Background: Nurses work at headache centres throughout Europe, and their care for migraine patients is acknowledged. However, the specific roles and tasks of nursing vary, and a unified understanding is lacking, posing challenges to knowledge sharing and research.
Objectives: Using an e-Delphi study method, the objective is to obtain healthcare professional headache experts' opinions on nursing-specific roles and tasks and combine this into consensus statements for nurse recommendations for migraine treatment.
Methods: A three-round questionnaire study was conducted with nurses and neurologists from 18 specialised headache centres in 10 countries. In round 1, statements were compiled from a systematic examination of existing literature and expert opinions. In rounds 2 and 3, the experts rated the importance of statements (from round 1) on a 5-point Likert scale. Statements were analysed using a content analysis method, and the consensus of pre-defined statements was evaluated with gradually increased predetermined criteria using descriptive statistics.
Results: Twenty-one experts, representing all 10 countries, participated. The predetermined consensus of ≥70% agreement was reached for 42 out of the initial 63 statements. These statements formed the final recommendations within two themes: "The nurses' roles and tasks in the clinical setting" and "The nurses' roles and tasks in educating patients and colleagues." The consensus level of statements was strong, with 40% receiving unanimous agreement (100%) and 97% achieving relatively high agreement (>80%).
Conclusion: Nursing plays a vital role with diverse tasks in migraine care. This study offers practical recommendations and a framework for nurses, equipping them with a clinical tool to enhance care and promote a coordinated approach to migraine treatment.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1177/03331024241252161 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
The role of spatial processing in verbal serial order working memory.
Cogn Affect Behav Neurosci
January 2025
Department of Psychological Sciences, Rice University, Houston, TX, 77005, USA.
In a sequence, at least two aspects of information-the identity of items and their serial order-are maintained and supported by distinct working memory (WM) capacities. Verbal serial order WM is modulated by spatial processing, reflected in the Spatial Position Association of Response Codes (SPoARC) effect-the left-beginning, right-end positional association between space and serial position of verbal WM memoranda. We investigated the individual differences in this modulation with both behavioral and neurobiological approaches.
View Article and Find Full Text PDFThe lateralized cerebellum: insights into motor, cognitive, and affective functioning across ages: a scoping review.
J Neurol
January 2025
Department of General Psychology, University of Padua, Via Venezia 8, 35131, Padua, Italy.
Research on the cerebellum and its functional organization has significantly expanded over the last decades, expanding our comprehension of its role far beyond motor control, including critical contributions to cognition and affective processing. Notably, the cerebellar lateralization mirrors contralateral brain lateralization, a complex phenomenon that remains unexplored, especially across different stages of life. The present work aims to bridge this gap by providing a comprehensive scoping review of the lateralization of motor, cognitive, and affective functioning within the cerebellum across the lifespan.
View Article and Find Full Text PDFImprovement in vision-related quality-of-life using the NEI-VFQ-9 over 1-year in the Manhattan Vision Screening and Follow-up Study (NYC-SIGHT).
Graefes Arch Clin Exp Ophthalmol
January 2025
Department of Ophthalmology, Columbia University, Vagelos College of Physicians and Surgeons, 630 W 168th Street, New York, NY, 10032, USA.
Purpose: To examine the nine-item National Eye Institute Vision Function Questionnaire (NEI-VFQ-9) scores at baseline and 12 months in participants enrolled in the Manhattan Vision Screening and Follow-up Study (NYC-SIGHT) and determine factors associated with improvements in vision-related quality-of-life (VRQOL).
Methods: Retrospective review of NEI-VFQ-9 scores at baseline and 12-month follow-up in a community-based eye health screening study conducted in Upper Manhattan, New York. Participants were age ≥ 40 years and older, living independently in public/affordable housing developments and able to provide informed consent.
The integral role of in brain function: from neurogenesis to synaptic plasticity and social behavior.
Acta Neurobiol Exp (Wars)
January 2025
Laboratory of Animal Models, Nencki Institute of Experimental Biology, Polish Academy of Sciences, Warsaw, Poland.
The phosphatase and tensin homolog deleted on chromosome 10 (PTEN) gene is a critical tumor suppressor that plays an essential role in the development and functionality of the central nervous system. Located on chromosome 10 in humans and chromosome 19 in mice, PTEN encodes a protein that regulates cellular processes such as division, proliferation, growth, and survival by antagonizing the PI3K‑Akt‑mTOR signaling pathway. In neurons, PTEN dephosphorylates phosphatidylinositol‑3,4,5‑trisphosphate (PIP3) to PIP2, thereby modulating key signaling cascades involved in neurogenesis, neuronal migration, and synaptic plasticity.
View Article and Find Full Text PDFMVCL-DTI: Predicting Drug-Target Interactions Using a Multiview Contrastive Learning Model on a Heterogeneous Graph.
J Chem Inf Model
January 2025
School of Computer Science and Technology, Soochow University, Jiangsu 215006, China.
Accurate prediction of drug-target interactions (DTIs) is pivotal for accelerating the processes of drug discovery and drug repurposing. MVCL-DTI, a novel model leveraging heterogeneous graphs for predicting DTIs, tackles the challenge of synthesizing information from varied biological subnetworks. It integrates neighbor view, meta-path view, and diffusion view to capture semantic features and employs an attention-based contrastive learning approach, along with a multiview attention-weighted fusion module, to effectively integrate and adaptively weight the information from the different views.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!