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Table 1.  
Summary of Categorical Variablesa
Summary of Categorical Variablesa
Table 2.  
Correlation Analysesa
Correlation Analysesa
Table 3.  
Demographic Characteristicsa
Demographic Characteristicsa
Table 4.  
Coefficients for Final Regression Model
Coefficients for Final Regression Model
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Chen  SC, Yu  PJ, Hong  MY,  et al.  Communication dysfunction, body image, and symptom severity in postoperative head and neck cancer patients: factors associated with the amount of speaking after treatment.  Support Care Cancer. 2015;23(8):2375-2382.PubMedGoogle ScholarCrossref
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Nund  RL, Rumbach  AF, Debattista  BC,  et al.  Communication changes following non-glottic head and neck cancer management: the perspectives of survivors and carers.  Int J Speech Lang Pathol. 2015;17(3):263-272.PubMedGoogle ScholarCrossref
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Baylor  C, Yorkston  K, Bamer  A, Britton  D, Amtmann  D.  Variables associated with communicative participation in people with multiple sclerosis: a regression analysis.  Am J Speech Lang Pathol. 2010;19(2):143-153.PubMedGoogle ScholarCrossref
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Ringash  J, Bernstein  L, Cella  D,  et al Outcomes toolbox for head and neck cancer research.  Head Neck. 2015;37(3):425-439. PubMedGoogle ScholarCrossref
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Baylor  C, Yorkston  K, Eadie  T, Kim  J, Chung  H, Amtmann  D.  The Communicative Participation Item Bank (CPIB): item bank calibration and development of a disorder-generic short form.  J Speech Lang Hear Res. 2013;56(4):1190-1208.PubMedGoogle ScholarCrossref
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Campbell  BH, Marbella  A, Layde  PM.  Candidate's thesis: quality of life and recurrence concern in survivors of head and neck cancer.  Laryngoscope. 2000;110(6):895-906. PubMedGoogle ScholarCrossref
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Funk  GF, Karnell  LH, Christensen  AJ.  Long-term health-related quality of life in survivors of head and neck cancer.  Arch Otolaryngol Head Neck Surg. 2012;138(2):123-133.PubMedGoogle ScholarCrossref
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Baylor  C, Yorkston  K, Eadie  T, Miller  R, Amtmann  D.  Levels of speech usage: a self-report scale for describing how people use speech.  J Med Speech Lang Pathol. 2008;16(4):191-198.PubMedGoogle Scholar
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Gray  C, Baylor  C, Eadie  T, Kendall  D, Yorkston  K.  The Levels of Speech Usage rating scale: comparison of client self-ratings with speech pathologist ratings.  Int J Lang Commun Disord. 2012;47(3):333-344.PubMedGoogle ScholarCrossref
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Hays  RD, Bjorner  JB, Revicki  DA, Spritzer  KL, Cella  D.  Development of physical and mental health summary scores from the patient-reported outcomes measurement information system (PROMIS) global items.  Qual Life Res. 2009;18(7):873-880.PubMedGoogle ScholarCrossref
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Gershon  RC, Lai  JS, Bode  R,  et al.  Neuro-QOL: quality of life item banks for adults with neurological disorders: item development and calibrations based upon clinical and general population testing.  Qual Life Res. 2012;21(3):475-486.PubMedGoogle ScholarCrossref
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Weymuller  EA  Jr, Alsarraf  R, Yueh  B, Deleyiannis  FW, Coltrera  MD.  Analysis of the performance characteristics of the University of Washington Quality of Life instrument and its modification (UW-QOL-R).  Arch Otolaryngol Head Neck Surg. 2001;127(5):489-493.PubMedGoogle ScholarCrossref
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Dormann  CF, Elith  J, Bacher  S,  et al.  Collinearity: a review of methods to deal with it and a simulation study evaluating their performance.  Ecography. 2013;36(1):27-46.Google ScholarCrossref
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Fung  K, Lyden  TH, Lee  J,  et al.  Voice and swallowing outcomes of an organ-preservation trial for advanced laryngeal cancer.  Int J Radiat Oncol Biol Phys. 2005;63(5):1395-1399.PubMedGoogle ScholarCrossref
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Stewart  MG, Chen  AY, Stach  CB.  Outcomes analysis of voice and quality of life in patients with laryngeal cancer.  Arch Otolaryngol Head Neck Surg. 1998;124(2):143-148.PubMedGoogle ScholarCrossref
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Terrell  JER, Ronis  DL, Fowler  KE,  et al.  Clinical predictors of quality of life in patients with head and neck cancer.  Arch Otolaryngol Head Neck Surg. 2004;130(4):401-408.PubMedGoogle ScholarCrossref
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Gan  HK, Bernstein  LJ, Brown  J,  et al.  Cognitive functioning after radiotherapy or chemoradiotherapy for head-and-neck cancer.  Int J Radiat Oncol Biol Phys. 2011;81(1):126-134.PubMedGoogle ScholarCrossref
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Moynihan  TJ, Ness  SM. Chemo brain: symptoms. Diseases and conditions2013; http://www.mayoclinic.org/diseases-conditions/chemo-brain/basics/symptoms/con-20033864. Accessed June 10, 2016.
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Original Investigation
From the American Head and Neck Society
December 2016

