Elsevier

Journal of Communication Disorders

Volume 44, Issue 4, July–August 2011, Pages 429-443
Journal of Communication Disorders

Quality of life in adults who stutter

https://doi.org/10.1016/j.jcomdis.2011.02.002Get rights and content

Abstract

Although persistent developmental stuttering is known to affect daily living, just how great the impact is remains unclear. Furthermore, little is known about the underlying mechanisms which lead to a diminished quality of life (QoL). The primary objective of this study is to explore to what extent QoL is impaired in adults who stutter (AWS). In addition, this study aims to identify determinants of QoL in AWS by testing relationships between stuttering severity, coping, functioning and QoL and by testing for differences in variable scores between two AWS subgroups: receiving therapy versus not receiving therapy. A total of 91 AWS filled in several questionnaires to assess their stuttering severity, daily functioning, coping style and QoL. The QoL instruments used were the Health Utility Index 3 (HUI3) and the EuroQoL EQ-5D and EQ-VAS. The results indicated that moderate to severe stuttering has a negative impact on overall quality of life; HUI3 derived QoL values varied from .91 (for mild stuttering) to .73 (for severe stuttering). The domains of functioning that were predominantly affected were the individual's speech, emotion, cognition and pain as measured by the HUI3 and daily activities and anxiety/depression as measured by the EQ-5D. AWS in the therapy group rated their stuttering as more severe and recorded more problems on the HUI3 speech domain than AWS in the non-therapy group. The EQ-VAS was the only instrument that showed a significant difference in overall QoL between groups. Finally, it was found that the relationship between stuttering severity and QoL was influenced by the individual's coping style (emotion-oriented and task-oriented). These findings highlight the need for further research into stuttering in relation to QoL, and for a broader perspective on the diagnosis and treatment of stuttering, which would take into consideration quality of life and its determinants.

Learning outcomes: Readers will be able to: (1) Understand how the Wilson and Cleary (1995) model of quality of life could be applied to comprehensively assess the quality of life in adults who stutter, (2) describe how health related quality of life is impaired in adults who stutter, (3) mention affected domains of functioning that are related to health related quality of life impairment in adults who stutter, (4) describe the relationship between stuttering severity, functioning, coping and health related quality of life in adults who stutter, (5) describe differences in stuttering severity, coping style, functioning and health related quality of life between adults who stutter who have registered for therapy and adults who stutter who have not.

Highlights

► We studied the overall quality of AWS in a comprehensive manner. ► Moderate to severe stuttering had a negative impact on overall quality of life. ► Affected domains of functioning were speech, emotion, cognition and pain (HUI3) and daily activities and anxiety/depression (EQ-5D). ► The relationship between stuttering severity and QoL was influenced by coping style. ► AWS registered for therapy rated their stuttering as more severe, recorded more problems on the HUI3 speech domain and had a lower EQ-VAS QoL score than AWS in the non-therapy group.

Introduction

How stuttering affects the overall quality of life (QoL) of adults who stutter (AWS) has not yet been extensively researched. This is surprising since about 1% of the adult population stutters (Bloodstein & Bernstein-Ratner, 2008) and because it is known that AWS often experience negative affective, behavioral, and cognitive reactions. Moreover, stuttering significantly limits the speaker's ability to participate in daily activities (Yaruss & Quesal, 2006). AWS frequently experience disabling levels of social anxiety (Kraaimaat et al., 2002, Messenger et al., 2004, Schneier et al., 1997). Whether this occurs, depends on their fear of a negative evaluation in social relations because of their stuttering, and whether or not they act upon that fear by adoption of a strategy of avoidance (Menzies, Onslow, Packman, & O’Brian, 2009). Recognizing the complexity of the stuttering disorder in adults, researchers have established the need to document not only speech symptoms, but also broad-based outcome parameters such as QoL (e.g. Craig et al., 2009, Franic and Bothe, 2008, Ingham, 2003, Yaruss and Quesal, 2006). Recently, a special edition of the Journal of Fluency Disorders dedicated to the QoL of people who stutter also raised awareness for the topic (e.g. Craig, 2010, Cruice et al., 2010, Yaruss, 2010). Until now, the magnitude of and mechanisms underlying the QoL effects of stuttering in adults have not been fully explored. The purpose of this study is to evaluate QoL in AWS by means of a comprehensive assessment.

