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Differential diagnostic characteristics between cluttering and stuttering-Part one

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Unlabelled: Speech-language pathologists generally agree that cluttering and stuttering represent two different fluency disorders. Differential diagnostics between cluttering and stuttering is difficult because these disorders have similar characteristics and often occur in conjunction with each other. This paper presents an analysis of the differential diagnostic characteristics of the two disorders, and a proposal for distinguishing between the two in clinical settings. The main goal of this two-part article is to set objective norms for differential diagnostic assessment of cluttering and stuttering symptoms, based on the three main characteristics of cluttering indicated/identified by St. Louis, Raphael, Myers & Bakker [St. Louis, K. O., Raphael, L. J., Myers, F. L., & Bakker, K. (2003). Cluttering updated. The ASHA leader. ASHA, 4-5, 20-22]: a fast and/or irregular articulatory rate together with errors in syllable, word or sentence structure and or a high frequency of normal disfluencies (not being stuttering). In the first half of the article objective measures are compared to the subjective clinical judgement made by fluency experts. In other words, which characteristics can be found in the speech profiles of persons who were diagnosed as people who clutter or stutter? In the second part of the article results on the Predictive Cluttering Inventory [Daly, D. A., & Cantrell, R. P. (2006). Cluttering characteristics identified as diagnostically significant by 60 fluency experts. Proceedings of second world congress on fluency disorders] are discussed in relationship to the subjective and objective measurements studied in the first half of the article. Educational objectives: The reader will learn about and be able to (1) describe obligatory characteristics of cluttering, (2) plan cluttering assessment on speech characteristics and (3) use and interpret a checklist on possible cluttering characteristics.
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Journal of Fluency Disorders 34 (2009) 137–154
Differential diagnostic characteristics between cluttering and
stuttering—Part one
Y. Van Zaalen- op ’t Hof a,b,, F. Wijnen d, P.H. De Jonckere c
aFontys University of Applied sciences, Eindhoven, The Netherlands
bCentre of Speech, Language and Fluency Disorders, Amersfoort, The Netherlands
cUniversity Medical Centre Utrecht, The Netherlands
dUtrecht University, UIL OTS & Department of Linguistics, The Netherlands
Received 15 January 2008; received in revised form 30 June 2009; accepted 2 July 2009
Abstract
Speech-language pathologists generally agree that cluttering and stuttering represent two different fluency disorders. Differential
diagnostics between cluttering and stuttering is difficult because these disorders have similar characteristics and often occur in
conjunction with each other. This paper presents an analysis of the differential diagnostic characteristics of the two disorders, and
a proposal for distinguishing between the two in clinical settings.
The main goal of this two-part article is to set objective norms for differential diagnostic assessment of cluttering and stuttering
symptoms, based on the three main characteristics of cluttering indicated/identified by St. Louis, Raphael, Myers & Bakker [St.
Louis, K. O., Raphael, L. J., Myers, F. L., & Bakker, K. (2003). Cluttering updated. The ASHA leader. ASHA, 4–5, 20–22]:
a fast and/or irregular articulatory rate together with errors in syllable, word or sentence structure and or a high frequency of
normal disfluencies (not being stuttering). In the first half of the article objective measures are compared to the subjective clinical
judgement made by fluency experts. In other words, which characteristics can be found in the speech profiles of persons who were
diagnosed as people who clutter or stutter? In the second part of the article results on the Predictive Cluttering Inventory [Daly, D.
A., & Cantrell, R. P. (2006). Cluttering characteristics identified as diagnostically significant by 60 fluency experts. Proceedings of
second world congress on fluency disorders] are discussed in relationship to the subjective and objective measurements studied in
the first half of the article.
Educational objectives: The reader will learn about and be able to (1) describe obligatory characteristics of cluttering, (2) plan
cluttering assessment on speech characteristics and (3) use and interpret a checklist on possible cluttering characteristics.
© 2009 Elsevier Inc. All rights reserved.
Keywords: Cluttering; Stuttering; Predictive Cluttering Inventory; Learning disabilities
Corresponding author at: Fontys University of Applied sciences, Eindhoven, The Netherlands. Tel.: +31 334564720.
E-mail address: y.vanzaalen@fontys.nl (Y. Van Zaalen- op ’t Hof).
0094-730X/$ – see front matter © 2009 Elsevier Inc. All rights reserved.
doi:10.1016/j.jfludis.2009.07.001
138 Y. Van Zaalen- op ’t Hof et al. / Journal of Fluency Disorders 34 (2009) 137–154
Part one: Differential diagnosis of cluttering and stuttering based on speech characteristics
1. Introduction
Speech-language pathologists generally agree that cluttering and stuttering represent two different fluency disorders.
Whereas research into stuttering has increased markedly in the past century, studies on cluttering remain scarce. “One
of the problems in diagnosing and treating cluttering is that it often occurs in conjunction with other disorders,
some of which are speech/language based and others that are not” (Ward, 2006, p. 359). Differentially diagnosing
between cluttering and stuttering is difficult because these disorders have similar characteristics and often occur in
conjunction with each other. For example, Van Borsel and Tetnowski (2007) reviewed stuttering patterns in clients with
mental retardation who showed evidence of disfluency patterns, concluding that not all would be considered stuttering.
This paper presents an analysis of the differential diagnostic characteristics of the two disorders, and a proposal for
distinguishing between the two in clinical settings.
Stuttering is a disorder characterized by a high frequency of involuntary interruptions of the forward flow of speech,
regarded by the person who stutters (PWS) as “stutters”, which are often accompanied by a feeling of loss of control
(Curlee & Conture, 2007; Guitar, 2006; Quesal, 2004; Shapiro, 1999; Van Borsel & Tetnowski, 2007; Ward, 2006).
These interruptions usually take the form of (1) repetitions of sounds, syllables or one syllable words; (2) prolongations
of sounds; (3) blocks of airflow or voicing in speech.The results of an exploratory study on speech motor practice and
learning by Namasivayam and Van Lieshout (2008) indicated that PWS and persons who do not stutter may resemble
each other on a number of performance variables (such as movement amplitude and duration), but they differ in terms
of practice and learning on variables that relate to movement stability and strength of coordination patterns.In the last
decades of the previous century research on cluttering has addressed overt as well as covert symptomatology (Daly,
1996; Daly & Burnett, 1999; Myers & Bradley, 1992; St. Louis, 1992; Weiss, 1968). Weiss (1964) described cluttering
as a disorder in the fluent flow of communication. According to experts, cluttering is characterized by three main
features: (1) a rapid and/or irregular articulatory rate (Daly, 1993; Damsté, 1984; Dinger, Smit, & Winkelman, 2008;
St. Louis, 1992; St. Louis et al., 1996; St. Louis, Raphael, Myers, & Bakker, 2003; Weiss, 1964); (2) a higher than
average frequency of disfluencies, dissimilar to those seen in stuttering [see section on stuttering characteristics above]
(Myers & Bradley, 1992; St. Louis, 1992, 1996; St. Louis et al., 2003) and (3) reduced intelligibility due to exaggerated
coarticulation (deletion of syllables or sounds in multi-syllabic words) and indistinct articulation (Daly & Burnett,
1999; Damsté, 1984; Dinger et al., 2008; Gutzmann, 1893; Mensink-Ypma, 1990; St. Louis et al., 2003; St. Louis,
Raphael, Myers, & Bakker, 2007; Van Zaalen & Winkelman, 2009; Voelker, 1935; Ward, 2006; Weiss, 1964).
1.1. Rapid and/or irregular articulatory rate
According to the St. Louis et al. (2003) working definition of cluttering a high and/or irregular articulatory rate is a
main characteristic in differential diagnostics between cluttering and stuttering, however, agreement on what defines
abnormally fast and abnormally irregular articulatory rate is needed. It is hypothesized that there are persons who clutter
that maintain a high articulatory rate in a more demanding speaking situation, and their speech-language system cannot
handle that fast speed. Due to speech motor or language planning problems in a high articulatory rate, intelligibility
problems or disfluencies occur (Daly, 1992).
1.2. Intelligibility and articulatory accuracy
Many researchers and clinicians (Bezemer, Bouwen, & Winkelman, 2006; Ward, 2006) report that persons who
clutter experience intelligibility problems due to exaggerated coarticulation (deletion of sounds or syllables in multi-
syllabic words) and indistinct articulation (substitution of sounds and/or syllables). Several researchers discuss the
fact that although persons who clutter experience intelligibility problems in running speech, they are able to produce
correct syllable and word structures in controlled situations (Damsté, 1984; Van Zaalen & Winkelman, 2009; Ward,
2006; Weiss, 1964). The findings of Hennessey, Nang, and Beilby (2008) suggest that contrary to persons who clutter
(PWC), PWS were not deficient in the time course of lexical activation and selection, phonological encoding, and
phonetic encoding. In order to be able to produce correct syllable or word structures, speech motor control should
be appropriate. Riley and Riley (1985) defined speech motor control as the ability to time laryngeal, articulatory and
Y. Van Zaalen- op ’t Hof et al. / Journal of Fluency Disorders 34 (2009) 137–154 139
respiratory movements, that lead to fast and accurate syllable production. It is hypothesized that cluttering is a fluency
disorder in which speech motor control at word level is disturbed in high speech rate, resulting in errors in word structure.
