TLDR on Causality:
| Causality or cause and effect, refers to the relationship where one variable (independent variable) causes the other (dependent variable) to change I would go so far to say that psychology is obsessed by causality aka what causes a certain behavior. Psychology makes it its own mission to pursue cause and effect, the same way science seeks to describe, explain, predict, and control a phenomenon Research can help us “determine” causality to some extent, yet, how (accurate) we are is debatable, as studies and data are often influenced by multiple confounding factors that complicate the cause-and-effect relationship Experiments are the best way to establish causal relationships, but issues like validity, extraneous variables, and controls must be tightly managed to accurately isolate the root cause To further complicate things, human behavior itself is complex and influenced by many factors, making causality harder to pinpoint |
Essentially, causality in psychology is tricky because behavior is shaped by biological, cognitive, and sociocultural factors interacting with each other.
Causality in Psychology: A Complex Web of Interactions
- Understanding Causality:
Causality is about understanding how one factor (the cause) leads to a change in another (the effect).
In psychology, it’s often about figuring out how specific variables—like caffeine, sleep, or social influence—impact behavior. The goal is to establish clear cause-and-effect relationships to explain and predict actions. - Complex Human Behavior
Human behavior is multifaceted and influenced by a mix of biological, cognitive, and social factors. These factors interact in ways that make causality difficult to pin down. It’s not just one thing causing behavior; it’s usually a combination of several elements working together. - Bidirectional Ambiguity:
Sometimes, it’s unclear whether one variable causes the other, or if the reverse is true. For example, does lack of sleep cause anxiety, or does anxiety prevent sleep? This ambiguity is a common challenge when studying causal relationships, where the cause and effect are intertwined.
Studies show that stress can increase the risk of heart disease, but it’s also true that people with heart disease may experience higher levels of stress due to health concerns. So, it’s unclear whether stress causes heart disease, or if heart disease causes more stress — or perhaps both factors influence each other in a cyclical pattern. This bidirectional relationship makes it difficult to draw clear conclusions about cause and effect. - Reductionism vs. Complexity:
Reductionism tries to break things down into simpler parts—such as focusing on biological causes of behavior—while complexity acknowledges that real-world behavior often involves many interacting variables. Reductionism is useful for understanding certain causes but can oversimplify the complex nature of behavior, missing important interactions. - Internal and External Validity:
Validity refers to the accuracy of an experiment’s findings.
A good study must control extraneous variables to establish a clear cause-and-effect relationship. The concept of internal validity is directly related to causality because it ensures that the observed effects in an experiment are genuinely due to the independent variable (ie. caffeine) and not influenced by confounding factors.
If internal validity is compromised by extraneous variables, it’s difficult to establish a true cause-and-effect relationship.
External validity, on the other hand, relates to whether the findings can be generalized to real-world situations or other populations. Even if a study has high internal validity, if it lacks external validity, the causal relationship identified may not apply to other settings or people, weakening the overall conclusions about causality. - Interaction of Variables:
Causality isn’t always a one-way street. Interaction of variables suggests that the effects of one variable (ie. study habits) may depend on the presence or level of another variable (ie. sleep).
This complicates our ability to establish simple cause-and-effect relationships because human behavior often results from the combined influence of multiple variables. For example, we may not be able to claim that sleep alone causes academic performance unless we also account for how other factors like study habits interact with sleep. - Agency and Motivation:
Personal choice and motivation play significant roles in human behavior. Agency refers to people’s ability to make choices that influence their behavior, making it harder to pinpoint a single causal factor. Motivation, a key driver of behavior, also adds complexity to causality.
If we only consider external factors like environment or biology, we might ignore how individual choices shape behavior. For instance, while stress might lead to poor sleep, an individual’s motivation to manage stress (ie. through coping strategies) could influence whether or not this effect occurs. - Reciprocal Determinism:
This concept emphasizes the dynamic interaction between individuals and their environments.
This cyclical relationship makes establishing clear causality tricky because the behavior we observe could be both the result of the environment and the cause of future changes in that environment.
For example, a child’s behavior in school may influence how teachers respond to them, which in turn affects the child’s future behavior. In this case, it’s not easy to say which one is the cause and which one is the effect. - Validity & Controls in Research:
To truly understand causality, experiments must be well-designed. This means using controls—like random assignment or placebo groups—to ensure the effects observed are due to the independent variable and not other factors. Proper experimental design strengthens the validity of the findings and helps eliminate biases.
Read here for more on Bias
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