Variables Associated With Communicative Participation After Head and Neck Cancer

Author Affiliations
  • 1Department of Speech and Hearing Sciences, University of Washington, Seattle
  • 2Department of Otolaryngology–Head and Neck Surgery, University of Washington, Seattle
  • 3Department of Rehabilitation Medicine, University of Washington, Seattle
 

Copyright 2016 American Medical Association. All Rights Reserved.

JAMA Otolaryngol Head Neck Surg. 2016;142(12):1145-1151. doi:10.1001/jamaoto.2016.1198
Key Points

Question  Which variables are significantly associated with communicative participation outcomes in adults with head and neck cancer?

Findings  In this study of 197 survey respondents, 4 significant variables emerged—self-rated speech severity, cognitive function, laryngectomy status, and time since diagnosis—making up 46% of the variance in the model.

Meaning  Better communicative participation was associated primarily with less severe speech and cognitive problems and, to a lesser extent, with not having undergone a total laryngectomy surgical procedure and longer time since diagnosis.

Abstract

Importance  For patients with head and neck cancer (HNC), communication difficulties often create substantial barriers in daily life, affecting a person’s ability to return to work, establish or maintain relationships, or participate in everyday activities.

Objective  To examine variables significantly associated with communication in everyday activities, or communicative participation, in adult survivors of HNC.

Design, Setting, and Participants  In a cross-sectional study, from November 1, 2008, through March 18, 2011, participants completed questionnaires about specific experiences and symptoms associated with their health and communication. Seventeen variables were considered in association with communicative participation. Data were collected from adult survivors of HNC residing in a community. Participants completed questionnaires, in English, either online or using paper forms according to their preference. Participants were recruited through support groups, professional email lists, and professional contacts.

Main Outcomes and Measures  Communicative participation and predictor variables were measured using a variety of validated patient-report scales and demographic information. Multiple linear regression analysis was conducted with variables entered using a backward stepwise regression procedure. Variables with significant regression coefficients were retained in the model and reported as change in R2.

Results  One hundred ninety-seven adults (121 males and 76 females; mean age, 61.5 years) participated, all at least 6 months posttreatment of HNC with no additional medical conditions affecting speech. The final model contained 4 significant variables (R2 = 0.462): self-rated speech severity, cognitive function, laryngectomy status, and time since diagnosis. Better communicative participation was associated with less severe speech and cognitive problems; together, these 2 variables explained 42% of the variance in the model (self-rated speech severity, R2 = 0.227, and cognitive function, R2 = 0.193 [0.227 + 0.193 = 0.420 = 42%]). To a lesser extent, better communicative participation also was associated with not having undergone a total laryngectomy surgical procedure (R2 = 0.035) and longer time since diagnosis (R2 = 0.007); full model: R2 = 0.462, P < .001; regression coefficients [SE]: self-rated speech severity 0.551 [0.065], P < .001, R2 = 0.227; cognitive function 0.063 [0.011], P < .001, R2 = 0.193; laryngectomy status 0.285 [0.117], P = .02; and time since diagnosis 0.015 [0.006], P = .02.

