疫学における観察研究の報告を強化する (STROBE) 声明:観察研究の報告に関するガイドライン
Erik von Elm1, Douglas G Altman, Matthias Egger
1Institute of Social and Preventive Medicine (ISPM),University of Bern, Bern, Switzerland.
Lancet (London, England)
|December 8, 2007
まとめ
疫学における観察研究の報告の強化 (STROBE) 声明は,観察研究の報告の質を改善するためのチェックリストを提供します. これにより,コホート,ケース・コントロール,横断的な研究の正確で完全な報告が保証されます.
科学分野:
- バイオメディカル・リサーチ
- エピデミオロジー エピデミオロジー
- 科学的報告 科学的報告
背景:
- 観察研究は,生物医学研究の重要な部分を占めています.
- 観察研究の不十分な報告は,その質と適用性の評価を妨げます.
- 標準化された報告の欠如は,発見の一般化と再現性に影響します.
研究 の 目的:
- 観察研究の報告のための根拠に基づいた勧告を策定する.
- 研究報告書の正確性と完全性を高めるチェックリストを作成します.
- 疫学研究の報告の質を向上させる必要性を解決する.
主な方法:
- 2004年9月に方法論家,研究者,編集者とのワークショップを開催しました.
- 繰り返し改訂と協議を通じて22項目のチェックリストを開発しました.
- コホート,ケース・コントロール,横断的な研究デザインをカバーするための推奨事項を定義します.
主要な成果:
- 22項目のチェックリストであるSTROBEステートメントが開発されました.
- 18項目が3つのデザイン (コホート,ケースコントロール,横断) に適用されます.
- 3つの研究デザインのそれぞれに特化した4つの項目があります.
結論:
- STROBEの声明は,観察研究に関する報告の質を改善することを目的としています.
- 声明の実施を支援するために,詳細な説明文書が提供されています.
- このイニシアチブは,疫学研究の信頼性と透明性を高めることを目指しています.
関連する概念動画
Observational Studies
Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One example of...
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One example of...
Introduction to Epidemiology
Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...
Study Designs in Epidemiology
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and case-control studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and case-control studies.
Bias in Epidemiological Studies
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
Data Collection by Observations
Data collection refers to a systematic way of obtaining, observing, measuring, and analyzing accurate information. Observational studies are one of the most widely used methods of data collection. It involves collecting data by observing the behavior and physical characteristics of a sample without making any modifications to the sample.
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
An astronomer viewing the motion and brightness of stars in the sky and recording the data is an example of observational data collection. A botanist recording...
Statistical Methods for Analyzing Epidemiological Data
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
