not mentioned Confidence in interprofessional end-of-life discussions Self-Efficacy for Interprofessional Experiential Learning (SEIEL) survey Simulation-based pediatric ACP training Interprofessional collaboration, realism of scenarios Improved confidence in end-of-life discussions Wolf & Wolf (2023) [ 47 ] USA Master's nursing students: Quasi-experimental Graduate-level nursing students Not mentioned Confidence in scholarly writing and research-based writing SAWSES self-efficacy survey AI-assisted online writing course AI-based feedback, structured writing support Improved writing self-efficacy and performance Squires et al. (2023) [ 65 ] USA Nursing students: Experimental Undergraduate nursing students Not mentioned Confidence in online simulation-based skill training Scenario-based online self-efficacy assessment Online clinical simulations Cognitive load, motivation Enhanced self-efficacy and skill transferability Takashiki et al. (2023) [ 31 ] Japan 37 novice nurses: Single-cohort study Second-year clinical nurses Convenience sampling Confidence in managing acute chest pain patients Pre-post self-efficacy and performance assessment Hybrid simulation-based mastery learning E-learning, hands-on simulation Improved performance and self-efficacy retained post-intervention Taylor et al. (2023) [ 73 ] Australia 717 first-year nursing students: Cross-sectional First-year nursing students, diverse backgrounds Not mentioned Confidence in clinical placement readiness Not explicitly mentioned Online interactive case studies English as an additional language, task value Increased self-efficacy for clinical placement Kim & Kim (2023) [ 32 ] South Korea 43 nursing students: Mixed-methods study Undergraduate nursing students Not mentioned Career decision-making self-efficacy Pre-post self-efficacy and satisfaction survey Metaverse-based career mentoring Realistic communication, mentoring interactivity Increased career decision-making self-efficacy Zhang et al. (2023) [ 5 ] China 48 distance vs. 36 face-to-face students: Quasi-experimental Nursing students in Sino-foreign cooperative program Not mentioned Academic self-efficacy in distance learning Self-efficacy questionnaire, academic engagement scale Distance education model Learning behavior self-efficacy, engagement Lower performance in distance learning vs. face-to-face Galan-Lominchar et al. (2024) [ 63 ] Spain, USA 70 nursing students: Quasi-experimental Undergraduate nursing students Not mentioned General self-efficacy in nursing education General Self-Efficacy Scale Internationalization at home program (Global Nursing Care) Virtual exchange, international clinical simulation Improved general self-efficacy in nursing students Gonçalves et al. (2024) [ 66 ] Brazil 39 undergraduate nursing students: Descriptive study Undergraduate nursing students Not mentioned Self-efficacy in telesimulation for pediatric and neonatal nursing Validated self-efficacy and self-confidence scales Expert-modeling videos in telesimulation Simulation engagement, remote learning advantages High self-confidence, self-efficacy, and satisfaction Chen et al. (2024) [ 37 ] China 329 medical and nursing students: Survey-based study Medical and nursing students using LMSs Not mentioned Computer self-efficacy and LMS satisfaction Technology Satisfaction Model framework Online LMS-based education Perceived ease of use, perceived usefulness Higher self-efficacy led to greater LMS satisfaction Demirelli & Karaçay (2024) [ 9 ] Turkey 632 nursing students: Cross-sectional Undergraduate nursing students Not mentioned Online learning self-efficacy Online Learning Self-Efficacy Scale Not explicitly mentioned Technology skills, study time, satisfaction Higher online self-efficacy correlated with engagement and success El-Gazar et al. (2024) [ 34 ] Egypt 208 nursing students: Cross-sectional Undergraduate nursing students Convenience sampling Academic self-efficacy in e-learning Academic Self-Efficacy Scale, Online Learning Readiness Scale Not explicitly mentioned E-learning readiness, GPA correlation Higher readiness and self-efficacy led to better academic achievement Hemmati Malsakpak & Pourteimour (2024) [ 33 ] Iran 70 undergraduate nursing students: Quasi-experimental Undergraduate nursing students Census sampling Academic self-efficacy in blended learning College Academic Self-Efficacy Scale (CASES) E-learning blended with collaborative learning and lecture-based teaching Collaboration, technical support Higher self-efficacy scores post-intervention, especially among female students Huang and Lee (2024) [ 74 ] Taiwan Nursing students: Quasi-experimental Pediatric nursing students Not mentioned Confidence in using AI-assisted tools in pediatric care Not explicitly mentioned AI-driven therapeutic games and health education e-books Fear reduction in children, interactive learning Increased self-efficacy in pediatric care Jeon H. et al. (2024) [ 62 ] South Korea 428 participants: Cross-sectional Nurses and nursing students Not mentioned Metaverse self-efficacy in nursing education Metaverse presence and usability assessment Interaction with metaverse platforms (ZEPETO, Gather) Platform usability, prior experience Higher self-efficacy in nurses than students; usability impacted learning outcomes Jeon Y. et al. (2024) [ 68 ] South Korea 80 nursing students: Randomized controlled trial Third- and fourth-year nursing students Not mentioned Self-efficacy in communication skills Pre-post self-efficacy survey Technology-based interactive communication simulation Empathy, knowledge retention Improved self-efficacy in handling communication challenges Makhlouf et al. (2024) [ 61 ] Saudi Arabia 73 nurses: Quasi-experimental Practicing nurses Purposive sampling Self-efficacy in AI chatbot-assisted nursing education Pre-post chatbot knowledge assessment AI chatbot integrated into nursing training Knowledge access, real-time support Improved knowledge and self-efficacy in chatbot-assisted learning Maynard et al. (2024) [ 25 ] USA 187 healthcare professionals: Quality improvement study Clinicians, nurses, clinical staff Not mentioned Confidence in recommending HPV vaccination Pre-post self-efficacy assessment HPV CHAT training on vaccine communication Motivational interviewing, bundled recommendations Improved self-efficacy and routine recommendation rates Moon et al. (2024) [ 20 ] South Korea 39 nursing students: Pretest-posttest study Senior nursing students Convenience sampling Confidence in managing acute coronary syndrome (ACS) Self-efficacy in learning survey Mixed reality-based ACS simulation Simulation immersion, hands-on practice Improved knowledge, self-efficacy, and performance Ko & Choi (2024) [ 16 ] South Korea 104 nurses: Randomized controlled trial Nurses working in general hospitals Not mentioned Self-efficacy in providing psychological support for infectious disease patients Self-efficacy and disaster competence assessment Virtual nursing simulation-based education Problem-solving, self-leadership, motivation to transfer knowledge Higher self-efficacy and competence in disaster mental health support Tornwall and Ikonen (2024) [ 75 ] USA, Finland Nursing students: Survey-based study Nursing students in global online education Not mentioned Self-efficacy in receiving and providing peer feedback Student engagement and feedback receptivity scale Online peer-to-peer feedback training Receptiveness to feedback, learning engagement Higher confidence in using feedback effectively Yossatorn et al. (2024) [ 36 ] Thailand University students: Cross-sectional study Undergraduate nursing students Not mentioned Academic self-efficacy in online learning Expectancy-value theory framework Online self-regulated learning strategies Self-regulation, task value, learning motivation Higher self-efficacy in students with strong self-regulation Note. CASES = College Academic Self-Efficacy Scale; CDMSCS = Clinical Decision-Making Self-Confidence Scale; CSES = Cultural Self-Efficacy Scale; DRSES = Disaster Response SE Scale; GSE = General SE Scale (Schwarzer); MNESEOT = Michigan Nurse Educators SE for Online Teaching; MSLQ = Motivated Strategies for Learning Questionnaire; NVC = nonviolent communication; OLSES = Online Learning SE Scale; PSEQ = Preceptor SE Questionnaire; RCT = randomized controlled trial; SAWSES = Self-Assessment Writing SE Scale; SE = self-efficacy; SEIEL = SE for Interprofessional Experiential Learning; SeQoL = SE Questionnaire for Online Learning; VR = virtual reality; VPLSE = Virtual Patient Learning System Evaluation. Author names with encoding characters (GarcÃa-Pazo = García-Pazo; Gonçalves = Gonçalves) reflect source file encoding and should be corrected before publication Results Study characteristics The 69 unique studies were published between 2018 and 2025 (Table 1 ), with the majority (n = 50, 72.5%) published between 2022 and 2025, reflecting the surge in digital nursing education research following the COVID-19 pandemic. Studies were conducted across 25 countries. The USA was the most frequently represented (n = 15, 21.7%), followed by South Korea (n = 11, 15.9%), Taiwan (n = 9, 13.0%), Turkey (n = 4, 5.8%), Indonesia (n = 3, 4.3%), Iran (n = 3, 4.3%), and China (n = 3, 4.3%). Other contributing countries included Saudi Arabia, Singapore, Thailand, South Africa, Canada, Belgium, Hong Kong, Israel, Morocco, Japan, Spain, Brazil, Egypt, UAE, Finland, Ghana, and Jordan. Study designs included quasi-experimental (n = 23, 33.3%), cross-sectional (n = 15, 21.7%), experimental (n = 7, 10.1%), randomized controlled trial (RCT; n = 5, 7.2%), mixed-methods (n = 5, 7.2%), pre-post or pilot (n = 4, 5.8%), single-cohort or other (n = 6, 8.7%), descriptive/exploratory (n = 2, 2.9%), correlational (n = 1, 1.4%), and qualitative (n = 1, 1.4%). Sample sizes ranged from 17 to 3,733 [ 14 ], with a median of 72. Convenience sampling was most common (n = 26); sampling was not reported in approximately 34% of studies. The full screening and selection process is illustrated in the PRISMA flow diagram (Fig. 1 ). The population breakdown was: undergraduate nursing students (n = 32, 46.4%), graduate or postgraduate nursing students (n = 16, 23.2%), clinical or practicing nurses (n = 7, 10.1%), faculty or preceptors (n = 6, 8.7%), and mixed or other populations (n = 8, 11.6%). In terms of digital modality, online modules and e-learning platforms were most prevalent (n = 28, 40.6%), followed by simulation-based approaches (n = 12, 17.4%), observational or factor studies without active intervention (n = 4), flipped classroom designs (n = 4), blended or hybrid learning (n = 4), and emerging modalities including gamification (n = 2), metaverse or XR (n = 2), mobile or AI chatbot (n = 2), and AI-assisted learning (n = 1). Conceptualization and measurement of self-efficacy Four-domain typology Systematic review of SE definitions across all 69 studies (Table 1 , column 6) revealed four interrelated but conceptually distinct domains.Domain-specific clinical self-efficacy was the most prevalent, appearing in approximately 36 studies. It was defined as belief in the ability to perform specific professional nursing competencies: disaster response [ 15 , 16 ]; depression screening [ 17 , 18 ]; infection control [ 19 ]; acute coronary syndrome management [ 20 ]; palliative care [ 21 , 22 ]; clinical judgment using a decision-reflection-interaction approach [ 23 ]; cultural competence [ 24 ]; HPV vaccine recommendation [ 25 ]; telehealth [ 26 ]; clinical teaching and preceptorship [ 27 , 28 ]; gender-affirming communication [ 29 ]; neonatal and acute care [ 30 , 31 ]; and career decision-making [ 32 ]. This domain-specificity is consistent with Bandura's conceptualization of SE as task-referenced. Academic self-efficacy referred to beliefs about general scholarly task performance and featured in approximately 18 studies — prominently in pandemic-era research [ 7 , 8 , 2 , 5 ], blended learning adoption [ 33 , 34 ], and self-regulated learning contexts [ 35 , 36 ]. Instruments included the College Academic Self-Efficacy Scale [ 33 ] and the Academic SE Questionnaire [ 7 ]. Computer and technology self-efficacy captured beliefs about using digital tools and navigating online platforms. It appeared in approximately 12 studies, most centrally in examinations of LMS satisfaction [ 37 ], technology acceptance [ 38 ], and e-learning readiness [ 34 , 39 ]. The largest study in the corpus, Jiang et al. [ 14 ], with 3,733 Chinese nursing and midwifery students across seven provinces, confirmed self-control and general SE as significant predictors of home-based e-learning behavior (β = 0.250 and β = 0.169 respectively). Online learning self-efficacy represented an integrated construct about succeeding in technology-mediated environments. It was measured with the OLSES in two studies [ 10 , 9 ] and the SeQoL in one [ 40 ]. Demirelli & Karacay [ 9 ], in 632 Turkish nursing students, reported a mean OLSES score of 74.54, with female students scoring significantly higher than males (75.53 vs. 70.61). Measurement instruments and heterogeneity Over 25 distinct instruments were identified. Ad hoc or self-developed scales predominated (n ≈ 22), followed by the General Self-Efficacy Scale (Schwarzer; n = 8) (Jiang et al., 2023; Warshawski, 2022; Buthelezi & Wyk, 2020; Demirelli & Karaçay, 2024; Hidayati et al., 2022; Kim & Jeon, 2020; Patton, 2018; Can et al., 2022), OLSES (n = 2) [ 10 , 9 ], and Technology Acceptance Model-derived SE items (n = 2) [ 37 , 38 ]. Validated domain-specific instruments included the DRSES [ 15 ], CDMSCS [ 30 ], PSEQ [ 27 ], CASES [ 33 ], MNESEOT [ 45 , 46 ], SAWSES [ 47 ], CSES [ 24 ], Palliative Care SE Scale [ 21 ], SEIEL [ 48 ], and VPLSE [ 32 ]. A key limitation was construct drift: some studies used SE, confidence, perceived competence, and self-assessed readiness interchangeably. Several studies employed structural equation modeling or path analysis to situate SE within nomological networks alongside digital literacy, engagement, burnout, and motivation [ 49 , 7 , 50 , 51 ], providing theoretically richer operationalizations than pre-post designs. Factors associated with self-efficacy Prior experience Prior clinical, academic, or teaching experience was the most consistently documented positive correlate, appearing in approximately 26 studies. Faculty SE was highest among those with prior online teaching experience and institutional support [ 45 , 46 ]. Wu et al. [ 27 ] found a significant pre-post SE gain (59.00 to 70.40; p < 0.001) among 150 Singapore nurse preceptors following blended preceptor training. Maenhout et al. [ 30 ] found years of NICU experience moderated simulation-based SE gains. Lin et al. [ 52 ] found VR-based flipped learning most benefited those with low baseline confidence. Digital literacy and technology capability Digital literacy was a consistently positive correlate across approximately 14 studies. Demirelli & Karacay [ 9 ] showed that high-technology skills significantly predicted OLSES scores. Kim & Jeon [ 42 ] found digital literacy predicted eHealth literacy and SE among 205 Korean nursing students. Jeon & Kim [ 49 ] confirmed digital literacy partially mediated between learning attitudes and eHealth literacy in 259 nursing students. Ibrahim & Aldawsari [ 51 ] found digital capabilities predicted academic performance through SE as a mediator. Fitriawan et al. [ 10 ], in 500 Indonesian students, found online learning readiness positively correlated with SE while psychological distress was negatively correlated. Buthelezi and Wyk [ 39 ] identified computer literacy, English proficiency, and technology access as joint correlates of SE in South African postgraduate students. Self-regulation, motivation, and task value Self-regulation and intrinsic motivation were robust positive predictors across approximately 14 studies. Jiang et al. [ 14 ] confirmed self-control as a significant independent predictor of e-learning behavior alongside SE in 3,733 students. Park and Seo [ 35 ] found