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Available online at www.sciencedirect.comJournal of Communication Disorders 41 (2008) 159–178Revisiting speech rate and utterance lengthmanipulations in stuttering speakersMichael Blomgren a, *, Alexander M. Goberman ba Department of Communication Sciences and Disorders, The University of Utah, 390 S. 1530 E.,Rm 1201, Salt Lake City, UT 84112-0252, United Statesb Department of Communication Disorders, Bowling Green State University, Bowling Green, OH, United StatesReceived 1 December 2006; received in revised form 2 October 2007; accepted 7 October 2007AbstractThe goal of this study was to evaluate stuttering frequency across a multidimensional (2 2)hierarchy of speech performance tasks. Specifically, this study examined the interaction betweenchanges in length of utterance and levels of speech rate stability. Forty-four adult male speakersparticipated in the study (22 stuttering speakers and 22 non-stuttering speakers). Participants wereaudio and video recorded while producing a spontaneous speech task and four different experimentalspeaking tasks. The four experimental speaking tasks involved reading a list of 45 words and a list 45phrases two times each. One reading of each list involved speaking at a steady habitual rate (habitualrate tasks) and another reading involved producing each list at a variable speaking rate (variable ratetasks). For the variable rate tasks, participants were directed to produce words or phrases at randomlyordered slow, habitual, and fast rates. The stuttering speakers exhibited significantly more stutteringon the variable rate tasks than on the habitual rate tasks. In addition, the stuttering speakers exhibitedsignificantly more stuttering on the first word of the phrase length tasks compared to the single wordtasks. Overall, the results indicated that varying levels of both utterance length and temporalcomplexity function to modulate stuttering frequency in adult stuttering speakers. Discussion focuseson issues of speech performance according to stuttering severity and possible clinical implications.Learning outcomes: The reader will learn about and be able to: (1) describe the mediating effectsof length of utterance and speech rate on the frequency of stuttering in stuttering speakers; (2)understand the rationale behind multidimensional skill performance matrices; and (3) describepossible applications of motor skill performance matrices to stuttering therapy.# 2007 Elsevier Inc. All rights reserved.* Corresponding author. Tel.: +1 801 585 6152; fax: +1 801 581 7955.E-mail address: michael.blomgren@health.utah.edu (M. Blomgren).0021-9924/$ – see front matter # 2007 Elsevier Inc. All rights reserved.doi:10.1016/j.jcomdis.2007.10.001

160M. Blomgren, A.M. Goberman / Journal of Communication Disorders 41 (2008) 159–1781. IntroductionThe history of stuttering research is replete with examinations of the effects of variousmotor and linguistic complexity manipulations on the speech of people who stutter. Two ofthe most widely examined factors thought to influence frequency of stuttering are speechrate (e.g., Andrews & Harris, 1964; Boberg & Kully, 1985; Goldiamond, 1965; Guttmann,1893; Helps & Dalton, 1979; Howie & Woods, 1982; Ingham, 1975; Johnson & Rosen,1937; Smith & Kleinow, 2000; Starkweather, 1987; Vanryckeghem, Glessing, Brutten, &McAlindon, 1999) and utterance length (e.g., Brown & Moren, 1942; Brundage & Ratner,1989; Kleinow & Smith, 2000; Logan & Conture, 1995; Riley & Ingham, 2000; Silverman,1972; Soderberg, 1966; Tornick & Bloodstein, 1976; Wells, 1979; Wingate, 1967). Takentogether, the findings of these studies strongly support the notion that increased motor and/or linguistic speaking task complexity result in decreased speech fluency for stutteringspeakers. However, the interaction between various types of different speaking taskcomplexities are not well understood (Howell, Au-Yeung, & Pilgrim, 1999; Max &Gracco, 2005). The purpose of the present study was to examine the interaction (andrelative strengths) of a motor variable (speech rate stability) and a linguistic variable(length of utterance) on stuttering frequency.Considering the temporal aspects of speech production, there is general agreement thatif a stuttering speaker reduces his/her speech rate they will also reduce their stutteringfrequency (e.g., Andrews & Harris, 1964; Boberg, 1976; Boberg & Kully, 1985; Johnson &Rosen, 1937; Onslow, Costa, Andrews, Harrison, & Packman, 1996; Runyan & Runyan,1986; Webster, 1980). It has also traditionally been reported that increased speech rateusually results in increased stuttering (e.g., Bloodstein, 1944; Howell et al., 1999; Johnson& Rosen, 1937). For example, Kalinowski, Armson, Roland-Miezkowski, Stuart, andGracco (1993) reported that seven of their nine participants displayed increased stutteringduring speaking tasks involving a fast speaking rate compared to habitual rate tasks.However, Kalinowski, Armson, and Stuart (1995) later found no difference in stutteringfrequency between habitual and fast speaking rates, which led these researchers toconclude that increased speech rate does not determine stuttering frequency with the sameconsistency as does decreased speech rate. While it appears that the exact effect of changesin speaking rate on stuttering frequency may vary somewhat among stuttering speakers, itis generally accepted that changes in the temporal dynamics of speech do produce changesin stuttering frequency. These findings support suggestions that stuttering is, at least in part,a disorder of speech timing (Cooper & Allen, 1997; De Nil, Kroll, & Houle, 2001; Kent,1984; Van Riper, 1982).Extant research evaluating length of utterance has shown that stuttering is less likely tooccur on shorter utterances compared to longer utterances (e.g., Brown & Moren, 1942;Brundage & Ratner, 1989; Logan & Conture, 1995; Silverman, 1972; Soderberg, 1966;Wells, 1979; Wingate, 1967). For example, Tornick and Bloodstein (1976) found that lessstuttering occurred in the reading of short sentences (e.g., ‘‘She learned to swim.’’) whenthis sentence stood alone compared to when it was the initial part of a longer sentence (e.g.,‘‘She learned to swim in the clear water of the lake.’’). Logan and Conture (1995) have alsosupported the observation of less stuttering on short sentences in young children whostutter.

