When data is collected at two or more points in time during an experiment, there will naturally be people who begin a study but then find that they cannot continue. Dropping out of a study can occur for a wide variety of reasons and can occur in both experimental and longitudinal designs. It is important to note that selective attrition does not mean that certain people are more likely to quit a study. Instead, it simply implies that there is a tendency for people to quit an experiment for a variety of reasons.
Causes of Attrition
The main reasons why people drop out of research studies are sometimes referred to as the four M’s:
Attrition Bias
While selective attrition doesn’t imply that certain types of participants are more likely to drop out of a study, attrition can result in a research bias when the people who prematurely exit a study are fundamentally different from those who remain in the study. When this happens, researchers end up with a final study group that is quite different from the original sample. It is important to note, however, that if there are no systematic differences between those who complete a study and those who drop out, then the results will not be impacted by the attrition bias.
Threats to Validity
When certain groups of individuals drop out of a study, attrition can also affect the validity of the results. Since the final group of participants no longer accurately reflects the original representative sample, the results cannot be generalized to a larger population. Imagine that researchers are doing a longitudinal study on how cardio exercise impacts cognitive functioning as people age. The researchers begin their study by collecting data from a representative sample of middle-aged adults between the ages of 40 and 45. Over the next few decades, the researchers continue to periodically collect data on the aerobic fitness and cognitive functioning of their original sample. Selective attrition will happen naturally with a study that occurs over such a long period of time. Some participants will move, some will lose interest, some with suffer from illness, and some will even pass away. But what if certain groups of individuals become more prone to selective attrition? Suppose that widowers tend to drop out of the study more frequently than those who have a surviving spouse. Because the final sample lacks data from this group, it may no longer reflect the tendencies that exist in the overall population at large, threatening the external validity of the study and making it difficult to generalize the results to the entire populace. Internal validity can also be a problem with there are different attrition rates between the control groups and the experimental groups. If researchers were conducting an experiment on treatment for anxiety, for example, the results of the study might be biased if people in the experimental group dropped out at a higher rate than those in the control group. Consider, for example, if this attrition rate is due to anxiety that prevents participants from completing the study. Since the experimental group includes a higher proportion of individuals who benefited from the treatment, the results will be biased and suggest that the treatment was perhaps more effective than it really was.
A Word From Verywell
Some attrition is only natural in psychology studies. Very high levels of attrition, however, can hurt the validity of the results. Research has also shown that selective attrition can also impact research results. In one study, for example, researchers found that attrition led to overestimates of the effects of treatment.