learning flow and self-regulation positively associated with SE in 245 Korean students, with live synchronous lectures producing higher SE than recorded asynchronous ones. Yossatorn et al. [ 36 ] confirmed, using an expectancy-value framework, that self-regulation and task value were the strongest SE predictors among Thai nursing students. Taylor et al. [ 73 ], in 717 first-year Australian nursing students, found high SE (AOR = 2.82) and task value (AOR = 5.05) were the strongest predictors of perceived usefulness of online interactive case studies in preparing for clinical placement, with students using English as an additional language and those with lower GPA also significantly more likely to benefit. Naciri et al. [ 54 ] found higher SE and performance in a flipped classroom group using the MSLQ. Wolf and Wolf [ 47 ] found AI-evaluated feedback produced significant SE gains (writing essentials d = 0.96; reflective writing d = 1.10) in graduate nursing students, confirming that structured scaffolding can drive SE in complex cognitive domains. Psychosocial stressors and the COVID-19 context Psychosocial stressors were consistently negative correlates across approximately 12 studies. Rohmani et al. [ 7 ] found a non-linear SE-burnout relationship: higher SE predicted lower burnout, while moderate SE paradoxically linked to severe burnout. Warshawski [ 8 ] identified resilience and social support as protective SE correlates in 222 Israeli first-year nursing students, while perceived study difficulty was negative. Hidayati et al. [ 41 ] confirmed SE negatively correlated with anxiety in 298 Indonesian students. Han et al. [ 50 ] found acculturative stress and perfectionism negatively predicted SE in 113 ESL nursing students in the USA, with equity implications for international students. Forced COVID-19 transitions produced some of the clearest negative SE findings in the corpus. Gulley et al. [ 2 ] documented SE decline and reduced NCLEX-RN confidence in 44 nursing students following unplanned online transition. Zhang et al. [ 5 ] found lower academic performance and engagement in distance versus face-to-face nursing students. These findings are critically important: they demonstrate that digitalization per se does not improve SE and that inadequate preparation, psychosocial support, and instructional quality are determinants of SE outcomes. Gender Gender effects were present but population-specific. Female nursing students reported higher online learning SE than males in multiple contexts [ 9 , 33 , 10 ]. Malsakpak [ 33 ] found female students in the collaborative e-learning condition showed larger SE gains (127.12 vs. 112.65, p = 0.019). These patterns suggest differential socialization with technology and professional training rather than stable gender traits. Instructional environment and social presence Social and teaching presence were significant positive correlates. Smith et al. [ 53 ] identified instructor presence and interactive course design as primary environmental contributors to student SE in a qualitative study. Tornwall and Ikonen [ 75 ] found that an asynchronous international online instructional design course significantly improved feedback SE — the perceived competence to interpret and respond to peer feedback — among 21 graduate nursing students in the US and Finland (p = 0.013), with teaching experience predicting higher baseline feedback orientation. Park and Seo [ 35 ] confirmed synchronous live lectures outperformed recorded asynchronous content for SE outcomes. Chen et al. [ 37 ] found perceived ease of use and usefulness of LMS were direct predictors of computer SE among 329 nursing and medical students. Interventions and self-efficacy outcomes Simulation-based digital learning Simulation was the most consistently effective intervention modality (n = 12 studies; positive outcomes in 11/12). Yu and Yang [ 19 ] found VR infection control simulation significantly improved SE (t = 4.93) in 50 Korean nursing students alongside performance and satisfaction. Moon et al. [ 20 ] documented significant SE, knowledge, and performance gains following mixed reality acute coronary syndrome simulation in 39 senior students. Ko and Choi [ 16 ], in an RCT of 104 Korean hospital nurses, found virtual simulation significantly improved SE and disaster mental health competence versus controls. Fung et al. [ 3 ] reported improved SE in clinical competence and decision-making following online virtual simulation with debriefing in 188 Hong Kong final-year students. García-Pazo et al. [ 67 ] found VR-based ICU training improved confidence in 111 Spanish nursing students without prior ICU experience. Squires et al. [ 65 ] found online clinical simulations enhanced SE and skill transferability during COVID-19. Gonçalves et al. [ 66 ] documented high SE and satisfaction among 39 Brazilian students following expert-modeling tele simulation. Takashiki et al. [ 31 ] found hybrid simulation-based mastery learning improved SE retained post-intervention in 37 Japanese novice nurses. Wada et al. [ 48 ] demonstrated interprofessional simulation improved SE for end-of-life discussions. Maenhout et al. [ 30 ] reported a nuanced null finding: in situ simulation improved individual SE but not team performance, distinguishing individual from collective efficacy. The mechanisms map onto Bandura's four sources: guided simulation practice creates mastery experience; expert modeling provides vicarious learning; structured debriefing delivers verbal persuasion; manageable clinical risk creates favorable affective states. Flipped classroom and active learning All four flipped classroom studies reported positive SE outcomes. Chang et al. [ 57 ] found RSI-based flipped teaching significantly improved SE, learning satisfaction, and critical thinking in 36 Taiwanese nursing students. Lin et al. [ 4 ] found interactive peer-review embedded in flipped learning improved SE, critical thinking, and reflection. Naciri et al. [ 54 ] replicated SE benefits in Moroccan students using the MSLQ. Chiu and Liu [ 64 ] found significant SE and knowledge gains in 80 Taiwanese nurses through video-based pre-learning for aromatherapy pain management. The consistent pattern is theoretically coherent: self-paced pre-class digital content enables initial mastery experiences at low stakes, while in-class application delivers social modeling, instructor feedback, and peer collaboration. Online modules and e-learning platforms Online modules were the most prevalent modality (n = 28) and produced positive SE outcomes in most studies when designed with authentic scenarios, interactive feedback, and learner control. Key positive findings include: Koca and Arkan [ 15 ], in a Turkish RCT (n = 235), found theory-grounded online disaster nursing training significantly improved SE; Beasley [ 17 ] and Link et al. [ 18 ] found online depression screening education improved SE in US nursing students and practitioners; Garber and Gustin [ 26 ] found online telehealth education improved SE and adoption confidence in APRNs; DeFusco et al. [ 21 ] found VitalTalk-based online palliative care education improved SE in 40 critical care nurses; Beck [ 69 ] found an online Lift the Spirit communication intervention significantly improved SE in conducting spiritual histories among 17 oncology nurses (Z = − 3.20, p = 0.001); Kasar [ 22 ] found an online palliative care course significantly improved SE in 46 Turkish students; Yang and Kim [ 70 ] found an online nonviolent communication training program significantly improved SE (t = 3.02, p = 0.004), empathy, and communication skills in 55 South Korean nursing students; Youngwanichsetha [ 71 ] found online computer-assisted instruction for maternal-newborn nursing care produced substantially higher SE in 80 Thai nursing students compared to lecture instruction (M = 79.00 vs. 37.25, t = 20.06, p < 0.001); and Zarshenas et al. [ 72 ] found micro-learning via short video clips significantly improved SE in 21 Iranian nursing internship students (p = 0.001; d = 0.504), while the control group receiving traditional lectures showed no SE change (p = 0.425). Fadaeinia et al. [ 24 ] found an online cultural care program significantly improved cultural SE in 80 Iranian postgraduate students; Hwang et al. [ 23 ] found the technology-supported Decision, Reflection, and Interaction (DRI) approach — combining decision-making, reflection, and guided interaction — significantly improved SE and learning achievement in 38 Taiwanese nursing students; and Wolf and Wolf [ 47 ] found AI-evaluated feedback in an online writing course produced substantial SE gains in graduate nursing students. Critical null findings qualify these positive results. Mun and Hwang [ 55 ] found in an RCT of 56 Korean clinical nurses that web-based and lecture-based chemotherapy training produced no significant SE difference the strongest null finding in the corpus, confirming that modality equivalence produces SE equivalence. Berga et al. [ 56 ] found no significant SE difference between blended and face-to-face health assessment learning in 217 Canadian students. Can et al. [ 44 ] found online communication skills training produced no significant general SE change despite improved specific skills in an RCT of 60 Turkish students. These null findings are theoretically important: delivery modality does not determine SE outcomes; instructional mechanism does. Gamification and game-based learning Both gamification studies reported positive SE outcomes. Chang et al. [ 59 ] found online game-based learning with the watch-summarize-question strategy produced higher SE, satisfaction, and engagement in 45 Taiwanese first-year nursing students. Najafi et al. [ 60 ] found gamification using Kahoot and Storyline produced higher SE and learning outcomes in 68 Iranian sixth-semester nursing students. Game mechanics provide immediate feedback, progressive challenge, and visible achievement, operationalizing Bandura's mastery experience and verbal persuasion sources simultaneously. Mobile, AI-assisted, and emerging digital modalities Mobile chatbot and AI-assisted tools produced positive SE outcomes in all three studies identified. Chang et al. [ 59 ] found a mobile chatbot approach significantly improved SE and learning achievement in 72 Taiwanese nursing students in vaccine administration training. Makhlouf et al. [ 61 ] found AI chatbot integration into nursing training improved SE and knowledge in 73 Saudi practicing nurses. Huang and Lee [ 74 ] found AI-generated image e-books (Canva AI) significantly improved nursing students’ SE in using therapeutic games with sick children compared to traditional paper handouts (β = 0.356, p < 0.05), with higher SE in the experimental group directly predicting reduced fear responses in sick children (β = −0.914, p = 0.009). Wolf and Wolf [ 47 ] demonstrated AI-evaluated online writing course feedback produced large SE gains in graduate nursing students. Metaverse-based nursing education was examined in two studies. Kim and Kim [ 32 ] found metaverse-based career mentoring significantly increased career decision-making SE in 43 Korean students. Jeon et al. [ 62 , 68 ] found platform usability and metaverse presence predicted SE in 428 Korean nurses and nursing students, with practicing nurses showing higher SE than students suggesting domain experience interacts with immersion to shape SE outcomes. Jeon et al. [ 62 , 68 , 76 ] found technology-based interactive communication simulation significantly improved SE in 80 Korean nursing students in an RCT. Galan-Lominchar et al. [ 63 ] found virtual international nursing exchange improved general SE in 70 nursing students. Blended and hybrid learning Blended learning outcomes were variable. Wu et al. [ 27 ] found a significant SE gain (59.00 to 70.40, p < 0.001) in 150 Singaporean nurse preceptors from a Clinical Teaching Blended Learning program. Liaw et al. [ 28 ] found significant SE improvement among nurse preceptors through tele-simulation-based training. Lin [ 58 ] found blended assessment with audience response systems improved SE and motivation in information security literacy. Hemmati and Pourteimour [ 33 ] found that e-learning with collaborative learning produced higher SE than lecture-based comparison, especially in female students. Against these, Berga et al. [ 56 ] found no significant SE difference between blended and face-to-face learning the most directly controlled comparison in the blended literature — reinforcing that the quality of the digital component, not the blend itself, determines outcomes. Faculty and preceptor self-efficacy Six studies focused on faculty or preceptors [ 46 , 27 , 45 , 53 , 38 , 28 ]. Culp-Roche et al. [ 45 ] found that online teaching SE was highest among 84 US faculty with prior online experience and institutional support. Hampton et al. [ 46 ] confirmed SE and satisfaction were highest in faculty with training support. Smith et al. [ 53 ] identified faculty SE as a primary antecedent of interactive course design with downstream consequences for student SE. Wu et al. [ 27 ] and Liaw et al. [ 28 ] demonstrated that targeted preceptor training significantly improved both preceptor SE and clinical teaching quality. Enyan et al. [ 38 ] extended these findings to Ghana, confirming that digital technology training for nurse preceptors significantly increased SE in digital technology and intention to use digital tools for clinical teaching. These studies collectively establish an SE transmission pathway from faculty/preceptor to student. The geographic distribution of included studies across 25 countries is shown in Fig. 2 . Null and negative findings Eight studies reported null or negative SE outcomes, providing theoretically necessary boundary conditions. Mun & Hwang (2020) [ 55 ] (RCT: web-based vs. lecture-based, no SE difference); Berga et al. [ 56 ] (quasi-experimental: blended vs. face-to-face, no SE difference); Gulley et al. [ 2 ] (pilot: forced COVID-19 transition, SE decline, NCLEX-RN confidence reduced); Maenhout et al. [ 30 ] (quasi-experimental: simulation improved individual but not team SE); Can et al. [ 44 ] (RCT: online communication training, no general SE change); Han et al. [ 50 ] (path analysis: acculturative stress and perfectionism negatively predicted SE); Thangam et al. [ 40 ] (cross-sectional: mixed SE levels, prior online exposure the only positive correlate); Zhang et al. [ 5 ] (quasi-experimental: distance learning students had lower performance and engagement than face-to-face). These eight studies collectively confirm that digital delivery does not inherently build SE; preparation, pedagogical quality, and learner readiness are determinants. Discussion Summary of findings This scoping review mapped 69 studies from 25 countries to examine how self-efficacy has been conceptualized, measured, and influenced within digital nursing education. The most important finding is that self-efficacy in this literature is not a unitary construct. Instead, it operates across at least four related but analytically distinct domains: domain-specific clinical self-efficacy, academic self-efficacy, computer or technology self-efficacy, and online learning self-efficacy. This distinction is not merely semantic. Each domain reflects a different object of confidence, requires different measurement approaches, and has different implications for instructional design. For example, confidence in navigating a learning management system is not equivalent to confidence in performing clinical assessment, managing disaster response, engaging in therapeutic communication, or succeeding academically in an online course. Treating these forms of self-efficacy as interchangeable risks weakens both theoretical interpretation and educational intervention design. Across the reviewed studies, prior experience, digital literacy, self-regulation, motivation, task value, social presence, and teaching presence emerged as recurring positive correlates of self-efficacy. Conversely, psychosocial