NEUROSCIENCE PODCASTS: A STUDY ON THE QUALITY AND RELIABILITY OF SCIENTIFIC COMMUNICATION CHANNELS
DOI:
https://doi.org/10.16891/2317-434X.v14.e1.a2026.id2934Keywords:
Aggregators, ; Episode analysis, Content evaluationAbstract
Neuroscience podcasts are emerging as a promising tool for Scientific Dissemination (SD). In this context, this study aimed to map and analyze the reliability and quality of SD channels in neuroscience. Among 324 channels identified on platforms such as Spotify and YouTube Music, only 13, comprising 290 episodes, were classified as SD channels. Of these, 30 episodes were analyzed through stratified sampling, categorized using a taxonomic model, and evaluated using the modified DISCERN tool and the Global Quality Index (GQI). Predominant topics included neuroscience, mental health, and emotions. Most channels demonstrated satisfactory performance, with DISCERN scores > 3 in 76.93% of cases and GQI scores 3 in 92.31%. An inverse relationship was also observed between episode duration and channel reliability (p=0.563). These findings highlight the relevance of podcasts as an SD tool, despite persistent limitations in quality and reliability.