BMC Nursing最新文献

Background: Multiple international studies report on the use of diaries in intensive care units focusing on benefits for patients, families, and occasionally professionals. Most studies use quantitative methods and have limitations such as small sample sizes and short follow-ups. Therefore, further research with larger samples and a longer follow-up period, employing a mixed-methods approach is suggested. This protocol aims to assess the efficacy of the use of intensive care unit diaries for patients and families and explore professionals' experiences and satisfaction.

Method/design: Mixed-method study: a quantitative phase followed by a qualitative phase. Phase 1: Randomised, parallel, non-blinded, multicentre clinical trial, with an experimental group (diary) and a control group (no diary), to identify the efficacy of the diary in improving quality of life and preventing post-traumatic stress and anxiety/depression in patients and family. Measurement tools include the SF-36 Health Questionnaire, EIE-R scale, and HADS scale, administered 2-, 6- and 12-months post-discharge. Each group comprises 120 cases. Data analysis will use IBM-SPSS (v.24) To evaluate the satisfaction of professionals a survey will be carried out. Phase 2: Hermeneutic phenomenological study with theoretical sampling. Size of 38-72 patients/family members until theoretical data saturation is reached. Data collection from in-depth interviews and field diary 6 months after discharge. Phenomenological analysis according to Smith. Guba and Lincoln's rigour criteria.

Discussion: This research will provide knowledge regarding the benefits and limitations of the use of diaries, based on quantitative and qualitative data, and will promote reflection on their implementation, considering patients, family, and professionals. This study will provide new knowledge about the satisfaction of professionals with diary implementation. This multicentre study will provide valuable information on the contribution of diaries in clinical practice and their impact on patient recovery and the experiences of families and professionals. If the efficacy of the diary is confirmed, it will mark a significant advancement in the care of critically ill patients, contributing to the expansion of their use.

Trial registration: ClinicalTrials.gov Identifier NCT05288140. First Published March 21, 2022. Version 1.

Background: Oncology nurses are at particular risk for closely related types of distress, such as compassion fatigue, burnout, occupational stress, and moral distress, because they are often the ones who must carry out what they consider to be medically futile treatments that may cause pain in a dying older patient. This study aimed to examine the influence of selected coping mechanisms on occupational stressors among oncology nurses in Jordan.

Methods: A descriptive, correlational, cross-sectional design was employed. Data were collected between February and March 2024 from oncology nurses working in three major teaching hospitals in Jordan. Occupational stressors were assessed using the Nurse Stress Scale (NSS), and coping mechanisms were measured using the Brief COPE. Descriptive statistics, Pearson correlation analysis, and hierarchical multiple regression analysis were used to examine relationships between occupational stressors and coping mechanisms.

Results: Pearson correlation analysis revealed a statistically significant moderate positive correlation between the NSS Death and Dying subscale and the Brief-COPE Problem-Focused Coping subscale (r = 0.254, p < 0.01). A significant positive correlation was also found between overall coping mechanisms and occupational stressors (r = 0.33, p < 0.01). Regression analysis further demonstrated that coping mechanisms were significant predictors of occupational stressors (β = 0.441, p < 0.001). The findings indicate that higher coping scores were associated with higher stress levels, suggesting that coping strategies were more frequently employed in response to elevated occupational stress rather than serving as a protective factor.

Conclusion: Jordanian oncology nurses who experience higher stress levels related to death and dying are more likely to employ problem-focused coping strategies, such as actively addressing challenges, seeking solutions, and obtaining support. Although these coping strategies are adaptive, the overall high stress levels observed suggest that occupational stress remains a serious concern for nurses' well-being and professional performance.

Background: The application of artificial intelligence in mental health faces unique challenges. Psychiatric nurses provide direct care to patients with mental illness, and their attitudes toward artificial intelligence will directly impact the effectiveness of related technologies in clinical practice.This study aims to explore psychiatric nurses' attitudes toward artificial intelligence applications, identify their needs and expectations, and assess their awareness of potential risks and challenges.

Methods: This qualitative descriptive study employed semi-structured in-depth interviews with 15 psychiatric nurses (each with at least two years of clinical experience) recruited from Henan Mental Health Center. Interview transcripts were coded independently by two researchers and analyzed using inductive thematic analysis with NVivo 12.0; any coding discrepancies were resolved through consensus.

Results: Thematic analysis revealed three core themes: Core needs and expectations, Key risks and challenges, and Implementation pathways and policy aspirations. For example, nurses anticipated that AI could alleviate their workload and improve patient safety, but they also voiced concerns about data privacy and the preservation of humanistic care.

Conclusions: Psychiatric nurses generally adopt a positive yet cautious stance toward clinical artificial intelligence applications. While they anticipate artificial intelligence to enhance nursing efficiency and patient safety, significant concerns exist regarding ethical issues, compromised humanistic care, and professional role displacement triggered by artificial intelligence.