1.3. Frequency and type of disfluencies
Relying upon clinical experience, St. Louis, Hinzman, and Hull (1985) and St. Louis et al. (1996) differentiated
the fluency disorders of disfluent people and concluded that persons who clutter had a high frequency of normal
disfluencies (e.g. revisions, interjections, phrase- and syllable repetitions) and a low frequency of disfluencies typical
for stuttering. A higher than average frequency of disfluencies, dissimilar to those seen in stuttering is considered to
be a characteristic of cluttering;
1.4. Subjective clinical judgement
Differential diagnostics in cluttering and stuttering has up till now mainly been based on the subjective clinical
judgement of the speech-language therapist. Clinical judgement in the assessment of cluttering and stuttering should
be based on different aspects of communication and cognition, for instance oral reading, spontaneous speech, retelling a
memorized story, and questionnaires (Sick, 2004; St. Louis et al., 2003, 2007; Ward, 2006). It would appear important to
develop a more objective assessment method for the above mentioned aspects besides the subjective clinical judgement.
The main goal of this two-part article is to set objective norms for differential diagnostic assessment of cluttering
and stuttering symptoms, based on the three main characteristics of cluttering indicated/identified by St. Louis et al.
(2003): a fast and/or irregular articulatory rate together with errors in syllable, word or sentence structure and or a high
frequency of normal disfluencies (not being stuttering). In the first half of the article, objective measures are compared
to the subjective clinical judgement made by fluency experts. In other words, which differentiating characteristics can
be found in the speech profiles of persons who were diagnosed as people who clutter or stutter? In the second part of
the article, results on the Predictive Cluttering Inventory (Daly & Cantrell, 2006) are discussed in relationship to the
subjective and objective measurements studied in the first half of the article.
2. Method
2.1. Participants
All persons participating in this study had been referred to centres for stuttering therapy in the centre of the
Netherlands (between January 2006 and January 2007) with self-reported fluency problems. Participants were 41 males
(mean age 10.2; range 6–39 years) and 13 females (mean age 12.9; range 6–47 years). Controls for disfluent adolescents
and adults were 17 males and 8 females (see Table 1.). A control group was included in order to obtain normative values
for articulatory rate in retelling a memorized story and scores on speech motor control on word level in Screening Pittige
Articulatie (SPA, Van Zaalen, Wijnen, & Dejonckere, 2009). For the tests used in the younger children no controls
were needed, due to existing normative data. For the older participants, groups were matched for age and gender.
None of the participants (including controls) reported any neurological or hearing disorders and all were Dutch
speaking mono- or bilinguals with an intermediate to high educational level. Subjects were tested in the first assessment
session prior to therapy or in case of subjects that were already in the course of treatment (at the most 3 months) prior
to any therapy session.
Table 1
Participants divided in gender, mean age and age range.
Males Females Total
NMean age Range NMean age Range N
Disfluent 41 10.2 6.0–39.4 13 12.9 6.3–47.2 54
Controls 17 24.3 12.6–47.3 8 25.2 12.4–52.1 25
Total 58 21 79
140 Y. Van Zaalen- op ’t Hof et al. / Journal of Fluency Disorders 34 (2009) 137–154
2.2. Diagnostic decision making
Participants were diagnosed based on subjective clinical judgement on audio recordings of three different speech
tasks: spontaneous speech, reading and retelling a story. Diagnostic decisions were separately determined by two
speech-language pathologists specialized in fluency disorders (both cluttering and stuttering). Data was blinded and
labelled in code. An independent researcher was in control of the coding system. Both speech-language pathologists
(SLPs) were aware of the age and gender of the participants. SLPs could choose between three diagnostic codes:
cluttering (C), stuttering (S) and cluttering–stuttering (CS). A participant was appointed to a diagnostic group based
on the diagnoses of both SLPs. When SLPs both diagnosed a person as cluttering, the participant was placed in the
PWC group. When SLPs both diagnosed a person as stuttering, the participant was placed in the PWS group. When
a participant was diagnosed as both cluttering and stuttering, he/she was placed in the PWCS group. When SLPs
disagreed the participant was placed in the undecided group. After analysing the objective measurements of the PWS,
PWCS and PWC group, participants in the undecided group were diagnosed based on the objective measurement in
the three diagnostic groups.
2.3. Speech tasks
Data was gathered on: articulatory rate; articulatory accuracy and smooth-flow frequency and type of normal
disfluencies. The test sequence for all participants was: (1) monologue; (2) reading; (3) story retelling; (4) speech
motor coordination.
2.3.1. Task 1: Monologue
Participants were asked to recount an event in the recent past of their own choosing without intervention of the
speech pathologist. Recordings lasted 3–5 min.
2.3.2. Task 2: Reading task
This task and the next were adapted to the age/reading skills of the participants. Children read a standardised story,
two levels below their reading level (as assessed in school). This was assumed to give the investigator a reasonable
degree of certainty that not the reading skills but the speech skills were tested. The adults read a text above childhood
reading level in order to examine complex sentences, multi-syllabic words and the appearance of more than one person
in the story.
2.3.3. Task 3: Story retelling: the bus-story and the wallet-story
For the children less than 12 years we used “the Bus story”(Renfrew, 1997, Dutch version by Jansonius & Roeloefs,
2006). This task is designed for use with children and has been used in several studies. Scoring norms are available.
The researcher first tells the child the story while showing the child a colour book with 12 pictures of the story and
accordingly the child is asked to retell the story. For the adolescents and the adults, we used the Wallet story”, which
was adapted by Van Zaalen and Bochane (2007) from the ABCD test (Arizona Battery for Communication Disorders
of Dementia).
In this study, an analysis of articulatory rate and disfluency measurements was undertaken. Due to lack of norms on
this test, fluent age matched controls were also tested and means were compared.
2.3.4. Task 4a: Speech motor control on syllable level
Speech motor control can be measured with the Oral Motor Assessment Scale (OMAS, Riley & Riley, 1985). In a
stable elicitation procedure ten repetitions of/puh/,/tuhkuh/and/puhtuhkuh/are obtained. These repetitions are judged
on articulatory accuracy, smooth-flow (co-articulation, flow and sequencing) and rate.
2.3.5. Task 4b: Speech motor control on word level: the SPA test (Van Zaalen et al., 2009)
Skills in oral motor coordination in multi-syllabic words were tested with the SPA test (Dutch: Screening Pittige
Articulatie, Van Zaalen et al., 2009). SPA, designed by the first author, is a specially designed speech task to provide
information on speech motor control at word level in a fast speech rate. SPA can provide information on retaining
correct word structure and intelligibility and was therefore included in our assessment procedure. In an elicitation
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procedure, three repetitions of ten complex multi-syllabic words at a fast speech rate were obtained. In order to
allow a comparison with OMAS results, the SPA elicits three words containing (a) mostly bilabial onset consonants
(similar to [py]; e.g. Dutch: [ɔpərserəmonimestər], or (b) mostly alveolar and velar onsets (as in [tyky], e.g. Dutch:
[vərɑndərəndəevənsɔmstɑndIxhedən]; (c) a combination of bilabial, alveolar and velar consonants (as in [pytyky],
e.g. Dutch: [ɔnœytsprekələkvrveləndəvrhɑndəIən]). These repetitions are judged on articulatory accuracy,
smooth-flow (co-articulation, flow and sequencing) and rate.
2.4. Rate measurements
In order to obtain articulatory rate norms for fast rate, we needed an answer to the question: ‘What is a fast
articulatory rate?’ To our knowledge, there is no clinical or scientific consensus on this issue. In disfluent speech,
speech rate variation can be influenced by extra or extended pauses. Pindzola, Jenkins, and Lokken (1989) and Hall,
Amir, and Yairi (1999) stated that articulatory rate measures are intended to reflect how quickly sound segments are
produced in stretches of speech that have no pauses. We decided to base our judgement on Mean Articulatory Rate
(MAR), which was defined as the mean of five rate measures in minimally 10 to maximally 20 consecutive syllables
in perceptually fluent speech without pauses. We defined fast articulatory rate in spontaneous speech for disfluent
speakers as a rate 1.0 SD above the MAR of disfluent speakers. It is well known that the fluent speech of PWS is
slower compared to age and gender matched controls. The disfluent people are chosen as a reference group because it
is known that differences in MAR between fluent and disfluent people exist.