A review of existing literature with respect to the QoL in AWS revealed that the majority of studies use a narrow conceptualization of QoL. That is, most studies investigated the QoL of AWS by focusing on the influence that stuttering has on the specific life domains which are believed to be most affected by stuttering (e.g. Andrade et al., 2008, Crichton-Smith, 2002, Hayhow et al., 2002, Klein and Hood, 2004, Klompas and Ross, 2004). For example, Hayhow et al. (2002) showed the major adverse effects of stuttering on school life and occupational choice. The negative impact of stuttering on school performance, relationships with teachers and classmates, and performance at work was confirmed by Klompas and Ross (2004), who interviewed 16 AWS. Klein and Hood (2004) found that the majority of the AWS perceived their stuttering to be a handicap in relation to employment opportunities and job performance. By exploring specific life domains potentially affected by the condition stuttering, these studies provide significant, but only limited, information on QoL. A disadvantage of such condition-specific QoL studies is that little insight is gained into the overall QoL (e.g. Brazier et al., 2007, Craig et al., 2009, Franic and Bothe, 2008). In other words, although these studies provide insight into problems associated with stuttering, not all aspects of QoL relevant to a person are taken into account. In addition, due to the incorporation of dissimilar domains, condition-specific QoL instruments cannot be used to compare different health conditions.

In contrast to condition-specific QoL instruments, generic QoL instruments embrace a broad conceptualization of QoL by measuring a comprehensive set of domains. A common element in these generic QoL instruments is the incorporation of physical, emotional and social domains of health. These domains are relevant for anyone, irrespective of the specific health problem. As a result, generic QoL instruments are suitable for comparison of stuttering to other health states. Well-known examples are the Medical Outcomes Study Short Form 36-Item Health Survey (SF-36) and the Nottingham Health Profile (NHP). A limitation of these descriptive generic QoL instruments is that they do not quantify how each dimension contributes to overall well-being. That is, if some domains are significantly affected but others are not, the effect on overall QoL cannot be established. To overcome this problem, QoL researchers frequently move beyond a multidimensional generic description of health by attaching a single value to the overall health status (Brazier et al., 2007). This value or ‘utility’ summarizes all the positive and negative aspects of health into one single QoL index, which is usually set between 0, which corresponds to a health state valued as equivalent to death, and 1, which corresponds to perfect health. Such QoL values can be established in two ways. Firstly, health states can be estimated by using validated ‘preference based’ techniques (Torrance, Furlong, & Feeny, 2002): Visual Analogue Scale (VAS), Time Trade-Off (TTO) or Standard Gamble (SG). Alternatively, a special class of generic QoL instruments can be used, for which QoL values are available for all health states described by the instrument (Coons, Rao, Keininger, & Hays, 2000). Well known examples are the EQ-5D, Health Utilities Index (HUI) and the SF-6D (derived from the SF-36 by Brazier, Roberts, & Deverill, 2002).

So far, only two studies have attempted to gain insight into overall QoL of AWS by using generic QoL instruments or by preference based techniques. Craig et al. (2009) used the SF-36 to explore the negative impact caused by stuttering in a population of AWS and adults who do not stutter (AWNS). The authors showed that, compared to a non-stuttering control group, stuttering affects social and emotional functioning, as well as vitality and mental health status. The effect sizes (standardised mean difference between the groups) on these domains varied between .28 and .59, indicating small to moderate QoL impairments in AWS. Because the associated SF-6D utilities were not reported by Craig et al. (2009), the effect on overall QoL remains unclear. The study by Bramlett, Bothe, and Franic (2006) is the only study that we are aware of that adopted a preference based approach to estimate utilities. Bramlett et al. (2006) obtained overall QoL values for mild, moderate and severe stuttering from 75 AWNS using the three validated preference based techniques mentioned before: VAS, TTO and SG. The results suggested that QoL is negatively affected by stuttering. Using the TTO method, non-stuttering adults valued their own health at .98 (SD .07), while they rated mild, moderate and severe stuttering at respectively .93 (SD .14), .85 (SD .18) and .63 (SD .24) (Bramlett et al., 2006, Table 2). Considering that a QoL weight of .63 has been found for living with home dialysis (Sackett and Torrance, 1978 in Bramlett et al., 2006), the results suggest that severe stuttering has a substantial impact on a person's overall QoL. However, the differences in QoL values between methods were substantial: VAS and SG resulted in QoL values of .44 (SD .20) and .81 (SD .19) respectively for severe stuttering. In addition, the applied methods provided little or no insight into the determinants (i.e., the underlying mechanisms) that lead to QoL impairments.

