Measuring the Science of Caring: A Patient-Centred Predictive Model for the Caring Interaction

Area of Science:

• Nursing Science
• Healthcare Quality Improvement
• Patient Experience Research

Background:

• The nurse-patient relationship is crucial for quality care but difficult to measure.
• Existing tools lack direct patient feedback on caring competencies.
• Validated instruments are needed to assess patient-perceived nursing interactions.

Purpose of the Study:

• To develop and validate the Nursing Interaction in Caring Competence Assessment-Patient (NIC_CA-Patient) tool.
• To create a patient-centered instrument for measuring nursing caring interactions.
• To establish a predictive model of caring interaction from the patient's viewpoint.

Main Methods:

• Cross-sectional study in eight hospitals with 1060 internal medicine patients.
• Adaptation of the Caring Nurse-Patient Interactions (CNPI) scale.
• Validation using Exploratory Factor Analysis (EFA) and Partial Least Squares Structural Equation Modelling (PLS-SEM).

Main Results:

• A three-dimensional model (therapeutic relationship, problem management, adaptation) explained 79% of patient-reported experiences.
• The NIC_CA-Patient tool demonstrated high reliability (Cronbach's α = 0.97).
• Excellent model fit indices (SRMR = 0.03, AVE > 0.7) confirmed the model's validity.

Conclusions:

• The NIC_CA-Patient tool offers a quantifiable, predictive measure of nursing care from the patient's perspective.
• Implementation can enhance patient-centered care by highlighting relational factors.
• This tool can improve health outcomes and patient experience in clinical practice and research.