FreshRSS

🔒
❌ Acerca de FreshRSS
Hay nuevos artículos disponibles. Pincha para refrescar la página.
AnteayerTus fuentes RSS

School health professionals understanding of culture: a scoping review

Por: Wahlström · E. · Landerdahl Stridsberg · S. · Larsson · C. · Stier · J.
Introduction

Culture underpins social interaction between school health professionals and children. Both practice and research suggest that cultural variations, migration and intercultural interactions pose potential challenges in encounters between school health professionals and children and may relate to the health professionals’ understanding of their own culture as a factor in such encounters. Still, for the school health services (SHS), reviews collating existing research on school health professionals’ understanding of culture are lacking.

Objectives

This review aims to identify, describe and analyse existing research on school health professionals’ (ie, school nurses, school social workers, school doctors and school psychologists) understanding of culture.

Design

A scoping review of peer-reviewed and published scientific articles on school health professionals’ understanding of culture.

Inclusion criteria

Articles published between 2013 and 2024 on culture, SHS and school nurses, school doctors, school social workers or school psychologists.

Methods and analysis

Searches were conducted in October 2023 and September 2024 in 10 databases. Two reviewers independently screened the article titles, abstracts and full texts for inclusion. Extracted data were analysed using descriptive statistics and qualitative content analysis. The qualitative content analysis focused on content related to theoretical considerations, key findings and conceptualisations of culture.

Results

From 1784 screened articles, 100 articles were screened in full text and 21 articles fulfilled the eligibility criteria. After identifying two additional articles through manual searches, a total of 23 articles were included in the review. The findings show that the articles primarily applied a quantitative study design, focused on school psychologists and school nurses and were conducted in the USA and Nordic-Baltic area. Self-understanding was mainly studied using validated instruments, leaving the conceptualisation of culture to the researchers. Still, only about half of all the articles described the theoretical conceptualisation of culture. Studies of intercultural interaction focused on the challenges of encountering ‘diverse’ children and raised concerns about barriers and hindrances to the encounters.

Conclusions

This review shows that SHS professionals’ understanding of culture has mainly been studied within two SHS professions, within a narrow geographical sphere and without a theoretical stance on culture. Thus, more qualitative research, a clearer theoretical conceptualisation of culture and more research on SHS professionals’ practice and self-understanding are needed.

Prevention of extubation failure in neurocritical care patients with residual disorder of consciousness: the Brain-Injured Patients Extubation Readiness (BIPER) study protocol for a stepped-wedge cluster-randomised controlled trial

Por: Chabanne · R. · Godet · T. · Andanson · B. · Borrel · P. · Astier · L. · Caumon · E. · Bourguignon · N. · Laclautre · L. · Morand · D. · De Jong · A. · Futier · E. · Constantin · J.-M. · Pereira · B. · Jabaudon · M.
Introduction

In the intensive care unit (ICU), brain-injured patients are frequently exposed to mechanical ventilation to protect the brain and preserve physiology. After intracranial pressure control and sedation withdrawal, this population is prone to residual disorder of consciousness and altered neurological control of respiratory drive, cough and airway protection. Consequently, extubation failure is more frequent than in general ICU patients, and there is no clear evidence-based clinical trigger for extubation. Different risk factors for extubation failure were described in observational trials, and clinical scores were constructed to detect patients at higher risk of extubation failure. Nevertheless, none of these scores were prospectively tested as interventional tools to prevent extubation failure. The Brain-Injured Patients Extubation Readiness (BIPER) study is an ongoing multicentre stepped-wedge cluster-randomised controlled trial aiming to test one of these scores as an intervention protocol to decrease extubation failure in neurocritical care patients with residual disorder of consciousness.

Methods and analysis

Trial design: Stepped-wedge cluster-randomised controlled trial with five groups of three to six clusters (20 ICUs). Groups of clusters are randomised to five possible sequences of nine periods with crossing from a control condition period (usual care for extubation) to an intervention condition period (BIPER-guided extubation protocol), separated by a 3-month transition period.

Participants: Participants are clinically stable brain-injured patients (18–75 years old), requiring more than 48 hours of invasive mechanical ventilation with residual disorder of consciousness after sedation withdrawal, and who achieved a spontaneous breathing trial.

Interventions: The control condition consists of extubation based on usual care and local practice. The intervention condition consists of extubation triggered by a clinical score evaluating deglutition, gag reflex, cough and visual tracking (Coma Recovery Scale-Revised Visual Scale).

Objective: To determine whether adoption of an extubation protocol based on a clinical score can lessen extubation failure compared with usual care in brain-injured patients with residual disorder of consciousness.

Outcome: The primary outcome measure is extubation failure, defined within 5 days following extubation. The key secondary outcome measure is time to effective extubation.

Randomisation: Clusters are allocated to sequence of treatments using random blocks randomisation. The constitution of groups of clusters was stratified according to planned recruitment of each centre.

Blinding: Investigators and outcome assessors are not blinded to condition allocation.

Number of participants: 660 patients (220 in the control condition and 440 in the intervention condition).

Ethics and dissemination

The BIPER trial was approved by an independent ethics committee. The study began on 9 February 2020, and 571 participants are now included. Results will be published in an international peer-reviewed medical journal. 

Trial registration number

NCT04080440.

Enhancing Chronic Pain Nursing Diagnosis Through Machine Learning: A Performance Evaluation

imageThis study proposes an evaluation of the efficacy of machine learning algorithms in classifying chronic pain based on Italian nursing notes, contributing to the integration of artificial intelligence tools in healthcare within an Italian linguistic context. The research aimed to validate the nursing diagnosis of chronic pain and explore the potential of artificial intelligence (AI) in enhancing clinical decision-making in Italian healthcare settings. Three machine learning algorithms—XGBoost, gradient boosting, and BERT—were optimized through a grid search approach to identify the most suitable hyperparameters for each model. Therefore, the performance of the algorithms was evaluated and compared using Cohen's κ coefficient. This statistical measure assesses the level of agreement between the predicted classifications and the actual data labels. Results demonstrated XGBoost's superior performance, whereas BERT showed potential in handling complex Italian language structures despite data volume and domain specificity limitations. The study highlights the importance of algorithm selection in clinical applications and the potential of machine learning in healthcare, specifically addressing the challenges of Italian medical language processing. This work contributes to the growing field of artificial intelligence in nursing, offering insights into the challenges and opportunities of implementing machine learning in Italian clinical practice. Future research could explore integrating multimodal data, combining text analysis with physiological signals and imaging data, to create more comprehensive and accurate chronic pain classification models tailored to the Italian healthcare system.
❌