Articulatory rate, in stuttering research, is usually calculated in syllables per second or phonemes per second by
analysing only perceptually fluent utterances. Perceptually fluent utterances are defined as those utterances that exclude
“within- or between-word disfluencies, hesitations, or pauses greater than 250 ms” (Yaruss, Logan, & Conture, 1994,
p. 221).
In counting syllables one has to decide between the linguistic word form or the speech motor output. There are
two reasons for choosing the linguistic word form in counting syllables of disfluent persons: (1) as cluttering is often
considered to be a disorder of speech planning, it is important to know how much time the person planned to produce
the word (Verhoeven, Pauw, & Kloots, 2004); (2) persons who clutter sometimes produce unintelligible speech in
which it is difficult to objectively determine how many and which syllables and phonemes have been realized. To avoid
overly subjective assessment, the articulatory rate was calculated on the basis of the number of syllables that should
have been realized [for the citations forms of words].
In St. Louis et al. (2003) definition of cluttering a deviant rate variability is considered to be a key symptom. For each
subject, articulatory rate variability was computed as the standard deviation around the mean for the rate measurements.
There are no normative values for MAR-variation (MAR-v). In our study, a deviant-MAR-v was defined as a variation
in articulatory rate 1.0 SD above the mean articulatory rate variation: an indicator of cluttering.
2.5. Ratio disfluencies
Evaluation of disfluencies, as a supplement to the diagnostic criteria based on articulatory rate and articulatory
accuracy was done using Campbell and Hill’s Systematic Disfluency Analysis procedure (Campbell & Hill, 1994). All
disfluencies in samples of spontaneous speech and speech in story retelling were counted. The percentage of stutter-like
disfluencies and normal disfluencies was calculated. The ratio disfluencies was obtained by dividing the percentage non-
stutter disfluencies by the percentage stutter disfluencies (for instance a participant with 20% non-stutter disfluencies
and 2% stutter disfluencies had a ratio of 20/2 =10) (Van Zaalen & Winkelman, 2009). It is expected that persons who
clutter will have a higher frequency of non-stutter disfluencies and therefore their ratio will be above one, while the
person who stutters will experience more stutter disfluencies and their ratio will be below one. It is also expected that
the mix group (PWCS) ratio’s will be either below or above one.
2.6. Articulatory accuracy and coarticulation measurements
In order to classify errors in sound, syllable or word structure, the Oral Motor Assessment Scale (OMAS; syllable
level) and the SPA (Dutch: Screening Pittige Articulatie; word level) were done. Scoring is done according to Riley’s
Oral Motor Assessment Screening protocol. Accuracy, smooth flow and rate were scored. Problems in sound accuracy
142 Y. Van Zaalen- op ’t Hof et al. / Journal of Fluency Disorders 34 (2009) 137–154
(distortions and substitutions of voicing and devoicing) were scored. Accuracy scores on the OMAS or SPA more than
1.5 SD below the group mean were considered as an indication of severe problems in adjusting voicing to articulatory
movement: an indicator of severe problems in realizing adequate voice-onset time. Problems in smooth flow were
divided into three categories: coarticulation, flow and sequencing. Coarticulation is the gradual transfer from one
speech movement to the other; errors in coarticulation include telescoping syllables and within sequence pausing.
Flow is the gradual stressing and rhythm of the sequence; errors are for instance changes in stress pattern of the
sequence. Sequencing errors are scored when a person makes errors in sound or syllable order. Smooth flow scores on
the OMAS or SPA more than 1.5 SD below the group mean, are considered to be an indication of severe problems in
oral motor coordination. Rate was determined by counting the mean time in seconds needed to produce three sequences
of target syllables.
A reference test on oral motor coordination on syllable and word level is not available for ages over 12/13 years.
In order to compare the results of the non-fluent speakers with fluent speakers, results of both adolescents and adults
were compared to results of gender and age matched controls.
2.7. Diagnostic decision based on subjective and objective clinical judgement
The data of the participants with an undecided diagnosis were reanalysed, in order to determine the value of adding
objective values to a subjective clinical judgement. Objective values obtained from the PWS, PWCS and PWC group,
were used as an additional diagnostic component to diagnose the participants in the undecided group. For instance,
when a participant was diagnosed as PWS by one SLP and PWCS by the other SLP and this participant scored according
to the mean of the cluttering group (on ratio disfluencies or sequencing scores), the participant was diagnosed as a
PWCS. In doing this, we could objectify the percentage of clients in which the cluttering component was missed by
one SLP.
Please, note: adding the objective diagnosis to the subjective diagnosis was only done for this part of the research
and had no influence on the objective values of the cluttering or stuttering group.
2.8. Data analysis
Recordings were made in a sound protected room. Digital audio- and video tape recordings were made of all
speaking tasks using a Sony digital video camera, a Trust digital head microphone, and a GoldWave Digital Audio
Editor v5.18.Articulatory rate was determined using a speech analysis program, PRAAT (Boersma & Weenink, 2007)
(see Fig. 2). All of the fluent speech utterances produced by the individual subjects were recorded through a Trust head
microphone into a high quality sound card using a HP Pavilion zv6000 laptop, sample frequency 22.050Hz.
Digital audiotakes were edited, replayed and blindly analysed with PRAAT. The Mean Articulatory Rate (MAR) of
five consecutive syllable strings was measured by counting the number of syllables per second in a string of at least 10
and maximum 20 consecutive syllables spoken, excluding pauses. Durational measures were made in ms by placing
a cursor at the enhanced onset and another cursor at the enhanced offset. Onset was visually defined as the first peak
(maximum amplitude in millivolts) that corresponded with a burst of spectral acoustic energy in the corresponding
microphone signal or oscillogram. Offset was defined as the last consecutive peak in the waveform that was followed
by a non-speech signal and also corresponded to the termination of spectral energy. Onset and offset of the utterance
detected in the oscillogram and corresponding spectrographic display of each utterance were verified through playback
of the auditory signal. Onsets and offsets of voiceless consonants that could not be clearly identified were excluded
from the analyses, such as in Hall et al. (1999) study. Next the duration of each utterance was calculated by subtracting
the onset time from the offset time. Finally, the number of syllables for each utterance was divided by the duration of
the utterance to provide a measure of articulation rate: syllables per second (SPS).
2.9. Reliability
A random sample of 8 participants was re-diagnosed to evaluate intra-judge reliability. A paired sample t-test
between the two diagnoses was done (p> .05). In addition, a different random sample of 8 participants was re-analysed
by the second experimenter, for evaluating inter-judge reliability on articulatory rate, articulatory accuracy and smooth
flow measurements. In a paired sample t-test results obtained by the two experimenters were compared (p> .05).
Y. Van Zaalen- op ’t Hof et al. / Journal of Fluency Disorders 34 (2009) 137–154 143
Table 2
Agreement on diagnostic decisions between speech-language pathologists based on subjective judgement or subjective judgement added with
objective measurements.
Diagnosis Total
PWC PWCS PWS Undecided
Subjective judgement 9(17%) 10 (18%) 8 (15%) 27 (50%) 54 (100%)
Objective and subjective judgement 10(18%) 23 (43%) 9 (17%) 12 (22%) 54 (100%)
3. Results
3.1. Diagnostic decision making
Pearson’s correlation between SLP diagnoses was low (r= .638). Of the 54 male and female disfluent speakers,
only 27 (50%) were agreed upon by the SLPs. Of the 54 male and female disfluent speakers, 7 (13%) were diagnosed
as PWC by one researcher and PWS by the other researcher; and 20 (37%) were diagnosed as PWC or PWS by one
researcher and PWCS by the other researcher. Analyses presented here were carried out only on the 27 subjects that
were agreed upon by the judges (PWC: N= 9; PWCS: N= 10; PWS: N= 8) (see Table 2).
3.2. Articulatory rate
Table 3 presents mean articulatory rate (MAR) in syllables per second (SPS) on three speech tasks (spontaneous
speech, reading and retelling) presented for each diagnostic group. Individual subject means for each speech task were
calculated. In the case of two participants no individual mean articulatory rates could be calculated, as they were not
able to produce at least 10 consecutive syllables.
No sex differences were found for MAR in monologue or retelling a memorized story, however, females were
superior to males for reading, F(1,22) = 4.662, p= .047. Group differences were found for MAR in retelling a memorized
story F(1,22) = 8.489, p= .002. MAR of PWS was slower (mean SPS = 3.7 SPS; SD = 1.5) compared to PWC (mean
SPS = 4.9; SD = 0.9) and controls (mean SPS = 5.9; SD = 0.5) (see Table 3).
