Conectar
To identify research gaps by mapping what is known about the barriers and enablers to pre-registration nursing students identifying signs of suicidal distress in healthcare consumers and providing clear pathways of support.
Scoping review.
This scoping review was conducted using Arksey and O'Malley's (2005) five stage framework and the Levec et al. (2010) extensions of this framework.
The Cumulative Index of Nursing and Allied Health Literature (CINAHL) Complete and Ovid MEDLINE databases were searched to identify relevant articles, keywords and search terms to inform the full search strategy for CINAHL. This search strategy was then adapted for Scopus, PsychInfo, Emcare, Medline and ERIC, searched in November 2024.
Studies eligible for inclusion (N = 28) represented research from 14 countries; most (53.5%, n = 15) used a quantitative design, 11 (39.3%) were qualitative and two (7.1%) used a mixed-methods design. Barriers found from the scoping review included a low level of knowledge of suicidality, stigma preventing students from assessing and acting on suicidal ideation, and a lack of confidence in providing care to healthcare consumers expressing suicidality. Enablers included lived experience, exposure to individuals expressing suicidal ideation and education, simulation and role play. This review also contributes to the existing literature about the relationship of nursing to existing suicide prevention frameworks and suggests revision of these frameworks to address staff attitudes and beliefs, as well as lived and living experience.
Nurses are ideally placed to assess and respond to suicidality among healthcare consumers, and preparation should begin during pre-registration studies. Our scoping review indicates that further research work is needed to address the barriers to working with healthcare consumers expressing suicidality and to enhance the enablers to provide safe care.
Addressing the barriers and enablers to pre-registration nursing students providing safe care for healthcare consumers expressing suicidality is essential. Further research is required to address the barriers and enhance the enablers identified in this scoping review.
What problem did the study address? This scoping review summarised the literature on pre-registration student ability to work with healthcare consumers expressing suicidality, identifying barriers and enablers. What were the main findings? Barriers include poor knowledge of suicidality, stigma, fear and a lack of confidence in working with healthcare consumers expressing suicidality. Enablers include lived experience, exposure to clinical settings where healthcare consumers express suicidality and simulation and education. Where and on whom will the research have an impact? The research will have an impact on providers of pre-registration nursing degrees, where the inclusion of content addressing suicidality and exposure to settings where individuals express suicidal ideation is shown to improve attitudes and knowledge of suicidality assessment.
PRISMA checklist for scoping reviews.
This study did not include patient or public involvement in its design, conduct or reporting.
Although the positive correlation between self-efficacy and quality of life and the negative correlation between symptom occurrence and self-efficacy are well established in the cancer literature, the underlying mechanism, whether self-efficacy mediates the effect of symptoms on quality of life, remains unclear due to the cross-sectional design of prior studies. Longitudinal investigation is crucial for establishing the causal mechanism of self-efficacy in mitigating the adverse impact of cancer-related symptoms on quality of life.
To examine the longitudinal mediating effect of self-efficacy on the relationship between symptom occurrence and quality of life among 534 cancer patients on treatment with moderate to high symptoms.
This is a secondary data analysis of the longitudinal mediating effect. A sample of patients with moderate to high symptoms on cancer treatments (N = 534) from a randomised controlled trial was used. We adopted a cross-lagged panel model (CLPM) approach to test the longitudinal mediating effect with three waves. The longitudinal invariance of the measurement was previously tested.
The results showed that cancer-coping self-efficacy predicted the following assessment of symptom occurrence, but not vice versa. Also, cancer-coping self-efficacy had an immediate direct impact on quality of life and the influence sustained to the following assessment. Our mediating analysis showed that cancer-coping self-efficacy totally mediated the relationship between symptom occurrence and quality of life (unstandardized β = −0.008, standardised B = −0.036, p = 0.036, CI95 = [−0.001, −0.016]).
Our findings provide initial evidence supporting the causal mechanism of cancer-coping self-efficacy in interventions that aim for symptom management and quality of life improvement.
This study is the first to test the longitudinal mediating mechanism of cancer-coping self-efficacy in the relationship between symptom occurrence and quality of life among the cancer population. Further testing using a randomised controlled trial of a specifically designed self-efficacy-enhancing intervention is needed.
