Video self-modeling as a post-treatment fluency recovery strategy for adults

https://doi.org/10.1016/j.jfludis.2015.01.003Get rights and content

Highlights

  • Two of 3 participants showed reductions in stuttering frequency.

  • All participants showed reductions in avoidance behaviours and expectancy to stutter.

  • Results suggest that VSM may be a viable fluency recovery intervention.

Abstract

Purpose

This multiple-baseline across subjects study investigated the effectiveness of video self-modeling (VSM) in reducing stuttering and bringing about improvements in associated self-report measures. Participants’ viewing practices and perceptions of the utility of VSM also were explored.

Methods

Three adult males who had previously completed speech restructuring treatment viewed VSM recordings twice per week for 6 weeks. Weekly speech data, treatment viewing logs, and pre- and post-treatment self-report measures were obtained. An exit interview also was conducted.

Results

Two participants showed a decreasing trend in stuttering frequency. All participants appeared to engage in fewer avoidance behaviors and had less expectations to stutter. All participants perceived that, in different ways, the VSM treatment had benefited them and all participants had unique viewing practices.

Conclusion

Given the increasing availability and ease in using portable audio-visual technology, VSM appears to offer an economical and clinically useful tool for clients who are motivated to use the technology to recover fluency.

Educational Objectives: Readers will be able to describe: (a) the tenets of video-self modeling; (b) the main components of video-self modeling as a fluency recovery treatment as used in this study; and (c) speech and self-report outcomes.

Introduction

Empirical support is growing for the use of video self-modeling (VSM) as a fluency maintenance and recovery tool for children who stutter (Bray and Kehle, 1996, Bray and Kehle, 1998, Bray and Kehle, 2001). Its use as a recovery tool for adults who stutter has also been demonstrated (Cream et al., 2009, Webber et al., 2004). However, the effectiveness of VSM as a maintenance tool in the treatment of adults who stutter has yet to be established (i.e., Cream et al., 2010). Given the availability of portable audio-visual technology, VSM offers an economical, potentially efficient, and increasingly feasible fluency recovery or maintenance tool.

According to social cognitive learning theory, self-modeling enhances skill performance by demonstrating how best to carry out a behavior and all related processes involved in imitating a behavior. Self-modeling reinforces one's belief in being capable of producing the desired behavior, thereby enhancing self-efficacy. With increased self-efficacy, performance improves because individuals are more likely to devote their energy to behavior needed to succeed and less likely to foster obstructive self-doubts (Bandura, 1997). Self-efficacy has been identified as an important factor in relapse prevention, particularly in conditions treated with cognitive behavioral skills (Granvold & Wodarski, 1994). Indeed, it has been argued that improvements in self-efficacy are the most clinically relevant treatment outcomes (Merhag & Woltersdorf, 1990) and that increased self-efficacy is the mechanism that results in improved performance (Bandura, 1997). However, recent evidence suggests that self-efficacy is not an explanatory mechanism for self-modeling effects (Ste-Marie, Vertes, Rymal, & Martini, 2011); rather, self-efficacy is thought to be a co-occurring process or a mediator of self-modeling effects (Dowrick, 2012).

Video self-modeling is the viewing of oneself engaged in a desirable behavior. As Bray and Kehle (2012) indicate, VSM is a time and resource friendly treatment option (Bray & Kehle, 2012). Factors critical to the success of self-modeling include: (a) paying attention to the model, (b) being motivated to produce the behavior, and (c) having the capability to perform the modeled behavior (Bandura, 1986, Bandura, 1997).

Video self-modeling has been successfully used as a fluency recovery and maintenance tool with children (Bray and Kehle, 1996, Bray and Kehle, 1998, Bray and Kehle, 2001). However, most relevant to the current study are the findings with adults that have reported inconsistent results and revealed methodological shortcomings that are addressed in this study.

In 1976, Hosford, Moss, and Morrell (1976) used self-modeling in combination with systematic desensitization and relaxation techniques in treating an adult inmate who stuttered. The participant was instructed to listen to an edited audio speech sample of his fluent speech and practice speaking the way he did on the audiotape. Hosford and colleagues reported that the individual's stuttering rate decreased from 8.7 times per minute to 0.8 times per minute and that fluency was maintained at 3 months follow up.

In 2004, using a single subject withdrawal design, Webber et al. examined the short-term effects of VSM with 3 adults. There were two treatment phases. In the first phase participants were asked to watch their videos only. In the second phase, participants were asked to watch their video and then try to speak like they did in the video. Only one participant demonstrated a treatment effect evidenced by a reduction in stuttering frequency; effects were most evident when the participant was asked to speak as he did on the video. In addition to the importance of instructing clients to try to speak as they did in the video, Weber et al. suggested that prior successful treatment with speech restructuring strategies (i.e., fluency shaping techniques) may be a prerequisite for success with VSM.