3.3. Fast articulatory rate
Fast articulatory rate (more than 1.0 SD above the MAR) was set at 5.5 SPS in monologue; 5.8 SPS in retelling
a memorized story and 5.7 SPS in reading. The majority of PWC (56%) met the description of fast articulatory rate
in spontaneous speech, where PWS did not. No group differences were found for fast articulatory rate in reading and
retelling a memorized story.
Table 3
Speech characteristics and between group analyses of variance, corrected by Tukey’s-b for unequal group size, on mean articulatory rate (MAR),
ratio disfluencies (RD) and error scores on Screening Pittige Articulatie (SPA).
PWC (N=9) PWCS (N= 30) PWS (N= 14) Controls (N= 25) FSig.
MSD MSD MSD MSD
MAR monologue 5.3 0.7 4.7 0.8 3.7*0.8
MAR reading 4.5 1.7 4.6 0.7 4.0 1.0
MAR retelling 4.9 0.9 4.8 1.1 3.7 1.5 5.9 0.5
RD Monologue 6.4 3.9 3.2 5.2 0.4** 0.5 8.7 .001**
RD Retelling 7.6 4.4 1.7 2.9 2.0** 2.0 8.5 .001**
Accuracy SPA 2.1 1.7 1.6 1.3 0.2** 0.8 0.1 0.2 11.4 .001**
Smooth flow SPA 8.7 2.0 6.8 2.2 1.4** 3.2 0.8 0.9 38.4 .001**
Rate SPA 4.3 0.8 4.8 1.6 8.7 6.1 5.2 0.8
MAR-v 2.5 2.2 2.4 0.1 .884
*Significant difference between PWC/PWCS and PWS.
** Significant difference between PWC and PWS.
144 Y. Van Zaalen- op ’t Hof et al. / Journal of Fluency Disorders 34 (2009) 137–154
Fig. 1. Ratio disfluencies in the cluttering and stuttering group in retelling a story, spontaneous speech and reading.
3.4. Articulatory rate variability
No group differences were found for Mean Articulatory Rate–variation (MAR-v) (see Table 2). A deviant MAR-v
was 3.99 SPS. A small number of persons who stutter (PWCS: 23%; PWS: 15%) fit the description of deviant MAR-v,
while PWC did not.
3.4.1. Ratio disfluencies
Between group differences were found in ratio disfluencies for spontaneous speech F(1,21) = 34.787, p< .001 and
retelling a story F(1,21) = 16.874, p= .001, but not in reading F(1,17) = 3.171, p= .094. PWC produced 6.4 times more
normal disfluencies compared to stutter disfluencies in spontaneous speech and 7.6 in retelling a memorized story. The
Ratio Disfluencies for PWS was 0.4 for spontaneous speech and 1.2 for retelling a memorized story (see Table 3.).
A ratio of disfluencies above 2.9 is considered to be a cluttering symptom; whilst a ratio normal disfluencies below
0.9 is considered to be a stuttering symptom. In the PWC group 75% met the ratio disfluencies criteria for cluttering in
both spontaneous speech and retelling a memorized story. In the PWS group 85.7% met the ratio disfluencies criteria
for stuttering in spontaneous speech (Fig. 1).
Fig. 2. Smooth flow and accuracy errors in Screening Pittige Articulatie (SPA).
Y. Van Zaalen- op ’t Hof et al. / Journal of Fluency Disorders 34 (2009) 137–154 145
3.5. Articulatory accuracy and smooth flow
PWC produced significantly more (M= 2.1) accuracy errors compared to controls (M= 0.19) and PWS (M= 0.21)
in repeating multi syllabic word strings (F(1,21) = 11.386, p< .0001) (Fig. 2).
Controls produced less smooth flow errors compared to PWS; PWS produced less smooth flow errors
compared to PWC, F(1,54) = 38.413, p< .0001. Smooth flow scores of PWCS were between PWS and PWC
scores.
3.6. Adding objective measures to the subjective diagnostic decision making
When a ratio disfluencies > 2.87, reflecting a cluttering symptom, was added to the subjective clinical judgement
11 cases out of 54 could be added to the 27 cases SLPs agreed on diagnosis, with 29.6% of the disfluent cases still
remain undecided. In adding accuracy problems > 2.1 (a cluttering component), to the subjective clinical judgement,
the diagnosis of an extra 9 participants could be confirmed. In adding measures of both ratio disfluencies and accuracy
error scores to the undecided diagnosis made by the subjective clinical judgement of the SLPs an agreement of 42 out
of 54 (77,8%) diagnosis were agreed upon (see Table 2.).
3.7. Reliability
Intra-judge correlation coefficients on all metrics ranged between .993 < r< .999. Inter-judge reliability on articu-
latory rate, articulatory accuracy and smooth flow measurements ranged between .675 < r< .868.
4. Discussion
The main goal of this research was to compare the subjective clinical judgements made by experts in fluency
disorders to results obtained by objective measurements. Findings indicate that a differential diagnosis based on a
subjective clinical judgement of a speech-language pathologist specialized in fluency disorders appeared to correspond
with the subjective clinical judgement of another SLP specialized in fluency disorders in only 50% of all disfluent
cases. In 37.0% of all disfluent cases a client was diagnosed as PWC or PWS by one researcher and PWCS by the
other researcher, in other words, one of the SLPs did not add the cluttering component to the diagnosis. Adding ratio of
disfluencies and accuracy and speech flow error scores on word level to the subjective clinical judgement appeared to be
of substantial diagnostic value, especially in locating a cluttering component. Of all cases, 15.2% of diagnoses remained
undecided after adding differentiating objective measures to the subjective diagnostic decision.Overall, the rate data
presented in our study are higher than those reported for (American) English-speakers. This finding corroborates data
from earlier research where substantial rate differences among languages have been observed (Carlo, 2006; Grinfeld
& Amir, 2006; Verhoeven et al., 2004). Articulation rate could be affected by linguistic as well as cultural aspects,
thus the establishment of normative bases for mean articulatory rate for each language is essential. Fast articulatory
rate for disfluent speakers, as defined as a rate 1.0 SD above the MAR of disfluent speakers, appeared to be of no
differentiating value. One possible explanation of this result might reflect the decision to analyse only perceptually
fluent or intelligible utterances.
In cluttering, a fast articulatory rate is mostly in those utterances that are not fluent (in calculating SPS only fluent
utterances were included) or intelligible “spurts”. It would be important to consider these factors in future studies and
find out a way to objectively measure such accelerated bursts of speech.
Sawyer, Chon, and Ambrose (2008) concluded, based on a single-speech sample in preschool children who stutter,
that influences of rate, length, and complexity were not significantly correlated to stutter-like disfluencies. Contrary
to that, a high amount of normal disfluencies in combination with a high level of syllable structure errors, can have a
negative influence on the naturalness and intelligibility of speech (Levelt, 1989). Thus, cluttered speech that is perceived
to be fast, may well be within normal limits when measured objectively.
Ratio disfluencies offer additional diagnostic criteria in retelling a memorized story. Based on the results of Boey,
Wuyts, Van de Heyning, De Bodt, and Heylen (2007) we assume that results on the ratio of disfluencies can reasonably
be used on both Dutch and English data. It is hypothesized that in retelling a memorized story a person who clutters
does not adjust speech rate to the more complex language level resulting in a high level of normal disfluencies (word
146 Y. Van Zaalen- op ’t Hof et al. / Journal of Fluency Disorders 34 (2009) 137–154
and phrase repetitions and interjections) and sentence structure errors (Van Zaalen, Wijnen, & Dejonckere, in press;
Van Zaalen & Winkelman, 2009).
Errors in speech motor control on word level and a ratio disfluencies above three, appear to be indicators for
cluttering behavior. Speech situations where a client is not focused on his/her speech or talks at a fast articulatory rate
are sensitive to errors in speech motor control and disfluencies. In case of cluttering this will mainly be outside the
clinic and in unstructured speech situations. Based on our results we advise SLPs to obtain data both outside and inside
the clinic (both with the conscious knowledge of the client and not).
Although the present research provides ideas of setting normative data and procedures for differential diagnosis
between cluttering and stuttering, the objective measurement values in this research are based on a small group of
disfluent participants that both SLPs agreed upon. It is recommended that future studies on cluttering and stuttering
include multiple factors or domains in the data collection process, especially with young children during the formative
years of the disorder, when substantial overlap in the development of several speech/language domains occurs (Yairi,
2007), in order to better understand the intriguing disorder of cluttering.
