Standardization of the MultiLevel discourse Analysis (MLA) and identification of data-driven age bands for research on language in healthy aging

Examining specific linguistic aspects in isolation, traditional language tests fail to capture the dynamic interactions that support discourse production abilities. The accurate assessment of discourse production is therefore crucial for identifying language difficulties and procedures of discourse analysis have emerged as a valid methodological solution. Despite this, heterogeneity in discourse measures limits comparability across studies, and the lack of normative data across the adult lifespan complicates the differentiation between healthy and pathological aging. The present study addresses this issue by providing the first standardization of linguistic measures extracted using a MultiLevel procedure of discourse Analysis (MLA). Narrative samples from 717 healthy Italian-speaking adults (aged 20 - 94) were elicited through a picture description task using two single images and three vignettes. Speech samples were transcribed and analyzed using a semi-automatic pipeline. Normative data, adjusted for age and education, and data-driven age bands were calculated for linguistic measures assessing productivity, lexical difficulties, grammatical construction, macrolinguistic difficulties, and lexical informativeness. Results provide standardized norms across multiple linguistic measures and reveal distinct age-related shifts in performance. Together, these findings offer the most comprehensive adult lifespan framework to date for narrative discourse production and highlight the importance of data-driven age bands for research and clinical assessment in healthy aging. Furthermore, they show that healthy aging disproportionately affects higher-order integrative discourse mechanisms rather than core lexical and morphosyntactic encoding processes.