M. Blomgren, A.M. Goberman / Journal of Communication Disorders 41 (2008) 159–178 161Length of utterance may be considered a spatial variable in speech production as theamount of spatial planning (segmental as well as coarticulatory) required to produce aseries of phonetic targets increases from words to phrases to sentences. For example,production of a single CVC word such as ‘‘bat’’ requires advance spatial planning for threephonetic targets, while production of even a simple sentence such as ‘‘Susan picked up thebat’’ requires advance planning for approximately 16 phonetic targets (Perkell & Nelson,1982). Length of utterance may also be viewed as a linguistic variable, as longer utteranceswould typically be more syntactically complex than shorter ones. However, the influence oflength of utterance and syntactic complexity is not necessarily analogous. For instance,Ratner and Sih (1987) reported that fluency breakdown in both stuttering and nonstutteringchildren is more highly correlated with increases in syntactic complexity thanlength of utterance. Further, Kleinow and Smith (2000) reported that adult stutteringspeakers (during perceptually fluent speech) exhibited decreased speech motor stabilityduring production of more syntactically complex utterances but did not exhibit decreasedstability during simply longer utterances (controlled for syntactic complexity). While theeffects may at times be subtle, certain aspects of linguistic structure do appear to have clearmediating effects on stuttering frequency in both children and adults (Au-Yeung & Howell,1998; Brown, 1945; Wingate, 1988; Wolk, Blomgren, & Smith, 1998).As the realized motor sequelae of thought and language, speech is one of the mostcomplex movement sequences produced by humans. As such, it is practically impossible toexamine every single mediating variable. In order to examine complex movementsequences in non-speech motor routines, dynamic systems theories have been developed.The goal of dynamic systems theory is to use multidimensional models to understand thepatterns that arise from coordinated movement (Kelso, 1988). To form a multidimensionalmodel, the identification of relevant pattern variables in the complex system is crucial(Thelen, Kelso, & Fogel, 1987). Thelen (1988) states: ‘‘The first step toward a dynamicalmodel of any developmental phenomenon is understanding the behavior over time. Herewe face the nontrivial (and maybe even monumental) task of choosing the appropriatecollective variable: how best to capture the compression of the degrees of freedom.’’ (p.365). Therefore, in order to create a workable dynamical model of behavior, degrees offreedom must first be reduced.To properly reduce the degrees of freedom in an examination of speech production,relevant variables must first be chosen, and one method of identifying relevant variables isthrough examination of physiological and linguistic constraints (Kelso, 1995). Twofundamental constraints for fluent speech production are speech rate and length ofutterance (Howell et al., 1999; Kent & Read, 1992; Kleinow & Smith, 2000; Smith &Kleinow, 2000). Speech rate refers to the number of phonemes, syllables, or words per unitof time, while length of utterance refers to the number of phonemes, syllables, or wordsproduced in any particular utterance. Speech rate is temporally constrained because thereis a finite speed (both slow and fast) at which intelligible speech can reasonably beproduced, and length of utterance is constrained due to both respiratory demands (i.e.,breath groups) and to semantic/syntactic realities (e.g., the need for informationchunking).In summary, rate of speech and length of utterance may be thought of as the fundamentaltemporal/motor and spatial/linguistic variables in normal speech production, respectively.