Differential diagnostic characteristics between cluttering and stuttering—Part two
Part two: Validation of the Predictive Cluttering Inventory
1. Introduction
In the first article objective measures on articulatory rate, rate variation, type and frequency of disfluencies and
scores on oral motor coordination tasks were compared to the subjective clinical judgement made by fluency experts.
This enabled the identification of speech characteristics that can be found in the speech profiles of persons who were
diagnosed as people who clutter or stutter? In this second article, results on the Predictive Cluttering Inventory (Daly
& Cantrell, 2006) are discussed in relationship to the subjective and objective measurements studied in the first part of
the article.
The Predictive Cluttering Inventory (PCI) (Daly, 1996; Daly & Cantrell, 2006) is a frequently used assessment
tool. Daly and Cantrell (2006) called on 60 expert researchers and clinicians in cluttering worldwide to respond to a
questionnaire containing a number of statements about the disorder. After analysing the data, the checklist contained 33
symptoms associated with cluttering, in four domains (pragmatics, speech motor, language and cognition, and motor
coordination and writing problems). Every symptom can be ranked with a score on a seven-point scale (0=not present,
6 = always present) in order to predict possible cluttering. The Predictive Cluttering Inventory is produced without a
norm for possible cluttering. The aim of the present study is to correlate PCI data with the characteristics of spontaneous
speech production in disfluent and fluent speakers and validate the PCI as a cluttering detection instrument. For use in
the Netherlands this Predictive Cluttering Inventory was translated into Dutch and back translated into English.
It is important to consider that the PCI is based on an email inventory developed by Daly and Cantrell (2006),
where stuttering therapists around the world had to identify characteristics they assumed were to be symptoms of
cluttering. The 33-item PCI is the result of a factor analysis performed on all the characteristics named by the
fluency experts. The PCI is produced without a discriminative norm, so it can be used as an inventory or check-
list rather than a decisive instrument. Adding a discriminative norm could help SLPs in detecting cluttering more
easily.
The PCI was developed to detect cluttering symptoms in running speech. A high sensitivity level is needed in order
to accurately detect cluttering symptoms. A high level of sensitivity (>75%) and a high level of specificity (>75%) are
needed in order to make the PCI a useful differentiating screening instrument. Children with learning disabilities (LD)
were included, but while they have language disturbances similar to cluttering; they also produce a high frequency of
normal (i.e., non-stutter-like) disfluencies, such as interjections, fillers, pauses, word- and phrase repetitions (Wigg &
Semel, 1984). Fluent children with LD were hypothesized to score low on the PCI. The main purpose of this research
was to investigate the validity of the PCI in a fluent and disfluent population. In other words is the PCI sensitive
enough to detect cluttering in persons with cluttering symptoms and specific enough to reject people that do not
clutter?
Y. Van Zaalen- op ’t Hof et al. / Journal of Fluency Disorders 34 (2009) 137–154 147
2. Method
2.1. Participants
In this study 137 Dutch speaking participants ranging in age between 10.6 and 12.11 years, were divided into five
groups and examined by eight different SLPs. The groups were based on SLPs diagnosis as described in part one of
this article. Age range in all groups was restricted to exclude bias due to developmental issues. Group 1 consisted
of cluttering children (N= 17, M= 11.5 years); Group 2 consisted of cluttering-stuttering children (N= 25, M= 11.6
years); Group 3 consisted of stuttering children (N= 15, M= 11.6 years); Group 4 consisted of children with learning
difficulties (N= 29, M= 11.6 years); and Group 5 consisted of controls (N= 51, M= 11.2 years). None of the participants
had known hearing or neurological problems. Disfluent children were recruited in two centres of stuttering therapy in
the centre and east part of the Netherlands. Children that satisfied the inclusion criteria for age (from 10.6 to 12.11
years) at the time of the assessment in the therapy centres were included in the study. Children with learning disabilities
and controls were recruited from a total of 21 (15 normal education; 6 special education) primary schools in Brabant
(part of Holland). All schools have numbered class lists. In every participating school, six children were randomly
selected on the basis of the student number on the class list. The parents received a consent form with explanation of
the project prior to the assessment. Parents were asked for permission for participation of their children in the research
project (informed consent). All parents gave permission for inclusion in the study.
2.1.1. Checklist
The Dutch translation of Predictive Cluttering Inventory (Van Zaalen & Winkelman, 2009) was completed by a
group of seven research assistants on the basis of observation of spontaneous speech, retelling a memorized story,
reading and parental information. All data was coded by an independent researcher who had access to the coding
system. Researchers were SLPs with less than one year working experience. Completing the checklist was done by the
researchers blinded (for SLP diagnosis). Groups were equally divided between researchers. In order to come closest
to the use by SLPs around the world who download the checklist from the internet (the available source of the list),
researchers were not informed on how to use the checklist other than by the notification made by Daly and Cantrell
(2006) on top of the form.
2.1.2. Norm hypothesized by Daly (in press)
Daly (in press) hypothesized that a norm of 120 points in a 7-point scale (3 per item) would be sufficiently able to
detect possible cluttering components in speech, based on clinical experience with cluttering clients. These hypothetical
norms are based on subjective clinical observation by Daly and research is needed for their validation.
2.1.3. Reference test
While a ‘gold standard’ in cluttering assessment is lacking, we chose to use the subjective clinical judgement of
two highly experienced SLPs specialized in fluency disorders, combined with objective measures (as described in part
one of the article) as the reference test.
2.1.4. Analyses
Pearson correlations were used to determine relationships between subjective and objective clinical judgement to the
checklist norm studied. Significant differentiating items were analysed. Within group and between group differences
were studied, using ANOVA. The sensitivity level, the proportion of actual positives correctly identified, and the
specificity, the proportion of negatives which are correctly identified, were also determined.
A factor analysis was conducted to determine factors that together may explain the variance present in the basic
variables. Results of the factor analysis were compared to results from a cluster analysis. The factor analysis grouping
was based on the SLPs diagnosis (cluttering–non-cluttering), while in the cluster analysis, clustering of the items
was conducted based on the individual item scores. In the hierarchical cluster analysis, between group linkages were
displayed with squared Euclidean distance. It is hypothesized that items detected by both factor and cluster analysis
present the best predicting cluttering items.
Items with significant differentiating value between diagnostic groups were found in the 33-tem list by using
an ANOVA with post hoc Tukey’s-b correction for different group size and a significance level of p< .05. It was
148 Y. Van Zaalen- op ’t Hof et al. / Journal of Fluency Disorders 34 (2009) 137–154
hypothesized that significant different items (for cluttering) with a mean value equal or above three (according to Daly’s
hypothesis) can serve as a predictor of possible cluttering. Supplementary to the total score of discriminating items,
scores on factor one and cluster one items were studied. We hypothesized that a mean score above 3 (often–always)
on all of these items provides a norm for cluttering.
Before using the checklist, items were not discussed between researchers to make sure that the use was similar to
those therapists who download the file from the Internet. After completion of all checklists, all items were evaluated
between researchers for the level of clarity. Item clarity analyses was done, by establishing inter judge correlation
scores. Inter judge agreement levels were computed for two items on the checklist. Inter judge reliability level of >.70
was believed to be acceptable, meaning that both the item and the scoring system were interpreted similarly by different
researchers.
After completion of all checklists, researchers could make comments on items they thought needed further expla-
nation or clarification. Comments were taken into account in describing possible alterations of the checklist.
3. Results
3.1. Checklist
Based on the proposed norm score for cluttering by Daly (in press), only two participants from the cluttering or
cluttering–stuttering group were detected by the checklist as having cluttering components (see Table 4.). That is,
only 4.44% (2/45) of persons with cluttering symptoms were tested positive on the index test. This sensitivity level
is considered to be extremely low. The specificity of the checklist is 94.7% (89/94), meaning, that 94.7% of a group
of persons without cluttering indeed tested negative on the index test. The percentage of false positives, i.e., the
percentage of positive tested people that did not clutter was high: 71.4%. The percentage of false negatives was high:
67.4%.
A factor analysis with a Varimax rotation on the cluttering item identified two factors with an eigenvalue above
1 explaining 85.8% of variance sums of squared loadings: Factor 1 included seven speech planning related items
(loading: .61–.86); factor 2 included six language structure items (loading: .61–.83) (see Table 5).
The cluster analysis with all 33 items on the list entered as variables identified four major clusters of coherent
variables (see Table 6.). Cluster one contained those items involved in speech planning; cluster two contained items
involved in language structure; cluster 3 contained items involving attentiveness and cluster 4 contained more common
communicative skills.
