Maturation effects and internal validity

If the experiment in your dissertation focuses on people (i.e., people are the population you are interested in), maturation is likely to threaten the internal validity of your findings. This has to do with time and the effect that time has on people. After all, experiments do not happen overnight, but often over a period of time, whether days, weeks, a few months, or in some cases, years. Whilst experiments at the undergraduate and master's dissertation level tend to last no longer than 2-3 months (at least the data collection phase), there are a number of changes that can take place within such short timeframes. During such periods of time, people change, and such change can affect your findings. This is the case for all types of experiment, whether in the physical or social sciences, psychology, management, education, or another field of study. Let's look at some examples of maturation effects in the short-term and long-term:

Short-term changes and their effects
There are a number of maturation effects that can occur during the very short term; that is, within a few hours or days. People's behaviour can change. For example, they can go from being in a good mood or a bad one. Factors such as subject tiredness, boredom, hunger and inattention can also occur. These factors can be driven by the research participant or the experiment. The participant may have stayed up late the night before an experiment, causing tiredness; the participant may be thinking about an upcoming coursework deadline or exam, causing inattention; and so forth. Such participant-led factors can be difficult to control, reducing the internal validity of an experiment. However, sometimes these factors (i.e., tiredness, boredom, hunger, inattention, etc.) are the result of the experiment.

Longer-term changes and their effects
Other maturation effects can result from longer term changes, such as getting older, becoming better educated, become more affluent, and so forth. However, even within experiments lasting less than a year, and perhaps even just a few months, it is possible for these factors to affect your findings. For example, people can get a new job with a relatively significant pay rise, or they may come into some inheritance money. They may start taking some form of further education, whether within the classroom, at home, or in work. At the same time, getting older can be an issue. Indeed, experiments that focus on people that are elderly, as well as those that involve young children have the potential to suffer from maturation effects because small changes in age can have a particularly marked impact on a range of physical, social, behavioural, and psychological factors. For example, as people become elderly, there can be a more rapid deterioration in certain physical characteristics such as vision, hearing, taste, and even memory. This may negatively impact their performance during an experiment. Amongst young children, there is a greater propensity for learning to take place (acquiring new knowledge and skills), as well as becoming stronger, stronger, and tasting in a short space of time. Such maturation effects, in addition to (or rather than) the treatment condition, may change the performance of participants in the post-test relative to the pre-test.

The question arises: How confident are you that the observed changes in the dependent variable are due to the treatment (i.e., intervention) and not maturation? In principle, such confidence will decrease as the experiment goes on. However, it is not as simple as saying that the longer an experiment, the greater the potential maturation effect. You need to look at the nature of your research, and examine whether maturation is likely to be a problem.

Testing effects and internal validity

Testing effects, also known as order effects, only occur in experimental and quasi-experimental research designs that have more than one stage; that is, research designs that involve a pre-test and a post-test. In such circumstances, the fact that the person taking part in the research is tested more than once can influence their behaviour/scores in the post-test, which confounds the results; that is, the differences in scores on the dependent variable between the groups being studied may be due to testing effects rather than the independent variable. Some of the reasons why testing effects occur include learning effects (practice or carry-over effects) and experimental fatigue. Each is discussed in turn:

Testing effects are not a problem in all studies. For example, as a "general rule of thumb", testing effects are less likely to be a threat to internal validity where there has been a large time period between the pre-test and post-test compared with experiments having a short interval between tests. You need to ask yourself: To what extent are learning effects a problem for the post-test in my experiment?

Instrumentation and internal validity

Instrumentation can be a threat to internal validity because it can result in instrumental bias (or instrumental decay). Such instrumental bias takes place when the measuring instrument (e.g., a measuring device, a survey, interviews/participant observation) that is used in a study changes over time. Instrumentation becomes a threat to internal validity when it reduces the confidence that the changes (differences) in the scores on the dependent variable may be due to instrumentation and not the treatments (i.e., the independent variable). It sometimes helps to think about instrumental bias arising either because of the use of a physical measuring device or the actions of the researcher. Each is discussed in turn:

Instrumentation is more likely to become an issue over time since there is greater potential for instrumental decay to occur.

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