162M. Blomgren, A.M. Goberman / Journal of Communication Disorders 41 (2008) 159–178As discussed, these same two variables also serve as modulating variables for frequency ofstuttering in stuttering speakers. However, the relative importance and possible interactionbetween these (and other) motor and linguistic variables is poorly understood in stutteringspeakers. One methodology to examine possible interactive effects of these variablescomes from the motor learning literature.Gentile (1987) and others (Hautala & Conn, 1993; Magill, 2004) have demonstratedthat temporal and spatial variables are relevant to the description of non-speech motortasks (e.g., walking, hitting a golf ball, or buttoning a jacket) and they have modeledthese variables using multidimensional skill performance matrices. Within these skillmatrices, the various skill categories (or tasks) place varying demands on the performer.These skills are often classified on a continuum varying from relatively simple torelatively complex tasks. Tasks conducted at the simple end of the continuum arereferred to as closed motor skills and skills conducted at the complex end of thecontinuum are referred to as open motor skills (Gentile, 1972; Poulton, 1957). Closedmotor skills occur in a stable task environment and tend to be serially ordered,temporally stable, and spatially stable. Conversely, open motor skills occur in a nonstableenvironment, where the temporal or spatial aspects of the task change during theperformance of the task. This inter-trial variability is often the defining characteristic ofopen motor skills.As rate of speech and length of utterance have both been shown to affect stutteringfrequency, it was hypothesized that a 2 2 speech performance matrix would allow for atwo-dimensional examination of speech fluency along a continuum of speech taskcomplexity. If specific tasks vary in terms of stability of speech rate and length of utterance,this can allow for an examination of the relative contributions of temporal/motor andspatial/linguistic parameters on speech motor control. A 2 2 speech performance matrixis shown in Fig. 1. The goal of this particular arrangement of speech production tasks is tocreate a hierarchy of performance complexity ranging from a relatively closed task (a seriesof single words spoken at a stable rate) to a relatively open task (a series of phrases spokenat varying rates of speech).Fig. 1. Illustration of 2 2 performance matrix applied to two speech variables: speech rate and length ofutterance. The matrix displays a progression from a relatively closed task (series of single words produced at asteady habitual rate) to a more open task (series of phrases produced with variable rates of speech). Note: 1: closedtask; 2 and 3: intermediate tasks; 4: open task.

M. Blomgren, A.M. Goberman / Journal of Communication Disorders 41 (2008) 159–178 163This is the second of a two-part series examining stuttering across 2 2performance matrices. An initial examination of 20 stuttering speakers found thatstuttering speakers produced increasing rates of stuttering as a function of increasingtask complexity along both spatial and temporal dimensions. These initial results werepublished as part of a paper discussing issues related to programming complexityin stuttering therapy (Blomgren, 2001). However, a number of issues may have limitedthe ability to draw conclusions from the initially published results. First, the taskpresentation order was not randomized across all participants, introducing a possibletask order effect. Second, non-stuttering control group data were not included.Third, the influence of stuttering severity on the results was not assessed. Therefore,the goals of the present study were to: (1) conduct a more controlled extension ofthe initial study on additional stuttering speakers; (2) add comparisons to a nonstutteringcontrol group; and (3) examine the effect of stuttering severity on taskperformance.In summary, the purpose of the present study was to assess the effects and theinteraction between two variables known to influence the frequency of stuttering instuttering speakers. Specifically, the present study examined the effect of both speechrate stability and length of utterance on stuttering frequency. The current goal is to createa multidimensional model of stuttering behavior utilizing a 2 2 performance matrix,along with determining the effects of stuttering severity on the present assessmentmodel. The effect of stuttering severity may be especially important, as mild and severestutterers have been shown to be differentially affected by rate change (Vanryckeghemet al., 1999).2. Methods2.1. ParticipantsForty-four adult males participated in this study. Twenty-two of the participantsstuttered and 22 were normally fluent speakers. All participants were native speakers ofAmerican English and were between 18 and 62 years of age (stuttering speakers: M = 34.0,S.D. = 13.0; non-stuttering speakers: M = 31.0, S.D. = 11.0). All participants reported andexhibited normal or corrected-normal vision, normal hearing, and normal language, voice,and speech articulation.In an attempt to minimize possible treatment effects, only participants who had notreceived formal stuttering therapy within the past year were included in the study.Formal therapy was defined as that provided by a speech-language pathologist with thegoal of reducing or altering stuttering behavior. Fourteen of the stuttering participantswere recruited from stuttering treatment programs. For those participants, participationoccurred prior to the initiation of therapy. The remaining eight stuttering participantswere recruited from stuttering support groups. The emphasis of the support groups wasto foster social interaction; specific fluency skill practice was not conducted. The nonstutteringcontrols were recruited from the faculty and student body at the University ofUtah.