An analysis of variance between groups on total cluster scores corrected for uneven group size by Tukey’s-b revealed
significant differences (p= .01) between disfluent (cluttering and stuttering) and fluent groups (controls and LD) on
cluster one: F(4,134) = 22.975, p< .0001; cluster two F(4,134) = 5.806, p< .0001 and between controls and other
diagnostic groups on cluster three F(4,134) = 12.961, p< .0001, There were no significant between group differences
on cluster four.
Table 4
Specificity and sensitivity of total scores on PCI and PCI-revised (PCI-r).
Reference norm + Reference norm Total
Index test PCI + 2 5 7
Index test PCI 43 89 132
Total 45 94 139
Sensitivity 2/45 = 4%
Specificity 89/94 = 95%
False negatives 43/132 = 33%
Index test PCI-r + 22 9 31
Index test PCI-r 10 86 96
Total 32 95 127
Sensitivity 22/32 = 69%
Specificity 86/95 = 91%
False negatives 10/96 = 10%
Y. Van Zaalen- op ’t Hof et al. / Journal of Fluency Disorders 34 (2009) 137–154 149
Table 5
Items adjusted to factors 1 and 2 according to a factor analyses of the Predictive Cluttering Inventory (6).
Factor 1 Factor 2
Irregular speech rate; speaks in spurts or bursts Language is disorganized; confused wording; word-finding problems
Rapid rate (tachylalia) Disorganized language increases as topic becomes more complex
Telescopes or condenses words Poor language formulation; poor story-telling; sequencing problems
Co-existence of excessive disfluencies and stuttering Inappropriate topic introduction, maintenance, or termination
Initial loud voice trailing off to unintelligible murmur Seems to verbalize before adequate thought formulation
Little or no anxiety regarding speaking; unconcerned
Oral diadochokinetic coordination below expected levels
A closer examination of these results in an analysis of variance on the clusters on mean cluster scores between
disfluent speakers revealed no significant difference on the three clusters. While differences on total cluster score failed
within disfluent speakers, both cluster two and cluster three showed significant differences between fluent speaking
LD and controls (cluster two: F(1,78) = 12.146, p< .001; cluster three: F(1,78) = 25.230, p< .0001).
An analyses of variance between different diagnostic groups corrected for uneven group size by Tukey’s-b procedure
(p= .01) revealed six significant item scores on cluttering: irregular speech rate, speaks in spurts or bursts; rapid rate
(tachylalia); initial loud voice trailing off to unintelligible murmur; little or no anxiety regarding speaking, unconcerned;
co-existence of excessive disfluencies and stuttering;disorganized language increases as topic becomes more complex.
The first five items mentioned above also appeared in factor 1 and cluster 1. The item on co-existence of disfluencies
appeared in factor two and cluster two.
3.2. Item clarity
Researchers were asked to comment on the comprehensibility of the checklist. Subjects and researchers should be
able to comprehend the behaviors required to secure accurate and valid measures. One main concern (noted by all
researchers) was uncertainty of how to interpret the scoring system. For instance, the word “often” can be interpreted as
‘in almost every speaking situation’ or ‘in almost every sentence within a speaking situation’. Researchers interpreted
this differently. This may have affected final scores.
Some items (item 3, item 6, item 21 and item 22) were considered difficult to score while a couple of conflicting
symptoms were within one item description together. For instance, item 3 was difficult to score in case of conflicting
scores on one part of the item description. Item 31 was difficult to score because oral diadochokinetic norms for
adolescents and adults are not available and because it was not clear whether coordination on syllable, word level or
during conversation was considered.
A checklist for possible cluttering should be highly sensitive on detecting cluttering. Therefore an adaptation of
the PCI, based on the results of the present study was analysed. This involved selecting all the items that significantly
differentiated cluttering from stuttering and controls (see Appendix A). A shortened version of the PCI was compiled
Table 6
Distribution of items in cluster analysis.
Cluster 1: Speech planning Cluster 2: Disorganized language Cluster 3: Attentiveness
Lack of pauses between words and phrases; repetition of
multi-syllabic words and phrases; irregular speech rate;
speaks in spurts or bursts; telescopes or condenses words;
initial loud voice trailing off to unintelligible murmur;
oral diadochokinetic coordination below expected norm
levels; co-existence of excessive disfluencies and
stuttering; speech rate progressively increases
(festinating)
Disorganized language increases as topic
becomes more complex; poor language
formulation; poor story-telling;
sequencing problems Many revisions;
interjections; filler words; Language is
disorganized; confused wording;
word-finding problems; Inappropriate
topic introduction, maintenance, or
termination; Improper linguistic
structure; poor grammar; syntax errors
Does not recognize or respond to
listener’s visual or verbal feedback;
does not repair or correct
communication breakdowns; lack of
awareness of own communication
errors or problems; speech better
under pressure; lack of effective
self-monitoring skills; distractible;
poor concentration; attention span
problems
150 Y. Van Zaalen- op ’t Hof et al. / Journal of Fluency Disorders 34 (2009) 137–154
on these eight differentiating items. A score of 3 on (24 points in total) all items of the shortened PCI resulted in an
increase in sensitivity level to 69%. Specificity of the shortened PCI was very high at 91% and the percentage false
negatives was lowered to 10% (see Table 5.).
4. Discussion
The main purpose of this research was to investigate the validity of the PCI in a fluent and disfluent population.
PCI/CBK in its original form is not sensitive enough to detect cluttering in persons with cluttering symptoms, but is
specific enough to reject people that do not clutter.
The low sensitivity level of the PCI is due to frequent type I errors, that is, a difference was observed when there was
none. This may be explained by the fact that a lot of symptoms on the list are common symptoms to all fluent speakers.
For instance, every fluent speaker will produce more normal disfluencies compared to cluttering disfluencies; and weak
time planning skills occur in people that do not clutter. Lack of adequate pausing is common in adolescent speech, but
only considered a cluttering symptom when influencing speech intelligibility. Besides that, some items were expected
to score high in the LD group. For instance, almost every child with learning disabilities will score high on attentional
focusing problems and weak social skills. A few type II errors occurred, where there is a failure to observe a difference
when in truth there is one. In case of cluttering, a type II error occurs if the test reports false when the person, in fact,
clutters. The explanation of these errors is that some items are formulated in a way to differentiate cluttering from
stuttering (items 8, 9, 19 and 20). It is expected that persons who only stutter will score low on this items but the
difference between fluent speakers and persons who clutter can be too small to be statistically significant. In solving
these type I and type II errors, individual item scores were combined to cluster scores on a revised PCI (see Appendix
A). The interpretation of item scores in the revised PCI heightened the sensitivity to a low but acceptable score of
69%. According to Pollit and Beck (2003), for group-level comparisons, coefficients in the vicinity of .70 are usually
adequate. A sensitivity score of 70% is acceptable but due to the fact that some items and issues concerning the scoring
system are not absolutely clear to all SLPs a short manual with clarification of items content and scoring system could
further heighten the sensitivity of the PCI. The supporting symptoms are still in the revised PCI as these symptoms
can be of great importance in therapy planning for an individual client (Bezemer et al., 2006; Daly & Cantrell, 2006;
Ward, 2006).
In comparing the results of factor and cluster analysis it was noticed that both analysing techniques came up with
the same two main clusters: speech planning and language structuring. Another quality to consider in assessing this
quantitative instrument is speededness. Researchers were able to complete the PCI within 20–30 min. In a relatively
short-time period the SLP is able to collect a substantial important data.
One significant problem in trying succinctly to identify the characteristics of a clutter lies in the fact that there
may be two basic strands to the disorder; a language component and a motor one” (Ward, 2006, p. 141). The fact
that it is common for cluttering to present more as a language problem than a motoric one, was supported by both
factor and cluster analysis which proposed two major clusters of variables: a speech motor and a language component.
“In case of linguistic cluttering speech output is more likely to show a lack of linguistic fluency, characterized by
poorly constructed language rather than as an output which is motorically disrupted” (Ward, 2006, p. 141), or as Daly
described: “in cluttering accelerated speech is not always present, but an impairment of language formulation always
is” (Daly, 1992, p. 107). In cases of motoric cluttering speech output is more likely to show a lack of speech flow
fluency characterized by excessive coarticulation, lack of speech rhythm, fast bursts of speech interspersed with short
inappropriate pauses (Bezemer et al., 2006; Daly, 1996; Damsté, 1984; Dinger et al., 2008; St. Louis, 1992; St. Louis
et al., 2003, 2007; Ward, 2006; Winkelman, 1990).
