## 6.2. Discussing your research

In the discussion section, you do two things: you discuss the quality of your research, and you discuss the implications of your research. In the discussion about the quality of your research, revisit the shortcomings of the design of your study which you have already talked about in the data and methods section. Also discuss the strengths of your research design, data and methods. The stronger the design of your research, the higher the quality of your data, and the more stringent the tests you conducted, the less likely your results can be explained as a result of its shortcomings. When you write this part of your discussion section, envision the fiercest critic you may encounter. What would be the arguments against your conclusions in your worst nightmare?

When you write about the implications of your research, envision two types of audiences: people who may want to use the conclusions of your study to change things, and people who may want to build on your research in the future. This means you revisit the arguments you made in the introduction about the societal and scientific relevance of your study. How does your research contribute to solving a social problem, help improve policy, explain anomalies, solve mysteries, open black boxes?

When you make recommendations for policy and practice, remember that your findings are essentially out of sample predictions about the consequences of a change in X, assuming that the effects on Y in the future are similar to the ones you observed in the situation you studied. You should discuss whether this assumption holds. Will the results you obtained also be valid in future situations that you have not examined? You do not want to make recommendations for future policy or practice in situations in which your recommendation is likely to result in different consequences.

- “Isn’t my research a complete failure now my hypothesis was not supported?”

No, not at all. First of all, it is good to know that you are not alone. In science, most things don’t work. All the nice results published in ‘top journals’ by glamorous professors you have relied on to construct your hypotheses may have given you the impression that hypotheses are always supported. The reality, however, is much different.

Second, have a little more faith in yourself. You had good reasons for your hypothesis, remember? Perhaps something was wrong with the way you tested your ideas. That is why typically, in the discussion section you first talk about methodological problems that may have affected the results. Scrutinize your data and methods. Discuss limitations to your research. If you were a really critical reviewer of your own work, what problems can you identify in the validity and reliability of the measures? What are the consequences of these problems for your results? If the measures would have been better, would the results have been different? In what way? In some cases, you can ‘save’ the hypothesis you rejected with an argument about the imperfections of your data and methods. Perhaps your results would have been in line with the hypothesis if the test had been better.

Do not give such explanations too lightly. They sound like excuses of the coach after a lost game, and you know what they say: “A winner always has a plan, a loser always has an excuse”. If after doing all the work you can think of obvious reasons why your data and methods were not good enough, why didn’t you think about them before? You should have used better data and methods. This is why your research design is so important. Also remember that usually more stringent tests give less positive results. In my experience, suboptimal data and methods increase the chance that you did not reject your hypotheses. Finally, when you make a case about characteristics of data and methods, spell out the complete argument. For instance, if you argue that using a convenience sample of online platform workers may be the reason why you did not observe the expected effect, explain why the participants did not behave in the way you expected. Did the workers complete the survey too quickly and were their answers not reliable or valid? Well, take the subsample of workers who took more time or provided more reliable and valid answers. If this subsample also does not display the expected behavior, your explanation is unlikely to hold. If you argue the manipulation you used in your experiment was not successful, provide results from a manipulation check, and leave out participants who failed it. If your results hold for those who successfully passed the manipulation check, your explanation holds.

After the discussion of the methodology of your research, you discuss the implications for the theories you used to develop the hypotheses. You start with a discussion of the reasons why some of your hypotheses were rejected. If these reasons are not methodological, you check whether the deduction of the hypotheses was correct. If the deductions are correct, you discuss to what extent the results of your research call the hypotheses into question and talk about the tenability of the theories and hypotheses. Go back to your theory section and construct a testable hypothesis to explain why some of your results turned out to be different than you expected. If possible, check your explanation using data. Start with the data you have at your disposal. Test the implications of your explanation with the data you already have. If you cannot test the explanation, suggest ways in which future research may do so.

Hypotheses that were supported are also worth discussing. Can they be explained by alternative mechanisms? Which alternative explanations can be ruled out by your own research? Which additional analyses of the same data could rule out alternative explanations? How should new research be designed to rule out alternative explanations?

If you found unexpected results that do not bear directly on the hypotheses that you formulated, but are interesting and worth attention, identify them. If you have space, give explanations for such unexpected results.

Finally, you suggest further research to correct the problems of your research or to find more meaningful answers. When you read previous research, pay particular attention to the paragraphs with suggestions for future research. Have subsequent studies tried these suggestions? If not, you may have found some ideas for your study.