stressors, acculturative stress, anxiety, inadequate digital preparation, low instructional support, and emergency transitions to online learning were associated with weaker self-efficacy outcomes. Intervention studies showed the strongest and most consistent gains when digital learning environments incorporated active learning, authentic practice, feedback, reflection, and structured support. Simulation, flipped classroom models, gamification, AI-assisted tools, and theory-grounded online modules were especially promising. However, the null and negative findings are equally important. Several studies showed no significant self-efficacy advantage for digital or blended formats over conventional instruction, and some pandemic-era studies reported declines in confidence, engagement, or readiness. These findings clarify a central boundary condition: digital modality alone does not produce self-efficacy. Self-efficacy develops when instructional design activates the mechanisms through which efficacy beliefs are formed. Implications for nursing education The evidence from Buthelezi and Wyk [ 39 ], Kim and Jeon [ 42 ], Jeon and Kim [ 49 ], Demirelli and Karacay [ 9 ], and Fitriawan et al. [ 10 ]] isconsistent: inadequate computer or digital literacy functions as a barrier that prevents domain-specific clinical SE from developing in digital environments. Programs should assess and, where necessary, explicitly scaffold digital literacy before deploying digital learning content.Design for SE mechanisms, not delivery modality. The null findings from Mun and Hwang [ 55 ], Berga et al. [ 56 ], and Can and Dalcali [ 44 ] confirm that modality equivalence produces SE equivalence. The most effective designs in this corpus simulation with debriefing [ 19 , 20 , 16 , 3 ], DRI-based online instruction [ 23 ], theory-grounded vaccination training [ 15 ], and AI-scaffolded writing courses [ 47 ] worked because they deliberately activated mastery experience, vicarious modeling, verbal feedback, and manageable affective challenges. This four-source scaffolding should be an explicit design criterion. Invest in faculty and preceptor SE. Studies of Culp-Roche et al. [ 45 ], Smith and Warner-[ 53 ], Wu et al. [ 27 ], Liaw et al. [ 28 ]],Enyan et al. [ 38 ], and Hampton et al. [ 46 ] establish a transmission pathway from faculty SE to student SE through course design quality. Faculty development in digital teaching is not merely a personnel concern it is a student SE and patient safety concern. Do not use emergency remote teaching as the benchmark. Gulley et al. [ 2 ] and Zhang et al. [ 5 ] demonstrate that forced unplanned digital transitions can actively harm SE and clinical readiness. These findings should not be generalized to planned, well-resourced digital nursing programs. The distinction between emergency digitalization and intentional digital design is both theoretical and practical. Address equity in digital nursing education. Han et al. [ 50 ] found acculturative stress and perfectionism negatively predicted SE among ESL nursing students. Demirelli and Karacay [ 9 ] and Hemmati and Pourteimour [ 33 ] found consistent female SE advantages in online nursing environments, while Gulley et al. [ 2 ] documented concerns about NCLEX-RN preparation in students from programs with lower digital infrastructure. Universal assumptions about digital readiness underestimate these differentials. Evaluate emerging technologies rigorously. Kim and Kim [ 32 ], Jeon et al. [ 62 , 68 ], and Makhlouf et al. [ 61 ] provide early promising evidence for metaverse environments, interactive simulation technology, and AI chatbots, respectively. Programs investing in these tools should design evaluation studies that measure SE as a primary outcome using validated instruments, not just satisfaction or novelty ratings. Limitations This review has several limitations. As a scoping review, it did not include a formal risk-of-bias appraisal; therefore, the findings should be interpreted as an evidence map rather than as conclusive estimates of intervention effectiveness. The included studies were methodologically heterogeneous, with variation in design, populations, interventions, comparison groups, and outcome measures. Measurement heterogeneity was especially substantial, with more than 25 self-efficacy instruments and frequent use of self-developed scales. This prevented meta-analysis and limited direct comparison across studies. The search was developed within a broader health professions education context and then narrowed to nursing, which may have introduced selection bias during population filtering. Qualitative evidence was limited, restricting insight into learners’ subjective experiences of self-efficacy development in digital environments. Finally, the concentration of studies during and after the COVID-19 pandemic may have amplified findings related to emergency remote instruction, stress, and digital adaptation. Conclusion Self-efficacy in digital nursing education is multidimensional, context-sensitive, and shaped by instructional design rather than delivery modality. This scoping review of 69 unique studies from 25 countries establishes that: (1) SE encompasses four interrelated domains requiring distinct measurement approaches measurement standardization is an urgent priority; (2) prior experience, digital literacy, self-regulation, and social/teaching presence are the most consistent positive correlates, while technostress, pandemic-related distress, and passive digital content delivery are negative; and (3) simulation with structured debriefing, flipped classroom designs, theory-grounded online modules with authentic feedback, gamification, AI-assisted tools, and deliberate faculty development reliably promote SE when they activate Bandura's four self-efficacy sources. Eight null and negative findings define the boundary: digital technology itself does not build SE. Future research should prioritize validated measurement batteries, longitudinal follow-up to clinical practice settings, equity-focused designs, and rigorous evaluation of emerging modalities. Declarations Ethics approval and consent to participate Not applicable. This scoping review analyzed previously published studies and did not involve direct recruitment of, or interaction with, human participants. No ethical approval or institutional review was required. Consent to participate Not applicable. This study is a scoping review of previously published literature. No human participants were directly recruited or enrolled, and therefore no consent to participate was required. Consent for publication Not applicable. Declaration of interest No potential conflict of interest relevant to this article was reported. Funding This scoping review received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors' contributions T.J.R. and B.M.B. conceptualized the study. T.J.R. and B.M.B. developed the methodology and conducted data curation and formal analysis. T.J.R. performed the literature search, screening, and data extraction. T.J.R. wrote the original draft of the manuscript. B.M.B. contributed to critical revision of the manuscript for important intellectual content. Both authors reviewed, edited, and approved the final manuscript. Data availability The full extraction table is presented as Table 1. References Koob C, Schröpfer K, Coenen M, Kus S, Schmidt N (2021) Factors influencing study engagement during the COVID-19 pandemic: A cross-sectional study among health and social professions students. PLoS ONE 16(7):e0255191. https://doi.org/10.1371/journal.pone.0255191 Gulley T, Hall T, Newsome A, Sidle MW, Simpson MR (2021) Perceived self-efficacy among nursing students during a pandemic: A pilot study. 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Int Nurs Rev 69(2):159–166 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9657971","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":637110272,"identity":"fba64d36-1d8c-405c-bf9f-5ca23bf8c890","order_by":0,"name":"Tamal Joyti Roy","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYFCCA0BcgSwgAcQ8eDTwgLWcgfMNiNECBIxtpGixZzz78DHvPDs5g/OLn30uqPjDYHC7gfHB2zbcWngYjhsb825LNja48cx49owzBgwGdw4wG87Fq+UYmzTvtgOJG24cMGbmbQNquZEAFCGoZQ5Iy/HPzLz/wFrYfxPW0gDUcr4HaEsDxBZmvFoOHGM2nHMs2VjyBk8xM88xYx7JG4nNknPO4dbCPuMY44M3NXZyfOePb2bmqZGT47uRfPDDmzLcWhgkDjAwgWNBIgHqUgbGBjzqgYC/gYHxB5hxAL/CUTAKRsEoGLkAALWCTrxPlsh+AAAAAElFTkSuQmCC","orcid":"","institution":"University of Houston","correspondingAuthor":true,"prefix":"","firstName":"Tamal","middleName":"Joyti","lastName":"Roy","suffix":""},{"id":637110273,"identity":"7aa5f085-3988-4f11-84ec-f175d0ddf7d2","order_by":1,"name":"Broti Mondal Bonya","email":"","orcid":"","institution":"University of Houston","correspondingAuthor":false,"prefix":"","firstName":"Broti","middleName":"Mondal","lastName":"Bonya","suffix":""}],"badges":[],"createdAt":"2026-05-08 21:03:56","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9657971/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9657971/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109205335,"identity":"e7305d2d-5eba-4872-99c3-81453d6dcdcf","added_by":"auto","created_at":"2026-05-13 15:04:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":40231,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA diagram for our study\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9657971/v1/76371cde4c6017a8168e7aaf.png"},{"id":109125105,"identity":"9ea243d5-a5c3-4694-9c6b-0031a663f60e","added_by":"auto","created_at":"2026-05-12 18:36:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":18968,"visible":true,"origin":"","legend":"\u003cp\u003eThe geographic distribution of included studies across 25 countries\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9657971/v1/b6a201654767bb6637b088d5.png"},{"id":109206672,"identity":"320c69c7-1e4a-4997-909c-08a3d09499ae","added_by":"auto","created_at":"2026-05-13 15:15:10","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":641778,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9657971/v1/956abb26-010a-4646-a74d-4231caf6c993.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eSelf-efficacy in digital nursing education: a scoping review\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eDigital technologies are now embedded in nursing education rather than functioning as supplemental instructional tools. Undergraduate and graduate nursing programs increasingly use asynchronous online modules, synchronous virtual classrooms, virtual and mixed reality simulations, mobile applications, AI-assisted chatbots, gamified platforms, metaverse environments, and flipped classroom models to support clinical, academic, and professional learning. This shift was accelerated by the COVID-19 pandemic, which forced many nursing programs to adopt remote instruction rapidly, often without adequate preparation, infrastructure, or pedagogical redesign [\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e]. Evidence from this period is mixed. Some studies reported preserved or improved learning outcomes in digitally mediated environments [\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e], whereas others found declines in students’ confidence, engagement, academic performance, and perceived clinical readiness following emergency transitions to online learning [\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e]. Thus, the central issue is not whether digital technologies are used in nursing education, but under what instructional conditions they support or undermine learner development.\u003c/p\u003e \u003cp\u003eSelf-efficacy is a theoretically important construct for interpreting this literature. Derived from Bandura's social cognitive theory, self-efficacy refers to an individual's belief in their capacity to organize and execute the courses of action required to produce specific attainments [\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e]. It is domain-specific, task-referenced, and shaped by four sources: mastery experiences, vicarious learning, verbal or social persuasion, and physiological and affective states [\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e]. In nursing education, self-efficacy has been associated with clinical skill acquisition, academic performance, professional identity formation, persistence under adversity, and quality of patient care [\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e]. In digital contexts, self-efficacy is not a single construct. Some studies address beliefs about using digital tools (computer or technology self-efficacy), others address beliefs about succeeding as a learner in online environments (online learning self-efficacy), and others concern domain-specific clinical competence beliefs that happen to be measured within digitally delivered training. These are related but distinct constructs with different antecedents and implications for instructional design [\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite a growing empirical literature spanning more than a decade, no comprehensive scoping review has mapped how self-efficacy is conceptualized, measured, associated with learner and contextual factors, and promoted through interventions specifically in digital nursing education. A scoping review is warranted because the evidence base is broad, methodologically heterogeneous, and still emerging conditions suited to evidence mapping rather than quantitative pooling [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eResearch questions\u003c/h3\u003e\n\u003cp\u003e(1) How is self-efficacy conceptualized and measured in digital nursing education?\u003c/p\u003e \u003cp\u003e(2) What learner, faculty, contextual, and instructional factors are associated with self-efficacy in digital nursing education?\u003c/p\u003e \u003cp\u003e(3) What digital interventions and strategies are reported to improve, reduce, or have no effect on self-efficacy outcomes?\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e\n\n \u003cp\u003e\u003c/p\u003e \u003cp\u003e\u003c/p\u003e\n\n \n\n \u003cp\u003e \u003c/p\u003e \u003cp\u003e\u003c/p\u003e"},{"header":"Methods","content":"\u003ch2\u003eDesign and framework\u003c/h2\u003e\u003cp\u003eThis scoping review followed Arksey and O'Malley's five-stage methodological framework [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e], refined by Levac et al. [\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e], and reported in accordance with PRISMA-ScR [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e]. A scoping review was selected over a systematic review because the aim was to map the breadth and nature of available evidence rather than to pool effect estimates or conduct a formal risk-of-bias appraisal.\u003c/p\u003e\u003ch3\u003ePopulation, concept, and context (PCC) framework\u003c/h3\u003e\u003cp\u003e \u003cstrong\u003ePopulation\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eNursing students at all levels (undergraduate, graduate, post-licensure), nursing faculty, and nurse preceptors involved in teaching-learning activities in digital environments. Studies of faculty or preceptors were included when outcomes could be referenced to the nursing education context. Studies were excluded when participants had no substantive educational connection to nursing for instance, studies exclusively of fully licensed practicing nurses with no educational component, patient self-management studies, or health disciplines without a nursing population.\u003c/p\u003e\u003cp\u003e \u003cb\u003eConcept\u003c/b\u003e: Self-efficacy as defined or operationalized in any form: domain-specific clinical self-efficacy (e.g., confidence in infection control), academic self-efficacy (e.g., beliefs about learning performance), computer or technology self-efficacy (e.g., confidence in using digital platforms), or online learning self-efficacy. Adjacent constructs operationally equivalent to self-efficacy, perceived clinical competence, and self-assessed teaching efficacy were included when measured using validated SE instruments or described explicitly as SE constructs.