164M. Blomgren, A.M. Goberman / Journal of Communication Disorders 41 (2008) 159–1782.2. Data collection and analysesEach participant was audio and video recorded with only one researcher and theparticipant present in the room. Participants were seated for all speaking tasks. For thestuttering participants, the audio and video signals were collected using either a tripodmountedVHS video camera (Panasonic AG-188) or a tripod-mounted digital camera(Canon Elura). For all of the non-stuttering controls, a tripod-mounted digital camera(Canon Elura) was used to capture the audio and video signals. The cameras were situatedapproximately 2.5 m from each participant and positioned to obtain a clear video image ofthe participants’ head, neck, upper torso, hands, and arms. The researcher was notpositioned in the video field.2.2.1. Spontaneous speech taskEach stuttering participant was requested to produce a spontaneous speech sample inorder to obtain a baseline percentage of words stuttered. Participants were requested tospeak on topics such as work or leisure-time interests. Participants were informed theyshould talk for at least 3 min and a minimum of 200 words were obtained from eachparticipant. The video recordings of each stuttering participant’s spontaneous speechsample were viewed on a video monitor (PANASONIC AG-520A). All possibleinstances of stuttering were identified in the initial 200 words of the spontaneousspeech sample. Initial stutter counts were conducted by an ASHA certified speechlanguagepathologist experienced in diagnosing and treating fluency disorders. Basedon the stuttering taxonomy of Teesson, Packman, and Onslow (2003), wordswerecoded as stuttered if they contained any type of repeated movement (whole syllablerepetitions, incomplete syllable repetitions, or multi-syllable unit repetitions) or anytype of fixed articulatory posture (with or without audible airflow). Each word wascoded as stuttered only once, regardless of the number of disfluencies present within aword. Interjections such as ‘‘ah’’ or ‘‘um’’ were not counted or analyzed. Finally, thepercentage of stuttering was calculated by dividing the number of stuttered words by200 (the total number of words analyzed). Stuttering severity ranged from mild to verysevere. On the 200-word spontaneous speaking task, the 22 stuttering speakersexhibited percentages of words stuttered ranging from 3.0% to 38.0% (M = 12.3%,S.D. = 8.9).2.2.2. Controlled speaking tasksFollowing collection of the spontaneous speech sample, each participant performedfour controlled experimental speaking tasks. The four speaking tasks required of eachparticipant were: (1) monosyllabic word productions spoken at a steady habitual rate;(2) monosyllabic productions spoken at varying speaking rates (randomly ordered slow,habitual, and fast); (3) short phrase productions spoken at a habitual rate; and (4) shortphrase productions spoken at varying speaking rates (see Fig. 1). The words andphrases were printed on 5 8-in. index cards and presented to the participants one-ata-time.Approximately 2 s were given between the completion of one token and thepresentation of the next token. The order of the words and phrases were randomized foreach participant. Additionally, in an attempt to control for any potential task

M. Blomgren, A.M. Goberman / Journal of Communication Disorders 41 (2008) 159–178 165presentation order effects, the order of presentation of the four tasks was randomizedfor each participant. Specific information on the four experimental speaking tasksfollows.2.2.2.1. Length of utterance.a. Monosyllabic words. Forty-five monosyllabic consonant + vowel + consonant (CVC)words were presented via index cards to each participant to be read aloud. Thespecific CVC words were chosen to represent various word initial phonemevariations in voicing, place, and manner of articulation. Johnson and Brown (1935)have noted that for most individuals who stutter, the likelihood they will stutter on agiven word is strongly influenced by the word-initial phoneme. However, the specificphonemes that may lead to difficulty vary markedly from one individual who stuttersto another (Quarrington, Conway, & Siegel, 1962; Wells, 1983), so a broadrepresentation of word-initial phonemes was sampled. There is also evidence thatstuttering occurs more often on content words (nouns, verbs, adjectives, andadverbs) compared to function words (e.g. articles, prepositions, pronouns; Brown,1937; Eisenson & Horowitz, 1945; Quarrington et al., 1962; Wingate, 1979),therefore a majority of the words presented were content words. The words are listedin Appendix A.b. Short phrases. Each participant read aloud 45 three-word phrases presented via indexcards. Each word in each of the phrases was monosyllabic; therefore, all phrasescontained three syllables. In an attempt to partially balance the lexical content betweenthe word and phrase conditions, each phrase contained one of the 45 CVC words fromthe word task. The phrases are also listed in Appendix A.2.2.2.2. Speech rate stability.a. Stable (habitual) speech rate. During the stable rate speech tasks, participants wererequired to read all of the words and phrases at a steady, self-determined habitualspeaking rate.b. Unstable (variable) speech rate. During the unstable speech rate tasks, participants readthe same words and phrases as during the stable speech rate tasks. For this task, eachtoken was read using variable speech rates, which randomly alternated between slow,habitual, and fast. Fifteen of the 45 words were produced at a fast rate, 15 at a normal(habitual) rate, and 15 at a slow rate. Rate cues (‘‘fast,’’ ‘‘normal,’’ or ‘‘slow’’) wereprinted on the lower left corner of each card.Before performing the experimental speaking tasks, each participant viewed a videotapecontaining demonstrations of the tasks. The videotape displayed an adult male speakerproducing five words and five phrases at slow, habitual, and fast rates. Thedemonstration words and phrases were different from those used in the study. Slowrate of speech was produced at a rate of approximately one syllable/s. Habitual rate wasmodeled at approximately two syllables/s, and fast rate was modeled at approximatelyfour syllables/s. This videotape was presented as an example of the tasks, and

