If you're going to listen to music while you read, choose instrumentals

A new meta-analysis of 65 studies that looked at the effect of background noise on reading comprehension found that all auditory distractions have some detrimental effect but "intelligible speech" and music with lyrics had the biggest negative impact. The researchers also found that the negative effect background noise has on reading comprehension is about the same for children and adults. The take-away?  If you're going to listen to music while you work or study, choose The Ventures rather than The Beach Boys. The study is called Auditory Distraction During Reading: A Bayesian Meta-Analysis of a Continuing Controversy and can be found at 13 Perspectives on Psychological Science 567 (June 2018) and available here. From the abstract:

Everyday reading occurs in different settings, such as on the train to work, in a busy cafeteria, or at home while listening to music. In these situations, readers are exposed to external auditory stimulation from nearby noise, speech, or music that may distract them from their task and reduce their comprehension. Although many studies have investigated auditory-distraction effects during reading, the results have proved to be inconsistent and sometimes even contradictory. In addition, the broader theoretical implications of the findings have not always been explicitly considered. We report a Bayesian meta-analysis of 65 studies on auditory-distraction effects during reading and use metaregression models to test predictions derived from existing theories. The results showed that background noise, speech, and music all have a small but reliably detrimental effect on reading performance. The degree of disruption in reading comprehension did not generally differ between adults and children. Intelligible speech and lyrical music resulted in the biggest distraction. Although this last result is consistent with theories of semantic distraction, there was also reliable distraction by noise. It is argued that new theoretical models are needed that can account for distraction by both background speech and noise.

(jbl).