JCPSLP Vol 18 no 2 July 2016

recover from stuttering – are gender (females being more likely to recover), age of onset (the older age of onset, the lower likelihood of recovery), time since stuttering onset (the more time that has passed, the lower the likelihood of recovery), and familial history of recovery. None of these prognostic factors have been consistently reported to predict an individual’s treatment outcomes. Instead pre-treatment stuttering severity is the most consistent predictor of successful stuttering treatment outcomes. Individuals with milder stuttering have better treatment outcomes. Stuttering severity has not been found to be a consistent prognostic factor for whether or not an individual continues to stutter or not. There is unlikely a single factor that can reliably predict treatment outcomes. Rather, it is likely that a combination of factors – for example, combinations of stuttering severity rate and relevant client factors (e.g., communication attitudes, personality profiles) – will be more accurate in predicting treatment outcome (Craig, 1998; Guitar, 1976). To improve the strength of the evidence in prognosis and predictive factors in stuttering, prospective studies are needed with appropriate statistical methods for analysing the data such as logistic regression analysis (Reed & Wu, 2013). The ideal study design for investigation of predictor factors is the randomised control trial and the ability of a factor to predict treatment outcome should be evaluated per specific treatment (Adolfsson & Steineck, 2000). To confirm that a factor gives prognostic as well as treatment predictive information, a randomised study stratified for the factor in question is needed. Also, for each predictive marker, it is necessary to evaluate the level of evidence as specified by evidence-based practice models of hierarchy (Adolfsson & Steineck, 2000). As the systematic review of randomised controlled trials is considered to be the highest evidence available according to models of evidence-based practice (e.g., Hoffmann et al., 2013), it is recommended that systematic reviews are conducted in the areas of prognostic and predictive factors in stuttering. The rigour expected for systematic reviews of treatment efficacy studies with methods such as the Cochrane Collaboration should be extended to studies of prognosis and predictive factors of treatment outcomes in the future. Systematic reviews of prognosis of health conditions are becoming more recognised. The Cochrane Prognosis Methods Group, established in 2004/5, aims to ensure the best use of prognostic evidence in Cochrane reviews and to conduct research to advance the methods of prognosis reviews and other types of reviews, where similar methods apply (The Cochrane Collaboration, 2015). In the meantime, clinicians can continue to integrate the available data on prognosis of stuttering and predictive factors of treatment with their clinical judgment and patients’ individual profiles to plan appropriate therapies. Clinicians should strive to continuously evaluate therapies, to establish therapeutic alliance and troubleshoot different problems of response with their clients (Bloodstein & Bernstein Ratner, 2008). References Adolfsson, J., & Steineck, G. (2000). Prognostic and treatment-predictive factors: Is there a difference? Prostate Cancer and Prostatic Diseases , 3 , 265–268. Ambrose, N., & Yairi, E. (1999). Early childhood stuttering I: Persistency and recovery rates. Journal of Speech, Language and Hearing Research , 42 , 1097–1112.

Block, S., Onslow, M., Packman, A., & Dacakis, G. (2006). Connecting stuttering management and measurement: IV. Predictors of outcome for a behavioural treatment for stuttering. International Journal of Language and Communication Disorders , 41 , 395–406. Bloodstein, O., & Bernstein Ratner, N. (2008). A handbook on stuttering (6th ed.).Clifton Park, NY: Thomson Delmar Learning. Bothe, A., Davidow, J., & Bramlett, R. (2006). Stuttering treatment research 1970–2005: I. Systematic review incorporating trial quality assessment of behavioural, cognitive, and related approaches. American Journal of Speech-Language Pathology , 15 (4), 321–341. Chang, S. E., Erickson, K., Ambrose, N., Hasegawa- Johnson, M., & Ludlow, C. L. (2005). Brain anatomy differences in childhood stuttering. Neuroimage , 39 (3), 1333–1344. Chang, S. E., & Ludlow, C. L. (2010). Brain imaging in children. In B. Maassen & P. van Leishout (Eds.), Speech motor control: New developments in basic and applied research (pp. 71-94). New York: Oxford University Press Inc. The Cochrane Collaboration. (2015). Cochrane methods prognosis. Retrieved from http://prognosismethods. cochrane.org/ Cook, S., Howell, P., & Donlan, C. (2013). Stuttering severity, psychosocial impact and language abilities in relation to treatment outcome in stuttering. Journal of Fluency Disorders , 38 , 124–133. Craig, A. (1998). Relapse following treatment for stuttering: A critical review and correlative data. Journal of Fluency Disorders , 23 , 1–30. Craig, A., Blumgart, E., & Tran, Y. (2011). Resilience and stuttering: Factors that predict people from the adversity of chronic stuttering. Journal of Speech, Language, and Hearing Research , 54 , 1485–1496. Craig, A., Hancock, K., Tran, Y., Craig, M., & Peters, K. (2002). Epidemiology of stuttering in the community across the entire life span. Journal of Speech, Language, and Hearing Research , 45 , 1097–1105. Dworzynski, K., Remington, A., Rijsdijk, F., Howell, P., & Plomin, R. (2007). Genetic etiology in cases of recovered and persistent stuttering in an unselected, longitudinal sample of young twins. American Journal of Speech - Language Pathology , 16 , 169–178. Gordis, L. (2014). Epidemiology (5th ed.). Philadelphia, PA: Elsevier, Saunders. Guitar, B. (1976). Pretreatment factors associated with the outcome of stuttering therapy. Journal of Speech and Hearing Research , 19 , 590–600. Guitar, B., Kazenski, D., Howard, A., Cousins, S. F., Fader, E., & Haskell, P. (2015). Predicting treatment time and long-term outcome of the Lidcombe Program: A replication and reanalysis. American Journal of Speech- Language Pathology , 24 (3), 533. Hancock, Karen, & Craig, Ashley. (1998). Predictors of stuttering relapse one year following treatment for children aged 9 to 14 years. Journal of Fluency Disorders , 23 (1), 31–48. Herder, C., Howard, C., Nye, C., & Vanryckeghem, M. (2006). Effectiveness of behavioral stuttering treatment: A systematic review and meta-analysis. Contemporary Issues in Communication Science and Disorders , 33 , 61–73. Hoffmann, T., Bennett, S., & Del Mar, C. (2013). Introduction to evidence-based practice. In T. Hoffmann, S. Bennett & C. Del Mar (Eds.), Evidence-based practice

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JCPSLP Volume 18, Number 2 2016

Journal of Clinical Practice in Speech-Language Pathology