\u003c/p\u003e\u003cp\u003e \u003cstrong\u003eContext\u003c/strong\u003e \u003c/p\u003e\u003cp\u003eAny technology-mediated or digitally enhanced nursing education context, including asynchronous online modules, synchronous virtual instruction, virtual or mixed reality simulation, mobile application-based learning, AI-assisted or chatbot-based tools, gamified platforms, metaverse environments, flipped classroom designs, blended or hybrid programs, and distance education. Studies conducted entirely in face-to-face settings without a digital component were excluded.\u003c/p\u003e\u003ch3\u003eSearch strategy\u003c/h3\u003e\u003cp\u003eA structured search was conducted across five databases: MEDLINE, PsycINFO, CINAHL, Education Source, and Web of Science. Three Boolean strings were combined with AND: (1) digital and technology-mediated learning (e.g., \"digital* learn*,\" \"e-learning*,\" \"virtual* teach*,\" \"metaverse education*\"); (2) nursing populations (e.g., \"nursing student*,\" \"nursing education*,\" \"nurse preceptor*,\" \"nursing faculty\"); and (3) self-efficacy (\"self efficacy\" OR \"self-efficacy\"). All publications through December 31, 2025 were eligible. No language or design filters were applied. The full search strategy is in Appendix 1.\u003c/p\u003e\u003cp\u003eThe initial search yielded 800 citations: MEDLINE (n = 258), PsycINFO (n = 83), CINAHL (n = 160), Education Source (n = 131), and Web of Science (n = 168). Following deduplication, supplementary Google Scholar hand searching and backward/forward citation tracking were performed. The nursing-specific extraction table contained 72 rows; three exact duplicate entries were identified during data cleaning and removed. The final corpus comprised 69 unique studies.\u003c/p\u003e\u003ch3\u003eData extraction and synthesis\u003c/h3\u003e\u003cp\u003eData were extracted by the lead author into a structured 10-variable form: (1) author and year; (2) country and timeframe; (3) sample size and design; (4) sample characteristics; (5) sampling technique; (6) how self-efficacy was defined; (7) scales or instruments used; (8) interventions or strategies; (9) correlates or factors associated with SE; and (10) SE outcomes. The complete extraction table is presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. No formal risk-of-bias appraisal was conducted, consistent with scoping review methodology [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e]. Narrative synthesis was adopted, with quantitative outcomes reported descriptively. Null and negative findings were identified and reported alongside positive findings.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\"\u003e\u003c/div\u003e\u003ctable id=\"Tab1\" border=\"1\"\u003e \u003ccaption\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of the findings\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003c/colgroup\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\"\u003e \u003cp\u003eAuthor (Year)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eCountry\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eSample \u0026amp; Design\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003ePopulation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eSampling\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eSE Defined As\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eSE Instrument(s)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eIntervention / Strategy\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eCorrelates of SE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\"\u003e \u003cp\u003eSE Outcome\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePatton (2018) [\u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e52 undergraduate and 22 graduate nursing students; pretest-posttest study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSenior nursing students and first-year graduate students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eConvenience sampling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBelief in one's ability to assess fall risk in older adults\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eOnline fall prevention education and practical assessment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePrior experience with fall risk assessment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eIncreased self-efficacy in fall risk assessment after training\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eButhelezi (2020) [\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSouth Africa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e60 postgraduate nursing students; exploratory quantitative study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePostgraduate nursing students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePurposive convenience sampling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eConfidence in using e-learning platforms for professional learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-reported questionnaire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTraining and technical support for using Moodle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eProficiency in English, computer literacy, access to technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigher self-efficacy in using e-learning after training\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eChang (2020) [\u003cspan class=\"CitationRef\"\u003e57\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTaiwan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e36 nursing students; experimental study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNursing students in neonatal health care training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eRandom assignment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBelief in one's ability to handle neonatal health care cases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eRSI-based flipped classroom approach\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eRSI-based flipped classroom model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eCritical thinking, decision-making skills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eImproved self-efficacy, learning satisfaction, and critical thinking\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHampton (2020) [\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eN/A (faculty study); survey-based study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNursing faculty in online education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in online teaching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy and satisfaction survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTraining and support for online teaching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eExperience with online teaching, institutional support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigher self-efficacy and satisfaction in online teaching after training\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eKim \u0026amp; Jeon (2020) [\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e205 nursing students; cross-sectional study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNursing students in two colleges\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eConvenience sampling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in online education and digital literacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eeHealth literacy scale, digital literacy scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eOnline learning and ICT integration in nursing education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eAcademic level, digital literacy, access to ICT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigher eHealth literacy with improved digital literacy and self-efficacy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eKoca \u0026amp; Arkan (2020) [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTurkey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e127 experimental, 108 control; randomized controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eThird-year nursing students in disaster preparedness training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eRandom assignment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in disaster response and management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eDisaster Response Self-Efficacy Scale (DRSES)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eJennings Disaster Nursing Management Model-based training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePrevious exposure to disaster management training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eIncreased disaster response self-efficacy and preparedness perceptions\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eLin (2020) [\u003cspan class=\"CitationRef\"\u003e58\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTaiwan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e102 nursing students; quasi-experimental study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNursing students in an introductory computer science course\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePurposive sampling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in information security literacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eInformation security literacy pre/post-tests\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBlended assessment strategy using audience response system and online system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePrior knowledge of information security, learning environment stimulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigher self-efficacy, motivation, and learning outcomes in information security\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMun \u0026amp; Hwang (2020) [\u003cspan class=\"CitationRef\"\u003e55\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e56 clinical nurses; randomized controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eClinical nurses in oncology settings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eRandomized selection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in anticancer chemotherapy nursing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy scale for chemotherapy nursing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eWeb-based learning course for chemotherapy nursing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePrior education and experience with chemotherapy nursing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNo significant difference in self-efficacy between web-based and lecture-based training\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eWu et al. (2020) [\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSingapore\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e150 nurse preceptors; quasi-experimental study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eRegistered nurse preceptors in a clinical teaching blended learning program\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eConvenience sampling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in clinical teaching and assessment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePreceptor self-efficacy questionnaire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eClinical Teaching Blended Learning (CTBL) with web-based pedagogy and case-based learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePrior teaching experience, attitudes toward online learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eIncreased clinical teaching competence and self-efficacy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBeasley (2021) [\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e71 nurse practitioner and medical students; quasi-experimental study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMedical and nurse practitioner students in antepartum depression screening training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eConvenience sampling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in antepartum depression screening and education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePhysician/Nurse Practitioner Student Teaching Self-Efficacy Questionnaire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eOnline educational intervention using a virtual learning platform\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMotivation for maternal depression screening, prior mental health education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eIncreased self-efficacy, knowledge, and motivation for antepartum depression screening\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBerga et al. (2021) [\u003cspan class=\"CitationRef\"\u003e56\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eCanada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e217 nursing students; quasi-experimental pre-post study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eUndergraduate nursing students in health assessment course\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eConvenience sampling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in nursing health assessment training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy scale for nursing assessment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBlended learning versus face-to-face learning in health assessment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eLearning preferences, prior exposure to blended learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNo significant difference in self-efficacy between blended and face-to-face learning groups\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eCulp-Roche et al. 