External and Internal Validity

Summary

This script discusses the importance of validity in research, focusing on internal and external validity. External validity ensures findings can be generalized to other populations and settings, while internal validity confirms the accuracy of measures within the study. The script outlines common threats to both, such as participant characteristics, setting, timing, selection bias, sample size, and confounding variables, emphasizing the need for careful study design to ensure reliable and generalizable results.

Takeaways

• 🔍 Research validity is about the soundness of the research design and methods.
• 🌐 External validity is the ability to generalize study findings to other populations and settings.
• 🚫 Lack of external validity means findings are limited and may not apply to other people or contexts.
• 🔬 Internal validity concerns the accuracy of measures within the study and the true relationship between variables.
• 🚫 Lack of internal validity suggests that findings may not reflect the intended constructs or relationships.
• 👥 Participant characteristics can affect external validity if they do not represent the larger population.
• 🏫 The controlled research environment can limit external validity due to its artificiality compared to real-world settings.
• ⏳ Timing is crucial; past studies may not have external validity in the present due to societal changes.
• 🎯 Selection bias can affect both external and internal validity if groups are not comparable at the study's start.
• 🔢 Small sample sizes can lead to unreliable statistics and findings that may be due to chance.
• 🔄 Confounding variables can undermine internal validity if they influence the dependent variable alongside the independent variable.
• 📚 History effects, such as external events, can impact how participants respond and affect internal validity.
• 📈 Maturation effects, like aging or fatigue, can internally influence responses over the course of a study.
• 🛠️ Instrumentation issues arise when measurement tools change, potentially skewing study results.
• 📝 Testing effects can occur in pre- and post-tests, where familiarity with the test can improve performance.
• 🔄 Attrition refers to participants leaving a study, which can introduce bias and affect both internal and external validity.

Q & A

What does 'validity' mean in the context of research design and methods?

In research, 'validity' refers to the soundness of the research design and methods used to ensure that the findings are accurate and meaningful.

What are the two main types of validity discussed in the script?

The two main types of validity discussed are internal validity and external validity.

Why is external validity important in research?

External validity is important because it allows researchers to generalize their findings to other populations and settings, extending the applicability of the research beyond the specific study context.

What does a lack of external validity imply about the research findings?

A lack of external validity implies that the research findings cannot be confidently applied to other people or contexts outside of the study, limiting the scope of the research's applicability.

What is internal validity and why is it crucial for a study?

Internal validity relates to the accuracy of the measures within a study and ensures that the findings reflect the true relationship between the independent and dependent variables, without being influenced by extraneous factors.

What are some common threats to external validity?

Common threats to external validity include participant characteristics, the research environment, and timing, all of which can reduce the generalizability of the study results to other populations and settings.

How can the research environment affect external validity?

The research environment, often being highly controlled and artificial, may not represent the real-world contexts to which researchers wish to generalize their findings, thus affecting external validity.

What are some threats to internal validity that can compromise a study's findings?

Threats to internal validity include selection bias, sample size, confounding variables, history, maturation, instrumentation, testing or practice effects, and attrition or mortality.

Why is controlling extraneous variables important for internal validity?

Controlling extraneous variables is important for internal validity because it ensures that any changes in the dependent variable are due to the independent variable, not other factors, thus establishing a clear causal relationship.

How can sample size impact the internal validity of a study?

A small sample size can reduce internal validity because it may lack the statistical power needed to produce reliable results, making the findings more susceptible to being due to chance.

What is meant by 'selection bias' and how can it affect both internal and external validity?

Selection bias occurs when the groups being compared in a study are not similar at the outset, potentially due to differences in participant characteristics. This can affect both internal validity by influencing the study's results and external validity by impacting the generalizability of those results.

Can you explain the difference between 'history' and 'maturation' as threats to internal validity?

History refers to external events that occur during the study that may affect participant responses, while maturation is an internal process, such as aging or fatigue, that naturally occurs and can influence the results. Both can affect how participants respond, but history is external, and maturation is internal.