166M. Blomgren, A.M. Goberman / Journal of Communication Disorders 41 (2008) 159–178participants were not asked to match these rates. Participants did not orally practice thetarget rates prior to production of the experimental tasks. Prior research (on differentspeakers than reported here) has shown that both stuttering and non-stuttering speakerseffectively alter their speech rate in response to these rate prompts (Blomgren &Goberman, 2003).All instances of stuttering in the four experimental speaking tasks were identifiedfollowing the same criteria as used for the spontaneous speech sample. However, for thephrases, only stuttering on the initial word comprising each of the 45 phrases wastabulated. Using this methodology, a direct comparison was made between the 45words spoken in isolation to the 45 words spoken within the context of a phrase. For thecontrol speakers, no stuttering was expected. In order to verify that the tasks werenot disfluency-provoking for these normally fluent speakers, normal disfluencieswere counted for this group (e.g., whole word repetitions, false starts, interjections,etc.).2.3. ReliabilityIntrajudge reliability for identification of stuttering in the four experimental speakingtasks was examined by re-analyzing the samples from 10 randomly selected participantsfrom each participant group (45% of the total participants). Interjudge reliability wasassessed by having a second ASHA certified speech-language pathologist analyze thespeaking tasks produced by the same 10 participants. Reliability was calculated on anoverall percentage of stuttering for each task.2.3.1. Normally fluent speakersThe standard error of measurement for identification of percent stuttering in theintrajudge reliability comparison of the experimental speech tasks was 0.0%. Forinterjudge reliability, the standard error of measurement for identification of percentstuttering in the experimental speaking tasks was also 0.0%. A Hoyt’s Analysis, whichprovided a correlation measure of the consistency of rater’s judgments, was conducted forboth intrajudge and interjudge comparisons of the experimental speaking tasks. For allmeasures of consistency, a correlation coefficient of r = 1.00 was achieved. The resultsindicated 100% agreement between the intrajudge and interjudge identification of speechdisfluencies in the experimental speaking tasks.2.3.2. Stuttering participantsThe standard error of measurement for identification of stuttering in the intrajudge andinterjudge reliability assessment of the spontaneous speech and experimental speech taskwas 0.9% and 0.8%, respectively. The standard error of measurement for identification ofstuttering in the intrajudge and interjudge reliability assessment of both speaking tasks was1.7% and 0.5%, respectively. A Hoyt’s Analysis was conducted for both the spontaneousspeech task and the experimental speaking tasks. For all measures of consistency, acorrelation coefficient of r = 0.99 was achieved. The results indicated very high intrajudgeand interjudge reliability for identification of speech disfluencies in the experimentalspeaking tasks.

3. ResultsM. Blomgren, A.M. Goberman / Journal of Communication Disorders 41 (2008) 159–178 1673.1. Controlled speaking tasks3.1.1. Non-stuttering speakersThe 22 normally fluent speakers exhibited no disfluency (stuttering or otherwise) in anyof the four experimental speaking tasks. Thus, the group mean disfluencies were 0.0% foreach of the four tasks. Therefore, speech fluency for the control participants was withinnormal limits. These findings clearly indicate that even the alternating rate tasks wererelatively easy for these individuals and did not result in any speech motor breakdown.3.1.2. Stuttering speakersOverall, the mean percentage of words stuttered by the 22 stuttering speakers across thefour tasks was 12.0% (S.D. = 12.8%). This mean percentage of stuttered words across thefour controlled speaking tasks was remarkably close to the mean percentage of stutteredwords on the spontaneous speaking task (12.3%). The mean percentage of stuttered wordson the single words – habitual rate task was 5.5% (S.D. = 8.9%), the single words – variablerate task was 11.0% (S.D. = 9.0%), the initial words of the phrases – habitual rate task was13.5% (S.D. = 14.1%), and the initial words of the phrases – variable rate task was 18.1%(S.D. = 14.4%).A randomized-blocks two factor ANOVA with repeated measures on both factors wasperformed on the group data to determine whether significant differences existed among thefour tasks with respect to the independent variables of length of utterance and speaking rate.In order to stabilize the inherent variance in percentage type data, the percentage of stutteredwords was transformed to arc-sine values before statistical comparisons were conducted.Length of utterance was the first repeated independent variable (with two levels: words andphrases), and speaking rate was the second repeated independent variable (with two levels:stable and variable). The analysis indicated no interaction between length of utterance andspeaking rate [F(1, 21) = 2.45, p = 0.13]. An ANOVA interaction plot is provided in Fig. 2.Significant main effects were identified for length of utterance [F(1, 21) = 20.91, p = 0.0002]and for speech rate complexity [F(1, 21) = 17.11, p = 0.0005]. Participants demonstratedsignificantly more stuttering on the first word of the phrases compared to single words, andmore stuttering in the variable rate tasks compared to the stable rate tasks.3.2. Performance according to severity levelIn order to evaluate participant performance according to severity of stuttering, twostuttering severity groups were identified from the original 22 participants. A median splitwas conducted and a ‘‘less severe group’’ was established using the 11 participants with thelowest percent of stuttering on the spontaneous speaking task (lower half). A ‘‘more severegroup’’ was established using the 11 participants with the highest percent of stuttering onthe spontaneous speaking task (upper half). It is acknowledged that this median splitmethod is somewhat arbitrary, but it does provide maximal power to examine severityeffects within the data. The spontaneous speaking task was used to separate the groupsbecause it involved a natural context and was also closely matched to the four experimental