In a pre-post group study with 10 adults, Cream et al. (2009) investigated the use of VSM as a fluency recovery tool with participants who had previously received intensive speech-restructuring treatment. The VSM videos were created at the onset of the study during a 1-h in-clinic session. Participants were asked to practice the speech-restructuring skills that they were taught in their initial treatment programs in monolog until they were able to maintain fluent speech for 5 min. For those who could not achieve fluent speech on their own, the first author (i.e., Cream) provided participants with a model of speech restructuring techniques to emulate. When participants stuttered, the first author also provided specific instructions to repeat the stuttered word fluently. The VSM video was then edited to remove any residual stuttering and any models or requests to repeat a stuttered word. Thus, the VSM videos showed participants speaking without stuttering (i.e., the target behavior was fluent speech). Participants were asked to view their VSM tapes twice a day for 4 weeks. Cream and colleagues measured percent syllables stuttered (%SS) in four conversational speech samples (two pre-treatment and two at the end of the 4th week of treatment). They also had participants provide pre- and post-treatment severity ratings of their stuttering in 5 self-selected speaking situations. Severity ratings were made using a 9 point scale in which 1 = no stuttering and 9 = extreme stuttering. Mean percent syllables stuttered (%SS) for the group decreased by 5.4% with 9 of 10 participants achieving reductions in stuttering. Mean self-reported severity ratings decreased by 1.7. The effect sizes for reductions in both %SS and stuttering severity ratings were large. The authors reported that some of the participants disliked their use of speech restructuring techniques; for example, one participant criticized 11 productions of/d/in his video. Some participants also did not like their general appearance in their VSM videos. In view of the feedback provided by the participants, the authors suggested that collaborating with participants in producing the VSM videos in future research might improve outcomes.

In a randomized control trial with 89 adolescents and adults, Cream et al. (2010) explored the utility of VSM as a strategy to improve maintenance immediately following a 5-day intensive speech-restructuring treatment. Videos were constructed on the 4th day of the intensive program. Following participation in a speech-restructuring program (using either the La Trobe Smooth Speech Program or the Camperdown Program), participants were randomly assigned to a control or treatment group. The control group received the standard maintenance program which consisted of 7 individual and small group sessions in the clinic. The treatment group received VSM in addition to the standard maintenance program. In contrast to Cream et al. (2009), no significant differences between the treatment and control groups were found for %SS; however, the VSM group had significantly reduced total impact scores on the Overall Assessment of the Speaker's Experience of Stuttering used for adult participants (Yaruss & Quesal, 2006) and the Assessment of the Child's Experience of Stuttering (Yaruss, Coleman, & Quesal, 2006). In addition, compared to the control group, the VSM group reported significantly higher overall satisfaction with fluency. Satisfaction with fluency was rated using a nine-point scale (1 = extremely satisfied; 9 = extremely dissatisfied). The difference between the two groups was 0.8 scale values. Cream and colleagues speculated that methodological issues that may have contributed to the non-effects for reductions in %SS include (a) lack of motivation to view the videos due to the low levels of stuttering that participants were experiencing at the end of the intensive clinic, (b) lack of reinforcement for viewing the videos during the VSM treatment phase, and (c) collection of speech data only from phone samples which are among the most difficult of speaking situations.

The primary aim of this study was to assess the effectiveness of VSM as a self-administered fluency recovery tool for adults who were experiencing relapse or fluency regression after successfully completing a stuttering treatment program. Specifically, this study investigated improvements in stuttering frequency, perceptions of stuttering, self-efficacy, and locus of control. Secondary aims were to explore how participants used VSM and their perceived clinical utility of VSM.

To address the methodological issues raised by Webber et al. (2004) and Cream et al., 2009, Cream et al., 2010, we (a) recruited participants who had successfully completed prior speech-restructuring therapy to ensure that they had the ability to produce the techniques, (b) collaborated with participants in developing their VSM videos to ensure that they liked the sound of their speech and their appearance in the video, (c) developed six unique videos to prevent boredom and increase motivation to view videos, and (d) had weekly meetings with participants to discuss their viewing-logs and provide reinforcement for viewing videos. A multiple-baseline across participants design was used. The baseline phases for P1, P2 and P3 lasted for 3, 4 and 5 weeks, respectively.