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Seo (2022) [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e245 nursing students; mixed-methods study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eUndergraduate nursing students during COVID-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eConvenience sampling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in clinical practice during online learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eStepwise multiple regression analysis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eVirtual clinical training and self-regulated learning interventions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eLearning motivation, lecture type (recorded vs. live)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigher self-efficacy linked to improved learning flow and motivation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eWarshawski (2022) [\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eIsrael\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e222 first-year nursing students; cross-sectional study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNursing students in online learning during COVID-19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eConvenience sampling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eAcademic self-efficacy in online environments\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSurvey using resilience and social support scales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eAssessment of social support and resilience factors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eGender, cultural background, perceived difficulty in studies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eResilience and social support positively correlated with self-efficacy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eYang and Kim (2022) [\u003cspan class=\"CitationRef\"\u003e70\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e55 nursing students; quasi-experimental study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eFinal-year nursing students in communication training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eRandom assignment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in nonviolent communication skills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePre- and post-self-efficacy assessment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eOnline nonviolent communication training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eEmpathy, workplace stress management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eImproved self-efficacy in communication, empathy, and teamwork\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eYoungwanichsetha (2022) [\u003cspan class=\"CitationRef\"\u003e71\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eThailand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e80 nursing students; quasi-experimental study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eThird-year nursing students in maternal-newborn care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSystematic random sampling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in nursing care for pregnant women with diabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePre- and post-self-efficacy survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eOnline computer-assisted instruction (CAI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eEngagement in digital learning, teaching strategy effectiveness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigher self-efficacy and knowledge retention with Cai\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eYu \u0026amp; Yang (2022) [\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e50 nursing students; quasi-experimental study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNursing students in infection control training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eRandom assignment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in infection control procedures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePre- and post-self-efficacy assessment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eVirtual reality infection control simulation (VRICS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eImmersion level, previous clinical exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eImproved self-efficacy, infection control performance, and learning satisfaction\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eZarshenas et al. (2022) [\u003cspan class=\"CitationRef\"\u003e72\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e46 nursing students; quasi-experimental study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNursing students in clinical education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eRandom assignment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in clinical learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePre- and post-self-efficacy evaluation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMicro-learning-based e-learning intervention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMultimedia learning strategies, student engagement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigher self-efficacy and improved clinical learning outcomes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eChiu \u0026amp; Liu (2022) [\u003cspan class=\"CitationRef\"\u003e64\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTaiwan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e80 nurses; quasi-experimental study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNursing personnel in non-pharmacological pain management training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eConvenience sampling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in aromatherapy-based pain management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy and knowledge assessment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eFlipped teaching intervention with video-based pre-learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePre-class preparation, interactive learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSignificant improvement in self-efficacy and knowledge compared to traditional teaching\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eDeFusco et al. 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(2023) [\u003cspan class=\"CitationRef\"\u003e67\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSpain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e111 nursing students: Cross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eThird-year nursing students, no prior ICU experience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNot mentioned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eConfidence in performing nursing assessments in ICUs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy perception questionnaire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eVirtual reality-based training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eImmersion in virtual reality, exposure to ICU environment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eEnhanced skill acquisition, increased confidence\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHwang et al. 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(2024) [\u003cspan class=\"CitationRef\"\u003e66\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eBrazil\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e39 undergraduate nursing students: Descriptive study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eUndergraduate nursing students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNot mentioned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in telesimulation for pediatric and neonatal nursing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eValidated self-efficacy and self-confidence scales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eExpert-modeling videos in telesimulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSimulation engagement, remote learning advantages\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigh self-confidence, self-efficacy, and satisfaction\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eChen et al. (2024) [\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eChina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e329 medical and nursing students: Survey-based study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMedical and nursing students using LMSs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNot mentioned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eComputer self-efficacy and LMS satisfaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTechnology Satisfaction Model framework\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eOnline LMS-based education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePerceived ease of use, perceived usefulness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigher self-efficacy led to greater LMS satisfaction\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eDemirelli \u0026amp; Karaçay (2024) [\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTurkey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e632 nursing students: Cross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eUndergraduate nursing students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNot mentioned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eOnline learning self-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eOnline Learning Self-Efficacy Scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNot explicitly mentioned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTechnology skills, study time, satisfaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigher online self-efficacy correlated with engagement and success\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eEl-Gazar et al. (2024) [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eEgypt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e208 nursing students: Cross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eUndergraduate nursing students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eConvenience sampling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eAcademic self-efficacy in e-learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eAcademic Self-Efficacy Scale, Online Learning Readiness Scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNot explicitly mentioned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eE-learning readiness, GPA correlation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigher readiness and self-efficacy led to better academic achievement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHemmati Malsakpak \u0026amp; Pourteimour (2024) [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eIran\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e70 undergraduate nursing students: Quasi-experimental\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eUndergraduate nursing students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eCensus sampling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eAcademic self-efficacy in blended learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eCollege Academic Self-Efficacy Scale (CASES)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eE-learning blended with collaborative learning and lecture-based teaching\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eCollaboration, technical support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigher self-efficacy scores post-intervention, especially among female students\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHuang and Lee (2024) [\u003cspan class=\"CitationRef\"\u003e74\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTaiwan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNursing students: Quasi-experimental\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePediatric nursing students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNot mentioned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eConfidence in using AI-assisted tools in pediatric care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNot explicitly mentioned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eAI-driven therapeutic games and health education e-books\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eFear reduction in children, interactive learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eIncreased self-efficacy in pediatric care\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eJeon H. et al. (2024) [\u003cspan class=\"CitationRef\"\u003e62\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e428 participants: Cross-sectional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNurses and nursing students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNot mentioned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMetaverse self-efficacy in nursing education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMetaverse presence and usability assessment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eInteraction with metaverse platforms (ZEPETO, Gather)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePlatform usability, prior experience\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigher self-efficacy in nurses than students; usability impacted learning outcomes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eJeon Y. et al. (2024) [\u003cspan class=\"CitationRef\"\u003e68\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e80 nursing students: Randomized controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eThird- and fourth-year nursing students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNot mentioned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in communication skills\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePre-post self-efficacy survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTechnology-based interactive communication simulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eEmpathy, knowledge retention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eImproved self-efficacy in handling communication challenges\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMakhlouf et al. (2024) [\u003cspan class=\"CitationRef\"\u003e61\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSaudi Arabia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e73 nurses: Quasi-experimental\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePracticing nurses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePurposive sampling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in AI chatbot-assisted nursing education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePre-post chatbot knowledge assessment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eAI chatbot integrated into nursing training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eKnowledge access, real-time support\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eImproved knowledge and self-efficacy in chatbot-assisted learning\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMaynard et al. (2024) [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eUSA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e187 healthcare professionals: Quality improvement study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eClinicians, nurses, clinical staff\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNot mentioned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eConfidence in recommending HPV vaccination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003ePre-post self-efficacy assessment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHPV CHAT training on vaccine communication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMotivational interviewing, bundled recommendations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eImproved self-efficacy and routine recommendation rates\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMoon et al. (2024) [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e39 nursing students: Pretest-posttest study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSenior nursing students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eConvenience sampling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eConfidence in managing acute coronary syndrome (ACS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in learning survey\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eMixed reality-based ACS simulation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSimulation immersion, hands-on practice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eImproved knowledge, self-efficacy, and performance\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eKo \u0026amp; Choi (2024) [\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSouth Korea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003e104 nurses: Randomized controlled trial\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNurses working in general hospitals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNot mentioned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in providing psychological support for infectious disease patients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy and disaster competence assessment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eVirtual nursing simulation-based education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eProblem-solving, self-leadership, motivation to transfer knowledge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigher self-efficacy and competence in disaster mental health support\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eTornwall and Ikonen (2024) [\u003cspan class=\"CitationRef\"\u003e75\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eUSA, Finland\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNursing students: Survey-based