What is 'instrumentation' and how can it threaten the internal validity of a study?

Instrumentation occurs when the measurement tool or method used in a study changes over time, potentially producing different results. This can threaten internal validity by introducing variability in the data collection process that is unrelated to the study's variables of interest.

How can 'testing' or 'practice effects' impact the internal validity of a study?

Testing or practice effects occur when participants perform better on a test the second time due to familiarity or practice, which can lead to improved performance not related to the study's independent variable, thus threatening internal validity.

What is 'attrition' and how can it affect both internal and external validity?

Attrition refers to participants dropping out of a study. It affects internal validity by potentially introducing bias if the reasons for dropping out are related to the study's variables. It can also affect external validity if the group that remains in the study differs significantly from the general population.

Outlines

00:00

📊 Understanding Research Validity: Internal and External

This paragraph introduces the concept of validity in research, distinguishing between internal and external validity. External validity is emphasized as the ability to generalize findings to other populations and settings, which is crucial for the applicability of research. The paragraph also explains the limitations of external validity, such as when a study's participant demographics limit the applicability of results. Internal validity, on the other hand, concerns the accuracy of measures within a study and the ability to confidently attribute changes in the dependent variable to the independent variable. The paragraph outlines common threats to both types of validity, such as participant characteristics, research environment, and timing, which can affect the generalizability of results.

05:01

🔍 Threats to Internal and External Validity in Research

This section delves deeper into the specific threats to internal and external validity. For external validity, it discusses the impact of participant characteristics, such as the common practice of recruiting undergraduates for psychological studies, which may not represent the broader population. The controlled nature of research settings and the passage of time are also highlighted as factors that can limit the generalizability of findings. Turning to internal validity, the paragraph addresses threats such as selection bias, which can affect the comparability of groups, and sample size, which can impact the reliability of statistical results. Confounding variables, history, maturation, instrumentation, testing effects, and attrition are also discussed as factors that can compromise a study's ability to establish a clear relationship between the dependent and independent variables.

10:02

🛠 Addressing Validity Threats for Reliable Research Outcomes

The final paragraph focuses on the importance of addressing threats to validity when designing a study. It emphasizes the need to ensure that the study's results accurately reflect the relationship between variables and are generalizable to other populations and contexts. The paragraph discusses the issue of attrition, where participants dropping out of a study can affect both sample size and the representativeness of the sample. It also touches on the potential for selection bias in studies involving pretests and post-tests. The paragraph concludes by stressing the importance of careful consideration of these threats to ensure that research findings are both valid and applicable to a wider audience.

Keywords

💡Validity

Validity refers to how well a study measures what it is intended to measure and how accurately its findings can be applied. In the video, it is discussed in terms of research design, emphasizing the importance of sound methodology to ensure reliable results.

💡Internal Validity

Internal validity pertains to the extent to which a study can establish a cause-and-effect relationship between the independent and dependent variables within the study itself. It depends on factors like controlling for extraneous variables. The video illustrates this with an example where pet type might affect mental health benefits, impacting the study's internal validity.

💡External Validity

External validity refers to the degree to which the results of a study can be generalized to other populations and settings beyond the study. The video explains that it is important for research findings to be applicable to broader contexts, not just the specific group studied. An example given is the generalizability of findings from a study with only white male participants.

💡Generalizability

Generalizability is the extent to which research findings can be applied to larger populations or different contexts outside the specific conditions of the study. The video emphasizes that for results to be useful, they should reflect broader trends, not just the specific group or setting studied.

💡Participant Characteristics

Participant characteristics refer to the demographic and personal attributes of study participants, such as age, gender, and socioeconomic status. The video mentions that these factors can impact the external validity of a study if the sample does not represent the larger population accurately.

💡Selection Bias

Selection bias occurs when the participants selected for a study do not represent the general population, which can skew the results. The video provides an example where different groups might have varying educational levels or motivations, potentially affecting the study's outcomes.