168M. Blomgren, A.M. Goberman / Journal of Communication Disorders 41 (2008) 159–178Fig. 2. ANOVA interaction analysis: length of utterance (spatial variable) compared with speech rate stability(temporal variable). Data are mean percentage of stuttering for each speaking task (N = 22). Note: data points areordinal and are connected by lines only for illustrative purposes.speaking tasks in relation to the overall percentage of stuttered words (see previoussection). The overall mean percentage of words stuttered across the four tasks was 6.3%(S.D. = 6.9%) for the less severe group and 17.8% (S.D. = 14.7%) for the more severegroup. These groups were significantly different in their mean percentage of stuttering(t(86) = 4.72, p < .0001).For the more severe group, the mean percentage of stuttered words on the single words –habitual rate task was 8.5% (S.D. = 13.3%), the single words – variable rate task was 15.0%(S.D. = 9.7%), the initial words of the phrases – habitual rate task was 21.2% (S.D. = 15.5%),and the initial words of the phrases – variable rate task was 26.3% (S.D. = 12.9%). For the lesssevere group, the mean percentage of stuttered words on the single words – habitual rate taskwas 2.2% (S.D. = 2.9%), the single words – variable rate task was 7.1% (S.D. = 5.4%), theinitial words of the phrases – habitual rate task was 5.9% (S.D. = 4.7%), and the initial wordsof the phrases – variable rate task was 9.9% (S.D. = 9.9%). An ANOVA interaction plot foreach of the two severity groups is provided in Fig. 3.For the less severe group, there was no interaction between length of utterance andspeaking rate [F(1, 10) = 1.6, p = 0.23]. A significant main effect was found for rate [F(1,10) = 26.3, p = 0.0004], indicating that percentage of stuttering was significantly higher inboth variable rate tasks compared to both habitual rate tasks. A main effect for length ofutterance approached, but did not reach, significance [F(1, 10) = 4.7, p = 0.06]. For themore severe group, there was also no interaction between the variables [F(1, 10) = 0.77,p = 0.40]. However, there was a reversal of the main effect pattern compared to the mild

M. Blomgren, A.M. Goberman / Journal of Communication Disorders 41 (2008) 159–178 169Fig. 3. ANOVA interaction plots for the least severe stuttering participants (N = 11) and most severe stutteringparticipants (N = 11) showing the mean percentage of stuttering for each speaking task. Length of utterance(spatial variable) is compared with speech rate stability (temporal variable). Note: data points are ordinal and areconnected by lines only for illustrative purposes.group. In the severe group there was a significant main effect for length of utterance [F(1,10) = 21.0, p = 0.001], but not for rate [F(1, 10) = 4.2, p = 0.07]. Overall, the groupsdisplayed different performance patterns across the tasks. The more severe group had anincrease of stuttering frequency primarily in relation to increased length of utterance. Theless severe group had an increase in stuttering frequency primarily in relation to increasedspeech rate variability.4. DiscussionThe purpose of this study was to examine stuttering across a multidimensional hierarchyof speech performance tasks. A 2 2 speech performance matrix provided the approachfor structuring the tasks and studying the potential interaction between two performancevariables known to have an effect on stuttering: length of utterance and speech rate.For the stuttering speakers, a systematic increase in frequency of stuttering across thefour tasks/assessment conditions was identified. The findings clearly indicated that bothincreased spatial complexity (linguistic complexity as measured by length of utterance)and increased temporal complexity (motor complexity as measured by speech ratevariability) are associated with increased stuttering frequency. With respect to length ofutterance, the frequency of stuttering on the initial words of the phrases was significantlyhigher than the frequency of stuttering on single words (see Fig. 2). The increase in

