Auditory verbal hallucinations (AVHs) are heterogeneous regarding phenomenology and etiology. This has led to the proposal of AVHs subtypes. Distinguishing AVHs subtypes can inform AVHs neurocognitive models and also have implications for clinical practice. A scarcely studied source of heterogeneity relates to the AVHs linguistic characteristics. Therefore, in this study we investigate whether linguistic features distinguish AVHs subtypes, and whether linguistic AVH-subtypes are associated with phenomenology and voice-hearers’ clinical status.
Twenty-one clinical and nineteen non-clinical voice-hearers participated in this study. Participants were instructed to repeat verbatim their AVHs just after experiencing them. AVH-repetitions were audio-recorded and transcribed. AVHs phenomenology was assessed using the Auditory Hallucinations Rating Scale of the Psychotic Symptom Rating Scales. Hierarchical clustering analyses without a priori group dichotomization were performed using quantitative measures of sixteen linguistic features to distinguish sets of AVHs.
A two-AVHs-cluster solution best partitioned the data. AVHs-clusters significantly differed in linguistic features (p < .001); AVHs phenomenology (p < .001); and distribution of clinical voice-hearers (p < .001). The "expanded-AVHs" cluster was characterized by more determiners, more prepositions, longer utterances (all p < .01), and mainly contained non-clinical voice-hearers. The "compact-AVHs" cluster had fewer determiners and prepositions, shorter utterances (all p < .01), more negative content, higher degree of negativity (both p < .05), and predominantly came from clinical voice-hearers.
Two voice-speech clusters were recognized, differing in syntactic-grammatical complexity and negative phenomenology. Our results suggest clinical voice-hearers often hear negative, “compact-voices”, understandable under Broca’s right hemisphere homologue and memory-based mechanisms. Conversely, non-clinical voice-hearers experience “expanded-voices”, better accounted by inner speech AVHs models.

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