💡Confounding Variables

Confounding variables are extraneous factors that can influence the results of a study, making it difficult to determine the true effect of the independent variable on the dependent variable. The video discusses how failing to control for such variables can undermine internal validity, using the example of different pet types affecting mental health.

💡Attrition

Attrition, or mortality, refers to the dropout of participants during a study, which can impact the study's sample size and potentially bias the results. The video explains that if participants who drop out differ in significant ways from those who remain, it can affect both internal and external validity.

💡Maturation

Maturation is the process of participants changing over time, which can affect the results of a study, especially in long-term research. The video highlights that these natural changes can impact how participants respond, potentially compromising internal validity if not accounted for.

💡Instrumentation

Instrumentation refers to changes in the measurement tools or procedures during a study, which can lead to inconsistencies in data collection. The video provides examples such as an experimenter altering a test or equipment wearing out over time, which can affect the study's results.

Highlights

Validity in research is crucial for ensuring the soundness of research design and methods.

Two main types of validity discussed: internal and external validity.

External validity concerns the generalizability of study findings to other populations and settings.

Research aims to expand knowledge beyond the specific study context.

Limitations in studying a small population can impact external validity.

External validity allows for confident application of findings to broader contexts.

Lack of external validity restricts the applicability of findings to other groups or situations.

Internal validity relates to the accuracy of measures within the study.

Internal validity ensures that findings reflect the intended constructs and relationships.

Threats to external validity include participant characteristics, research environment, and timing.

Undergraduate participants may not represent the larger population.

Controlled research settings may not reflect real-world conditions.

Temporal changes can affect the external validity of past studies.

Threats to internal validity include selection bias, sample size, confounding variables, and more.

Selection bias can affect both external and internal validity if groups are not comparable.

Sample size impacts the statistical power and reliability of study results.

Confounding variables can influence results if not properly controlled.

History effects, maturation, instrumentation, testing effects, and attrition are specific threats to internal validity.

Careful study design can mitigate threats to both internal and external validity.

Ensuring validity strengthens the confidence in the true relationship between variables.

Generalizability of results to other populations and contexts is a key outcome of validity.

