Volunteer Effect

The volunteer effect is a form of selection bias, sometimes referred to as self-selection or volunteer bias. This phenomenon is based on the idea that individuals who volunteer to participate in epidemiological studies are different in some way from the target population that they have originated from. The result of this effect is that the resulting measure between exposure and disease is distorted.

The selection of the study population is a critical part of any epidemiological study. One of the methods of selecting individuals is to recruit volunteer participants from the target population. However, the main risk in this method is that this subset of the population differs in some way from the general population. It has been suggested that individuals who volunteer to participate in epidemiological studies are often healthier than the general population, and it is their interest in health that motivates them to participate in such studies. As a result, healthier individuals who may be more knowledgeable about health in general will be overrepresented in the study population. A consequence of this is that the measure of effect could be distorted, and the results cannot be generalized to the larger population. An example of this was seen in the Iowa Women's Health Study that investigated the relationship between mortality and cancer in women. When participants and [Page 1090]nonparticipants were compared, it was found that there was a higher proportion of smokers in the nonparticipant group. This group also had a greater occurrence of smoking-related cancers. A similar situation is seen in studies examining treatment interventions and alcoholism. Often, individuals who volunteer for these studies have a different baseline level of alcoholism severity than those who do not volunteer.

Participants who volunteer may not actually be healthier than the target population, but it could be that they are interested in a study because they have a family history of the disease in question and are actually more at risk of the disease than the general population. This is another form of the volunteer effect. For example, a study investigating a potential intervention on the subsequent development of breast cancer that recruits women may actually find little effect simply because the volunteer participants are at a higher risk of developing breast cancer anyway.

Individuals who volunteer to participate in studies may also differ from the general population by education, gender, socioeconomic status, and other demographic characteristics. The result of this is that it can limit the generalizability of results to the general population. In situations where the possibility of volunteer bias is a concern, random sampling methods can be used to recruit study participants and therefore minimize the volunteer effect.