Name: placebos and bias in randomized trials
Uploaded: 2023-04-30T12:48:15.000Z
Duration: 1 min 11 s
Channel: JoVE

K12 Standards

Virginia  Standards of Learning

HIgh School

Biology

BIO.1

BIO.1.c

Blinding

Zaślepienie jest istotnym elementem randomizowanych badań kontrolnych w celu zmniejszenia błędu systematycznego i zwiększenia wiarygodności wyników. Ukrywa informacje o leczeniu dla pacjentów, lekarzy, analityków danych i innego personelu zaangażowanego w badanie.
W randomizowanych badaniach kontrolnych stosuje się placebo w celu uzyskania ślepoty. Efekt placebo jest zjawiskiem psychologicznym, w którym nieleczony pacjent może fałszywie wierzyć, że otrzymał rzeczywiste leczenie i zgłaszać poprawę objawów. Tak więc, aby zmniejszyć to odchylenie, wraz z leczeniem testowym podaje się placebo lub leczenie pozorowane.
W badaniach klinicznych powszechnie stosuje się pojedyncze, podwójne i potrójne zaślepienie.
W technikach pojedynczej ślepej próby pacjenci nie wiedzą, czy otrzymali placebo, czy rzeczywiste leczenie.
Podwójnie ślepe badania ukrywają informacje o leczeniu zarówno przed pacjentem, jak i lekarzem. W rezultacie nie będzie fałszywych informacji od pacjentów lub lekarzy, którzy mogą być przychylni leczeniu i zgłaszać stronnicze obserwacje.
Badanie z potrójnie ślepą próbą ukrywa informacje o leczeniu przed pacjentami, lekarzami i analitykami danych.

Ślepa próba

Ślepa próba jest powszechnie stosowaną metodą nie informowania uczestników, jakie leczenie otrzymuje. Jest to kluczowa część randomizowanego badania kontrolnego lub RCT. Zmniejsza błąd mający wpływ na wyniki. W RCT ślepą próbę stosuje się w postaci placebo. Efekt placebo występuje, gdy nieleczeni pacjenci fałszywie wierzą, że otrzymali leczenie i zgłaszają poprawę objawów. Pacjentom podaje się placebo lub leczenie pozorowane, aby zanegować stronniczość spowodowaną takim efektem. Kiedy udział w badaniu wywołuje u uczestnika reakcję fizyczną, trudno jest wyizolować wpływ zmiennej objaśniającej. Aby przeciwdziałać sile sugestii, badacze wyznaczyli jedną grupę badaną jako grupę kontrolną. Grupie tej podaje się placebo – leczenie, które nie ma wpływu na zmienną odpowiedzi. Grupa kontrolna pomaga badaczom zrównoważyć skutki udziału w eksperymencie z efektami aktywnych terapii. Oczywiście, jeśli bierzesz udział w badaniu i wiesz, że otrzymujesz pigułkę niezawierającą prawdziwego leku, siła sugestii nie ma już znaczenia. Zaślepienie w randomizowanym eksperymencie pozwala zachować siłę sugestii. Kiedy osoba zaangażowana w badanie jest zaślepiona, nie wie, kto otrzymuje aktywne leczenie, a kto otrzymuje placebo. Eksperyment z podwójnie ślepą próbą to taki, w którym zarówno uczestnicy, jak i badacze poddawani są ślepej próbie. Ślepą próbę można wykonać wobec wszystkich osób biorących udział w badaniach klinicznych – uczestników, klinicystów, osób zbierających dane, osób orzekających o wynikach i analityków danych. Ten tekst jest adaptacją <a href="https://openstax.org/books/introductory-statistics/pages/1-4-experimental-design-and-ethics">Openstax, Introductory Statistics, Section 1.4, Experimental Design and Ethics.</a>

Zaślepienie jest powszechnie stosowaną metodą polegającą na nieinformowaniu uczestników, jakie leczenie otrzymuje badany. Zaślepienie jest krytyczną częścią randomizowanej kontroli ...

Education

JoVE Core

Statistics

Statystyka

Unit 1

Jednostka 1

Statistics in Practice

Statystyka w praktyce

KEY TERMS AND CONCEPTS

Kluczowe terminy i pojęcia

placebos and bias in randomized trials

Placebos and blinding are key tools in randomized control trials, or RCTs. They help researchers reduce bias, which can affect study results. In a blinded study, participants do not know which treatment they are receiving.

A placebo is a dummy treatment that does not contain the active treatment. Researchers use a placebo in the control group to compare against the treatment group. This helps balance the effects of being in an experiment with the effects of the active treatment itself. A placebo effect can happen when untreated subjects believe they received the treatment and report improved symptoms.

Blinding keeps the power of suggestion from changing the results. If a person knows they received a pill with no actual medication, that suggestion effect is no longer hidden. In a double-blind experiment, both the subjects and the researchers who work with them are blinded. Blinding can also include clinicians, data collectors, outcome adjudicators, and data analysts in clinical trials.

