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172M. Blomgren, A.M. Goberman / Journal of Communication Disorders 41 (2008) 159–178At least two possible explanations exist that might describe the absence of a ratecomplexity effect for the severe stuttering speakers in the current study. First, manystuttering speakers tend to be more fluent when speaking in ways unique to them, such aswhen assuming a dialect, or imitating another person’s speech (Bloodstein, 1995). For themore severe stuttering speakers, the variable rate tasks in the present study may haveprovided a unique and novel manner of speaking and, effectively nullified the complexityeffect. For the mild stuttering speakers, the novelty of attempting to speak at variable ratesmay not have been great enough to ‘‘overcome’’ the inherent increase in task complexity.In effect, the severe stuttering speakers might have been more susceptible to the proposednovelty effect than the milder stuttering speakers.A second explanation for the different performances observed between the mild andsevere stuttering speakers might relate to the treatment histories of the subjects. Arequirement for participation was that the stuttering speakers must not have received anystuttering therapy within the past year. However, 9 of the 11 severe stuttering speakersreported having some form of speech therapy in the past, while only 4 of the 11 mildstuttering speakers reported receiving any form of treatment. By including slow speech asone of the three rate targets in the variable rate tasks, some speakers may have reverted topreviously learned prolonged speech techniques. Previous therapy may have served tofacilitate fluency during recitation of the slow rate tokens, which, in turn, may haveimproved fluency on the habitual and fast rate tokens as well. The overall result of thistreatment effect may have been strong enough to nullify the complexity of the two‘‘temporally complex’’ (variable) rate tasks. In order to address this potential confound insubsequent studies utilizing this methodology, it may be beneficial to have participantsvary their rate only between habitual and fast levels.4.2. Future researchAreas that could possibly be better controlled in future research studies in this areapertain to the specific tasks and tokens chosen for analysis in the current study. In thepresent study, one of the complexity dimensions consisted of habitual rates versus unstablerates (i.e., lists of tokens produced at randomly varying slow, habitual, and fast rates), andthe other dimension consisted of single words versus phrases. The unstable rate task hadinter-trial variability by nature of task design and the phrase length utterances had intertrialvariability by nature of the fact that longer utterances are assumed to have more token totoken variability (e.g., varying intonation, stress, timing demands, etc.) compared to singlewords (Kleinow & Smith, 2000). Nevertheless, while there was intertrial variability in bothtasks, there was arguably less inter-trial variability between the individual phrases on thephrase length tasks compared to the words and phrases on unstable rate tasks. To betterbalance the levels of inter-trial variability across tasks, future research could increase intertrialvariability on the utterance length tasks by having participants produce lists ofrandomly ordered words and phrases.Another consideration may relate to the possibility that people utilize differentlinguistic and/or motor strategies, or different neurological pathways, when readingphrases versus single words. Reading phrases assumes some level of intrinsic syntacticprocessing while reading single words, presented in isolation, would appear to be a
M. Blomgren, A.M. Goberman / Journal of Communication Disorders 41 (2008) 159–178 173relatively syntax-free process. Similar to the work of Ratner and Sih (1987) and Kleinowand Smith (2000), future studies in this areas may control for this possible processingdifference by comparing phrases of varying lengths and complexities, rather thancomparing single words to phrases.4.3. Clinical implicationsResults from the present study suggest that fluency breakdown can be plotted along aspatiotemporal continuum of increasingly difficult speech task performance. Magill (2004)indicated that a 2 2 performance matrix could be applied to assessment of motorperformance and to aid in structuring motor skill learning. In this context, motorperformance relates to the observable behavior produced during any motor task. Incontrast, motor learning is described as a modification in behavior that results from practiceor experience (Sage, 1984). Fitts (1964) suggested that the basic issue in describing motorskill learning has to do with detailing how spatial and temporal organization develops. Byutilizing the performance matrix as a stuttering assessment strategy, multidimensionalseverity information may be obtained. While the mean group data reported in this papersuggests levels of both length of utterance and speech rate stability played similar roles inmodulating stuttering frequency, this may not be the case for all individual stutteringspeakers. For instance, as the stuttering severity analyses in this study appears to indicate,stuttering may be modulated more by decreases in temporal stability in some stutteringspeakers and more by increased length of utterance demands in other speakers. In thisrespect, the 2 2 performance matrix may be a useful clinical assessment tool indisentangling the motor dynamics of some stuttering speakers.Magill (2004) and Hautala and Conn (1993) have revealed that a 2 2 skill matrix isuseful in examining gross motor skill learning. The results from this study indicated that a2 2 skill matrix might also be beneficial in examining fluency skill development tasks.Although skill learning was not directly evaluated in this study, it seems plausible that the2 2 format could have therapeutic implications. Specifically, the 2 2 matrix might beused to structure a learning hierarchy that fosters improved fluency success in treatment.Application of some form of closed to open continuum of speech motor performance to theclinical setting has been the backbone of behaviorally based stuttering treatments for over100 years (e.g., Blomgren, 2005; Boberg & Kully, 1985; Guttmann, 1893; Ryan, 1979;Shine, 1980; Webster, 1982). However, a formalized multidimensional assessment couldbe used to customize the therapy routine based on the unique motor performancecharacteristics of individual speakers. For example, if a particular stuttering speakerexhibited decreasing fluency primarily as a function of speaking rate complexity, thentherapy could be programmed to address this speech dimension. If another stutteringspeaker exhibited little stuttering in the production of single words, then instatement offluency facilitating techniques might begin directly with longer utterances for thatindividual, bypassing single word practice altogether. Overall, stuttering treatment timecould potentially be decreased and made more relevant for clients. While the effectivenessof utilizing multidimensional performance matrices to improve treatment has not yet beenexamined, the present results provide support for the functionality of evaluating stutteringbehavior using a speech motor performance strategy.
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