ناروانی گفتار در بزرگسالان غیر لکنت زبان در سراسر طول نمونه و موضوعات

Data on disfluencies in the speech of non-stuttering adults are relevant to several aspects of the assessment and treatment of adults who stutter. Currently, very few sources provide relevant data. In the existing literature on normally fluent speakers, there is no consistency in sample length or topic or in which types of disfluency are counted. Many studies report incomplete data, making it difficult to compare new results to previous ones. The purpose of this study was to assess the effect of sample length and topic on fluency levels in the speech of non-stuttering adult men. Monologues produced by 25 English-speaking men with no reported communication disorder were analyzed for the presence of disfluencies. The group means for total disfluencies were between 6 and 8 per 100 syllables for all samples. A within-subjects Length (3) by Topic (3) ANOVA found a significant interaction (Length by Topic), however, the clinical importance of this result is minimal. The mean number of within-word disfluencies (also called stuttering-like disfluencies or SLDs) was below 1.5 per 100 syllables for all samples, although there was some variation across individual speakers. The data presented will be useful to clinicians and to researchers interested in disfluencies in spontaneous speech. Learning outcomes: Readers will be able to (1) identify several methodological problems in studies of disfluency including counting methods and descriptions of participants; (2) identify the range of within-word disfluencies (also called SLDs) and other disfluencies in this study and other similar ones; (3) know whether topic/type of speech or sample length is more likely to affect disfluency levels in non-stuttering adults.

Disfluencies in the spontaneous speech of adults have been studied by psychologists, psycholinguists, criminologists, neurologists, and speech language pathologists. What the psychology literature often calls “hesitation phenomena” reveal something about of the planning and production of speech and language (e.g., Levelt, 1998 and Postma and Kolk, 1993) and recent work shows that interjections affect language comprehension by listeners (Corley et al., 2007 and Fox Tree, 2001). Patterns of pauses and interjections have been studied for what they reveal about malingering or lying (e.g., Coppens et al., 2000 and Davis et al., 2005). A change/increase in disfluencies beyond that seen in normal aging (e.g., De Andrade and de Oliveira Martins, 2007, Searl et al., 2002, Walker et al., 1988 and Yairi and Clifton, 1972) is one symptom of some neurological conditions (Jokel, De Nil, & Sharpe, 2007). In clinical work with adults who stutter, stuttering severity can be measured, in part, by comparisons between the client's speech and the disfluency patterns of non-stuttering speakers. Similarly, in treatment, one benchmark in setting appropriate targets for natural-sounding speech is to use the range of disfluencies seen in the speech of non-stuttering adults. Following early work by Webster, 1974 and Webster, 1980, and influenced, perhaps, by the series of studies of children's disfluencies done by Yairi and Ambrose (2005), 3%SS has been widely adopted as a definition of ‘within normal limits’ in adult speech (Conture, 2001), or as an acceptable treatment outcome for both children and adults (Boberg and Kully, 1994, Caron and Ladouceur, 1989, Ingham, 1999, Langevin and Boberg, 1993, Mallard and Kelley, 1982 and Miltenberger et al., 1996). Yaruss (1998, p. 231) has said that a mean stuttering-like disfluency level of 1% and mean non-stuttered disfluency level of 3% indicated that adult “clients completed the program with speech that could be judged as within normal limits”. Kully, Langevin, and Lomheim (2007) use “less than 1% stuttering” (p. 219) as one criterion for successful completion of some stages of treatment for adults. Langevin and Boberg (1993) used a benchmark of less than 3% stuttering as one measure of the long-term success of treatment. Given the importance of disfluencies in assessing and treating stuttering, we have surprisingly little data on disfluencies in normal adult speech during tasks similar to those used in clinical assessments. 1.1. Studies of disfluencies in adult speech There are 3 studies that present data on the full range of disfluency types in adult speech, using tasks similar to those used in clinical assessments. Their findings are summarized in Table 1. Table 1. Previous studies of adults’ normal speech disfluencies in monologues or conversation. Authors Disfluencies counted N (men) Mean age (years) Topic Sample size Disfluencies Johnson 1961 8 types 25 19.6 Job Studies 5 min 6.5/100 words (mean) Lutz and Mallard 1986 9 types 25 20 Studies, Family, Hometown 250–1062 syllables 2.6/100 syllables (median) Duchin and Mysak (1987) 8 types 75 21–91 in 5 groups Summer Family Job unknown 7.55/100 words, 7.4 for 21–30 year olds Notes: Johnson counted interjections, revisions, phrase, whole word and part word repetitions, prolongations, incomplete phrases, and broken words. Lutz and Mallard counted interjections of words or phrases, interjections of fillers or sounds, revisions, phrase, whole word and part word repetitions, prolongations, dysrythmic phonations, and incoherent sounds. Duchin and Mysak counted interjections, revisions, phrase repetitions, whole word and part word repetitions, prolongations, incomplete phrases, and dysrythmic phonations. Table options Using these figures as benchmarks for normal speech is problematic due to a number of shortcomings in these studies. These include: (a) Limited range of ages and educational levels: This limits the external validity (generalizability) of their findings. Johnson (1961) and Lutz and Mallard (1986) tested only university students. Johnson's participants were all taking psychology or speech classes. Lutz and Mallard do not report the field of study of their student participants. Given that students tend to select their classes/majors based upon the verbal and cognitive abilities needed for different fields of study and different professions, psychology students cannot be said to be representative of “college students” nor of the general, non-student population. Duchin and Mysak (1987) tested a wide range of ages, but did not report the education or occupations of their subjects. (b) Subject descriptions are incomplete: Bilingualism and regional dialects can affect many aspects of speech, including features such as voice onset time and features of plosive consonants that are relevant to the field of stuttering (e.g., Flege, 2001 and Flege et al., 1997). There is no indication of whether any of Lutz and Mallard's 50 volunteers were bilingual, or even if they were all native English speakers. Since 48 were from Texas, many of them may have spoken a regional dialect of English. Duchin and Mysak (1987) and Johnson (1961) report that their participants lived in Philadelphia and in Iowa, respectively, but do not say what dialect(s) of English they spoke. (c) Incomplete and different values reported in each study: One of the barriers to progress in the field of fluency disorders is that there is no agreement on what to count or how to define it. Different rules for counting syllables and disfluencies will yield different numbers (Roberts, 2007 and Yairi, 1997). As Roberts (2007) has pointed out, some authors use “%SS” as if it were a synonym for SLDs (e.g., Armson & Kiefte, 2008). Too often, studies are published with no information about how the syllable counts and disfluency counts were done. Different studies also report different metrics (see Table 1). Johnson (1961) presents the little-used deciles (but Andrews and Ingham calculated means and medians from these data, 1971). Lutz and Mallard (1986) report a median value and a range for number of syllables and words on which at least 1 disfluency occurred, but give no mean or standard deviation. Duchin and Mysak report the mean and standard deviation for each type of disfluency, but no range. Their data are broken down by type of disfluency, but there is no overall mean. Furthermore, little detail is given about how the syllables or words were counted: Did Johnson and Duchin and Mysak count only intended words, or all words produced? If two different disfluencies occurred before or during the same syllable, did they count as two disfluencies or as one? Were revisions included in the syllable count? What about interjections that are also words, such as “you know” or “like”? See Roberts (2007) on how different ways of counting syllables and disfluencies can lead to very different figures from the same speech sample. In order to compare reference/normative data to the speech of individual clients, the disfluencies and number of syllables per minute must be counted the same way. Thus statements such as “Stuttering frequency was measured as %SS and syllables per minute (SPM) was the measure of speech rate” (O’Brian, Packman, & Onslow, 2008) are not explicit enough to allow readers to compare the results of participants to those of other speakers. The two shortcomings of previous studies that are the main focus of the current study are the wide range of sample lengths and the use of different topics across speech samples. Sample lengths: The Lutz and Mallard (1986) sample lengths ranged from 250 to 1062 syllables. The Johnson (1961) Job task samples ranged from 60 to 689 words, with a mean of 359 words (men only). How long a sample is needed to reliably measure disfluency rates in adults? If sample length matters, it is inappropriate for Lutz and Mallard and for Johnson to combine different sample lengths, or for readers to compare results across studies which used very different lengths. If disfluency rates in adults are stable over different sample lengths, then there is no need to analyze long samples in future studies of non-stuttering adults. It may be that the effect of sample length is different across different age groups and/or different for adults who stutter and those who do not, but as part of understanding this issue, studies of non-stuttering adults are needed. Different topics used in the 3 studies: We do not know if, or to what extent, the topic of a monologue influences disfluency rate. Two recent studies suggest that topic is important. An innovative study of 45 lecturers found that the number of filled pauses per minute (and per 100 words) was significantly higher in lectures on the Humanities than in lectures on Science and Mathematics. When these lecturers all spoke on the same topic, there were no differences in the number of filled pauses (Schachter, Christenfeld, Ravina, & Bilous, 1991). The clinical value of this study is limited because only one type of disfluency was counted, and the only filled pauses counted were non-word fillers (e.g., um, er, uh). Similarly, Bortfeld, Leon, Bloom, Schober, and Brennan (2001) found that disfluency rates vary with the topic (easy or complex picture description) and with a speaker's role in a speech task. In clinical assessments and in treatment outcome studies a range of topics is used (see Table 1, for example). We do not know to what extent changing topics changes disfluency levels in adults who stutter. To minimize potential practice effects, some studies use reading passages on different topics and/or allow pre-treatment and post-treatment monologues and conversation samples on different topics (e.g., Armson and Kiefte, 2008 and Huinck and Rietveld, 2007). Some studies deliberately sample different topics. White (2002), for example, combined 4 different topics and two different types of speech (narrative and expository) within a single, 300 word sample (describe your typical day AND explain how to drive a car, make a meal, and change a tire. Should clinical examples only be compared to non-stuttering samples on the same topic? Data on this issue will help answer this question. If one goal of treatment is to teach adults who stutter to speak in a natural manner, it is important to know the normal range of all types of disfluencies on the tasks used in clinical assessments. The preceding review demonstrated a number of shortcomings in the existing studies of disfluency in non-stuttering adults. In light of these, the goals of the present study are: 1. to measure the number of disfluencies in the spontaneous speech of non-stuttering men, reporting an overall rate, and also frequencies for each type of disfluency and to compare these results to the various 3% and 1% thresholds for “normal limits” cited above; 2. to determine whether these disfluency rates vary across 3 sample lengths (300, 500 and 800–1000 syllables); 3. to determine whether these disfluency rates vary across 3 topics commonly used in clinical assessments of adults who stutter (job, hobbies, a sport).