Conectar
To examine healthcare providers' extent of and perceived barriers and facilitators to screening for intimate partner violence in pregnant women attending prenatal clinics.
Cross-sectional descriptive design was used to collect data from 130 healthcare providers.
Seventeen healthcare providers from 17 prenatal clinics in Kanungu district, Uganda, were recruited via convenience sampling to participate in an online survey implementing a modified Normalization Measure Development instrument. Data were collected between February 2023 and March 2023 (02/8/2023 to 03/12/2023) and analysed using descriptive and Mann–Whitney U test and chi-square tests.
Slightly more than half (56%) of healthcare providers report screening pregnant women for intimate partner violence. There was a statistically significant relationship between healthcare providers screening for intimate partner violence and having previous training on intimate partner violence screening. The only barrier to screening identified was a lack of understanding of how intimate partner violence screening affects the nature of participant's own work. There were numerous potential facilitators identified for healthcare providers' intimate partner violence screening.
Although higher-than-expected number of healthcare providers reported screening of pregnant women for intimate partner violence, the extent of screening is still suboptimal. The barrier to screening identified needs to be addressed and facilitators promoted. Receiving training among healthcare providers on intimate partner violence screening was associated with higher levels of screening; thus, this needs to be enhanced to optimize screening rates. Future studies should assess screening practices objectively and implement interventions to improve healthcare providers’ intimate partner violence screening rates.
Screening for intimate partner violence should be part of standard care provided by healthcare providers to all pregnant women during prenatal clinic visits. The study supports the need for more training for healthcare providers in aspects related to intimate partner violence screening in order to ensure prompt diagnosis and treatment of those affected, identify those at risk and increase awareness. There is a need to enhance healthcare providers' capacity for intimate partner violence screening through education by integrating intimate partner violence screening pre- and post-registration courses and preparation programs or curriculum.
Intimate partner violence (IPV) in pregnancy is a global health problem. Screening for IPV by healthcare providers is suboptimal. This study found that only 56% of healthcare providers were routinely screening for IPV in Ugandan prenatal clinics. This study identified the main facilitators and one barrier to IPV screening.
This study has adhered to the relevant EQUATOR guidelines for quantitative studies.
No patient was involved in this study.
For artificial intelligence (AI) to help improve mental healthcare, the design of data-driven technologies needs to be fair, safe, and inclusive. Participatory design can play a critical role in empowering marginalised communities to take an active role in constructing research agendas and outputs. Given the unmet needs of the LGBTQI+ (Lesbian, Gay, Bisexual, Transgender, Queer and Intersex) community in mental healthcare, there is a pressing need for participatory research to include a range of diverse queer perspectives on issues of data collection and use (in routine clinical care as well as for research) as well as AI design. Here we propose a protocol for a Delphi consensus process for the development of PARticipatory Queer AI Research for Mental Health (PARQAIR-MH) practices, aimed at informing digital health practices and policy.
The development of PARQAIR-MH is comprised of four stages. In stage 1, a review of recent literature and fact-finding consultation with stakeholder organisations will be conducted to define a terms-of-reference for stage 2, the Delphi process. Our Delphi process consists of three rounds, where the first two rounds will iterate and identify items to be included in the final Delphi survey for consensus ratings. Stage 3 consists of consensus meetings to review and aggregate the Delphi survey responses, leading to stage 4 where we will produce a reusable toolkit to facilitate participatory development of future bespoke LGBTQI+–adapted data collection, harmonisation, and use for data-driven AI applications specifically in mental healthcare settings.
PARQAIR-MH aims to deliver a toolkit that will help to ensure that the specific needs of LGBTQI+ communities are accounted for in mental health applications of data-driven technologies. The study is expected to run from June 2024 through January 2025, with the final outputs delivered in mid-2025. Participants in the Delphi process will be recruited by snowball and opportunistic sampling via professional networks and social media (but not by direct approach to healthcare service users, patients, specific clinical services, or via clinicians’ caseloads). Participants will not be required to share personal narratives and experiences of healthcare or treatment for any condition. Before agreeing to participate, people will be given information about the issues considered to be in-scope for the Delphi (eg, developing best practices and methods for collecting and harmonising sensitive characteristics data; developing guidelines for data use/reuse) alongside specific risks of unintended harm from participating that can be reasonably anticipated. Outputs will be made available in open-access peer-reviewed publications, blogs, social media, and on a dedicated project website for future reuse.
