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Related Concept Videos

Data Collection by Observations01:08

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...
Observational Studies01:11

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...
Study Designs in Epidemiology01:20

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.
Bias in Epidemiological Studies01:29

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:
Statistical Methods for Analyzing Epidemiological Data01:25

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:
Longitudinal Studies01:26

Longitudinal Studies

Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...

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Articles linked to this work by shared authors, journal, and citation graph.

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[Endoscopic Submucosal Dissection as a Therapeutic Option for Rectal Lesions in Patients with Ulcerative Colitis].

Acta gastroenterologica Latinoamericana·2025
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[Prevalence of Thrombotic Events in Patients with Inflammatory Bowel Disease with Follow-Up in a Referral Center in the City of Buenos Aires. A Cross-Sectional Study].

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[Endoscopic Sclerotherapy in Small Bowel Haemangioma. A Case Report].

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Control of intestinal inflammation by glycosylation-dependent lectin-driven immunoregulatory circuits.

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Treatment Adherence in Inflammatory Bowel Disease Patients from Argentina: A Multicenter Study.

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Related Experiment Video

Updated: Jun 23, 2026

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[Argentina and Chile Data Analysis from the ICONIC Observational Study].

Alicia Sambuelli1, Gustavo Walsen Arangua2, Juan Andrés de Paula3

  • 1Centro de Estudios y Tratamiento de Enfermedades Inflamatorias (CEYTIN). Grupo médico del Consultorio de Enfermedades Inflamatorias del Intestino (CEIDI), Ciudad Autónoma de Buenos Aires, Argentina. Centro de Estudios y Tratamiento de Enfermedades Inflamatorias (CEYTIN) Grupo médico del Consultorio de Enfermedades Inflamatorias del Intestino (CEIDI) Ciudad Autónoma de Buenos Aires Argentina.

Acta Gastroenterologica Latinoamericana
|December 4, 2025
PubMed
Summary

Early treatment reduced suffering in ulcerative colitis (UC) patients. The Pictorial Representation of Illness and Self Measure (PRISM) tool effectively quantified patient distress, correlating with other UC outcome measures.

Area of Science:

  • Gastroenterology
  • Clinical Medicine
  • Patient-Reported Outcomes
Keywords:
PRISMUlcerative colitispatient-reported outcomessuffering

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