Transcripts

there are many forms of validity and

research in general validity refers to

how sound your research design and

method are we are going to talk about

two types of validity internal validity

and external validity external validity

refers to how well the findings of our

study can be generalized to other

populations and settings after all the

purpose of research is to learn more

about the world at large and not just

about our specific group of participants

or what goes on in our lab alone it

would be great if we could just study

everyone in all possible contexts but

unfortunately our access is typically

limited to a small population of

participants in a single context or

situation however we still want to be

able to take our findings and say with a

degree of confidence that they represent

what goes on outside of our study

that's what external validity gives us a

lack of external validity means that our

findings cannot be applied to other

people or other contexts outside of the

study we performed or that application

to other people and contexts is limited

for example if we only had white males

participate in our study our findings

might not apply to females or non-white

races and ethnicities so while external

validity refers to factors outside of

our study internal validity on the other

hand relates to the validity of measures

within our study it depends on factors

such as did we capture the construct

that we intended to with our measure was

the independent variable really the

cause of the changes in the dependent

variable or did we control for all other

possible factors that could have

affected our results a lack of internal

liddie means that our findings may not

necessarily reflect what we think they

do

for example our study may have looked at

the effect of pet ownership on mental

health but let's say that unbeknownst to

us at the time the type of pet has a

significant effect on whether or not the

owner will experience mental health

benefits if we did not control for the

type of pet in our study that our

findings do not necessarily reflect what

we think they do

and our study lacks internal validity

let's review some common threats to

external and internal validity this is

by no means an exhaustive list rather

here we just have three examples of

threats to external validity remember

anything that reduces the

generalizability of the study results to

other populations and settings will

reduce external validity let's take a

look at participant characteristics the

question we want to ask is do they

represent the larger population we want

to generalize to for example a large

majority of studies in psychology

recruit undergraduates looking to get

extra credit in their courses

however these participants may differ

from the larger population in a number

of factors such as age IQ and

socioeconomic status setting

the research environment is typically a

very controlled and artificial one very

much unlike the everyday world that we

want to generalize our findings to it is

important for studies to be able to

control all possible extraneous

variables to be sure of the relationship

between the independent and dependent

variables but this does come at a cost

of external validity to a world in which

the variables of interest will almost

always occur in the presence of other

extraneous variables and timing the

world changes with time and so studies

conducted in the past may not have

external validity to the world today for

example a study conducted sixty years

ago on sexism in the workplace may have

produced very different results than a

similar study conducted today and what

about threats to internal validity we'll

go over a few more here since internal

validity can involve such a wide variety

of factors within a study so the thing

to remember here is that anything that

reduces the studies ability to establish

a relationship between the dependent and

independent variable reduces its

internal validity so starting with

selection bias selection bias can be a

problem for the same reasons that

participant characteristics can be a

problem for external validity if we are

comparing two groups of participants we

want to make sure the two groups are as

similar to each other as possible at the

beginning of the study so that

differences in the characteristics of

participants don't affect our results

for example if one group consists of

college undergrads volunteering for

extra credit and the other group was

recruited from flyers at a local arcade

we may find that the two groups differ

in their level of education

motivation and possibly IQ not saying

that those who hang out at the arcade

have low IQs just that there may be a

larger proportion of individuals with

higher IQs in a group that is pursuing

an education and putting forth the

outside effort to earn extra credit next

we have sample size having too few

participants in the study can mean that

the statistics don't have enough power

to produce results we can trust in other

words our findings are more likely to be

the result of chance if we are basing

them on only a few individuals

confounding this occurs when an

extraneous variable we did not control

for has an effect on our results in

other words something other than the

independent variable is affecting the

dependent variable in history history

refers to events outside of the study or

between a pretest and a post-test having

an effect on how participants respond

this could be something as significant

as a natural disaster or as simple as a

participant reading a book on

memorization skills during a study on

memory maturation maturation is a

natural process in which participants

change between a pretest or post-test or

during the course of a study in which

multiple measurements are made it may

simply be that they got older in a study

that spans years or that they became

fatigued or hungry during testing

maturation is similar to history and

that both affect how a participant

responds in a study but they differ in

that maturation is internal

and is a natural course of things while

history has to do with an external event

of some kind

instrumentation this occurs when the

instrument or measure we are using in a

study changes in some way over the

course of a study if the measure is

different at the beginning than it is at

the end it could possibly be producing

different results instrumentation can

occur for example if an experimenter

decides to tweak a test to make it

better or if the springs on a scale

start to wear out it can also occur in

observational measures if the observer

gets better with practice at detecting

certain behaviors over the course of a

study next we have testing also

sometimes referred to as practice

effects in studies that use the same or

similar measure for a pretest and a

post-test run the risk of practice

effects if a participant is given a math

test for a pretest and a post-test she

is likely to perform better the second

time that she has seen the test before

it could be a matter of the participant

getting better with repeated practice or

it could simply be familiarity with a

test that leads to better performance

and finally we have attrition or

mortality attrition refers to

participants dropping out during the

course of a study not only does this

become a problem for sample size but

there may also very likely be a reason

that some participants drop out and

others continue on with the study for

example participants who drop out may

have a more difficult time with

transportation to and from the location

of a study and therefore may be of lower

socioeconomic

Attis this factor that differs between

those who stick around and those who

don't

may have an impact on the sorts of

findings we end up with if the study

involves a pretest and a post-test the

group who took the pretest at the

beginning of the study may differ from

the group who took the post-test at the

end also the factor determining which

participants are still in the study may

be exerting a sort of selection bias on

the characteristics of the participants

our results are based on which is a

threat to the internal validity of our

results but this can also create a

threat to external validity if the

participant sample our results are based

on differs in a significant way from the

general population with careful

consideration of the potential threats

to internal and external validity when

designing your study you should be

confident that your results reflect a

true relationship between your dependent

and independent variables and that those

results are generalizable to most other

populations and contexts