As described in the results section of item clarity, researchers reported that the scoring system was multi-
interpretable. It is not clear whether scoring is done on one particular speech moment (for instance spontaneous
speech) or concerns all speaking situations of a day (both focused and unattended speech) and what a particular
score means (‘always’ = every day, every speaking situation or every word). It is known that speech and language dis-
turbances of fluent speakers can differ between speaking situations and themes. In PWC the differences between
speaking situations can be very large; especially the difference in speaking situations when attention to speech
is given and those when a PWC is not alert to his/her speaking performance (Bezemer et al., 2006; Daly, 1992;
Damsté, 1984; Dinger et al., 2008; Mensink-Ypma, 1990; St. Louis et al., 2003; Ward, 2006; Weiss, 1964, 1968).
This difference can partially be scored in item ten: Speech better under pressure (improves short-term with con-
Y. Van Zaalen- op ’t Hof et al. / Journal of Fluency Disorders 34 (2009) 137–154 151
centration), but sensitivity of the PCI would benefit from a more prominent place of this important symptom in
cluttering.
Some item formulation more than likely needs to be reconsidered as many contain conflicting elements or researchers
had problems in dealing with the negative statement in relation to the scoring system. However, using this revised scoring
interpretation system produced improved sensitivity and specificity. While a number of type I errors still occurred in
the revised PCI, it is not meant to be a diagnostic instrument on its own, though it has the potential to make contribution
to the SLP working with disfluent persons.
In conclusion, the PCI in its current state does not serve as a valid diagnostic instrument for cluttering, but it
serves as a valid screening instrument for possible cluttering symptoms. In its current state it does differentiate
between fluent and disfluent speakers, but a differentiation between different fluency problems cannot be based
on total PCI scores only. Although the revised PCI subtotal score did not differentiate between cluttering and
stuttering, the revised PCI could be of value in the prediction of cluttering components in speech. Further research
on defining items is required in order to make this screening instrument a valid diagnostic tool that can be used by
SLPs.
CONTINUING EDUCATION
Differential diagnostics between cluttering and stuttering
QUESTIONS
1. Articulatory rate is best measured in:
(a) words per minute
(b) words per second
(c) syllables per minute
(d) syllables per second
(e) words and syllables per second
2. Daly and Cantrell (2006) developed a checklist on:
(a) stuttering symptoms
(b) cluttering and stuttering symptoms
(c) cluttering symptoms
(d) symptoms of high speech rate
(e) language production in cluttering
3. The main and obligate characteristic of cluttering is:
(a) a high speech rate
(b) a high frequency of disfluencies not being stuttering
(c) unitelligibility
(d) a (too) high or irregular articulatory rate
(e) failures in syllable, word or sentence structure
4. The most differentiating speech task between cluttering and stuttering is;
(a) SPA-test on oral motor control on word level
(b) reading out loud
(c) running speech
(d) retelling a memorized story
(e) OMAS
5. A score above 24 on section number one predicts a cluttering component
(a) yes, a score above 24 on section number one predicts cluttering to be present
(b) yes, a score above 24 on section number one predicts no stuttering present
(c) no, a score above 24 on section number two predicts cluttering
(d) no, the PCI cannot predict a cluttering component
(e) yes, a score above 12 on section number one predicts cluttering to be present
152 Y. Van Zaalen- op ’t Hof et al. / Journal of Fluency Disorders 34 (2009) 137–154
Appendix A.
Y. Van Zaalen- op ’t Hof et al. / Journal of Fluency Disorders 34 (2009) 137–154 153
References
Bezemer, B. W., Bouwen, J., & Winkelman, C. (2006). Stotteren van theorie naar therapie. Bussum: Coutinho.
Boersma, P., & Weenink, D. (2007). Praat: Doing phonetics by computer (Version 4.4.26) [Computer program]. Retrieved July 24, 2006, from
[http://www.praat.org/].
Boey,R. A., Wuyts, F. L., Van de Heyning, P.H., De Bodt, M. S., & Heylen, L. (2007). Characteristics of stuttering-like disfluencies in Dutch-speaking
children. Journal of Fluency Disorders,32, 310–329.
Campbell, J. G., & Hill, D. G. (1994). Systematic disfluency analysis. Evanston, IL: Northwestern University.
Carlo, E. J. (2006). Speech rate of non-stuttering Spanish speaking adults. In Second World Congress on fluency disorders. Proceedings (pp.
111–117).
Curlee, R. F., & Conture, E. G. (2007). Stuttering and related disorders of fluency (3eED). New York, Stuttgart: Thieme.
Daly, D. (1992). Helping the clutterer: Therapy considerations. In F. Myers, & K. St. Louis (Eds.), Cluttering: A clinical perspective (pp. 107–124).
Leicester, England: FAR Communications.
Daly, D. (1993). Cluttering, another fluency syndrome. In R. F. Curlee (Ed.), Stuttering and related disorders of fluency (3rd ed., pp. 179–204). New
York: Thieme.
Daly, D. (1996). The source for stuttering and cluttering. East Moline, IL: LinguiSystems.
Daly, D. (in press). Strategies for identifying and working with difficult to threat cluttering clients. Presented July 5th, proceedings of the Oxford
Dysfluency conference.
Daly, D., & Burnett, M. (1996). Cluttering: Assessment, Treatment planning, and case study illustration. Journal of Fluency Disorders,21, 239–244.
Daly, D. A., & Burnett, M. L. (1999). Cluttering: Traditional views and new perspectives. In R. F. Curlee (Ed.), Stuttering and disorders of fluency
(2nd ed., pp. 222–254). New York: Thieme.
Daly, D. A., & Cantrell, R. P. (2006). Cluttering characteristics identified as diagnostically significant by 60 fluency experts. In Proceedings of
second world congress on fluency disorders
Damsté, P. H. (1984). Stotteren. Utrecht: Bohn, Scheltema & Holkema.
Dinger, T., Smit, M., & Winkelman, C. (2008). Expressiever en gemakkelijker spreken. Bussum, the Netherlands: Coutinho.
Grinfeld, D., & Amir, O. (2006). Articulation rate in children and adolescents: Hebrew speakers. In Proceedings of second world congress on fluency
disorders (pp. 125–129).
Guitar, B. (2006). Stuttering an integrated approach to its nature and treatment (3rd ed.). Lippincott Williams & Wilkins.
Gutzmann, H. (1893). Vorlesungen über die Störungen der Sprache und ihre Heilung. Berlijn.
Hall, K. D., Amir, O., & Yairi, E. (1999). A longitudinal investigation of speaking rate in preschool children who stutter. Journal of Speech Language
and Hearing Research,42, 1367–1377.
Hennessey, N. W., Nang, C. Y., & Beilby, J. M. (2008). Speeded verbal responding in adults who stutter: Are there deficits in linguistic encoding?
Journal of Fluency Disorders,33(3), 180–202.
Jansonius, K., & Roeloefs, M. (2006). Het vertellen van Renfrew’s busstory. Alle taal centraal, http://www.alletaalcentraal.nl/2006/handouts/46.pdf;
visited 16.05.2007,21.33.
Mensink-Ypma, M. (1990). Broddelen en leerstoornissen. Houten/Antwerpen: Bohn Stafleu van Loghum.
154 Y. Van Zaalen- op ’t Hof et al. / Journal of Fluency Disorders 34 (2009) 137–154
Myers, F. L., & Bradley, C. L. (1992). Clinical management of cluttering from a synergistic framework. In Cluttering: A clinical perspective (pp.
85–105). St. Louis. Kibworth, Great Britain: Far Communications.
Namasivayam, A. K., & Van Lieshout, P. (2008). Investigating speech motor practice and learning in people who stutter. Journalof Fluency Disorders,
33, 32–51.
Pindzola, R. H., Jenkins, M. M., & Lokken, K. J. (1989). Speaking rates of young children. Language, Speech, and Hearing Services in Schools,
20, 133–138.
Pollit, D. F., & Beck, C. T. (2003). Nursing research. In Principles and methods (7th ed.). Baltimore: Lippincott Williams & Wilkens.
Quesal, B. (2004). Fluency and Fluency Disorders [Stuttering course. Downloaded June 1, 2007 (http://www.mnsu.edu/comdis/
kuster/StutteringCourseSyllabi/Quesal.html)].
Renfrew, C. (1997). The Renfrew language scales: Bus story test, a test of narrative speech. Speechmark.
Riley, G. D., & Riley, J. (1985). Oral motor assessment and treatment: Improving syllable production. Austin: Pro-Ed.
Sawyer, J., Chon, H., & Ambrose, N. G. (2008). Influences of rate, length, and complexity on speech disfluency in a single-speech sample in
preschool children who stutter. Journal of Fluency Disorders,33, 220–240.
Shapiro, D. (1999). Stuttering intervention: A collaborative journey to fluency freedom. Austin, TX: Pro Ed.
Sick, U. (2004). Poltern, Theoretische Grundlagen, Diagnostik, Therapie. Stuttgart: Thieme.
