Despite being called history effects, the events that happen in the environment that change the conditions of a study do not only occur in the past. These events can occur prior to the study taking place and during the study. Each is discussed in turn:
Events that occur prior to the study taking place
Irrespective of the type of quantitative (or mixed methods) research design that you use, there are a wide range of events that can occur prior to a study taking place that can become a threat to internal validity. These events are likely to have the greatest impact on the pre-test scores in an experiment, but if particularly severe, could also carry through to affect the post-test scores (although this is far less likely). Take the following example:
Study #1
The impact of exercise (i.e., fitness level) on how well people sleep (i.e., sleep quality)
NOTE: For the purposes of this example, let's imagine that the sample of people investigated were students living in halls of residence.
Event: A student burns some toast after a drunken night out, which sets off the fire alarm in the halls of residence in the middle of the night. The fire service are called out, there are loud sirens going off, all the students have to go outside, and it takes 2 hours before the students can go back into the build to return to sleep. Amongst those students living in the halls of residence that night are the participants taking part in a study investigating the impact of exercise on how well people sleep (i.e., their sleep quality). The pre-test for the study starts the next morning.
The experiment: The students taking place in the study arrive at the sports science labs in the morning to complete their first exercise test to show their level of fitness, and complete a questionnaire about their level of sleep quality. Participants are divided into two groups: (a) a control group that receives no intervention, meaning that the participants simply carry on their normal lives until the post-test measurement is taken; and (b) a treatment group that receives an intervention consisting of 6 weeks of personal training to help participants improve their fitness levels. The results from these two measurement procedures (i.e., the exercise test and sleep questionnaire) provide the data for the pre-test of the experiment.
History effects: Since the participants suffered from a lack of sleep the night before, including an interruption to their sleep patterns, due to the fire alarm, there is the potential for exercise/fitness scores (i.e., the independent variable) and the sleep quality scores (i.e., the dependent variable) to be lower than they would be normally. Therefore, when the post-test is conducted, and the students complete their second exercise test and complete their second sleep quality questionnaire, the difference between the two scores (i.e., the pre-test and post-test scores) are likely to be greater than they would be normally. Let's imagine that when comparing the difference between the pre-test and post-test scores, we were able to conclude that an increase in exercise improved sleep quality, we cannot be sure that this result was due to the increase in exercise and not the fact that the pre-test scores were lower than normal due to the fire alarm, which left participants more tired and physically fatigued that usual. This event, which occurred prior to the study taking place, acted as a history effect that threatened the internal validity of the study.
Events that occur during the study
Events may also occur during the study; that is, between the pre-test and the post-test, which result in a change in the post-test scores on the dependent variable compared to what they would have been normally if no event had taken place. Note that unlike events that occur prior to the study taking place, which largely affect the pre-test scores on the dependent variable (although sometimes the post-test scores), events that take place during the study only affect the post-test scores. Take the following example:
Study #2:
The impact of teaching method (i.e., lectures, or lectures and seminars) on exam performance
The experiment: We want to examine how two different teaching methods (i.e., the independent variable) affect the exam performance (i.e., the dependent variable) of university students. More specifically, we want to know if the addition of a seminar class to traditional lecturing improves exam performance, and if so, by how much. This is important because the university only has a limited budget, so it would not want to add seminar classes to lectures if students' exam performance was not significantly improved as a result. The course in question is Research Methods 101.
Students took an exam at the beginning of the course (i.e., the pre-test) to determine their general aptitude for the subject matter (i.e., their natural ability in Research Methods). This was done to ensure that the two groups being investigated (i.e., the control group and treatment group) were more or less equal in terms of natural ability. Each group consisted of 50 students. For the next 12 weeks (i.e., the duration of the course), the control group were given the "normal" teaching method, which consisted of two 1-hour long lectures each week. During this same period, the treatment group were given the same two 1-hour lectures each week, but also attended one 1-hour seminar. At the end of the 12 weeks, the students from the control group and the treatment group would be given the same Research Methods 101 exam (i.e., the post-test). The goal of the experiment was to compare the differences in the scores on the dependent variable (i.e., exam performance) between the two groups (i.e., the control and treatment groups). On exam day, the two groups took their exam in different rooms (i.e., all the control group students were in one room, whilst all the treatment group students were in a different room).
Event: The two groups of students (i.e., the treatment and control group) are about to take their exam. Since its summer, it is very hot outside, but the exam rooms are normally air-conditioned. The air conditioning keeps the room at a temperature that research has shown is more or less "optimal" for students to concentrate. However, 30 minutes into the 2 hour exam, the air conditioning fails in the room where the control group are taking their exam (i.e., the control group that received the lectures only). Within a few minutes, the temperature in the room increases rapidly, 10oC (i.e., 18oF) above the recommended "optimal" temperature. Students in the control group complain about the heat. The air conditioning is not fixed before the end of the exam.
History effects: When the pre- and post-test scores of the control group (i.e., lectures only) and treatment group (i.e., lectures and seminars) are compared, the results suggest that students who received lectures and seminars (i.e., the treatment group) outperformed the students who only received lectures (i.e., the control group) by an average (i.e., mean) of 6.3% (out of 100%). Therefore, we may conclude that there is a relationship between teaching method and exam performance; at least in the Research Methods 101 course. However, the question arises: Should the university start adding seminar classes to lectures? Let's assume for the moment that an increase of 6.3% justifies the financial commitment of adding seminar classes to lectures; we still have a problem trusting our results. After all, did the control group perform worse than the treatment group in their exams because they had an inferior teaching method, or was their poorer performance the result of a history effect, namely the failure of the air conditioning in the exam room during the post-test. This may have distorted the performance of the control group not only during the post-test, but also when comparing the gains in performance between the treatment and control groups from the pre-test. Such a history effect would be a threat to the internal validity of the study.
The length of a study
In principle, the longer a study takes place, the more likely that history effects may become a threat to internal validity. This is based on the assumption that the longer a study last, the more likely an unpredictable event may take place that threatens the internal validity of your study.
The magnitude of history effects
When we talk about the magnitude of history effects, we are interested in how critical an event is; that is, how likely an event is to change the outcome of your study.
In Study #1, mentioned above, the fire alarm was a threat to internal validity because it affected the sleep patterns, and arguably, the quality of sleep that students received before taking part the next day in an experiment on sleep quality. In other words, the event (i.e., the fire alarm in the middle of the night) was critical / very likely to change the outcome of the study (i.e., change the outcome of the pre-test, where students levels of tiredness were recorded). The same event (i.e., the fire alarm) could be considered critical in other experiments that were not about sleep; for example, studies where the pre-test involved (a) students taking an exam, (b) performing memory tests, (c) taking part in a sports competition, or (d) some other pre-test that could be influenced by a lack of quality sleep. However, if the study was unlikely to be affected by sleep quality (e.g., studies on (a) attitudes towards African American prejudice, (b) factors that make Apple a popular brand, etc.), then it is probably unnecessary to mention such an event (i.e., the fire alarm) as a possible history effect; that is, as a possible threat to internal validity. In other words, the event was not critical / not likely to change the outcome of your study.
Events that lead to history effects are often unpredictable, which makes them very difficult to plan for. When an event does take place, it can still be difficult to reduce the threat to internal validity that such an event creates. The important point is to understand the impact of the history effect and its potential magnitude, and explain what effect it may have had on your results.