Invited talk: Deep Diving into PRISMA 2020 Guidelines

Mar 23, 2026·
陳映竹
陳映竹
· 2 min read
Presenter: Ying-Chu Chen
Abstract
In this invited talk, Ph.D. Candidate Steve Ying-Chu Chen presented the core principles of the PRISMA 2020 guidelines. The presentation focused on enhancing research transparency, navigating new flow diagrams, and the importance of evidence synthesis rigor to safeguard against bias. / 本次邀請演講由博士候選人陳映竹分享 PRISMA 2020(系統性回顧與統合分析報告首選)的核心規範,深入拆解新版流程圖與檢核表,強調透明度對於提升研究誠信與可重複性的重要性。
Date
Mar 23, 2026 2:20 PM — 4:00 PM
Event
PACNL Journal Meeting
Location

Physical Activity and Cognitive Neuroscience Lab, National Taiwan Normal University

162, Section 1, Heping E. Rd., Taipei City, Daan Dist. 106

Presentation Highlights / 報告精華

Introduction & Rationale

Transparency is the bedrock of scientific integrity. PRISMA 2020 provides an updated framework for reporting systematic reviews and meta-analyses, reflecting advances in methods to identify, select, appraise, and synthesize studies. This presentation aims to transform complex reporting standards into actionable insights, creating a “reject-proof firewall” for academic publishing.

Key Insights

  • Methodological Rigor: The 2020 iteration demands higher execution standards, including the use of multi-track flow diagrams and the integration of automated screening tools.
  • Bias Safeguarding: Strictly following the checklist effectively mitigates risk of bias and enhances the reproducibility of evidence synthesis.
  • Clinical Impact: Beyond just “ticking boxes,” adherence to these guidelines elevates the overall quality and clinical relevance of exercise science research.

Practical Application

Using PRISMA 2020 as a “playbook” ensures that researchers meet the highest standards of excellence, facilitating smoother peer review and increasing the likelihood of high-impact publication.


研究動機與背景

「透明度」是科學學術誠信的基石。PRISMA 2020 是系統性回顧與統合分析報告的首選指南。本次報告旨在深入拆解更新後的規範,將複雜的報告標準轉化為具體的實踐洞見,為同儕建立一道提升研究品質的「拒稿防火牆」。

核心發現

  • 嚴謹的方法論:2020 年版本要求更高水準的執行,包含解析新版流程圖、檢核表,以及如何有效整合自動化篩選工具。
  • 防範研究偏誤:透過更嚴格的報告標準,能有效降低偏誤風險(risk of bias),並提升證據整合(Evidence Synthesis)的可重複性。
  • 學術誠信與影響力:遵循 PRISMA 不僅是為了符合清單要求,更是為了確保研究具備卓越的標準,進而提升在運動科學領域的臨床影響力。

實務建議

研究者應將 PRISMA 2020 視為學術「攻略手冊(Playbook)」,從研究設計階段即納入規範考量,以確保研究成果能以最高品質呈現,並在國際期刊中脫穎而出。


報告資訊

  • Presenter / 報告人: Ying-Chu Chen (陳映竹), Ph.D. Candidate
  • Advisor / 指導教授: Yu-Kai Chang (張育愷博士), Ph.D.
  • Lab / 實驗室: Physical Activity & Cognitive Neuroscience Lab (PACNL), NTNU