St. Louis, K. O. (1992). On defining cluttering. In F. L. Myers, & K. O. St. Louis (Eds.), Cluttering: A clinical perspective. Kibworth, Great Britain:
Far Communications, Ltd.
St. Louis, K. (1996). A tabular summary of cluttering subjects in the special edition. Journal of Fluency Disorders,21, 337–344.
St. Louis, K. O., Hinzman, A. R., & Hull, F. M. (1985). Studies of cluttering: Disfluency and language measures in young possible clutterers and
stutterers. Journal of Fluency Disorders,10, 151–172.
St. Louis, K. O., Myers, F. L., Cassidy, L. J., Michael, A. J., Penrod, S. M., Litton, B. A., et al. (1996). Efficacy of delayed auditory feedback for
treating cluttering: Two case studies. Journal of Fluency Disorders,21, 305–314.
St. Louis, K. O., Raphael, L. J., Myers, F. L., & Bakker, K. (2003). Cluttering updated. The ASHA leader. ASHA,4–5, 20–22.
St. Louis, K. O., Raphael, L. J., Myers, F. L., & Bakker, K. (2007). In E. Conture, & R. Curlee (Eds.), Stuttering and other fluency disorders.
Philadelphia, PA: Thieme Medical.
Van Borsel, J., & Tetnowski, J. A. (2007). Fluency disorders in genetic syndromes. Journal of Fluency Disorders,32, 279–296.
Van Zaalen, Y., & Bochane, M. (2007). The wallet story. In Proceedings of the 27th world congress of the International Association of Logopedics
and Phoniatrics (p. 85).
Van Zaalen, Y., Wijnen, F., & Dejonckere, Ph. (2009). A test on speech motor control on word level, the SPA test. International Journal of Speech
and Language Pathology,11(1), 26–33.
Van Zaalen, Y., Wijnen, F., & Dejonckere, Ph. (in press). Language planning disturbances in children who clutter or have learning disabilities.
International Journal of Speech and Language Pathology,doi:10.1080/17549500903137249.
Van Zaalen, Y., & Winkelman, C. (2009). Broddelen, een (on) begrepen stoornis. Bussum: Coutinho.
Verhoeven, J., Pauw, G., & Kloots, H. (2004). Speech rate in a pluricentric language: A comparison between Dutch in Belgium and the Netherlands.
Language and Speech,47, 297–308.
Voelker, C. H. (1935). The prevention of cluttering. The English Journal,24(10), 808–810.
Ward, D. (2006). Stuttering and cluttering. Frameworks for understanding and treatment. East Sussex: Psychology Press.
Weiss, D. A. (1964). Cluttering. Englewood Cliffs, NJ: Prentice-Hall.
Weiss, D. A. (1968). Cluttering: Central language imbalance. Pediatric Clinics of North America,15, 705–720.
Wigg, E. H., & Semel, E. M. (1984). Language assessment and intervention for the learning disabled (2nd ed.). Columbus, OH: Charles E. Merrill.
Winkelman, C. L. (1990). Broddelen. In W. Mensink (Ed.), Broddelen en Leerstoornissen. Utrecht: Bohn, Scheltema & Holkema.
Yairi, E. (2007). Subtyping stuttering I: A review. Journal of Fluency Disorders,32, 165–196.
Yaruss, S., Logan, K., & Conture, E. (1994). Speaking rate and diadochokinetic abilities of children who stutter. Journal of Fluency Disorders,19,
221–222.
Yvonne Van Zaalen-op’t Hof, MSc works as a speech-language therapist specialized in stuttering since 1988, in a centre for stuttering therapy in
the Netherlands. In 2006, she graduated as a member of the first cohort of ten speech-language scientists in the Netherlands. Yvonne is lecturer at
Fontys University of applied sciences Eindhoven (NL). In May 2007, Yvonne became the first coordinator of clinical issues of the International
Cluttering Association.
P.H. Dejonckere, MD, PhD is currently full professor at the University of Utrecht (NL), general coordinator of the Scientific Council at the Institute
of Occupational Diseases (Fed. Gov., Brussels), guest professor at the Catholic University of Leuven (B), visiting professor at the Université de
Lille II (F) and Chairman of the European Laryngological Research Group.
Frank Wijnen obtained his PhD in psychology in 1990 at the Radboud University, Nijmegen (NL). Currently he is a professor of psycholinguistics
in the Linguistics Programme/UIL OTS and the Department of Psychology at Utrecht University. His research revolves around primary language
development. In several publications he has explored the connections between language acquisition, developmental dysfluency and stuttering.
... The aims of this study were to investigate the occurrence of stuttering behavior across time and to assess the relationship between stuttering behavior and language ability in first-graders with Down syndrome. Observable characteristics of speech are commonly used to identify stuttering in both clinical practice and research (Eggers & van Eerdenbrugh, 2018;Van Zaalen-Op't Hof et al., 2009). Speech that contains repetitions of sounds, syllables, and monosyllabic words (particularly in young children) as well as prolongations of sounds and blocks is generally considered to reflect stuttering (also called "stuttering-like" disfluencies). ...
... The retelling is supported by a textless story book with 12 color pictures. This test has been used in several studies of speech disfluency in typically developing children (see, e.g., Van Zaalen-op't Hof et al., 2009), and it has been recommended as an appropriate addition to a conversational context in the assessment of stuttering (Byrd et al., 2012). ...
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Purpose: The aims of this study were to investigate the occurrence of stuttering behavior across time and to evaluate the relationship between stuttering behavior and language ability in children with Down syndrome. Method: A national age cohort of Norwegian first graders with Down syndrome (N = 75) participated in the study. Speech samples from a story-retelling task and a picture book dialogue as well as standardized measures of vocabulary, grammar, and nonverbal mental ability were collected at two time points approximately 5 months apart. Stuttering behavior was evaluated through counting stuttering-like disfluencies and stuttering severity ratings. The relationship between stuttering behavior and language ability was investigated through hierarchical regression analysis. Results: The participants had stuttering severity ratings ranging from no stuttering behavior to severe and displayed all types of stuttering-like disfluencies. There were significant relationships between stuttering behavior and language ability at the first time point, whereas the relationships were not significant at the second time point. The stuttering severity ratings were significantly predicted by language ability across time, whereas the frequency of stuttering-like disfluencies was not. Conclusions: The occurrence of stuttering behavior was high across the measures and time points; however, the relationship between stuttering behavior and language ability varied across these variables. Thus, the nature of the relationship does not seem to follow a strict pattern that can be generalized to all children across time.
... Cluttered speech is often described as 'too fast', 'unintelligible', or both, and it may occur inconsistently in a person's speech. Some have referred to it as a 'central language imbalance' (Weiss, 1964) or a syndrome (St. Louis et al., 2003) and the specific characteristics required for diagnoses (Daly & Cantrell, 2006;Van Zaalen et al., 2009;Ward, 2006) have been the topic of debate. The lowest common denominator definition, a definition that is currently broadly used, defines cluttering as a fluency disorder wherein segments of the speaker's conversation are perceived as too fast overall, too irregular, or both; in combination with excessive normal disfluencies, collapsing or deletion of syllables, and/or abnormal pauses, syllable stress, or speech rhythm (St. Louis & Schulte, 2011). ...
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Stuttering and Cluttering provides a comprehensive overview of both theoretical and treatment aspects of disorders of fluency: stuttering (also known as stammering) and the lesser-known cluttering. The book demonstrates how treatment strategies relate to the various theories as to why stuttering and cluttering arise, and how they develop. Uniquely, it outlines the major approaches to treatment alongside alternative methods, including drug treatment and recent auditory feedback procedures. Part one looks at different perspectives on causation and development, emphasizing that in many cases these apparently different approaches are inextricably intertwined. Part two covers the assessment, diagnosis, treatment, and evaluation of stuttering and cluttering. In addition to chapters on established approaches, there are sections on alternative therapies, including drug therapy, and auditory feedback, together with a chapter on counselling. Reference is made to a number of established treatment programs, but the focus is on the more detailed description of specific landmark approaches. These provide a framework from which the reader may not only understand others' treatment procedures, but also a perspective from which they can develop their own. Offering a clear, accessible and comprehensive account of both the theoretical underpinning of stammering therapy and its practical implications, the book will be of interest to speech language therapy students, as well as qualified therapists, psychologists, and to those who stutter and clutter.
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Two clutterers were treated with similar preplanned delayed auditory feedback (DAF) procedures, using probe samples in which the DAF was not present to measure treatment efficacy. Whereas both clients met established fluency criteria during treatment, both clutterers had difficulty transferring gains to probe sessions—one more than the other. Differences in results of DAF treatment are discussed from the perspectives of differences in cluttering severity, coexisting disorders, and supplementary clinical techniques.