Extraneous Variables in Sleep Study

Extraneous variables are unwanted variables that can impact the dependent variable in an experiment. They are a nuisance variable in research and can make it difficult to determine if the changes in the dependent variable are due to the manipulation of the independent variable or caused by the extraneous variable. If an extraneous variable is not controlled, it becomes a confounding variable.

One extraneous variable that could have affected the results of a sleep study is the delay between waking and responding to the questionnaire. For instance, if a participant's phone battery ran out, or they took a shower before completing the questionnaire, they may feel more awake and, as a result, pay greater attention to the sleep data provided by the sleep tracker. This could then increase the impact of the independent variable (the sleep tracker data) on the dependent variable (self-reported sleep quality).

It would have been important to control this extraneous variable because it could have obscured the true relationship between sleep tracker data and self-reported sleep quality. If participants who had more time to wake up were also more likely to report better sleep quality, it would be difficult to determine if this was due to the sleep tracker data itself or simply because they were more alert and attentive when completing the questionnaire.

This extraneous variable could have been controlled in this study by asking students to keep their phones on charge overnight and to complete the questionnaire immediately upon waking, before getting up, or engaging in other activities. This would ensure that all participants had the same amount of time to wake up and that their responses were not influenced by other factors such as alertness or mood.

Additional Extraneous Variable and Control

Another extraneous variable that could have confounded the results is the consumption of alcohol or caffeine prior to sleep. These substances could affect the quality of sleep regardless of the data from the sleep tracker. For example, alcohol consumption might initially induce sleep but can then lead to more disrupted sleep later in the night. This could lead to participants feeling worse in the morning, regardless of the sleep tracker data, causing them to provide a lower rating of their sleep quality, which would decrease the validity of the results.

To control for this extraneous variable, researchers could instruct participants to abstain from consuming any stimulants or depressants, including alcohol and caffeine, in the evenings leading up to and during the study. This would help ensure that participants' sleep quality is not unduly influenced by these substances, allowing for a more accurate assessment of the relationship between sleep tracker data and perceived sleep quality.