Placebos and Bias in Randomized Trials

what is an experiment?

Random Assignment in Experiments

Random assignment in experiments helps researchers test cause and effect between two variables. An experiment is a planned activity carried out under controlled conditions. It is used to study how one variable affects another. The variable that causes change is the explanatory or independent variable. The variable that changes in response is the response or dependent variable. In a randomized experiment, the researcher changes the explanatory variable and measures the response variable. The...

study design in statistics

Experimental and Observational Study Types

Study design in statistics helps researchers collect and analyze data from variables in a specific research problem. It supports stronger experiments and more reliable data. Questions about aspirin and heart attacks, fertilizer and rose growth, or fatigue and alcohol-related driving risk all depend on careful study design. Study designs are usually grouped into two main types: descriptive and analytical studies. Descriptive studies describe the variables and answer what is happening, rather...

observational studies

Types of Observational Research Methods

Observational research methods let scientists study events without changing them. The researcher does not intervene, so the response variable and the outcome are left alone. These studies are used to look for patterns and relationships in real-world settings. There are three main types of observational studies: prospective, retrospective, and cross-sectional. Each type collects information in a different way. Together, they help researchers answer questions about health, behavior, and risk. <br...

experimental designs

Types of Experimental Design

Experimental design is a systematic way to study how an independent variable affects a dependent variable. Researchers use it to compare results and judge whether a treatment or intervention changes the outcome. Three common experimental designs are pre-experimental design, true experimental design, and quasi-experimental design. Each one supports research in a different way, depending on how groups are formed and how the data are collected. In pre-experimental design, the researcher compares...

randomized experiments

How Random Assignment Reduces Bias

Random assignment helps researchers place participants into experimental and control groups. It gives each person an equal chance of being assigned to either group. This process is used to reduce selection bias and to balance known and unknown confounding factors, so the control group is as similar to the treatment group as possible. A computer program or a random number generator can make the assignment process less biased. Simple randomization is the most direct method. It uses a single...

crossover experiments

Repeated-Measures Study Design

Crossover experiments are a repeated-measurements study design used in science and medicine. In this design, the same experimental units receive all treatments during different time periods. That setup helps compare how each treatment performs within the same group. These studies are used in psychology, the pharmaceutical industry, agriculture, and medicine. They can work with smaller sample sizes because the samples act as their own controls. That makes crossover designs useful when...

controls in experiments

Why Control Groups Improve Experiment Results

Control groups help experiments produce more reliable results. They reduce bias and make it easier to measure the dependent variable. In an experiment, controls have the same features as the treatment groups but are not affected by the independent variable. Researchers sort data into control and experimental conditions to see the relationship between the independent and dependent variables. A randomized experiment includes a control group that receives an inactive treatment. The control group...

bias

Biased Sampling and Fair Tests

Bias is any tendency that keeps a question from being unprejudiced. In research, bias appears when one outcome or answer is favored over others during sampling or testing. It can happen at many stages, including study design, data collection, analysis, and publication. A common form is sampling bias. This happens when a sample is taken from a population and some members are less likely to be chosen than others. In a fair sample, each member of the population should have an equally likely...

blinding

Placebos and blinding are key tools in randomized control trials, or RCTs. They help researchers reduce bias, which can affect study results. In a blinded study, participants do not know which treatment they are receiving. A placebo is a dummy treatment that does not contain the active treatment. Researchers use a placebo in the control group to compare against the treatment group. This helps balance the effects of being in an experiment with the effects of the active treatment itself. A...

clinical trials

How Clinical Trials Test New Treatments

Clinical trials test new treatments in people to check safety and effectiveness. These experimental studies can look at drugs, diet methods, and medical devices. Researchers use statistics to turn collected data into reasonable and accurate conclusions, so they can make sound decisions when results are uncertain. Statistics also help medical researchers reduce error and bias. That matters because clinical trial data can be influenced by chance or by uneven study design. Careful analysis...

key terms and concepts

Learn how placebos and blinding reduce bias in randomized control trials, including control groups, placebo effects, and double-blind studies.

Placebos and Bias in Randomized Trials | JoVE K12

statistics

JoVE Core Statistics introduces the concepts and application of the collection, analysis, presentation, and interpretation of data to students. These animated lessons provide an understanding of statistics beneficial to students from a wide range of disciplines. Additionally, the scientist-in-action videos demonstrate the application of related concepts in classical and original research experiments performed in today's laboratories worldwide

Chemistry

CH.1

CH.1.c

Physical Science

PS.1

PS.1.b

Physics

PH.1

PH.1.b

Texas Essential Knowledge and Skills

High School

CHEM.1

CHEM.1.B

Georgia Standards of Excellence

9-12

Epidemiology

SEPI3.

