With a little help from familiar interlocutors: real-world language use in young and older adults

Aging Ment Health. 2021 Dec;25(12):2310-2319. doi: 10.1080/13607863.2020.1822288. Epub 2020 Sep 26.

Abstract

Objectives: Functional psychologists are concerned with the performance of cognitive activities in the real world in relation to cognitive changes in older age. Conversational contexts may mitigate the influence of cognitive aging on the cognitive activity of language production. This study examined effects of familiarity with interlocutors, as a context, on language production in the real world.

Method: We collected speech samples using iPhones, where an audio recording app (i.e. Electronically Activated Recorder [EAR]) was installed. Over 31,300 brief audio files (30-second long) were randomly collected across four days from 61 young and 48 healthy older adults in Switzerland. We transcribed the audio files that included participants' speech and manually coded for familiar interlocutors (i.e. significant other, friends, family members) and strangers. We computed scores of vocabulary richness and grammatical complexity from the transcripts using computational linguistics techniques.

Results: Bayesian multilevel analyses showed that participants used richer vocabulary and more complex grammar when talking with familiar interlocutors than with strangers. Young adults used more diverse vocabulary than older adults and the age effects remained stable across contexts. Furthermore, older adults produced equally complex grammar as young adults did with the significant other, but simpler grammar than young adults with friends and family members.

Conclusion: Familiarity with interlocutors is a promising contextual factor for research on aging and language complexity in the real world. Results were discussed in the context of cognitive aging.

Keywords: Electronically Activated Recorder (EAR); Grammatical complexity; cognitive aging; social contexts; vocabulary richness.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Aging
  • Bayes Theorem
  • Humans
  • Language*
  • Linguistics
  • Vocabulary*