Background Family members of ICU decedents are at high risk of adverse psychological outcomes, including prolonged grief. However, evidence regarding the effectiveness of existing family support interventions remains limited. Objectives To evaluate the effectiveness of interventions to prevent or treat prolonged grief symptoms among families of patients who die in ICUs. Methods A systematic review and meta-analysis were conducted following JBI methodology. Family members of ICU decedents were included. Databases searched included CINAHL, Academic Search Complete, Psychology and Behavioral Sciences Collection, Cochrane Central Register of Controlled Trials, MEDLINE via PubMed, APA PsycINFO, Web of Science Core Collection, and Scopus. The primary outcome was prolonged grief symptoms. Secondary outcomes included post-traumatic stress symptoms, anxiety and depression symptoms. Mean differences (MD) were pooled using random-effects models with 95% CI. Certainty of the evidence was assessed using the GRADE approach. Results Eight studies were included. Evidence regarding prolonged grief symptoms at six months was uncertain, with no consistent pooled effect observed (MD 0.50; 95% CI –6.41 to 7.41; very low certainty). The pooled estimate was limited by the small number of studies contributing to the meta-analysis. Post-traumatic stress symptoms were reduced at three months (MD –9.29; 95% CI –13.36 to −5.23; low certainty) and at the longest available follow-up, with very low certainty. Small reductions in anxiety and depression symptoms were observed with very low certainty. Conclusions Evidence regarding the effects of ICU-based interventions on prolonged grief symptoms is uncertain. Some interventions may reduce post-traumatic stress, anxiety and depression symptoms. Future research should prioritise powered trials evaluating sustained, theory-driven, multicomponent, and culturally adapted interventions spanning the dying process and bereavement, with explicit attention to grief adaptation mechanisms and longer follow-up periods. Implications for clinical practice Current evidence is uncertain to support recommendations for preventing or treating prolonged grief symptoms. Structured information provision, psychoeducational and supportive approaches, and opportunities for emotional expression delivered before death, during the dying process, and throughout bereavement may be considered as components of family-centred ICU care.
The AlSi10Mg alloy is widely used in metal additive manufacturing (AM), yet optimal post-processing routes for components produced by Powder Bed Fusion-Laser Beam (PBF-LB/M) remain unclear due to their highly refined and non-equilibrium microstructures. Conventional T6 heat treatments, effective for cast alloys, often cause softening in PBF-LB/M AlSi10Mg. This work establishes aging curves through a systematic assessment of temperature-time combinations and correlates them with microstructural evolution and mechanical behavior. The as-built alloy exhibited a supersaturated and highly refined non-equilibrium microstructure, resulting in high tensile strength. Among all evaluated conditions, direct aging at 150°C for 2 h (DA 150/2.0) produced the highest hardness and tensile performance without prior solution treatment. Natural aging for at least 48h was required to achieve peak hardness. DA 150/2.0 preserved the eutectic Si network while promoting dense precipitation of nanometric Si particles, which improved strengthening via the Orowan mechanism. This condition increased yield and ultimate tensile strengths by 17% and 13%, respectively, and enhanced ductility relative to the as-built state. Higher-temperature treatments dissolved the cellular structure and coarsened Si, reducing strength. Overall, this study demonstrates that low-temperature direct aging offers an efficient route to optimize the strength-ductility balance of PBF-LB/M AlSi10Mg without solution treatment.
While emerging Artificial Intelligence (AI) techniques can accelerate processes like literature reviews, grammar refinement, and initial text generation, there is no clear, standardized approach for their responsible integration in academic engineering. This paper focuses on the empirical identification of these writing challenges and the subsequent development of a comprehensive framework for AI adoption. Based on a Systematic Literature Review (SLR) and a detailed survey of engineering researchers, this work outlines the core benefits and ethical risks of AI tools. Ultimately, it presents a structured, task-by-task set of guidelines to ensure researchers can leverage these tools without compromising scientific honesty, accuracy, or rigor.
Background: A clinical educator who embodies humanistic qualities and emotional intelligence (EI) is attentive to the affective dimensions of the teaching–learning process. The integration of emotional intelligence into clinical teaching offers multiple advantages that enhance the quality of learning outcomes. The objective of this scoping review (SR) is to map and describe research that includes emotional intelligence competencies that are used by clinical teachers in internships and to gain a clearer picture of the concepts related. Methods: SR following the Joanna Briggs Institute methodology. A deductive approach was used once we mapped the data within the Daniel Goleman Emotional Intelligence Model. Twenty-seven studies were included. The main identified strategy is encouragement and motivation of students’ development through interactive feedback. Conclusions: This SR offers an evidence‑based perspective on the key competences involved in clinical teaching with EI. Clarifying the role of emotional intelligence in clinical teaching helps illuminate its complexity and provides a foundation for future correlational research. Findings also guide researchers into primary studies evaluating the effectiveness of EI strategies for clinical education.
This literature review analyzes current research on artificial intelligence (AI) in marketing, focusing on ethical considerations and managerial applications. Recent studies cover a range of AI applications, including customer engagement, personalization, and brand loyalty, alongside the ethical challenges AI poses, such as data privacy, transparency, and fairness. The review identifies core theoretical frameworks such as social identity theory and affordance theory that underpin these discussions. Findings highlight that while AI can enhance consumer experiences and drive brand loyalty, it also requires ethical oversight to ensure responsible data usage and avoid potential consumer mistrust. This review contributes to a deeper understanding of AI's dual role in marketing as both an enhancer of consumer engagement and a domain for ethical scrutiny
