Artificial Intelligence (AI), Communication Skills, Empathy, Grit, Pediatric Nursing, Scaffolding
Conditions
Brief summary
The nurse-patient communication environment in pediatric care is characterized by high uncertainty and complexity. Due to children's limited language development and emotional regulation abilities, coupled with parents' high level of involvement, nursing students often experience anxiety, lack of confidence, and avoidance behaviors, which negatively affect their clinical learning outcomes and the establishment of therapeutic relationships. Therefore, providing effective communication support strategies is essential in pediatric nursing education. This study aims to implement an instructional scaffolding model using artificial intelligence (AI)-generated empathy maps to enhance the communication skills, empathy performance, and grit of nursing students during pediatric clinical practicums when encountering communication challenges. A mixed-methods research design was adopted, and the participants were third-year nursing students enrolled in a pediatric nursing practicum course. The teaching intervention included AI-assisted generation of age-appropriate communication strategies, the construction of a grit-oriented empathy map, small group scenario-based exercises, and the application of learned strategies in clinical settings. Quantitative data were collected using pre- and post-intervention assessments, including an empathy scale, a communication skills scale, and a grit scale, to evaluate changes in learning outcomes. Qualitative data, including reflective journals, clinical observations, and focus group interviews, were analyzed to explore students' learning processes and strategy adaptations. Triangulation was applied to strengthen the validity of the findings. It is anticipated that this teaching model will enhance students' understanding of pediatric patients' emotional needs, strengthen their communication strategy application and clinical interaction quality, and promote persistence and adaptability in challenging situations. Through evidence-based teaching practice, this study is expected to provide a feasible and scalable innovative instructional model that supports the effective integration of AI into clinical nursing education, thereby improving pediatric nursing competence and the quality of care for children.
Interventions
BEHAVIORALAI-Supported Empathy-Map Scaffolding Model
The AI-Supported Empathy-Map Scaffolding Model is an educational intervention that combines empathy-map construction with AI-assisted reflective prompts to enhance communication skills, empathy, and grit in pediatric nursing students. The intervention uses case-based learning within regular coursework, involves no clinical treatment or patient contact, and is considered minimal risk.
Sponsors
Mackay Memorial Hospital
Study design
Allocation
NON_RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to 25 Years
Healthy volunteers
Yes
Inclusion criteria
1. Undergraduate nursing students aged 18 years or older 2. Students enrolled in the Pediatric Nursing Practicum course
Exclusion criteria
1\. Students who have not passed the Pediatric Nursing course
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Communication Skills | Baseline (pre-intervention) and immediately post-intervention | Communication Competence Instrument (CCI). The Communication Competence Instrument was developed by Lee (2013) to enhance nurse-patient communication skills among nursing students. The instrument consists of eight items rated on a five-point Likert scale, with scores ranging from 1 (strongly disagree) to 5 (strongly agree). Sample items include: "I am able to establish a good nurse-patient relationship with patients/family members" and "I am able to ensure that patients/family members understand the key points of the communication." Higher scores indicate better communication competence. In Lee's study, the instrument demonstrated excellent reliability and validity, with a Cronbach's α of 0.92, a Spearman-Brown coefficient of 0.88, and a Guttman split-half coefficient of 0.88, indicating strong internal consistency and satisfactory psychometric properties for assessing communication behaviors. |
Outcome results
None listed