Abstract
Recent evidence suggests that the incorporation of visual biofeedback technologies may enhance response to treatment in individuals with residual speech errors. However, there is a need for controlled research systematically comparing biofeedback versus non-biofeedback intervention approaches. This study implemented a single-subject experimental design with a crossover component to investigate the relative efficacy of visual-acoustic biofeedback and traditional articulatory treatment for residual rhotic errors. Eleven child/adolescent participants received ten sessions of visual-acoustic biofeedback and 10 sessions of traditional treatment, with the order of biofeedback and traditional phases counterbalanced across participants. Probe measures eliciting untreated rhotic words were administered in at least three sessions prior to the start of treatment (baseline), between the two treatment phases (midpoint), and after treatment ended (maintenance), as well as before and after each treatment session. Perceptual accuracy of rhotic production was assessed by outside listeners in a blinded, randomized fashion. Results were analyzed using a combination of visual inspection of treatment trajectories, individual effect sizes, and logistic mixed-effects regression. Effect sizes and visual inspection revealed that participants could be divided into categories of strong responders (n = 4), mixed/moderate responders (n = 3), and non-responders (n = 4). Individual results did not reveal a reliable pattern of stronger performance in biofeedback versus traditional blocks, or vice versa. Moreover, biofeedback versus traditional treatment was not a significant predictor of accuracy in the logistic mixed-effects model examining all within-treatment word probes. However, the interaction between treatment condition and treatment order was significant: biofeedback was more effective than traditional treatment in the first phase of treatment, and traditional treatment was more effective than biofeedback in the second phase. This is consistent with existing theory and data suggesting that detailed knowledge of performance feedback is most effective in the early stages of motor learning. Further research is needed to confirm that an initial phase of biofeedback has a facilitative effect, and to determine the optimal duration of biofeedback treatment. In addition, there is a strong need for correlational studies to examine which individuals with residual speech errors are most likely to respond to treatment.
Highlights
Visual biofeedback utilizes instrumentation to provide a realtime display of some physiological function or behavior, intended to help learners gain conscious control over these functions (Davis and Drichta, 1980; Volin, 1998)
1Because the present study focuses on visual-acoustic rather than articulatory biofeedback intervention for rhotic errors, we will not go into extensive detail regarding the articulatory characteristics of rhotics; readers are referred to AdlerBock et al (2007), Klein et al (2013), or Boyce (2015) for in-depth discussion
The current study provided treatment for residual rhotic errors using the real-time LPC function of the SonaMatch program within the KayPentax Computerized Speech Lab (CSL) software suite
Summary
Visual biofeedback utilizes instrumentation to provide a realtime display of some physiological function or behavior, intended to help learners gain conscious control over these functions (Davis and Drichta, 1980; Volin, 1998). Different parameters of practice, such as the intensity of treatment and the frequency and type of feedback provided, have been argued to have differential impacts on the acquisition versus generalization of motor skills (Maas et al, 2008). KP feedback is thought to facilitate the acquisition of new motor skills by helping the learner understand how to achieve an unfamiliar target (Maas et al, 2008; Preston et al, 2013). Previous biofeedback treatment research has reported that changes in speech production are readily induced within the treatment setting for most participants, but these gains do not automatically generalize to a setting in which biofeedback is not available (Gibbon and Paterson, 2006; McAllister Byun and Hitchcock, 2012)
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