Mental health nurses, together with psychiatrists, are the healthcare professionals who display the highest levels of empathy and the best attitudes towards patients with mental disorders. However, burnout is a common problem among these professionals. The aim of our study is to describe the association between empathy, burnout, and attitudes towards patients with mental disorders among mental health nurses in Spain. A descriptive cross-sectional design was used involving a sample of 750 specialist nurses working in mental health facilities in Spain. An intentional, non-probability, non-discriminative, exponential snowball sampling method was used. The Jefferson Scale of Empathy, the Maslach Burnout Inventory, and the Community Attitudes towards Mental Illness Inventory were used to measure the study variables. A positive correlation was observed between empathy and all the study variables, with the exception of the personal accomplishment dimension of burnout and the social restrictiveness and authoritarianism dimensions of attitudes towards mental illness, where a negative relation was observed. Our findings suggest that empathy is associated with an increase in positive attitudes towards patients with mental disorders, decreasing associated stigma, but did not act as a protective factor against burnout in the study sample.

Stress and stressors related to clinical practice are some of the main reasons for the discomfort reported by nursing students. It is important to identify the causes of stress and seek strategies to reduce the stress levels in nursing students. Clinical training seminars have proven to be a useful tool to reduce stress levels. This study aims to evaluate the effects of a series of clinical training seminars on the levels of stress and perception of stress factors before the start of clinical practice among undergraduate Spanish nursing students. A two-phase, sequential mixed-methods design was used. For the quantitative phase, data were collected using Cohen’s Perceived Stress Scale and the KEZKAK questionnaire before and after the clinical training seminars. Qualitative data were collected through a focus group session held after the clinical training period. The results show a significant reduction (p = 0.002) in perceived stress levels after the clinical training seminars, and also a change in students’ perception of stressors in the clinical placement. This study provides valuable information for the development of content for clinical training seminars. Universities should develop strategies to reduce stress in their students caused by the clinical placement.

Background/Objectives: Nursing diagnosis is a complex process that requires clinical judgment, time, and resources and whose implementation is hindered by factors such as workload, lack of time, and resistance to computerized systems. This study aimed to compare the quality and efficiency of care plans generated by nursing professionals versus those produced by an artificial intelligence (AI) model, using the NANDA, NOC, and NIC taxonomies as criteria. Methods: An observational study was carried out with three simulated clinical cases. Thirty experts, fifty-four nursing professionals, and the ChatGPT model (GPT-4) were included. The experts established the referral plans using the Delphi technique. Responses were evaluated with a validated rubric (EADE-2) and analyzed using nonparametric tests. Professionals’ perceptions on the use of computer systems were also collected. Results: ChatGPT scored significantly higher on several dimensions (p < 0.001) and resolved all three cases in 35 s, compared to an average of 30 min for practitioners. Professionals expressed dissatisfaction with current diagnostic documentation systems. Conclusions: AI demonstrates high potential in optimizing the diagnostic process in nursing, although for its implementation human supervision, ethical aspects and improvements in current systems must be considered to achieve effective integration.

Introduction: Of the serious problems that characterise the current crisis in Spain, the most alarming and revealing is unemployment, which, despite being so common, continues to be quite a negative experience for most people, often with serious negative effects on their biopsychosocial health. The perpetuation of this situation has given rise to a new syndrome of the unemployed. If these effects of economic downsizing are accompanied by the magnitude of the current situation brought about by COVID-19, the results can be devastating for the individuals and families experiencing it. Objective: To compare the symptoms of the unemployed syndrome in three population groups. Method: Three groups were studied: short-term unemployed (n = 91), long-term unemployed (n = 150), and those unemployed during the COVID-19 pandemic (n = 94). Unemployment syndrome was assessed with the Unemployment Syndrome Scale (USS). The three population groups were contacted through web pages, social networks, etc. and answered the instruments online in a single session. Once the responses were obtained, their information was encoded in a database and analysed through the SPSS v. 21 program. Population groups were compared using the ANOVA analysis and the Bonferroni post hoc test. Results: The unemployed individuals who lost their job during the pandemic reported higher scores in the symptoms of the Unemployed Syndrome Scale compared to the long- and short-term unemployed individuals. ANOVA analyses for symptoms of USS were all significant in the different groups considering a significance level of <0.005. Participants who were unemployed for less than one year had lower scores in the USS than the long-term unemployed participants and those unemployed during the COVID-19 pandemic that reported a significantly higher number of symptoms in the USS.

Background: Digital health literacy is crucial for navigating social media as a primary health information source. However, its interactive and unregulated nature fosters misinformation, requiring critical evaluation skills. Existing tools assess general internet use, but no validated instrument measures competencies specific to social media. This study aimed to adapt and validate the eHealth Literacy Scale (eHEALS) for this context. Methods: A content validation process was conducted with 33 experts, who evaluated the clarity, coherence, and relevance of the adapted questionnaire using item-level (I-CVI) and scale-level (S-CVI) content validity indices. A pilot study was then carried out with 250 participants to assess the instrument’s reliability and feasibility, measured through Cronbach’s alpha and McDonald’s Omega. Results: The adapted eHEALS demonstrated excellent content validity (S-CVI > 0.90) and high internal consistency (Cronbach’s α = 0.92; McDonald’s Ω = 0.92). The tool effectively captures key competencies for evaluating and applying health information in social media contexts, with exploratory factor analysis confirming a unidimensional structure that explained over 60% of the variance, supporting its robustness for use in population-based studies. Conclusions: This validated instrument provides a reliable method for assessing digital health literacy in social media, supporting the development of educational interventions to enhance critical appraisal skills and mitigate the impact of misinformation.

(1) Background: The Covid-19 pandemic has put our healthcare systems to the test, exposing their vulnerability and demanding a high degree of commitment and dedication from healthcare teams to confront and contain the disease. In this sense, nursing professionals have played a prominent role in the treatment of complex cases that have required hospitalisation and have manifested pre-existing health complications or mortality. This unprecedented situation made it difficult to regulate the emotional impact and manage grief, often turning it into a traumatic grief whose psychological and emotional manifestations are increasingly evident but very little researched in the current context. (2) Purpose: Validation of the definition, defining characteristics and related factors for the proposal of the nursing diagnosis of professional traumatic grief. (3) Method: Based on Fehring’s content validation model, the label name, defining characteristics and other related factors were agreed upon by Spanish experts. (4) Results: The content validity index was 0.9068. A total of 21 defining characteristics were validated by the experts, as all of them scored above 0.6. With respect to the related factors of the proposed 10, all were validated. (5) Conclusion: The present study supports the proposal to develop a nursing diagnosis for professional traumatic grief. The use of standardised language is only the first step in establishing professional traumatic grief as a diagnostic category.