SEPI3.c

The Scientific Method

The scientific method is a detailed, empirical problem-solving process used by biologists and other scientists. This iterative approach involves ...

Inductive Reasoning

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Deductive Reasoning

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Correlation and Causation

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The student will demonstrate an understanding of scientific and engineering practices by asking questions and defining problems
• ask questions that arise from careful observation of phenomena and/or
organisms, from examining models and theories, and/or to seek additional
information
• determine which questions can be investigated within the scope of the
school laboratory or field to determine relationships between independent
and dependent variables
• generate hypotheses based on research and scientific principles
• make hypotheses that specify what happens to a dependent variable when
an independent variable is manipulated

BIO.1.a

Case Studies

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Archival Research

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Longitudinal Research

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Cross-Sectional Research

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Group Design

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Factorial Design

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The Placebo Effect

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Blind Procedures

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Ethics in Research

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The student will demonstrate an understanding of scientific and engineering practices by planning and carrying out investigations
 • individually and collaboratively plan and conduct observational and experimental investigations 
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BIO.1.b

Introduction to Statistics

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How Data are Classified: Categorical Data

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How Data are Classified: Numerical Data

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Ogive Graph

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Histogram

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Relative Frequency Histogram

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Scatter Plot

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Time-Series Graph

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Bar Graph

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Multiple Bar Graph

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Pareto Chart

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Pie Chart

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What is Central Tendency?

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Arithmetic Mean

The arithmetic mean is the most commonly used measure of the central tendency of a data set. It is defined as the sum of all the elements constituting the ...

Mean From a Frequency Distribution

Sometimes, data gathered from an experiment on a large sample or population are organized into concise tables. In such cases, the frequency of the ...

What is a Mode?

The mode is one of the commonly used measures of a central tendency. It is defined as the most frequent value in a data set.
There can be more than one ...

Bias

Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected ...

Median

Besides mean, the median is a widely used measure of central tendency. Typically, median is defined as the central or middle value of a data set, measured ...

Blinding is a commonly used method of not telling participants which treatment a subject is receiving. Blinding is a critical part of a randomized control ...

Midrange

A somewhat easy to compute quantitative estimate of a data set&#8217;s central tendency is its midrange, which is defined as the mean of the minimum and ...

Clinical Trials

Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and ...

What is Variation?

Apart from the measures of central tendency, distribution, outliers, and the changing characteristics of data with time, an important characteristic of ...

Range

The range is one of the measures of variation. It can be defined as the difference between a dataset&#39;s highest and lowest values. For example, in the ...

Standard Deviation

The most commonly used measure of variation is the standard deviation. It is a numerical value measuring how far data values are from their mean. The ...

Standard Error of the Mean

The sampling variability of a statistic is defined as how much the statistic varies from one sample to another. The sampling variability of a statistic is ...

Calculating Standard Deviation

The standard deviation is the most common measure of variation. It is a value that tells us how far a data value is from the mean value in a dataset. ...

Crossover Experiments

Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in ...

Controls in Experiments

When conducting an experiment, it is crucial to have control to reduce bias and accurately measure the dependent variables. It also marks the results more ...

The student will demonstrate an understanding of scientific and engineering practices by interpreting, analyzing, and evaluating data 
 • construct and interpret data tables showing independent and dependent variables, repeated trials, and means
 • construct, analyze, and interpret graphical displays of data
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 • analyze data using tools, technologies, and/or models to make valid and reliable scientific claims or determine an optimal design solution

What is a Hypothesis?

A hypothesis can be a simple sentence or statement about a property or any phenomenon observed or predicted for a population. It is usually a claim about ...

Null and Alternative Hypotheses

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Critical Region, Critical Values and Significance Level

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P-value

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P-value stands for the probability value. &#160;P-value is the probability that, if the null ...

Types of Hypothesis Testing

There are three types of hypothesis tests: right-tailed, left-tailed, and two-tailed.
When the null and alternative hypotheses are stated, it is observed ...

The student will demonstrate an understanding of scientific and engineering practices by  constructing and critiquing conclusions and explanations
• make quantitative and/or qualitative claims regarding the relationship between dependent and independent variables 
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• apply scientific ideas, principles, and/or evidence to provide an explanation of phenomena and design solutions 
• compare and evaluate competing arguments or design solutions in light of currently accepted explanations and new scientific evidence
• construct arguments or counterarguments based on data and evidence differentiate between a scientific hypothesis and theory

BIO.1.d

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Modeling and Similitude

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This setup predicts the ...

Typical Model Studies

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...

The student will demonstrate an understanding of scientific and engineering practices by  developing and using models
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It involves the sender encoding an ...

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The student will demonstrate an understanding of scientific and engineering practices by  obtaining, evaluating, and communicating information 
• compare, integrate, and evaluate sources of information presented in different media or formats to address a scientific question or solve a problem
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Placebos and Bias in Randomized Trials

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