study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNursing students in global online education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNot mentioned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-efficacy in receiving and providing peer feedback\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eStudent engagement and feedback receptivity scale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eOnline peer-to-peer feedback training\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eReceptiveness to feedback, learning engagement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigher confidence in using feedback effectively\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eYossatorn et al. (2024) [\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eThailand\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eUniversity students: Cross-sectional study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eUndergraduate nursing students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eNot mentioned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eAcademic self-efficacy in online learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eExpectancy-value theory framework\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eOnline self-regulated learning strategies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eSelf-regulation, task value, learning motivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\"\u003e \u003cp\u003eHigher self-efficacy in students with strong self-regulation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e\u003cem\u003eNote. CASES = College Academic Self-Efficacy Scale; CDMSCS = Clinical Decision-Making Self-Confidence Scale; CSES = Cultural Self-Efficacy Scale; DRSES = Disaster Response SE Scale; GSE = General SE Scale (Schwarzer); MNESEOT = Michigan Nurse Educators SE for Online Teaching; MSLQ = Motivated Strategies for Learning Questionnaire; NVC = nonviolent communication; OLSES = Online Learning SE Scale; PSEQ = Preceptor SE Questionnaire; RCT = randomized controlled trial; SAWSES = Self-Assessment Writing SE Scale; SE = self-efficacy; SEIEL = SE for Interprofessional Experiential Learning; SeQoL = SE Questionnaire for Online Learning; VR = virtual reality; VPLSE = Virtual Patient Learning System Evaluation. Author names with encoding characters (GarcÃa-Pazo = García-Pazo; Gonçalves = Gonçalves) reflect source file encoding and should be corrected before publication\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStudy characteristics\u003c/h2\u003e \u003cp\u003eThe 69 unique studies were published between 2018 and 2025 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), with the majority (n\u0026thinsp;=\u0026thinsp;50, 72.5%) published between 2022 and 2025, reflecting the surge in digital nursing education research following the COVID-19 pandemic. Studies were conducted across 25 countries. The USA was the most frequently represented (n\u0026thinsp;=\u0026thinsp;15, 21.7%), followed by South Korea (n\u0026thinsp;=\u0026thinsp;11, 15.9%), Taiwan (n\u0026thinsp;=\u0026thinsp;9, 13.0%), Turkey (n\u0026thinsp;=\u0026thinsp;4, 5.8%), Indonesia (n\u0026thinsp;=\u0026thinsp;3, 4.3%), Iran (n\u0026thinsp;=\u0026thinsp;3, 4.3%), and China (n\u0026thinsp;=\u0026thinsp;3, 4.3%). Other contributing countries included Saudi Arabia, Singapore, Thailand, South Africa, Canada, Belgium, Hong Kong, Israel, Morocco, Japan, Spain, Brazil, Egypt, UAE, Finland, Ghana, and Jordan.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eStudy designs included quasi-experimental (n\u0026thinsp;=\u0026thinsp;23, 33.3%), cross-sectional (n\u0026thinsp;=\u0026thinsp;15, 21.7%), experimental (n\u0026thinsp;=\u0026thinsp;7, 10.1%), randomized controlled trial (RCT; n\u0026thinsp;=\u0026thinsp;5, 7.2%), mixed-methods (n\u0026thinsp;=\u0026thinsp;5, 7.2%), pre-post or pilot (n\u0026thinsp;=\u0026thinsp;4, 5.8%), single-cohort or other (n\u0026thinsp;=\u0026thinsp;6, 8.7%), descriptive/exploratory (n\u0026thinsp;=\u0026thinsp;2, 2.9%), correlational (n\u0026thinsp;=\u0026thinsp;1, 1.4%), and qualitative (n\u0026thinsp;=\u0026thinsp;1, 1.4%). Sample sizes ranged from 17 to 3,733 [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], with a median of 72. Convenience sampling was most common (n\u0026thinsp;=\u0026thinsp;26); sampling was not reported in approximately 34% of studies. The full screening and selection process is illustrated in the PRISMA flow diagram (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe population breakdown was: undergraduate nursing students (n\u0026thinsp;=\u0026thinsp;32, 46.4%), graduate or postgraduate nursing students (n\u0026thinsp;=\u0026thinsp;16, 23.2%), clinical or practicing nurses (n\u0026thinsp;=\u0026thinsp;7, 10.1%), faculty or preceptors (n\u0026thinsp;=\u0026thinsp;6, 8.7%), and mixed or other populations (n\u0026thinsp;=\u0026thinsp;8, 11.6%). In terms of digital modality, online modules and e-learning platforms were most prevalent (n\u0026thinsp;=\u0026thinsp;28, 40.6%), followed by simulation-based approaches (n\u0026thinsp;=\u0026thinsp;12, 17.4%), observational or factor studies without active intervention (n\u0026thinsp;=\u0026thinsp;4), flipped classroom designs (n\u0026thinsp;=\u0026thinsp;4), blended or hybrid learning (n\u0026thinsp;=\u0026thinsp;4), and emerging modalities including gamification (n\u0026thinsp;=\u0026thinsp;2), metaverse or XR (n\u0026thinsp;=\u0026thinsp;2), mobile or AI chatbot (n\u0026thinsp;=\u0026thinsp;2), and AI-assisted learning (n\u0026thinsp;=\u0026thinsp;1).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eConceptualization and measurement of self-efficacy\u003c/h3\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eFour-domain typology\u003c/h2\u003e \u003cp\u003eSystematic review of SE definitions across all 69 studies (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, column 6) revealed four interrelated but conceptually distinct domains.Domain-specific clinical self-efficacy was the most prevalent, appearing in approximately 36 studies. It was defined as belief in the ability to perform specific professional nursing competencies: disaster response [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]; depression screening [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]; infection control [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]; acute coronary syndrome management [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]; palliative care [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]; clinical judgment using a decision-reflection-interaction approach [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]; cultural competence [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]; HPV vaccine recommendation [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]; telehealth [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]; clinical teaching and preceptorship [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]; gender-affirming communication [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]; neonatal and acute care [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]; and career decision-making [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This domain-specificity is consistent with Bandura's conceptualization of SE as task-referenced.\u003c/p\u003e \u003cp\u003eAcademic self-efficacy referred to beliefs about general scholarly task performance and featured in approximately 18 studies \u0026mdash; prominently in pandemic-era research [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], blended learning adoption [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], and self-regulated learning contexts [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Instruments included the College Academic Self-Efficacy Scale [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] and the Academic SE Questionnaire [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eComputer and technology self-efficacy captured beliefs about using digital tools and navigating online platforms. It appeared in approximately 12 studies, most centrally in examinations of LMS satisfaction [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e], technology acceptance [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], and e-learning readiness [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The largest study in the corpus, Jiang et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], with 3,733 Chinese nursing and midwifery students across seven provinces, confirmed self-control and general SE as significant predictors of home-based e-learning behavior (β\u0026thinsp;=\u0026thinsp;0.250 and β\u0026thinsp;=\u0026thinsp;0.169 respectively).\u003c/p\u003e \u003cp\u003eOnline learning self-efficacy represented an integrated construct about succeeding in technology-mediated environments. It was measured with the OLSES in two studies [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and the SeQoL in one [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Demirelli \u0026amp; Karacay [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], in 632 Turkish nursing students, reported a mean OLSES score of 74.54, with female students scoring significantly higher than males (75.53 vs. 70.61).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMeasurement instruments and heterogeneity\u003c/h2\u003e \u003cp\u003eOver 25 distinct instruments were identified. Ad hoc or self-developed scales predominated (n\u0026thinsp;\u0026asymp;\u0026thinsp;22), followed by the General Self-Efficacy Scale (Schwarzer; n\u0026thinsp;=\u0026thinsp;8) (Jiang et al., 2023; Warshawski, 2022; Buthelezi \u0026amp; Wyk, 2020; Demirelli \u0026amp; Kara\u0026ccedil;ay, 2024; Hidayati et al., 2022; Kim \u0026amp; Jeon, 2020; Patton, 2018; Can et al., 2022), OLSES (n\u0026thinsp;=\u0026thinsp;2) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and Technology Acceptance Model-derived SE items (n\u0026thinsp;=\u0026thinsp;2) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Validated domain-specific instruments included the DRSES [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], CDMSCS [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], PSEQ [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], CASES [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e], MNESEOT [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e], SAWSES [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e], CSES [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], Palliative Care SE Scale [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], SEIEL [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], and VPLSE [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eA key limitation was construct drift: some studies used SE, confidence, perceived competence, and self-assessed readiness interchangeably. Several studies employed structural equation modeling or path analysis to situate SE within nomological networks alongside digital literacy, engagement, burnout, and motivation [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], providing theoretically richer operationalizations than pre-post designs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eFactors associated with self-efficacy\u003c/h2\u003e \u003cdiv id=\"Sec14\" class=\"Section3\"\u003e \u003ch2\u003ePrior experience\u003c/h2\u003e \u003cp\u003ePrior clinical, academic, or teaching experience was the most consistently documented positive correlate, appearing in approximately 26 studies. Faculty SE was highest among those with prior online teaching experience and institutional support [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Wu et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] found a significant pre-post SE gain (59.00 to 70.40; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) among 150 Singapore nurse preceptors following blended preceptor training. Maenhout et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] found years of NICU experience moderated simulation-based SE gains. Lin et al. [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e] found VR-based flipped learning most benefited those with low baseline confidence.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eDigital literacy and technology capability\u003c/h2\u003e \u003cp\u003eDigital literacy was a consistently positive correlate across approximately 14 studies. Demirelli \u0026amp; Karacay [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] showed that high-technology skills significantly predicted OLSES scores. Kim \u0026amp; Jeon [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] found digital literacy predicted eHealth literacy and SE among 205 Korean nursing students. Jeon \u0026amp; Kim [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e] confirmed digital literacy partially mediated between learning attitudes and eHealth literacy in 259 nursing students. Ibrahim \u0026amp; Aldawsari [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e] found digital capabilities predicted academic performance through SE as a mediator. Fitriawan et al. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], in 500 Indonesian students, found online learning readiness positively correlated with SE while psychological distress was negatively correlated. Buthelezi and Wyk [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] identified computer literacy, English proficiency, and technology access as joint correlates of SE in South African postgraduate students.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSelf-regulation, motivation, and task value\u003c/h2\u003e \u003cp\u003eSelf-regulation and intrinsic motivation were robust positive predictors across approximately 14 studies. Jiang et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] confirmed self-control as a significant independent predictor of e-learning behavior alongside SE in 3,733 students. Park and Seo [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] found learning flow and self-regulation positively associated with SE in 245 Korean students, with live synchronous lectures producing higher SE than recorded asynchronous ones. Yossatorn et al. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] confirmed, using an expectancy-value framework, that self-regulation and task value were the strongest SE predictors among Thai nursing students. Taylor et al. [\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e], in 717 first-year Australian nursing students, found high SE (AOR\u0026thinsp;=\u0026thinsp;2.82) and task value (AOR\u0026thinsp;=\u0026thinsp;5.05) were the strongest predictors of perceived usefulness of online interactive case studies in preparing for clinical placement, with students using English as an additional language and those with lower GPA also significantly more likely to benefit. Naciri et al. [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] found higher SE and performance in a flipped classroom group using the MSLQ. Wolf and Wolf [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] found AI-evaluated feedback produced significant SE gains (writing essentials d\u0026thinsp;=\u0026thinsp;0.96; reflective writing d\u0026thinsp;=\u0026thinsp;1.10) in graduate nursing students, confirming that structured scaffolding can drive SE in complex cognitive domains.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePsychosocial stressors and the COVID-19 context\u003c/h2\u003e \u003cp\u003ePsychosocial stressors were consistently negative correlates across approximately 12 studies. Rohmani et al. