ArticleHealthcare (Basel, Switzerland)2025
A Collective Intelligence Strategy for Evaluating and Advancing Nurse Autonomy in Primary Care.
Article in Healthcare (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Administrative Perspectives on Digital Workflow Transformation and Artificial Intelligence Implementation in Dental Clinics.Dentistry journal · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundEuropean health systems are shifting toward more proactive, person-centered models, thereby highlighting the need to strengthen nurses' clinical leadership in primary care. Nurse demand management (NDM) has emerged as an innovative practice which allows nurses to autonomously and comprehensively respond to a population's health needs. However, knowledge on its implementation varies widely, often being intuitive, partly due to the absence of standardized evaluation tools. The xGID instrument aims to measure the degree of NDM adoption in primary care teams (PCTs), activating collective intelligence mechanisms to foster shared diagnosis, organizational reflection, and the generation of targeted recommendations.
methodsWe designed and implemented xGID in 47 PCTs in Catalonia, involving 1474 healthcare professionals. Data were collected through structured surveys assessing key dimensions of NDM adoption, including professional autonomy, teamwork, continuity, and accessibility.
resultsOverall adoption of NDM was high, with a mean score of 7.6 out of 10. Notable differences emerged between professional groups and practice areas. Nurses tended to be more critical of teamwork, longitudinal care, and accessibility, reflecting the central yet high-pressure role they play in NDM. High-scoring dimensions included professional autonomy and the capacity to act across multiple domains, whereas weaker areas pointed to systemic organizational challenges.
conclusionsThe preliminary findings indicate that a standardized tool for NDM evaluation is a cornerstone for identifying contextual barriers and guiding the transformation of care models. Its participatory and strategic approach offers novel pathways to embed data-driven decision-making into daily clinical practice, consolidating NDM as a key pillar of future primary care.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.