Self-Control is Important

Imagine you want to reduce your social media use because it takes up too much of your free time. You decide that, for the coming 4 months, you only want to spend 30 min on social media each day. This will probably not be easy! On some days, you may be watching an interesting video or chatting with friends when time is running out. Self-control is what helps you to put away your phone anyway, and do something more active and fun instead. Self-control means that you are avoiding short-term temptations (e.g., watching more videos on YouTube) to achieve a long-term goal (e.g., reducing your social media time). Self-control is related to many important things, like staying healthy and doing well in school [1].

There are several strategies for self-control (Figure 1). For example, you can simply fight through the urge to look at your phone, or you could reward yourself for each day that you spend less than 30 min on social media [2, 3]. You would probably like to know which strategies are the best—and so do scientists. To find out, we can compare people who use different self-control strategies to see who successfully achieves their goals. But to do this, we need to find a way to assess which strategies someone uses. Psychologists typically use questionnaires for research like this.

To compare research results with other groups, it is best if everyone uses the same questionnaire. Developing questionnaires is a science in itself, and it can be pretty challenging to develop a trustworthy one. Knowing how much effort goes into this process can help you recognize questionnaires that are not very useful scientifically, for example those from the internet that may be fun but should not be taken seriously.

The Process

We translated a questionnaire on self-control strategies [2] from English into German and then and validated it, to see whether is works well [3]. This process involved eight main steps.

Step 1: Generating Questions

The first step of creating a questionnaire is to collect many possible questions or statements, the best of which will go into the questionnaire. In our case, the statements already existed, and we translated them from English to German. Translation was done by a team that included a native English speaker. We translated all questions into German, discussed the results, and translated everything back into English to see if we came back to a similar wording. This helped us to make sure the translation was accurate.

Step 2: Getting Feedback

Next, we had to make sure that the questions we created were easy to understand and did not sound odd or confusing. To do this, we asked 41 people of different ages to answer the questions and give us some feedback. We incorporated their feedback by changing the wording of some of the questions, for example by switching some complex terms to more commonly used words.

Step 3: Checking Factor Structure

After including the feedback, we asked many people (more than 3,000) to fill out our questionnaire and answer additional questions about their lives. A common first step is to check the factor structure of the data, which means testing whether the data shows the structure that we would expect (the answers are associated with their respective overall factors, such as “reward” or “punishment”). Checking the factor structure helped us to better understand self-control. For example, it could tell us whether there is one overall “self-control score” (meaning people either use all the strategies or none of them) or if the strategies are more independent from each other. Like other researchers before us [2], we found that the self-control strategies are independent. Hence, using one strategy is not necessarily linked to using other strategies as well.

Step 4: Verifying Internal Consistency

Next, we tested whether all questions about the same strategy were consistent with each other, meaning whether they referred to the same strategy. This is done to make sure that questions about a strategy actually assess that specific strategy. We want a clean assessment of each strategy individually, not a mixture of several strategies. We can test internal consistency by looking at whether questions about the same strategy get fairly similar answers from the same people. If the same person gives very different answers to questions about the same strategy, that could indicate that one of the questions may be misleading or difficult to understand. Fortunately, most of the questions in our questionnaire were as consistent, as we hoped. The only exception was the strategy called pre-commitment. This strategy is quite diverse, which may be why it was not as consistent.

Step 5: Testing Stability Over Time

We also tested how stable participants’ answer behavior was across time. So, is a person who is high in “cognitive change” a certain dimension of self-control, like distraction, in January still high in this dimension in March? For some things, like mood, we did not expect a high time stability, as people’s moods often change. For self-control strategies, however, we assumed that the behavior would not change too much over time, as these strategies are usually based on habits or personal preferences. If the answers to the questions are stable over time, we can, for example, select people who regularly punish themselves too much and help them to reduce this behavior. Luckily, most self-control strategies were demonstrated to be relatively stable over several weeks.

