Conectar
Commentary on: Women’s caesarean section preferences: a multicounty cross-sectional survey in low- and middle-income countries by Etcheverry et al. 2024;132.
Implications for practice and research Pregnant women in low- and middle-income countries should be counselled about the benefits and risks of both caesarean sections and vaginal deliveries to facilitate informed choices, the most suitable opportunity being antenatal clinic visits. Further studies are needed to explore decision aids in order to help women and doctors make informed shared decisions regarding the mode of delivery.
Caesarean section (CS) rates are rising globally from 7% in 1990 to 21% in 2018.
Neurodegenerative disorders (NDDs) represent an unprecedented public health burden. These disorders are clinically heterogeneous and therapeutically challenging, but advances in discovery science and trial methodology offer hope for translation to new treatments. Against this background, there is an urgent unmet need for biomarkers to aid with early and accurate diagnosis, prognosis and monitoring throughout the care pathway and in clinical trials.
Investigations routinely used in clinical care and trials are often invasive, expensive, time-consuming, subjective and ordinal. Speech data represent a potentially scalable, non-invasive, objective and quantifiable digital biomarker that can be acquired remotely and cost-efficiently using mobile devices, and analysed using state-of-the-art speech signal processing and machine learning approaches. This prospective case–control observational study of multiple NDDs aims to deliver a deeply clinically phenotyped longitudinal speech dataset to facilitate development and evaluation of speech biomarkers.
People living with dementia, motor neuron disease, multiple sclerosis and Parkinson’s disease are eligible to participate. Healthy individuals (including relatives or carers of participants with neurological disease) are also eligible to participate as controls. Participants complete a study app with standardised speech recording tasks (including reading, free speech, picture description and verbal fluency tasks) and patient-reported outcome measures of quality of life and mood (EuroQol-5 Dimension-5 Level, Patient Health Questionnaire 2) every 2 months at home or in clinic. Participants also complete disease severity scales, cognitive screening tests and provide optional samples for blood-based biomarkers at baseline and then 6-monthly. Follow-up is scheduled for up to 24 months. Initially, 30 participants will be recruited to each group. Speech recordings and contemporaneous clinical data will be used to create a dataset for development and evaluation of novel speech-based diagnosis and monitoring algorithms.
Digital App for Speech and Health Monitoring Study was approved by the South Central—Hampshire B Ethics Committee (REC ref. 24/SC/0067), NHS Lothian (R&D ref. 2024/0034) and NHS Forth Valley (R&D ref. FV1494). Results of the study will be submitted for publication in peer-reviewed journals and conferences. Data from the study will be shared with other researchers and used to facilitate speech processing challenges for neurological disorders. Regular updates will be provided on the Anne Rowling Regenerative Neurology Clinic web page and social media platforms.
ClinicalTrials.gov NCT06450418 (pre-results).
by Kennedy M. Peter-Marske, Annie Green Howard, Kelly R. Evenson, Sara Jones Berkeley, Joanna Maselko, Mario Sims, Stuart D. Russell, Anna Kucharska-Newton, Kevin J. Sullivan, Wayne D. Rosamond
We assessed whether social isolation (SI), social support (SS), and subtypes of SS were associated with self-rated health trajectories and clinical heart failure (HF) outcomes among participants with incident HF hospitalizations. We included 2967 Atherosclerosis Risk in Communities study participants with incident HF hospitalization after Visit 2 (1990–1992). SI, SS, and subtypes of SS were measured at Visit 2. We identified incident HF hospitalization as ICD-9 code 428 and physician adjudicated events; on average HF occurred 17 (SD 8) years after Visit 2. We assessed associations with trajectories of annually measured self-rated health in the 4 years prior to and after incident HF hospitalization (excellent/good self-rated health on a 0–100 scale), using linear mixed effects models. We calculated hazard ratios (HR) and 95% confidence intervals (CIs) for associations with time to first all-cause rehospitalization and all-cause mortality using Cox proportional hazard models. Low overall SS had a 5.8 point (95% CI 7.8, 3.8) lower self-rated health value over time than high SS; associations of subtypes of SS with this outcome were similar. Low belonging SS was associated with greater days to first rehospitalization (HR 0.85; 95% CI 0.79, 0.96) compared to the highest tertile; however, belonging SS was not associated with mortality (HR 1.05; 95% CI 0.95, 1.17). Being socially isolated/high risk for SI was associated with greater hazard of all-cause mortality among females (HR 1.57; 95% CI 1.20, 2.06) but not males (HR 0.95; 95% CI 0.75, 1.19), compared to low SI. SI and SS were not associated with number of hospitalizations in the first year or percent of first year spent at home.To develop and validate the Perceived Social Risk Scale (PSRS) for assessing perceptions of socially risky behaviours, and to validate it against existing psychological measures such as perceived social status and depressive symptoms in a UK sample of older adolescents and adults.
