PURPOSE: The purpose of this study was to explore metrical aspects of phonological encoding (i.e., stress and syllable boundary assignment) in adults who do and do not stutter (AWS and AWNS, respectively). METHOD: Participants monitored nonwords for target sounds during silent phoneme monitoring tasks across two distinct experiments. For Experiment 1, the 22 participants (11 AWNS, 11 AWS) silently monitored target phonemes in nonwords with initial stress. For Experiment 2, an additional cohort of 22 participants (11 AWNS, 11 AWS) silently monitored phonemes in nonwords with noninitial stress. RESULTS: In Experiment 1, AWNS and AWS silently monitored target phonemes in initial stress stimuli with similar speed and accuracy. In Experiment 2, AWS demonstrated a within-group effect that was not present for AWNS. They required additional time when monitoring phonemes immediately following syllable boundary assignment in stimuli with noninitial stress. There was also a between-groups effect, with AWS exhibiting significantly greater errors identifying phonemes in nonwords with noninitial stress than AWNS. CONCLUSIONS: Findings suggest metrical properties may affect the time course of phonological encoding in AWS in a manner distinct from AWNS. Specifically, in the absence of initial stress, metrical encoding of the syllable boundary may delay speech planning in AWS and contribute to breakdowns in fluent speech production.
PURPOSE: The purpose of this study was to explore metrical aspects of phonological encoding (i.e., stress and syllable boundary assignment) in adults who do and do not stutter (AWS and AWNS, respectively). METHOD:Participants monitored nonwords for target sounds during silent phoneme monitoring tasks across two distinct experiments. For Experiment 1, the 22 participants (11 AWNS, 11 AWS) silently monitored target phonemes in nonwords with initial stress. For Experiment 2, an additional cohort of 22 participants (11 AWNS, 11 AWS) silently monitored phonemes in nonwords with noninitial stress. RESULTS: In Experiment 1, AWNS and AWS silently monitored target phonemes in initial stress stimuli with similar speed and accuracy. In Experiment 2, AWS demonstrated a within-group effect that was not present for AWNS. They required additional time when monitoring phonemes immediately following syllable boundary assignment in stimuli with noninitial stress. There was also a between-groups effect, with AWS exhibiting significantly greater errors identifying phonemes in nonwords with noninitial stress than AWNS. CONCLUSIONS: Findings suggest metrical properties may affect the time course of phonological encoding in AWS in a manner distinct from AWNS. Specifically, in the absence of initial stress, metrical encoding of the syllable boundary may delay speech planning in AWS and contribute to breakdowns in fluent speech production.