Nursing Practice Today

Factors related to depression among transgender women: A systematic review

Patcharin Krongtham — 2025-03-16

Background & Aim: Transgender women represent a vulnerable population with a high rate of depression. This systematic review aims to identify and analyze the factors associated with depression in this population.
Methods & Materials: The research protocol was registered with PROSPERO. A systematic search was conducted using PubMed, MEDLINE, Scopus, and ProQuest for studies published between 2014 and 2024. Relevant studies focusing on depression and related factors in transgender women were selected. Data extraction focused on identified factors associated with depression. The reporting of this review adhered to PRISMA guidelines, and the quality of included studies was appraised using JBI’s critical appraisal tools. A narrative synthesis was conducted to synthesize the findings.
Results: From 2,511 records identified in the database, 14 cross-sectional studies were included in the review. The analysis revealed three primary categories of factors related to depression: demographic, psychological, and sociological factors. Key demographic factors included age and insufficient income, both of which were at increased risk of depression. Psychological factors such as self-stigma and self-esteem were associated with higher depression rates. Sociological factors, including family support, peer support, and violence, were also significant predictors of depression in transgender women.
Conclusion: Depression in transgender women is influenced by a complex interaction of demographic, psychological, and sociological factors. These findings underscore the need for tailored nursing interventions that incorporate mental health support.

AI-driven fall risk prediction in inpatients: Development, validation, and comparative evaluation

Chia-Lun Lo — 2025-03-15

Background & Aim: Falls among hospitalized patients pose severe consequences, necessitating accurate risk prediction. Traditional assessment tools rely on cross-sectional data and lack dynamic analysis, limiting clinical applicability. This study developed an AI-based fall risk prediction model using supervised learning techniques to enhance predictive accuracy and clinical integration.
Methods & Materials: This study was conducted at a medical center in Taiwan, excluding pediatric patients due to non-disease-related fall factors. Fall cases were obtained from hospital records, and non-fall cases were stratified based on age and gender to create a balanced 1:1 dataset.
A total of 52 predictive variables were identified and refined to 39 through expert review. The AI model was compared with MORSE, STRATIFY, and HII-FRM using supervised learning with 10-fold cross-validation. Performance was evaluated based on accuracy, sensitivity, and specificity.
Results: The results demonstrated that the AI-based model significantly outperformed traditional fall risk assessment tools in accuracy, sensitivity, and specificity. More importantly, the model’s superior predictive power allows for real-time risk assessment and seamless integration into clinical decision support systems. This integration can enable timely interventions, optimize patient safety protocols, and ultimately reduce fall-related incidents in hospitalized settings.
Conclusion: By automating risk assessment, the AI model can alleviate the workload of healthcare professionals, reducing the time required for manual evaluations and minimizing subjective biases in clinical decision-making. This not only enhances operational efficiency but also allows nursing staff to allocate more time to direct patient care. These findings underscore the transformative potential of AI-driven approaches in healthcare, improving patient safety through data-driven.

Psychometric evaluation of the Farsi version of the stressor scale for emergency nurses

Fazel Dehvan — 2025-03-03

Background: Emergency department nurses experience unique stressors that contribute to elevated levels of occupational stress. Most existing instruments assess general occupational stress without addressing workplace-specific factors. This study aims to evaluate the psychometric properties of the Farsi version of the Stressor Scale for Emergency Nurses (F-SSEN).

Methods: Face and content validity were assessed by five clinical nurses and five nursing experts, respectively. Construct validity, known group validity, and convergent validity were tested on 198 emergency nurses. The test-retest reliability was evaluated in 21 nurses over a two-week interval. Internal consistency was measured using Cronbach's alpha and McDonald's omega coefficients.

Results: Face and content validity were found to be satisfactory. Exploratory factor analysis (EFA) identified four factors—conflicts, life and death situations, patients' families' actions and reactions, and technical and formal supports—which explained 60.64% of the total variance. Convergent validity showed a correlation of 0.554 between job stress scores based on SSEN and Brief Nursing Stress Scale (BNSS). Known group validity revealed that occupational stress scores were higher in women than in men, and there was a significant negative correlation between occupational stress scores and work experience in the emergency department. Cronbach's alpha and McDonald's omega coefficients were 0.953 and 0.954, respectively, and the intraclass correlation coefficient was 0.943.

Conclusions: The Farsi version of the stressor scale for emergency nurses demonstrates strong psychometric properties, making it reliable for measuring occupational stress in emergency nurses.

Prioritizing just culture: A call to action for patient safety

Esmaeil Moshiri — 2025-03-03

Patient safety incidents have emerged as a significant global concern, impacting healthcare systems worldwide, as highlighted by the WHO's report of 134 million adverse events annually in hospitals. Healthcare professionals often hesitate to report such incidents due to stigma and the fear of criticism. To combat this, the implementation of a "no-blame culture," introduced by James Reason in 1997, has gained traction, evolving into the concept of a just culture—an environment fostering open discussion of safety-related information without fear of retribution. This approach facilitates an effective incident reporting system and enhances staff capabilities while building organizational trust and accountability. Previous research indicates that adopting a just culture can lead to increased reporting of patient safety incidents, enabling healthcare staff to learn from them, thus reducing the likelihood of future incidents. It’s critical to recognize that a just culture focuses on systemic issues rather than individual blame, which encourages reporting and corrective action. However, this culture is not yet widespread due to misunderstandings. Healthcare leaders and policymakers are urged to promote a just culture by implementing strategies like transparent reporting mechanisms, clear error identification processes, exemplary leadership, and ongoing assessments, ultimately prioritizing patient safety.

The effect of pro-self-pain control and its plus guided imagery on pain in breast cancer outpatients: A quasi-experimental study

Nurnianingsih A. Yasin — 2025-02-17

Background & Aim: Globally and in Indonesia, the number of people with breast cancer is still rising, and one of the most commonly reported symptoms is pain. After hospitalization, patients continue their lives at home, and most receive care in an outpatient setting. In this setting, they voluntarily need to be able to manage their pain. Therefore, teaching and assisting patients in self-management is essential for adequate pain management. This study aims to determine the effect of pro-self-pain control and guided imagery interventions on reducing pain intensity in outpatient breast cancer.
Methods & Materials: A quasi-experimental design, using convenience sampling on 49 patients, and allocated into an intervention group (n=25) that received pro-self-pain control and guided imagery intervention and a control group as a comparison (n=24) that received pro-self-pain control only. Pain intensity in both groups was measured before the experiment and ten days after using the Numeric Rating Scale.
Results: The results showed that there was a significant decrease in pain intensity in the intervention group p<0.001. The control group also experienced a decrease in pain intensity, but not significant p=0.212. Before the intervention, both groups showed no significant difference (p=0.872). However, after the intervention, the difference test between the two groups showed a significant difference with a p=0.004 and a small effect size (d=0.40).
Conclusion: The combination intervention of Pro-self-pain control and guided imagery (with audio recordings) effectively reduces pain intensity, although the effect size produced tends to be small. In caring for cancer patients, it is recommended to improve health education regarding pain management, thereby enabling them to self-manage their pain and participate actively in controlling it.