Conclusions and Relevance  These results suggest that communicative participation in adults with HNC is associated with self-rated speech severity, cognitive function, whether or not a person has undergone total laryngectomy, and time since diagnosis. Clinicians can use these results to inform their practice in pretreatment counseling, patient education, and rehabilitation for survivors of HNC.

Introduction

According to the American Cancer Society,1 an estimated 59 000 new cases of head and neck cancer (HNC) were diagnosed in the United States in 2015. Treatments for HNC often result in alterations to structures of the speech and/or voice mechanism. Consequently, survivors of HNC frequently have difficulties with verbal communication. In fact, among HNC survivors, speech outcomes are the strongest predictor of overall health-related quality of life,2 inhibiting a person’s ability to return to work, establish or maintain relationships, or participate in everyday activities. Communication in everyday activities, or communicative participation, has emerged in recent years as a meaningful patient-reported outcome.3

Communicative participation has been defined as “taking part in life situations where knowledge, information, ideas, or feelings are exchanged.”4(p310) The most obvious barriers to communicative participation in patients with HNC may be associated with changes in voice quality and reduced speech intelligibility. However, research showed that clinician ratings of these factors are only weakly to moderately associated with communicative participation in this population.5 In fact, communicative participation has been associated with many factors beyond speech and voice function. For example, treatment-related variables, such as tumor site (eg, laryngeal and hypopharyngeal), as well as physical symptoms, such as xerostomia, hearing loss, and poor dentition, may negatively affect communication in HNC.6,7 A few studies also have shown that factors associated with the person, such as changes in body image, and factors associated with the environment, such as social support, affect communication after HNC.6,7

Research in other patient populations, such as those having multiple sclerosis, has revealed the effect of multiple environmental (eg, social support, familiarity of communication partners, and background noise) and personal (eg, age, sex, educational background, coping strategies, and cognitive function) factors on communicative participation.8 Together, the results suggest that communicative participation is a complex construct with many potential contributing variables. Yet, to our knowledge, there are no quantitative studies exploring the many variables that may contribute to communicative participation in survivors of HNC. This is an especially important area of investigation in HNC, in which there is a wide range of concerns.9 Identifying these variables would have implications for counseling as well as providing targets for rehabilitation.

The purpose of this study, therefore, was to examine variables that are significantly associated with communicative participation in adults with HNC. We hypothesized that for survivors of HNC, communicative participation would be significantly associated with multiple variables that include, but also extend beyond, overt communication symptoms. These variables include demographic (eg, age and education), personal (eg, emotional distress and use of speech), and physical and/or functional symptoms (eg, swallowing difficulties, hearing loss, and speech severity) known to be of concern in HNC.9

Methods

All procedures for this cross-sectional study were approved by the Institutional Review Board at the University of Washington, Seattle. All study participants provided written, informed consent in English.

Participants

Participants were recruited through support groups, professional email lists, and professional contacts as part of a larger investigation of the Communicative Participation Item Bank (CPIB).10 All participants were adults (≥18 years), residing in a community, who had completed treatment of HNC at least 6 months before their participation. The 6-month inclusion criterion was selected to ensure that all participants had lived with the consequences of HNC long enough to have experienced a wide range of communication situations and how it affected daily communication, as well as to avoid the fluctuation in scores that may occur immediately posttreatment.11 All were able to complete the questionnaires in English and reported no additional medical conditions (beyond HNC) that affected their speech. Participants were paid $20 for completing a series of questionnaires.