Step 6: Assessing Measurement Invariance

When we create a questionnaire, we want it to work well for different kinds of people: for men and women, for young people and older ones. We also want to make sure that the answers from different people can be compared and that different groups, like men and women, do not regularly give different answers. We call this measurement invariance. For example, if Anna scores higher than Oliver does on the questionnaire for using rewards as a self-control strategy, we want to be sure that this is not just because Anna is a girl and girls always have higher scores for the rewards strategy—because in that case, it would not tell us much about Anna herself. To test for measurement invariance, we used a statistical method that compares the factor structure that we talked about in Step 3 for men and for women (Figure 2). We also compared young, middle-aged, and older people the same way. These tests showed us that the questionnaire works very similarly for people of different genders and ages. So, for the Anna and Oliver example, we can say that Anna’s use of rewards is specific to her and not just because she is young or a girl.

Step 7: Testing Convergent and Discriminant Validity

After checking the consistency and stability of the questionnaire, we then tested its validity. If a questionnaire is valid, it measures what we want it to measure. For example, if we measure height by seeing who can reach the top kitchen cabinet, this may be a very stable measure, since it is always the same people who can reach the cabinet, but not very valid—because some short people could just use a ladder. To test validity for our self-control questionnaire, we need to know other concepts related to self-control. The test then goes in two directions: for convergent validity, we tested the association between the questionnaire and a different questionnaire on the same construct (self-control), which already exists, and hoped for a high score. To do this, we used a different questionnaire, with a different focus than ours, to measure self-control.

Discriminant validity should show that the scale does not correlate too strongly with similar concepts, to show that it is not just the same thing again. Here, we tested the association with meta-cognition in self-control (i.e., how people think about self-control) and lay beliefs of willpower (i.e., if people think self-control is limited or not). We showed that our scale is related to these concepts, but still distinct.

Step 8: Prediction

Once we checked that our questionnaire was similar enough to closely related questionnaires and different enough from questionnaires designed to measure different topics, the most exciting part could start. We wanted to know if our questionnaire could predict important things in our lives. Remember how we said earlier that self-control is important for many of things, like doing well in school and being healthy? Using statistical analysis, we tested whether people who often use certain self-control strategies experience those good outcomes more often (e.g., is physical exercise higher in people who report more usage of the pre-commitment strategy?). For example, we found, that people who used the self-control strategies of pre-commitment, cognitive change, or behavioral inhibition were happier, ate more healthy foods, and procrastinated less. Different strategies were also helpful in specific cases, for example, the distraction strategy was useful when studying for exams. This showed that our questionnaire can help predict different helpful behaviors and positive feelings. To make sure that our results are trustworthy, other researchers can repeat our study with a different set of people, to see if they find similar results. This way, we can make sure that our findings were not just a coincidence and can be applied to different groups of people.

Summary

After all these steps, we now have a trustworthy German version of our questionnaire. Now, other researchers can use our scale for their own research projects and could, for example, test if Germans use the same strategies as Americans, or if people can be trained to use certain strategies. Further, scientists from other countries could use our procedure to translate the questionnaire into even more languages. Overall, this is important because only questionnaires of high quality can help researchers answer their questions well.

Glossary

Self-control: ↑ The ability to resist short-term temptations or impulses to achieve long-term goals (e.g., choosing to train instead of relaxing on the sofa when preparing to run 10 km).

Factor Structure: ↑ Pattern of relationships between questions and the strategies, they are supposed to assess.

Internal Consistency: ↑ How well do questions (items) about one strategy relate to each other.

Cognitive Change: ↑ Consciously choosing to change thoughts about a given object (e.g., not thinking about sweets as a tasty treat but as something that can harm your teeth).

Measurement Invariance: ↑ Do members of different groups respond similarly to a questionnaire (e.g., Germans and US Americans).

Validity: ↑ The extent to which a measure accurately assesses what it is intended to measure. For example, a scale is a valid tool for measuring weight but not for measuring height.

Correlation Analysis: ↑ This analysis quantifies the association between two measures. A typical example of a positive correlation is height and weight, as taller people usually weigh more.

Conflict of Interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgment

The work was supported by the Support Scholarship by the Austrian Federal Ministry of Education, Science and Research, awarded through the University of Vienna to Victoria Wagner, Artemis Lydia Nordmann, Loana-Corine Stenzel and Olga Freiman.

AI Tool Statement

The author(s) declared that generative AI was not used in the creation of this manuscript.

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