Who are producers and consumers in research?

Some psychology students would like to become a researcher or a scientist. They are called producers of research. Other psychology students would rather not become a researcher or work in a laboratory, but like to read research to apply it to their job, hobbies, or relationships. They are known as consumers of research. In practice, psychologists are both producers and consumers of research. Producers and consumers share a love for empiricism: they want to answer psychological questions through direct and formal observation.

Why is it important to be a producer?

It is important to be a producer and have knowledge about research methods to finish your studies. Usually, you have to know how to interpret research other people have done, how to measure certain things, or how to read graphs. You also have to understand how to write according to the guidelines of the American Psychological Association (APA) to write your thesis.

Why is it important to be a consumer?

To be a good consumer of research is essential. You have to be able to read research in a curious, but critical way. A part of the research you come across in your career will be well thought out and usable, but another part may be bad or even made up. If you understand research methods well you will be able to ask the right questions in order to evaluate the research that you are reading. You should be able to interpret studies to stay up to date and know about new, possibly effective therapies. These therapies are known as evidence-based treatments: treatments that were formally researched and are now known to be effective.

How do scientists approach their job?

What is empiricism?

Empiricism, the empirical method or empirical research means that evidence from the senses or instruments that help the senses (such as photographs, questionnaires, measuring scales, thermometers or timers) are used to draw conclusions. Empiricists want to be systematic and rigorous in their research and want to make sure other researchers can verify or debunk their conclusions independently.

What is the theory-data cycle?

The theory-data cycle means that scientists collect data to test their theories, and change or adapt them. This happens as follows: first, a scientist asks a question about a phenomenon they want to be able to explain with their theory. Then, they make a prediction or predictions about how the phenomenon could be explained. They then test these predictions by collecting data. Based on the data they determine whether they should adapt or change their theory, and whether to ask follow-up questions.

The way in which attachment works has been looked at in psychology and can be used to explain the theory-data cycle in detail. One theory of attachment is known as the cupboard theory. This states that a baby attaches itself to the mother because the mother feeds the baby, which makes the child happy. Another theory is the contact-comfort theory. This states that babies attach themselves to the mother for comfort. This latter one was coined by Harlow, who tried to study which of these two theories was correct. He did this by separating the influence of food and comfort in a lab. He built one mother made from wire that was able to give the baby milk through a bottle. Another mother he built was made from soft cloth instead but was not able to feed the baby. Then, Harlow observed how long the baby monkeys clung to the mothers. Based on the data it was found that the contact-comfort theory was supported: the monkeys clung to the cloth mother the whole time and only moved away from her as soon as they wanted some food. They then walked to the wire mother and walked straight back.

What are theories, hypotheses, and data?

A theory makes claims that concern the relationship between variables. These claims are supposed to be as simple as possible. Theories lead to specific hypotheses. A hypothesis can be seen as a prediction. It says something about what the researchers expect to observe if their theory is correct. One single theory can have many hypotheses, and multiple studies can be done with the same theory in mind. If multiple pieces of research are done, hypotheses should be preregistered: registered in advance publicly before data is collected. Data is a set of observations. Data can support a theory or challenge it. If the data does not fit the hypotheses then this may be a sign that the theory should be changed or that we need to make use of different research methods. Often replications are done, meaning the whole research is done from scratch based on the same research question and hypotheses in order to check whether the result is consistent with data that was found earlier.

A good theory should be falsifiable: we should be able to conclude that the theory is wrong based on research. If data fit the theory, we are never allowed to conclude that research 'proves' the theory. We can say that data is 'consistent with' or 'supports' the theory.

What is it like to work in a community?

Scientists and researchers are part of a community, meaning they have to stick to certain norms. Norms are expectations about the way somebody should behave in certain situations. Merton stated four of these norms:

• Universalism: scientific claims should always be evaluated based on quality and not based on the reputation of the researcher that made the claim. All researchers and studies have to stick to the same guidelines. This means everybody can do research as long as they stick to these guidelines and criteria.
• Communality: scientific knowledge is created by a community. This means that researchers should always be transparent about their results and should share them with other researchers and the general public.
• Disinterestedness: researchers want to know the truth, regardless of what this might be. This means that they should never publish wrong information based on politics, idealism, or profit. Scientists should always accept what the data tells them and should never be guided by their own ideas, income, or prestige.
• Organized skepticism: scientists should question everything, including their own theories, ideas that are widely accepted as 'the truth', and ancient wisdom. This means they should never accept things at face value, but should always look for evidence.

What is the difference between applied and basic research?

Applied research means that researchers do a study based on a real-life practical problem. Basic research aims to increase the overall knowledge we have about certain topics, without focusing on a practical problem specifically. Translational research makes use of the knowledge from basic research to develop and test treatments. It forms the bridge between basic and applied research.

How is scientific work published?

When researchers want others to know what they found in a study they try to get it published in a scientific journal. These journals usually come out every month and contain all sorts of peer-reviewed articles. When an article is peer-reviewed it means that it was sent to three or four experts in the field who determined it was good enough to be published in the journal. These experts comment on how important the work is, whether it fits other knowledge there is about the topic, whether the research was done correctly and how believable the results are. This is anonymous. After the approval of the experts, the article is published in the journal. When other researchers still find errors then, they can send this to the journal, or they could start researching the topic themselves.

How does scientific work end up in newspapers?

Articles in scientific journals are read by other scientists or students. The general public does not read these articles. They usually read it in a news article that was based upon the research and was written by a journalist. This journalist usually shortens the work, gives it an interesting title, and makes use of general terms instead of jargon so people who are not experts on the topic can understand the story. This is important because it makes scientific research available to the general public. However, there are dangers in this. Journalists could interpret the research wrongly or could make the results sound more important than they actually are. An example of the latter is the Mozart effect. Rauscher conducted research in which he found that when students listened to Mozart, they scored higher on tests that measured their spatial intelligence. In a radio interview, he mentioned that this effect was very small and was not found for any tasks other than spatial. He said it was not found for general intelligence. Yet, journalists published articles that said that Mozart would make you smarter in general.