Section snippets

Participants

Participants were three male adults who self-referred in response to information sent to a pool of clients who had demonstrated their ability to produce speech restructuring skills in previous treatment with the Comprehensive Stuttering Program (CSP) (Langevin, Teshima, Kully, Hagler, & Prasad, 2010). To be included in the study participants had to have completed the CSP within 6 years of the study; this criterion was set because we thought it would be more likely that participants who more

Composition of data points

Fig. 1 shows baseline and treatment data points. Weekly data points represented either all three conditions (i.e., face-to-face conversations with volunteers, phone calls with volunteers, and conversations with familiar listeners at home or work), two conditions, or, in the case of P3 for baseline week 2 and treatment weeks 4 and 5, a single condition. Missing data were due either to participants’ travel that precluded collection of all requested weekly face-to-face conversation and/or phone

Discussion

Overall, results suggest that VSM may be a viable fluency recovery tool for some adults who are experiencing relapse after having completed speech-restructuring treatments.

Conclusion

Given advancements in the availability and ease in using portable audio-visual technology, VSM appears to offer an economical and clinically useful tool for adults who stutter who are motivated to attend to the videos and apply the modeled behaviors.
CONTINUING EDUCATION
Video self-modeling as a post-treatment fluency recovery strategy for adults
QUESTIONS

  • 1.

    According to social cognitive learning theory, self-modeling enhances skill performance by:

    • (a)

      Demonstrating how to carry out the behavior and

Acknowledgements

This study was supported by a research grant from an anonymous donor group and operations grants from the Alberta and National Elks and Royal Purple. Neither funding agencies had involvement in this study. Jessica Harasym and Marilyn Langevin contributed equally to this study. We thank the participants, volunteers, and Paul Hagler, former Associate Dean of Research, Faculty of Rehabilitation Medicine, University of Alberta, who contributed to the design and execution of this study. We also

Jessica Harasym holds the Elks & Royal Purple Fund for Children Clinical Chair at the Institute for Stuttering Treatment and Research (ISTAR). Her clinical and research interests include stuttering treatment for children and adults who have complex needs, clinical application of video self-modeling, and telehealth delivery of stuttering treatment.

References (38)

  • M.A. Bray et al.

    Long-term follow-up of self-modeling as an intervention for stuttering

    School Psychology Review

    (2001)
  • M.A. Bray et al.

    Introduction to the special issue self-modeling: Self-modeling as a treatment for a myriad of issues

    Psychology in the Schools

    (2012)
  • P.L. Busk et al.

    Meta-analysis for single-case research

  • B.J. Byiers et al.

    Single-subject experimental design for evidence-based practice

    American Journal of Speech-Language Pathology

    (2012)
  • J.M. Campbell

    Efficacy of behavioral interventions for reducing problem behavior in persons with autism: A quantitative synthesis of single-subject research

    Research in Developmental Disabilities

    (2002)
  • E. Clark et al.

    Evaluation of the parameters of self-modeling interventions

    School Psychology Review

    (1992)
  • J. Cohen

    Statistical power analysis for the behavioral sciences

    (1988)
  • A.R. Craig et al.

    A scale to measure locus of control of behaviour

    British Journal of Medical Psychology

    (1984)
  • A. Cream et al.

    Self-modelling as a relapse intervention following speech restructuring treatment for stuttering

    International Journal of Language & Communication Disorders

    (2009)
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      Bandura (1997) suggested that self-modeling can improve self-believe, and this in turn can lead to improved fluency outcomes. For example, video self-modeling after speech restructuring treatment was linked with improvements in self-reporting outcomes (Cream et al., 2010; Harasym, Langevin, & Kully, 2015). A number of studies pertaining to stuttering treatments include both within-clinic and beyond-clinic measures (e.g., Bothe, Davidow, Bramlett, Franic, & Ingham, 2006; Bothe & Richardson, 2011; Curlee, 1993; Ingham & Cordes, 1999; Ingham & Costello, 1984; Ingham & Costello, 1985Ingham et al., 2012; James, 1981; Jones et al., 2005; Onslow, Costa, & Rue, 1990).

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    Jessica Harasym holds the Elks & Royal Purple Fund for Children Clinical Chair at the Institute for Stuttering Treatment and Research (ISTAR). Her clinical and research interests include stuttering treatment for children and adults who have complex needs, clinical application of video self-modeling, and telehealth delivery of stuttering treatment.

    Marilyn Langevin is Director of Research at the Institute for Stuttering Treatment and Research (ISTAR), Faculty of Rehabilitation Medicine, University of Alberta. Her research and clinical interests include the impact of stuttering on preschool and school-age children, evidence-based treatment and clinical training practices, and neural function associated with stuttering.

    Deborah Kully is Co-founder of the Institute for Stuttering Treatment (ISTAR) and former Executive Director of ISTAR and Associate Professor in the Department of Speech Pathology and Audiology, University of Alberta. She retired from the University of Alberta in 2011.

    1

    These authors contributed equally to this study.

    2

    Now at: 12409 28A Avenue, Edmonton, AB T6J 4L5, Canada.

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