Thus the purpose of this study is to explore to what extent overall QoL is impaired in AWS and to investigate the determinants of such QoL impairment. Based on the conceptualization of QoL by Wilson and Cleary (1995), the determinants measured in this study are stuttering severity, functioning and coping. Differences in stuttering severity, functioning, coping and QoL are examined between AWS who were in therapy and those who were not. Both groups are included because we hypothesize that studying QoL solely in a clinical population might lead to observing a greater reduction in QoL than when also taking into account the QoL of AWS who do not seek therapy. In terms of impaired quality of life, AWS who present themselves to a clinic might be those who are most severely affected by their condition. This could either be because their level of stuttering is more severe or because they have poorer coping skills and are more bothered by the effect of stuttering on their social interactions. Busschbach, Rikken, Grobbee, De Charro, and Wit (1998) observed a lower QoL for adults with a short stature who had presented themselves to a clinic compared with a population based sample of short adults. It is thus considered important to include both AWS who were in therapy and AWS who were not in order to account for variability in the determinant variables of QoL in both groups and to provide a broad view of QoL. These insights could provide valuable support in designing possible starting-points for diagnosis, therapy, and measuring end points in clinical trials (Guyatt et al., 1997, Guyatt et al., 1989).

Section snippets

Conceptualization of QoL

The empirical evaluation of QoL in AWS in this study is based on the theoretical conceptualization of QoL published by Wilson and Cleary (1995). This conceptual framework shows how different health measures can be combined to constitute a broad assessment of QoL. This section will explain how the QoL model extracted from the original Wilson and Cleary (1995) model is built up.

The core of the model (Fig. 1) is the relationship between symptoms, functioning and general health perception, the

Operationalization of QoL in AWS

This section indicates and motivates the selection of instruments for the operationalization of the Wilson and Cleary (1995) model in this study. The instruments will be described in more detail in Section 4.3.

Participants

The study population consisted of AWS who were not receiving therapy and AWS who either had just started therapy or were on a waiting list for therapy at the time of the investigation. AWS in therapy (the T group) were recruited from 14 stuttering and/or speech and language therapy centres throughout the Netherlands and from a family system therapy program for persons who stutter. AWS not receiving treatment (the NT group) were recruited informally, by asking relatives and acquaintances of the

Characteristics of participants and response rate

A total of 91 AWS participated in this study: 38 AWS in the NT group and 53 AWS in the T group (Table 1). Significant group differences were found for age (t(89) = 2.390, p = .019) and gender (χ2(1) = 4.670, p = .031). The response rate for the NT group contacted informally was 92%. In addition, four people responded to the appeal on the Hyves-stuttering website. Two of them were added to the NT group. The other two people were currently in treatment, and consequently added to the T group. Twenty-nine

Discussion

The objectives of the present study were (1) to investigate to what extent QoL is impaired in AWS and (2) to identify determinants of QoL in AWS. The latter was pursued by exploring relationships between stuttering severity, coping, functioning and QoL and by testing for differences in variable scores in two subgroups: the NT group and the T group. The results of this study show that stuttering severity affects overall QoL considerably. HUI3 derived QoL values were .91 for mild stuttering and

Acknowledgments

We would like to thank all adults who stutter who have participated in this study. Furthermore, we would like to thank all the participating clinicians and ‘Stichting Support Stotteren’ for their active contribution to the collection of the data in this project. Lastly we would like to thank the anonymous reviewers for their constructive feedback on earlier versions of this paper.

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