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To systematically review and synthesise qualitative research on nurses' experiences of speaking up in various contexts and to identify factors facilitating or impeding such a behaviour.
This review was conducted as a qualitative metasynthesis, utilising the qualitative meta-ethnography approach.
A total of 6250 articles were screened. Two reviewers screened titles, abstracts and full texts. A total of 15 studies were included in this review. Researchers conducted a quality appraisal using the JBI critical appraisal checklist for qualitative research. An a priori protocol was created and registered on the Open Science Framework.
Literature searches were conducted in five international bibliographic databases (MEDLINE, Embase, PsycINFO, CINAHL and ProQuest Dissertations and Theses Global) and five Korean databases (RISS, KISS, DBpia, KCI and NDSL).
Three main themes were identified from the 15 studies used in the metasynthesis: (1) decisional complexity of speaking up, (2) motivators for speaking up and (3) barriers to speaking up. Nurses experienced challenges in speaking up. They were, and continue to be, concerned about negative responses. Hierarchy structure and poor work environment were identified as barriers to speaking up; professional responsibility and a supportive atmosphere were identified as facilitators for speaking up.
This review synthesised nurses' experiences of speaking up and influencing factors. Speaking up is crucial for nurses to improve patient safety, as frontline nurses are ideally positioned to observe early indicators of unsafe conditions in healthcare delivery.
Identified motivators and barriers of nurses' speaking-up behaviour offer considerations and opportunities for healthcare leaders and managers. This could lead to improvement in patient safety through the establishment of a safety culture that facilitates nurses' speaking-up behaviour.
The review adhered to the ENTREQ guideline.
No patient or public contribution has been made in this review.
Type 1 diabetes (T1D) demands self-management skills, knowledge and confidence to prevent medical complications. Adolescents living with T1D have distinct developmental challenges resulting in a worsening in glycaemic stability, irregular care and an increased risk for complications all while transitioning to adult healthcare. Age-specific online platforms could facilitate transition by fostering self-management education and support. The Support online self-guided training platform has been shown to increase the confidence of adults with T1D in managing their glycaemia. We aim to test the effectiveness of Support-t (ie, adapted for youth), compared with usual care, in improving haemoglobin A1c (HbA1c) and to understand the context of its implementation.
We will conduct a multisite, assessor-blinded, randomised controlled, parallel group, two-arm, superiority trial, evaluating effectiveness and implementation of Support-t versus usual care in 200 adolescents (14–16 years old) living with T1D. The active arm will have an 18-month access to Support-t, and their healthcare team will be trained on the platform’s content. The control arm will receive usual care. The primary outcome is HbA1c at 18 months. Secondary outcomes include self-efficacy for diabetes self-management, transition readiness, diabetes-specific quality of life, diabetes distress, continuous glucose monitoring metrics, number of severe hypoglycaemic events, diabetic ketoacidosis, T1D-related emergency department visits and hospitalisations as well as engagement and satisfaction. A subgroup of participants in the active arm and of healthcare providers will be interviewed assessing barriers, facilitators, engagement and fidelity of the intervention. Primary analysis will be by intention-to-treat. The difference in mean HbA1c at 18 months (with a 95% CI) will be calculated between both arms. A cost-effectiveness analysis is also planned.
December 8, 2024 version of the protocol was approved by the McGill University Health Centre Research Ethics Board (MP-37-2024-9734). Results will be disseminated through peer-reviewed publications and patient-partners’ network.
ClinicalTrials.gov (NCT05910840).
The integration of artificial intelligence such as ChatGPT into educational frameworks marks a pivotal transformation in teaching. This quasi-experimental study, conducted in September 2023, aimed to evaluate the effects of artificial intelligence–assisted learning on nursing students' ethical decision-making and clinical reasoning. A total of 99 nursing students enrolled in a pediatric nursing course were randomly divided into two groups: an experimental group that utilized ChatGPT and a control group that used traditional textbooks. The Mann-Whitney U test was employed to assess differences between the groups in two primary outcomes: (a) ethical standards, focusing on the understanding and applying ethical principles, and (b) nursing processes, emphasizing critical thinking skills and integrating evidence-based knowledge. The control group outperformed the experimental group in ethical standards and demonstrated better clinical reasoning in nursing processes. Reflective essays revealed that the experimental group reported lower reliability but higher time efficiency. Despite artificial intelligence's ability to offer diverse perspectives, the findings highlight that educators must supplement artificial intelligence technology with strategies that enhance critical thinking, careful data selection, and source verification. This study suggests a hybrid educational approach combining artificial intelligence with traditional learning methods to bolster nursing students' decision-making processes and clinical reasoning skills. 
FreshRSS 