170M. Blomgren, A.M. Goberman / Journal of Communication Disorders 41 (2008) 159–178stuttering on the initial words of phrases compared to single words was consistent withprevious research reporting higher stuttering rates on longer words versus shorter words(e.g., Brown & Moren, 1942; Soderberg, 1966; Wingate, 1967) and higher stuttering rateson longer sentences versus shorter sentences (e.g., Logan & Conture, 1995; Tornick &Bloodstein, 1976).With respect to speech rate variability, the results were consistent with the hypothesisthat frequency of stuttering increases with increased temporal complexity. Across thegroup of stuttering participants, the mean frequency of stuttering increased from bothhabitual rate tasks to both variable rate tasks. However, it is difficult to compare the presentresults with previous studies, as studies have traditionally examined rate within a onedimensionalmodel, and found that increased stuttering is associated with increased rate(e.g., Bloodstein, 1944; Johnson & Rosen, 1937). More recently, Kalinowski et al. (1995)found no statistically significant increases in stuttering frequency with self-determinedincreased speech rate, and Vanryckeghem et al. (1999) found statistically significantincreases in stuttering associated with a computer-controlled 30% increase in rate. Thecurrent study examined speech rate variability within the context of a two-dimensionalmodel, finding that increased variability of rate (i.e., random changes between habitual,slow, and fast) resulted in increased stuttering.One method that has been used to classify motor skills is to place the skills along aclosed-to-open continuum (Gentile, 1972; Poulton, 1957; Schmidt, 1991). A closed skill isone in which the environment and/or attributes of the skill are stable and predictable, whilean open skill is one for which the environment and/or attributes are more variable andunpredictable. This classification scheme has previously been used only for non-speechmotor movements; however, it was hypothesized in the present study that the closed-toopenclassification scheme (cast in a 2 2 matrix) would be informative in describingmotor performance deficits in the speech production of stuttering speakers. The outcome ofthe previous (Blomgren, 2001) and present study clearly support the use of the 2 2performance model as a means of describing the breakdown in speech production as afunction of speech task complexity in stuttering speakers. The stuttering participantsdisplayed progressively more stuttering as the nature of the tasks shifted from closed(simple) to relatively more open (complex). The absence of an interaction between the twoindependent variables further indicated that increases in the levels of length of utteranceand speech rate complexity (as measured in this study) equally contributed to the observedsystematic increases in stuttering frequency. McCune (1992) stated that a goal in using amultidimensional model is to strike a balance in the description of the motor system byassuming equipotentiality of all performance variables in their ability to contribute to theoutput of the motor system. In the present 2 2 comparison, a relative balance between thelinguistic/spatial (length of utterance) and temporal/motor (speech rate stability) controlfactors appeared evident.For the stuttering speakers, the current findings suggest that the applied levels ofincreased motor and linguistic complexity were more than adequate to result in significantand substantial increases in stuttering frequency. This finding would tend to support thenotion that fundamental constraints in speech production are related to both speech rateand utterance length. The non-stuttering speakers, however, did not produce anydisfluencies (stuttering-like or otherwise) on these tasks. This indicates that for these

M. Blomgren, A.M. Goberman / Journal of Communication Disorders 41 (2008) 159–178 171normally fluent speakers, the overall complexity of the tasks, even the relatively more‘‘challenging’’ tasks, were clearly within their speech production abilities. The fact thatthe non-stuttering speakers were 100% fluent across the tasks may be interpreted invarious ways. One explanation may be that speech fluency breakdown in non-stutteringspeakers does not occur in the same predictive manner of stuttering speakers. In regard tothe present data, another likely explanation may be that the lack of fluency disruption inthe non-stuttering speakers was simply due to a statistical ‘‘ceiling effect.’’ Ceiling effectsarise when testing situations are insufficiently challenging. For the normally fluentspeakers, the utility of the present 2 2 matrix may have been compromised due the lackof adequate variability in complexity of the tasks. It is unknown if a similarmultidimensional pattern of speech fluency breakdown might occur in normally fluentspeakers if the speaking tasks were of sufficient complexity and difficulty to causeoccasional speech production problems. Application of more challenging speaking tasksthan those used in this study will be required to further examine this issue in normallyfluent speakers.4.1. Performance according to severity levelIn addition to examining stuttering across the entire group of stuttering speakers,stuttering severity level was also examined separately in the least and most severeindividuals. Groups were established by identifying the 11 subjects with the lowestfrequency of stuttering and the 11 subjects with the highest frequency of stuttering based onthe spontaneous speaking task. Mean stuttering frequencies of the milder versus moresevere stuttering speakers were compared for all four tasks comprising the 2 2performance matrix. Based on this comparison, both similarities and differences wereidentified between the mild and severe stuttering speakers.Both the least and most severe speakers demonstrated increased stuttering across thetasks. However, there was a clear difference in the relative influence of the two complexityvariables in the two severity groups. Increasing utterance length caused a statisticallysignificant increase in stuttering frequency in the more severe group but not in the lesssevere group. For rate stability there was a statistically significant difference for the lesssevere group, but not for the more severe group (although the mean increased stutteringfrequencies appear identical for both groups; see Fig. 3).One interesting observation was that the severe stuttering speakers did not display astatistically significant increase in stuttering frequency in the variable rate tasks comparedto the habitual rate tasks. While the average stuttering frequency values for the severestuttering group were higher in the variable rate tasks, they did not meet the threshold forstatistical significance. The expectation, which was supported by the mild stuttering group,was that the inclusion of fast rates within the variable rate task would cause the task tobecome problematic and yield increased levels of stuttering for both groups. Previousliterature has indirectly supported this prediction, as prior studies have found an increase instuttering frequency as speech rate increases (e.g., Bloodstein, 1944; Johnson & Rosen,1937; Kalinowski et al., 1993; Vanryckeghem et al., 1999). Further, Vanryckeghem et al.(1999) found that rate-related increases in stuttering were greater for those who stutteredmost.

