An Interpretable Machine Learning Approach to Predict Sensory Processing Sensitivity Trait in Nursing Students.

Sensory processing sensitivity (SPS) is a personality trait that makes certain individuals excessively sensitive to stimuli. People carrying this trait are defined as Highly Sensitive People (HSP). The SPS trait is notably prevalent among nursing students and nurse staff. Although there are HSP diagnostic tools, there is little information about early detection. Therefore, the aim of this work was to develop a prediction model to identify HSP and provide an individualized nursing assessment. A total of 672 nursing students completed all the evaluations. In addition to the HSP diagnosis, emotional intelligence, communication skills, and conflict styles were evaluated. An interpretable machine learning model was trained to predict the SPS trait. We observed a 33% prevalence of HSP, which was higher in women and people with previous health training. HSP were characterized by greater emotional repair (p = 0.033), empathy (p = 0.030), respect (p = 0.038), and global communication skills (p = 0.036). Overall, sex and emotional intelligence dimensions are important to detect this trait, although personal characteristics should be considered. The present individualized prediction model could help to predict the presence of the SPS trait in nursing students, which may be useful in conducting intervention strategies to avoid the negative consequences and reinforce the positive ones of this trait.

Adaptation of the Highly Sensitive Person Scale (HSP) and Psychometric Properties of Reduced Versions of the Highly Sensitive Person Scale (R-HSP Scale) in Spanish Nursing Students.

Sensory processing sensitivity (SPS) can be defined as a personality characteristic that includes the individual characteristics of sensitivity towards endogenous and exogenous stimuli. The differences in environmental sensitivity can play a crucial role in the academic context of health professionals, thus defining it as an area of research that must be addressed. The reduced scale for highly sensitive people (HSP) is a short (16 items) and adapted version of the original scale for highly sensitive people (HSP). This study aims to analyze the psychometric properties of reduced versions of the Highly Sensitive Person Scale (r-HSP Scale) in Spanish nursing students. Once the questionnaire was translated, its psychometric characteristics were analyzed. The Spanish version of the r-HSP scale was administered to 284 university students enrolled in the Nursing Degree. The results from the factorial analysis confirmed the structure of sensitiveness of six factors in our sample. This structure included the following dimensions: (1) Instability, (2) Surroundings, (3) Interaction with others, (4) Sensoperception, (5) Sensitivity, and (6) Insecurity. Additionally, the Cronbach's α values indicated that the Spanish version of the r-HSP scale had an adequate reliability (α = 0.702). The r-HSP scale is defined as a reliable, valid, and agile replica of the original structure of sensitivity in Spanish university students.

Nurse Training in Gender-Based Violence Using Simulated Nursing Video Consultations during the COVID-19 Pandemic: A Qualitative Study.

Gender-based violence (GBV) is a serious global public health problem that becomes aggravated during public health emergencies that involve quarantine measures. It is important to train nursing students on GBV, especially in vulnerable situations, such as the current COVID-19 pandemic. The purpose of our study is to explore the perceptions of third-year nursing students about simulated nursing video consultations for providing assistance to potential cases of GBV victims using a high-fidelity clinical simulation methodology. After all of the simulated scenarios were completed, 48 scripted interviews were carried out following a guide composed of four open-ended questions to facilitate in-depth discussion. A descriptive qualitative study based on the interpretative paradigm was conducted. The nursing students indicated that they improved their knowledge on GBV victim management (mainly their awareness of the problem, recognition of the role of nursing professionals, and performance of non-technical skills), although they also mentioned the need for continuous training (particularly in socio-emotional skills, interview techniques, a holistic nursing care approach, and not presupposing). This innovative high-fidelity simulation methodology allows nursing students to improve their awareness of the GBV problem, acquire a realistic view about their role in addressing GBV, and build their non-technical skills (such as active listening, communication skills, empathy, and generating confidence) required to adequately care for victims of GBV.