To determine the well-being of physicians and nurses in hospital practice in Europe, and to identify interventions that hold promise for reducing adverse clinician outcomes and improving patient safety.
Baseline cross-sectional survey of 2187 physicians and 6643 nurses practicing in 64 hospitals in six European countries participating in the EU-funded Magnet4Europe intervention to improve clinicians’ well-being.
Acute general hospitals with 150 or more beds in six European countries: Belgium, England, Germany, Ireland, Sweden and Norway.
Physicians and nurses with direct patient contact working in adult medical and surgical inpatient units, including intensive care and emergency departments.
Burnout, job dissatisfaction, physical and mental health, intent to leave job, quality of care and patient safety and interventions clinicians believe would improve their well-being.
Poor work/life balance (57% physicians, 40% nurses), intent to leave (29% physicians, 33% nurses) and high burnout (25% physicians, 26% nurses) were prevalent. Rates varied by hospitals within countries and between countries. Better work environments and staffing were associated with lower percentages of clinicians reporting unfavourable health indicators, quality of care and patient safety. The effect of a 1 IQR improvement in work environments was associated with 7.2% fewer physicians and 5.3% fewer nurses reporting high burnout, and 14.2% fewer physicians and 8.6% fewer nurses giving their hospital an unfavourable rating of quality of care. Improving nurse staffing levels (79% nurses) and reducing bureaucracy and red tape (44% physicians) were interventions clinicians reported would be most effective in improving their own well-being, whereas individual mental health interventions were less frequently prioritised.
Burnout, mental health morbidities, job dissatisfaction and concerns about patient safety and care quality are prevalent among European hospital physicians and nurses. Interventions to improve hospital work environments and staffing are more important to clinicians than mental health interventions to improve personal resilience.
To determine whether periods of disruption were associated with increased ‘avoidable’ hospital admissions and wider social inequalities in England.
Observational repeated cross-sectional study.
England (January 2019 to March 2022).
With the approval of NHS England we used individual-level electronic health records from OpenSAFELY, which covered ~40% of general practices in England (mean monthly population size 23.5 million people).
We estimated crude and directly age-standardised rates for potentially preventable unplanned hospital admissions: ambulatory care sensitive conditions and urgent emergency sensitive conditions. We considered how trends in these outcomes varied by three measures of social and spatial inequality: neighbourhood socioeconomic deprivation, ethnicity and geographical region.
There were large declines in avoidable hospitalisations during the first national lockdown (March to May 2020). Trends increased post-lockdown but never reached 2019 levels. The exception to these trends was for vaccine-preventable ambulatory care sensitive admissions which remained low throughout 2020–2021. While trends were consistent by each measure of inequality, absolute levels of inequalities narrowed across levels of neighbourhood socioeconomic deprivation, Asian ethnicity (compared with white ethnicity) and geographical region (especially in northern regions).
We found no evidence that periods of healthcare disruption from the COVID-19 pandemic resulted in more avoidable hospitalisations. Falling avoidable hospital admissions has coincided with declining inequalities most strongly by level of deprivation, but also for Asian ethnic groups and northern regions of England.
In a small percentage of patients, pulmonary nodules found on CT scans are early lung cancers. Lung cancer detected at an early stage has a much better prognosis. The British Thoracic Society guideline on managing pulmonary nodules recommends using multivariable malignancy risk prediction models to assist in management. While these guidelines seem to be effective in clinical practice, recent data suggest that artificial intelligence (AI)-based malignant-nodule prediction solutions might outperform existing models.
This study is a prospective, observational multicentre study to assess the clinical utility of an AI-assisted CT-based lung cancer prediction tool (LCP) for managing incidental solid and part solid pulmonary nodule patients vs standard care. Two thousand patients will be recruited from 12 different UK hospitals. The primary outcome is the difference between standard care and LCP-guided care in terms of the rate of benign nodules and patients with cancer discharged straight after the assessment of the baseline CT scan. Secondary outcomes investigate adherence to clinical guidelines, other measures of changes to clinical management, patient outcomes and cost-effectiveness.
This study has been reviewed and given a favourable opinion by the South Central—Oxford C Research Ethics Committee in UK (REC reference number: 22/SC/0142).
Study results will be available publicly following peer-reviewed publication in open-access journals. A patient and public involvement group workshop is planned before the study results are available to discuss best methods to disseminate the results. Study results will also be fed back to participating organisations to inform training and procurement activities.
FreshRSS 