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.

174M. Blomgren, A.M. Goberman / Journal of Communication Disorders 41 (2008) 159–178Appendix A. Speech stimuli: 45 CVC words and 45 three-word phrasesTokens Single word tasks Phrase tasks1 Pete Give Pete heck2 Pot Fill the pot3 Pan Wash the pan4 Beat She beat him5 Bought Fred bought it6 Bang Bang the pan7 Tight Seal it tight8 Taught I taught him9 Tune Tune the dial10 Dam Dam the stream11 Deep Dig it deep12 Dad Dad and mom13 Kite Fly a kite14 Cat Feed the cat15 Keep Keep the change16 Get Get some mild17 Gap Watch the gap18 Guess Guess how much19 Seat Find a seat20 Sit Sit down here21 Zip Zip it up22 Zoom Zoom he said23 Fit He is fit24 Feet Some big feet25 Vine Trim the vine26 Vet Call the vet27 Thing Not one thing28 That That is yours29 Leap Leap of faith30 Less Less is more31 Run Run each day32 Read Read at night33 Wheat Wheat grows tall34 Whip Whip in shape35 Sheet Fold the sheet36 Shout Please shout loud37 Cheat Do not cheat38 Chap Tell the chap39 Jeep Large brown jeep40 Jam Bread and jam41 Nice Nice and clean42 Nick Nick was tall43 Mom No mom said44 Meet Meet the press45 Heat Heat the house

M. Blomgren, A.M. Goberman / Journal of Communication Disorders 41 (2008) 159–178 175CE Questions:1. As discussed in this paper, two of the most widely examined factors thought to influencestuttering frequency are:a. speech rate and utterance length.b. speech rate and the specific word initial phoneme.c. utterance length and age of listener.d. age of stuttering onset and duration of stuttering moments.2. A ‘‘closed’’ motor skill:a. occurs in a non-stable environment.b. includes aspects of a task that change during performance of the task.c. occurs in a temporally and spatially stable environment.d. tends to be spatially and temporally complex.3. The ‘‘variable rate’’ tasks utilized in this study included:a. reading a series words at a slow rate of speech and a series of phrases at a fast rate ofspeech.b. reading numerous paragraph length texts at variable speaking rates.c. reading a series of single words and a series of phrases at alternating slow, normaland fast rates of speech.d. reading a series of words three times each at a normal speaking rate.4. The overall findings of the specific 2 2 speech performance matrix utilized in thispaper indicated that:a. stuttering frequency was most influenced by the linguistic complexity variable.b. stuttering frequency is most influenced by temporal complexity variable.c. stuttering was most influenced by the words and phrases beginning with consonants.d. stuttering was influenced by both length of utterance and speech rate variability(temporal complexity).5. In the present study, the relatively less severe (milder) stuttering speakers tended tostutter most:a. during the stable rate tasks.b. during the longer utterances.c. during the variable rate tasks.d. during the shorter utterances.ReferencesAndrews, G., & Harris, M. (1964). The syndrome of stuttering. London: Heinemann.Au-Yeung, J., & Howell, P. (1988). Lexical and syntactic context and stuttering. Clinical Linguistics andPhonetics, 12, 67–78.Blomgren, M. (2001). Reinventing the wheel: New approaches to programming complexity in stuttering therapy.In H. Bosshardt, J. Yaruss, & H. Peters (Eds.), Fluency disorders: Theory, research, treatment and self-help(proceedings of the third world congress of fluency disorders) (pp. 114–118). Nijmegen: Nijmegen UniversityPress.Blomgren, M. (2005). Intensive stuttering therapy: A programmed approach for adults and adolescents. AnnArbor, MI: Copley Custom Textbooks – National Archive Publishing Company.

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