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This proposed study aims to develop augmented reality (AR) based intervention during the smoking cessation counselling(SCC) training for master nursing students in the University of Hong Kong.
Hypotheses to be tested: (1) AR animations can improve nursing students' knowledge, skills in SCC compared to conventional teaching methods. (2)Student satisfaction and engagement with AR-based learning can be improved. (3) The training will increase master nursing students' self-efficacy to application of 5As SCC skill.
The study is a pragmatic randomized controlled trial (RCT) with a 1:1 allocation ratio, using AR animations for intervention and control groups. The intervention group receives messages related to SCC, while the control group receives generic mental health information. The subjects are MN students enrolled in the "Tobacco Dependency Nursing Intervention and Management" course.
The study uses various tools for measurement, including Providers Smoking Cessation Training Evaluation(ProSCiTE), and The Instructional Materials Motivation Survey (IMMS). The main outcome measures include SCC practice frequency,SCC knowledge score, SCC attitude score, and SCC practice score.
Data will be entered into SPSS for Windows (version 20) for analysis. Descriptive statistics including frequency, percentage, and mean will be used to summarize the outcomes and other variables. By intention-to-treat analysis, participants who are lost or refuse the follow-up will be treated as no change in the training outcomes. Chi-square tests and t-tests will be used to compare outcomes between intervention and control groups. The effect size, Cohen's d, will be computed for the standardized mean of the pre-post differences, both with and without adjustment for baseline characteristics. Additionally, Cohen's f will be calculated to assess the magnitude of the intervention effect in the linear mixed models. These models, which account for multiple observations per subject and clustering effects, will be used to analyze the intervention's impact on self-efficacy, motivation, and KAP. Both the main effect (group allocation) and interaction effect (group × time) will be examined to determine the intervention's effectiveness.
Full description
This study proposes the development and evaluation of an augmented reality (AR)-based intervention integrated into the smoking cessation counselling (SCC) training for Master of Nursing (MN) students at the University of Hong Kong. The goal is to enhance students' competencies in applying the 5As framework (Ask, Advise, Assess, Assist, Arrange) in tobacco dependency interventions.
This study adopts a two-arm, waitlist-controlled, pragmatic randomized controlled trial (RCT) design with a 1:1 allocation ratio. Eligible participants are MN students enrolled in the "Tobacco Dependency Nursing Intervention and Management" course (NURS8205) in the Spring 2025 semester. Participants will be randomly assigned into intervention and control groups, stratified by tutorial group, and balanced across four trained facilitators.
Intervention Group: Receives the AR-enhanced SCC tutorial, which includes the following components:
Control Group: Receives the standard tutorial format, which includes:
The intervention has been developed to align with adult learning theory and aims to enhance knowledge retention, skill application, and learner engagement. Tutors leading both intervention and control sessions will receive standardized training to ensure consistency.
Measurement and Data Collection Assessments will be conducted at baseline (pre-intervention), immediately post-intervention, and follow-up at 2-month post-intervention.
Key instruments include:
Data Analysis Data will be analyzed using SPSS for Windows version 20. Descriptive statistics (means, SDs, frequencies, and percentages) will summarize baseline characteristics and outcome variables.
Intention-to-treat analysis will be applied, where participants lost to follow-up will be assumed to have no change from baseline scores.
Independent t-tests and chi-square tests will compare primary and secondary outcomes between groups.
Effect sizes will be calculated:
Cohen's d for standardized pre-post mean differences. Cohen's f for evaluating the intervention effect size in linear mixed-effects models, which will control for repeated measures and potential clustering effects (e.g., by tutorial group or tutor).
These models will assess both:
Main effect of the intervention (between-group differences). Interaction effect between group and time (i.e., whether change over time differs between groups).
Expected Impact
It is anticipated that the AR-based intervention will lead to:
Increased self-efficacy in delivering SCC using the 5As model. Enhanced knowledge and positive attitudes toward smoking cessation. Improved SCC practice behaviors during clinical placements. Greater learner motivation and satisfaction compared to traditional tutorial methods.
This innovative pedagogical approach aligns with contemporary nursing education trends and aims to equip future nurses with effective behavioral counselling skills to address tobacco dependence.
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50 participants in 2 patient groups, including a placebo group
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Data sourced from clinicaltrials.gov
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