A cross-sectional study involving exploratory and confirmatory factor analyses.
Participants were recruited from the Cardiff University’s Department of Psychology participant pool (students completing studies for course credit) and Prolific Academic (a crowdsourcing platform for research volunteers). Data collection occurred between 17 February and 6 May 2024.
A total of 640 UK participants, including both men and women, aged 18-65.
We measured the internal consistency of the PSRS, test-retest reliability and validity against measures including rejection sensitivity, perceived social status, depressive symptoms and resistance to peer influence. Moderation analyses examined the role of perceived social status, age and a sense of belonging in the relationship between PSRS scores and depressive symptoms.
The PSRS showed excellent internal consistency (α=0.96) and good test-retest reliability (Intraclass Correlation Coefficient (ICC)=0.70). Perceptions of social risks significantly declined with age (r=–0.20, p) and factor analyses confirmed that the PSRS differentiates among four distinct but related social risk constructs: authenticity and integrity (α=0.91), social assertiveness (α=0.72), reservedness (α=0.83) and social non-conformity (α=0.72). For evidence of convergent validity, higher PSRS scores were associated with increased sensitivity to social rejection (r=0.23, p elevated depressive symptoms (r=0.13, p=0.012) and negatively correlated with resistance to peer influence (r=–0.13, p=0.013). Local perceived social status significantly moderated the relationship between PSRS scores and depressive symptoms (β=0.005, SE=0.002, t=2.36, p=0.019). A general sense of belonging did not moderate this relationship.
Our results confirm that social risk is not a uniform construct but is instead multidimensional. The PSRS offers a reliable and valid tool for assessing multidimensional social risk-taking, with strong internal consistency and test–retest reliability. The interaction between depression and local perceived social status highlights the importance of perceived status on social risk perception.
The North East of England has the lowest healthy life expectancy and the highest health inequalities of any region in England. The conventional model, whereby we ‘expect’ individuals to be motivated to attend a ‘healthcare setting’ to undergo cardiovascular disease (CVD) health checks every 5 years has low levels of uptake, with populations most at risk frequently failing to engage.
The objective of this study was to gather behavioural insights into the barriers/challenges that limit engagement with the current NHS CVD Health Checks.
Drawing on a Behavioural Insight approach, 7 qualitative focus groups with members of ethnic minorities and underserved groups (n=45 participants) were conducted to understand barriers and challenges to uptake of NHS CVD Health Checks in one region in North East England (Middlesbrough). Data were analysed using a Behavioural Insights approach, applied to establish key themes, barriers and enablers.
Our findings identified that underserved communities in North East England find engaging with NHS CVD Health Checks challenging due to issues related to access, understanding and attitudes. Communities identified that harnessing relationships with existing community champions would raise awareness and confidence in engaging. Making services accessible where communities gathered, while also increasing understanding and knowledge, was also recognised as key to engagement.
Our study suggested that despite there being substantial barriers to engagement with NHS CVD Health Checks, novel methods encouraging uptake may be effective to address the significant health inequalities seen in deprived communities. Ensuring a co-developed and co-delivered approach to CVD risk reduction with underserved communities, together with social marketing campaigns to raise awareness about the importance of CVD, and why reducing its risk is so important, is key to success.
Computers are ubiquitous to nursing and nursing practice, often in the form of electronic health records. Most nurses do not know the history of computers, how they were developed, or who the computing pioneers were that enabled the discipline of nursing to use this technology in its practices. Computers were first envisioned in the early 19th century, and one of the most influential computer programming visionaries was Ada Lovelace. It is important for the discipline of nursing to know Ada Lovelace, not only who she was, but also how her pioneering work influenced the history of computer technology. This article highlights the life of Ada Lovelace, her contributions to computer programming, and how her work paved the way for the use of computers in nursing and, ultimately, nursing informatics as a nursing specialty. 
FreshRSS 