The WHISPER (Widespread Hearing Impairment Screening and PrEvention of Risk) platform was recently developed for screening for hearing loss (HL) and cognitive decline in adults. It includes a battery of tests (a risk factors (RF) questionnaire, a language-independent speech-in-noise test, and cognitive tests) and provides a pass/fail outcome based on the analysis of several features. Earlier studies demonstrated high accuracy of the speech-in-noise test for predicting HL in 350 participants. In this study, preliminary results from the RF questionnaire (137 participants) and from the visual digit span test (DST) (78 participants) are presented. Despite the relatively small sample size, these findings indicate that the RF and DST may provide additional features that could be useful to characterize the overall individual profile, providing additional knowledge related to short-term memory performance and overall risk of HL and cognitive decline. Future research is needed to expand number of subjects tested, number of features analyzed, and the range of algorithms (including supervised and unsupervised machine learning) used to identify novel measures able to predict the individual hearing and cognitive abilities, also including components related to the individual risk.