No patient or public contribution.
Differences in the profile of the vaginal microbiota (VMB) have been associated with pregnancy rates after medical assisted reproduction (MAR) such as in vitro fertilisation (IVF) or intracytoplasmic sperm injection (ICSI). Monitoring the VMB profile of IVF patients creates an opportunity to identify the best window for IVF treatment and embryo transfer. The ReceptIVFity test is a predictive test that assesses the chances of becoming pregnant in women undergoing IVF treatment based on the VMB composition. A VMB profile dominated by beneficial strains, most notably Lactobacillus species, is associated with increased pregnancy chances. However, to date, limited evidence is available on the effect of active modification strategies to facilitate the modulation of the VMB profile to help restore a VMB dominated by Lactobacillus species.
This is a randomised, placebo-controlled, double-blind intervention study. The study will involve 1:1 randomisation to one of the two arms: oral probiotic or placebo. Vaginal and rectal swabs will be collected at intake and 4, 6 and 8 weeks after the start of the treatment. Our objective is to determine if oral probiotic treatment improves the VMB profile of IVF patients from a low to a medium/high ReceptIVFity score, compared with placebo treatment. Secondary outcomes are: the potential of the bacterial strains in the oral probiotic to be detected in the vaginal tract and/or in the gut, and if the treatment leads to an increased ongoing pregnancy rate after IVF.
Ethical approval was obtained by the local medical ethical review committee at the Maastricht University Medical Centre. Findings from this study will be published in a peer-reviewed scientific journal and presented at one or more scientific conferences.
CCMO NL81210.068.22, registered 25 September 2023.
Congenital heart defect (CHD) is a significant, rapidly emerging global problem in child health and a leading cause of neonatal and childhood death. Prenatal detection of CHDs with the help of ultrasound allows better perinatal management of such pregnancies, leading to reduced neonatal mortality, morbidity and developmental complications. However, there is a wide variation in reported fetal heart problem detection rates from 34% to 85%, with some low- and middle-income countries detecting as low as 9.3% of cases before birth. Research has shown that deep learning-based or more general artificial intelligence (AI) models can support the detection of fetal CHDs more rapidly than humans performing ultrasound scan. Progress in this AI-based research depends on the availability of large, well-curated and diverse data of ultrasound images and videos of normal and abnormal fetal hearts. Currently, CHD detection based on AI models is not accurate enough for practical clinical use, in part due to the lack of ultrasound data available for machine learning as CHDs are rare and heterogeneous, the retrospective nature of published studies, the lack of multicentre and multidisciplinary collaboration, and utilisation of mostly standard planes still images of the fetal heart for AI models. Our aim is to develop AI models that could support clinicians in detecting fetal CHDs in real time, particularly in nonspecialist or low-resource settings where fetal echocardiography expertise is not readily available.
We have designed the Clinical Artificial Intelligence Fetal Echocardiography (CAIFE) study as an international multicentre multidisciplinary collaboration led by a clinical and an engineering team at the University of Oxford. This study involves five multicountry hospital sites for data collection (Oxford, UK (n=1), London, UK (n=3) and Southport, Australia (n=1)). We plan to curate 14 000 retrospective ultrasound scans of fetuses with normal hearts (n=13 000) and fetuses with CHDs (n=1000), as well as 2400 prospective ultrasound cardiac scans, including the proposed research-specific CAIFE 10 s video sweeps, from fetuses with normal hearts (n=2000) and fetuses diagnosed with major CHDs (n=400). This gives a total of 16 400 retrospective and prospective ultrasound scans from the participating hospital sites. We will build, train and validate computational models capable of differentiating between normal fetal hearts and those diagnosed with CHDs and recognise specific types of CHDs. Data will be analysed using statistical metrics, namely, sensitivity, specificity and accuracy, which include calculating positive and negative predictive values for each outcome, compared with manual assessment.
We will disseminate the findings through regional, national and international conferences and through peer-reviewed journals. The study was approved by the Health Research Authority, Care Research Wales and the Research Ethics Committee (Ref: 23/EM/0023; IRAS Project ID: 317510) on 8 March 2023. All collaborating hospitals have obtained the local trust research and development approvals.
FreshRSS 