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] found a non-linear SE-burnout relationship: higher SE predicted lower burnout, while moderate SE paradoxically linked to severe burnout. Warshawski [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] identified resilience and social support as protective SE correlates in 222 Israeli first-year nursing students, while perceived study difficulty was negative. Hidayati et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] confirmed SE negatively correlated with anxiety in 298 Indonesian students. Han et al. [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] found acculturative stress and perfectionism negatively predicted SE in 113 ESL nursing students in the USA, with equity implications for international students.\u003c/p\u003e \u003cp\u003eForced COVID-19 transitions produced some of the clearest negative SE findings in the corpus. Gulley et al. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] documented SE decline and reduced NCLEX-RN confidence in 44 nursing students following unplanned online transition. Zhang et al. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] found lower academic performance and engagement in distance versus face-to-face nursing students. These findings are critically important: they demonstrate that digitalization per se does not improve SE and that inadequate preparation, psychosocial support, and instructional quality are determinants of SE outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eGender\u003c/h2\u003e \u003cp\u003eGender effects were present but population-specific. Female nursing students reported higher online learning SE than males in multiple contexts [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Malsakpak [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] found female students in the collaborative e-learning condition showed larger SE gains (127.12 vs. 112.65, p\u0026thinsp;=\u0026thinsp;0.019). These patterns suggest differential socialization with technology and professional training rather than stable gender traits.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eInstructional environment and social presence\u003c/h2\u003e \u003cp\u003eSocial and teaching presence were significant positive correlates. Smith et al. [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] identified instructor presence and interactive course design as primary environmental contributors to student SE in a qualitative study. Tornwall and Ikonen [\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e] found that an asynchronous international online instructional design course significantly improved feedback SE \u0026mdash; the perceived competence to interpret and respond to peer feedback \u0026mdash; among 21 graduate nursing students in the US and Finland (p\u0026thinsp;=\u0026thinsp;0.013), with teaching experience predicting higher baseline feedback orientation. Park and Seo [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] confirmed synchronous live lectures outperformed recorded asynchronous content for SE outcomes. Chen et al. [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] found perceived ease of use and usefulness of LMS were direct predictors of computer SE among 329 nursing and medical students.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eInterventions and self-efficacy outcomes\u003c/h2\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003eSimulation-based digital learning\u003c/h2\u003e \u003cp\u003eSimulation was the most consistently effective intervention modality (n\u0026thinsp;=\u0026thinsp;12 studies; positive outcomes in 11/12). Yu and Yang [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] found VR infection control simulation significantly improved SE (t\u0026thinsp;=\u0026thinsp;4.93) in 50 Korean nursing students alongside performance and satisfaction. Moon et al. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] documented significant SE, knowledge, and performance gains following mixed reality acute coronary syndrome simulation in 39 senior students. Ko and Choi [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], in an RCT of 104 Korean hospital nurses, found virtual simulation significantly improved SE and disaster mental health competence versus controls. Fung et al. [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] reported improved SE in clinical competence and decision-making following online virtual simulation with debriefing in 188 Hong Kong final-year students. Garc\u0026iacute;a-Pazo et al. [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e] found VR-based ICU training improved confidence in 111 Spanish nursing students without prior ICU experience. Squires et al. [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e] found online clinical simulations enhanced SE and skill transferability during COVID-19. Gon\u0026ccedil;alves et al. [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e] documented high SE and satisfaction among 39 Brazilian students following expert-modeling tele simulation. Takashiki et al. [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] found hybrid simulation-based mastery learning improved SE retained post-intervention in 37 Japanese novice nurses. Wada et al. [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e] demonstrated interprofessional simulation improved SE for end-of-life discussions. Maenhout et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] reported a nuanced null finding: in situ simulation improved individual SE but not team performance, distinguishing individual from collective efficacy. The mechanisms map onto Bandura's four sources: guided simulation practice creates mastery experience; expert modeling provides vicarious learning; structured debriefing delivers verbal persuasion; manageable clinical risk creates favorable affective states.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eFlipped classroom and active learning\u003c/h2\u003e \u003cp\u003eAll four flipped classroom studies reported positive SE outcomes. Chang et al. [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] found RSI-based flipped teaching significantly improved SE, learning satisfaction, and critical thinking in 36 Taiwanese nursing students. Lin et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] found interactive peer-review embedded in flipped learning improved SE, critical thinking, and reflection. Naciri et al. [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e] replicated SE benefits in Moroccan students using the MSLQ. Chiu and Liu [\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e] found significant SE and knowledge gains in 80 Taiwanese nurses through video-based pre-learning for aromatherapy pain management. The consistent pattern is theoretically coherent: self-paced pre-class digital content enables initial mastery experiences at low stakes, while in-class application delivers social modeling, instructor feedback, and peer collaboration.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eOnline modules and e-learning platforms\u003c/h2\u003e \u003cp\u003eOnline modules were the most prevalent modality (n\u0026thinsp;=\u0026thinsp;28) and produced positive SE outcomes in most studies when designed with authentic scenarios, interactive feedback, and learner control. Key positive findings include: Koca and Arkan [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], in a Turkish RCT (n\u0026thinsp;=\u0026thinsp;235), found theory-grounded online disaster nursing training significantly improved SE; Beasley [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] and Link et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] found online depression screening education improved SE in US nursing students and practitioners; Garber and Gustin [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e] found online telehealth education improved SE and adoption confidence in APRNs; DeFusco et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] found VitalTalk-based online palliative care education improved SE in 40 critical care nurses; Beck [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e] found an online Lift the Spirit communication intervention significantly improved SE in conducting spiritual histories among 17 oncology nurses (Z\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;3.20, p\u0026thinsp;=\u0026thinsp;0.001); Kasar [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] found an online palliative care course significantly improved SE in 46 Turkish students; Yang and Kim [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e] found an online nonviolent communication training program significantly improved SE (t\u0026thinsp;=\u0026thinsp;3.02, p\u0026thinsp;=\u0026thinsp;0.004), empathy, and communication skills in 55 South Korean nursing students; Youngwanichsetha [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e] found online computer-assisted instruction for maternal-newborn nursing care produced substantially higher SE in 80 Thai nursing students compared to lecture instruction (M\u0026thinsp;=\u0026thinsp;79.00 vs. 37.25, t\u0026thinsp;=\u0026thinsp;20.06, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); and Zarshenas et al. [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e] found micro-learning via short video clips significantly improved SE in 21 Iranian nursing internship students (p\u0026thinsp;=\u0026thinsp;0.001; d\u0026thinsp;=\u0026thinsp;0.504), while the control group receiving traditional lectures showed no SE change (p\u0026thinsp;=\u0026thinsp;0.425). Fadaeinia et al. [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] found an online cultural care program significantly improved cultural SE in 80 Iranian postgraduate students; Hwang et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] found the technology-supported Decision, Reflection, and Interaction (DRI) approach \u0026mdash; combining decision-making, reflection, and guided interaction \u0026mdash; significantly improved SE and learning achievement in 38 Taiwanese nursing students; and Wolf and Wolf [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] found AI-evaluated feedback in an online writing course produced substantial SE gains in graduate nursing students.\u003c/p\u003e \u003cp\u003eCritical null findings qualify these positive results. Mun and Hwang [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] found in an RCT of 56 Korean clinical nurses that web-based and lecture-based chemotherapy training produced no significant SE difference the strongest null finding in the corpus, confirming that modality equivalence produces SE equivalence. Berga et al. [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] found no significant SE difference between blended and face-to-face health assessment learning in 217 Canadian students. Can et al. [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] found online communication skills training produced no significant general SE change despite improved specific skills in an RCT of 60 Turkish students. These null findings are theoretically important: delivery modality does not determine SE outcomes; instructional mechanism does.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eGamification and game-based learning\u003c/h2\u003e \u003cp\u003eBoth gamification studies reported positive SE outcomes. Chang et al. [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] found online game-based learning with the watch-summarize-question strategy produced higher SE, satisfaction, and engagement in 45 Taiwanese first-year nursing students. Najafi et al. [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] found gamification using Kahoot and Storyline produced higher SE and learning outcomes in 68 Iranian sixth-semester nursing students. Game mechanics provide immediate feedback, progressive challenge, and visible achievement, operationalizing Bandura's mastery experience and verbal persuasion sources simultaneously.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eMobile, AI-assisted, and emerging digital modalities\u003c/h2\u003e \u003cp\u003eMobile chatbot and AI-assisted tools produced positive SE outcomes in all three studies identified. Chang et al. [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] found a mobile chatbot approach significantly improved SE and learning achievement in 72 Taiwanese nursing students in vaccine administration training. Makhlouf et al. [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e] found AI chatbot integration into nursing training improved SE and knowledge in 73 Saudi practicing nurses. Huang and Lee [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e] found AI-generated image e-books (Canva AI) significantly improved nursing students\u0026rsquo; SE in using therapeutic games with sick children compared to traditional paper handouts (β\u0026thinsp;=\u0026thinsp;0.356, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with higher SE in the experimental group directly predicting reduced fear responses in sick children (β = \u0026minus;0.914, p\u0026thinsp;=\u0026thinsp;0.009). Wolf and Wolf [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] demonstrated AI-evaluated online writing course feedback produced large SE gains in graduate nursing students.\u003c/p\u003e \u003cp\u003eMetaverse-based nursing education was examined in two studies. Kim and Kim [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] found metaverse-based career mentoring significantly increased career decision-making SE in 43 Korean students. Jeon et al. [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e] found platform usability and metaverse presence predicted SE in 428 Korean nurses and nursing students, with practicing nurses showing higher SE than students suggesting domain experience interacts with immersion to shape SE outcomes. Jeon et al. [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e] found technology-based interactive communication simulation significantly improved SE in 80 Korean nursing students in an RCT. Galan-Lominchar et al. [\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e] found virtual international nursing exchange improved general SE in 70 nursing students.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eBlended and hybrid learning\u003c/h2\u003e \u003cp\u003eBlended learning outcomes were variable. Wu et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] found a significant SE gain (59.00 to 70.40, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in 150 Singaporean nurse preceptors from a Clinical Teaching Blended Learning program. Liaw et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] found significant SE improvement among nurse preceptors through tele-simulation-based training. Lin [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] found blended assessment with audience response systems improved SE and motivation in information security literacy. Hemmati and Pourteimour [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] found that e-learning with collaborative learning produced higher SE than lecture-based comparison, especially in female students. Against these, Berga et al. [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] found no significant SE difference between blended and face-to-face learning the most directly controlled comparison in the blended literature \u0026mdash; reinforcing that the quality of the digital component, not the blend itself, determines outcomes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section3\"\u003e \u003ch2\u003eFaculty and preceptor self-efficacy\u003c/h2\u003e \u003cp\u003eSix studies focused on faculty or preceptors [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Culp-Roche et al. [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e] found that online teaching SE was highest among 84 US faculty with prior online experience and institutional support. Hampton et al. [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] confirmed SE and satisfaction were highest in faculty with training support. Smith et al. [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] identified faculty SE as a primary antecedent of interactive course design with downstream consequences for student SE. Wu et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] and Liaw et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] demonstrated that targeted preceptor training significantly improved both preceptor SE and clinical teaching quality. Enyan et al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] extended these findings to Ghana, confirming that digital technology training for nurse preceptors significantly increased SE in digital technology and intention to use digital tools for clinical teaching. These studies collectively establish an SE transmission pathway from faculty/preceptor to student. The geographic distribution of included studies across 25 countries is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003eNull and negative findings\u003c/h2\u003e \u003cp\u003eEight studies reported null or negative SE outcomes, providing theoretically necessary boundary conditions. Mun \u0026amp; Hwang (2020) [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e] (RCT: web-based vs. lecture-based, no SE difference); Berga et al. [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] (quasi-experimental: blended vs. face-to-face, no SE difference); Gulley et al. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] (pilot: forced COVID-19 transition, SE decline, NCLEX-RN confidence reduced); Maenhout et al. [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e] (quasi-experimental: simulation improved individual but not team SE); Can et al. [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] (RCT: online communication training, no general SE change); Han et al. [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] (path analysis: acculturative stress and perfectionism negatively predicted SE); Thangam et al. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] (cross-sectional: mixed SE levels, prior online exposure the only positive correlate); Zhang et al. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] (quasi-experimental: distance learning students had lower performance and engagement than face-to-face). These eight studies collectively confirm that digital delivery does not inherently build SE; preparation, pedagogical quality, and learner readiness are determinants.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec30\" class=\"Section2\"\u003e \u003ch2\u003eSummary of findings\u003c/h2\u003e \u003cp\u003eThis scoping review mapped 69 studies from 25 countries to examine how self-efficacy has been conceptualized, measured, and influenced within digital nursing education. The most important finding is that self-efficacy in this literature is not a unitary construct. Instead, it operates across at least four related but analytically distinct domains: domain-specific clinical self-efficacy, academic self-efficacy, computer or technology self-efficacy, and online learning self-efficacy. This distinction is not merely semantic. Each domain reflects a different object of confidence, requires different measurement approaches, and has different implications for instructional design. For example, confidence in navigating a learning management system is not equivalent to confidence in performing clinical assessment, managing disaster response, engaging in therapeutic communication, or succeeding academically in an online course. Treating these forms of self-efficacy as interchangeable risks weakens both theoretical interpretation and educational intervention design. Across the reviewed studies, prior experience, digital literacy, self-regulation, motivation, task value, social presence, and teaching presence emerged as recurring positive correlates of self-efficacy. Conversely, psychosocial stressors, acculturative stress, anxiety, inadequate digital preparation, low instructional support, and emergency transitions to online learning were associated with weaker self-efficacy outcomes. Intervention studies showed the strongest and most consistent gains when digital learning environments incorporated active learning, authentic practice, feedback, reflection, and structured support. Simulation, flipped classroom models, gamification, AI-assisted tools, and theory-grounded online modules were especially promising. However, the null and negative findings are equally important. Several studies showed no significant self-efficacy advantage for digital or blended formats over conventional instruction, and some pandemic-era studies reported declines in confidence, engagement, or readiness. These findings clarify a central boundary condition: digital modality alone does not produce self-efficacy. Self-efficacy develops when instructional design activates the mechanisms through which efficacy beliefs are formed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003eImplications for nursing education\u003c/h2\u003e \u003cp\u003eThe evidence from Buthelezi and Wyk [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], Kim and Jeon [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], Jeon and Kim [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e], Demirelli and Karacay [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and Fitriawan et al. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]] isconsistent: inadequate computer or digital literacy functions as a barrier that prevents domain-specific clinical SE from developing in digital environments. Programs should assess and, where necessary, explicitly scaffold digital literacy before deploying digital learning content.Design for SE mechanisms, not delivery modality. The null findings from Mun and Hwang [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], Berga et al. [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], and Can and Dalcali [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] confirm that modality equivalence produces SE equivalence. The most effective designs in this corpus simulation with debriefing [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], DRI-based online instruction [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], theory-grounded vaccination training [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e], and AI-scaffolded writing courses [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] worked because they deliberately activated mastery experience, vicarious modeling, verbal feedback, and manageable affective challenges. This four-source scaffolding should be an explicit design criterion. Invest in faculty and preceptor SE. Studies of Culp-Roche et al. [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], Smith and Warner-[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], Wu et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], Liaw et al. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]],Enyan et al. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], and Hampton et al. [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] establish a transmission pathway from faculty SE to student SE through course design quality. Faculty development in digital teaching is not merely a personnel concern it is a student SE and patient safety concern. Do not use emergency remote teaching as the benchmark. Gulley et al. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] and Zhang et al. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] demonstrate that forced unplanned digital transitions can actively harm SE and clinical readiness. These findings should not be generalized to planned, well-resourced digital nursing programs. The distinction between emergency digitalization and intentional digital design is both theoretical and practical. Address equity in digital nursing education. Han et al. [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e] found acculturative stress and perfectionism negatively predicted SE among ESL nursing students. Demirelli and Karacay [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and Hemmati and Pourteimour [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] found consistent female SE advantages in online nursing environments, while Gulley et al. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] documented concerns about NCLEX-RN preparation in students from programs with lower digital infrastructure. Universal assumptions about digital readiness underestimate these differentials.\u003c/p\u003e \u003cp\u003eEvaluate emerging technologies rigorously. Kim and Kim [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], Jeon et al. [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e], and Makhlouf et al. [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e] provide early promising evidence for metaverse environments, interactive simulation technology, and AI chatbots, respectively. Programs investing in these tools should design evaluation studies that measure SE as a primary outcome using validated instruments, not just satisfaction or novelty ratings.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec32\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis review has several limitations. As a scoping review, it did not include a formal risk-of-bias appraisal; therefore, the findings should be interpreted as an evidence map rather than as conclusive estimates of intervention effectiveness. The included studies were methodologically heterogeneous, with variation in design, populations, interventions, comparison groups, and outcome measures. Measurement heterogeneity was especially substantial, with more than 25 self-efficacy instruments and frequent use of self-developed scales. This prevented meta-analysis and limited direct comparison across studies. The search was developed within a broader health professions education context and then narrowed to nursing, which may have introduced selection bias during population filtering. Qualitative evidence was limited, restricting insight into learners\u0026rsquo; subjective experiences of self-efficacy development in digital environments. Finally, the concentration of studies during and after the COVID-19 pandemic may have amplified findings related to emergency remote instruction, stress, and digital adaptation.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eSelf-efficacy in digital nursing education is multidimensional, context-sensitive, and shaped by instructional design rather than delivery modality. This scoping review of 69 unique studies from 25 countries establishes that: (1) SE encompasses four interrelated domains requiring distinct measurement approaches measurement standardization is an urgent priority; (2) prior experience, digital literacy, self-regulation, and social/teaching presence are the most consistent positive correlates, while technostress, pandemic-related distress, and passive digital content delivery are negative; and (3) simulation with structured debriefing, flipped classroom designs, theory-grounded online modules with authentic feedback, gamification, AI-assisted tools, and deliberate faculty development reliably promote SE when they activate Bandura's four self-efficacy sources. Eight null and negative findings define the boundary: digital technology itself does not build SE. Future research should prioritize validated measurement batteries, longitudinal follow-up to clinical practice settings, equity-focused designs, and rigorous evaluation of emerging modalities.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e \u003cp\u003eNot applicable. This scoping review analyzed previously published studies and did not involve direct recruitment of, or interaction with, human participants. No ethical approval or institutional review was required.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to participate\u003c/strong\u003e \u003cp\u003eNot applicable. This study is a scoping review of previously published literature. No human participants were directly recruited or enrolled, and therefore no consent to participate was required.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDeclaration of interest\u003c/strong\u003e \u003cp\u003eNo potential conflict of interest relevant to this article was reported.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis scoping review received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthors' contributions\u003c/h2\u003e \u003cp\u003eT.J.R. and B.M.B. conceptualized the study. T.J.R. and B.M.B. developed the methodology and conducted data curation and formal analysis. T.J.R. performed the literature search, screening, and data extraction. T.J.R. wrote the original draft of the manuscript. B.M.B. contributed to critical revision of the manuscript for important intellectual content. Both authors reviewed, edited, and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eThe full extraction table is presented as Table\u0026nbsp;1.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKoob C, Schr\u0026ouml;pfer K, Coenen M, Kus S, Schmidt N (2021) Factors influencing study engagement during the COVID-19 pandemic: A cross-sectional study among health and social professions students. 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Int Nurs Rev 69(2):159\u0026ndash;166\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Houston","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"digital learning, nursing education, nursing students, online learning, self-efficacy","lastPublishedDoi":"10.21203/rs.3.rs-9657971/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9657971/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSelf-efficacy is central to nursing education because it shapes learners\u0026rsquo; confidence in acquiring clinical, academic, and technology-mediated competencies. The rapid expansion of digital learning after the COVID-19 pandemic has created diverse instructional contexts in which nursing students, nurses, faculty, and preceptors develop self-efficacy. However, evidence on how self-efficacy is conceptualized, measured, and strengthened in digital nursing education remains fragmented. This scoping review mapped the literature on self-efficacy in digital nursing education by addressing three questions: how self-efficacy is conceptualized and measured; which learner, faculty, contextual, and instructional factors are associated with self-efficacy; and which digital interventions improve, reduce, or show no effect on self-efficacy outcomes. Five databases were searched: MEDLINE, PsycINFO, CINAHL, Education Source, and Web of Science. After deduplication and eligibility screening, 69 unique studies published between 2018 and 2025 were included. Studies were conducted in 25 countries and primarily involved undergraduate nursing students, followed by graduate students, practicing nurses, and faculty or preceptors. Four self-efficacy domains were identified: domain-specific clinical self-efficacy, academic self-efficacy, computer or technology self-efficacy, and online learning self-efficacy. Measurement was highly heterogeneous, with more than 25 instruments and frequent use of ad hoc scales. Most studies reported positive self-efficacy outcomes, particularly for simulation, flipped classroom models, gamification, AI-assisted tools, and theory-grounded online modules. However, null and negative findings showed that digital delivery alone does not improve self-efficacy. Effective outcomes depend on instructional design, learner readiness, feedback, and structured opportunities for mastery.\u003c/p\u003e","manuscriptTitle":"Self-efficacy in digital nursing education: a scoping review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-12 18:36:49","doi":"10.21203/rs.3.rs-9657971/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"45fbecd2-841c-4226-ad95-232fc8fad157","owner":[],"postedDate":"May 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":67817410,"name":"Nursing"},{"id":67817411,"name":"Educational Psychology"}],"tags":[],"updatedAt":"2026-05-12T18:36:49+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-12 18:36:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9657971","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9657971","identity":"rs-9657971","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}