Data Collection

Using a series of self-reported questionnaires, participants answered questions about specific experiences and symptoms associated with their health and communication, known to influence outcomes in HNC survivors.12 Questionnaires were administered either using paper forms or online through a secure website according to participant preference. Participants who did not complete the questionnaires within 3 weeks were contacted once for follow-up. Seventeen variables, described below, were included in the analysis because they are associated with communicative participation.

Communicative participation was measured using the CPIB.10 The CPIB asks participants to rate how much their condition (ie, HNC) interferes with communication in everyday situations (eg, making a telephone call to get information). Ratings range from “not at all” to “very much” on a 4-point Likert-type scale. The CPIB was calibrated using item response theory that, as the name implies, draws on the properties of individual items to measure latent traits.13 Summary scores are converted either to logits, with scores typically ranging from −3.0 to 3.0 logits (M = 0), or to T-scores (M = 50 and SD = 10). In both scoring systems, the mean is the average of the calibration sample used when developing the CPIB. Higher scores represent better communicative participation. The CPIB has possessed strong psychometric properties in multiple communication disorders, including HNC.3,10

Variables associated with demographic information and medical history consisted of age, sex, living situation, educational level, employment status, cancer location, time since diagnosis, laryngectomy status, and history of hearing loss. Self-rated speech severity was reported using a single item from the Amyotrophic Lateral Sclerosis Functional Rating Scale–Revised.14 Although originally designed to measure physical function in the daily lives of patients with amyotrophic lateral sclerosis, the questions pertain to a range of issues common to a variety of patient populations, including those with HNC.

Use of speech was measured with the Levels of Speech Usage rating scale.15,16 Consisting of a single item, participants chose 1 of 5 categories15 to describe the demands placed on their speech in daily activities.

Fatigue, pain, physical activity, and emotional distress were measured with single items from the Patient-Reported Outcome Measurement Information System global health instrument (http://www.nihpromis.org).17 These items are detailed in Table 1.

Cognitive symptoms were measured using a custom set of 8 items from the Neuro-QoL (quality of life in neurological disorders) item bank (http://www.healthmeasures.net/explore-measurement-systems/neuro-qol); these items were used with permission before publication of the finalized cognitive function instrument.18 Participants rated the level of difficulty performing tasks associated with memory, reading, writing, and problem solving. Ratings were made on a 5-point Likert-type scale, ranging from none to cannot do. Scoring for custom sets of items from the Neuro-QoL item bank is not currently available. Summary scores are reported in this article (possible range, 8-40), with higher scores reflecting a higher level of self-reported cognitive function.

Swallowing difficulties were described using a single item from the University of Washington Quality of Life questionnaire.19 Designed specifically to measure health-related quality of life in people with HNC, swallowing difficulties are categorized in 4 ways: normal, cannot swallow certain foods, can swallow only liquids, or cannot swallow.

Statistical Analysis

Before conducting the regression analyses, correlation analyses were performed to exclude potential multicollinearity among communicative participation and the 17 variables. Any variables with correlations greater than 0.70 would be considered for removal. This threshold has effectively indicated the point at which model estimation and subsequent prediction can be severely distorted by multicollinearity.20 Pearson product moment correlations were used for the continuous (interval) level data, whereas Spearman rank correlations were used for the categorical data (ordinal and nominal) (Table 2). Because no correlations were greater than the cutoff of 0.70, all variables were retained for entry into the regression analysis.

The associations of the 17 variables with communicative participation were examined with multiple linear regression analysis in SPSS, version 18.0 (IBM). Communicative participation, age, time since diagnosis, and self-reported cognitive function were continuous variables; all others were categorical variables. Throughout the process of backward stepwise regression, model fit was analyzed with an overall regression F statistic. Individual variables with regression coefficients significant at P < .05 were retained in the model.

Results
Participants

Of 242 questionnaires provided to potential participants, 197 were completed and returned (response rate of 81.4%). The mean (SD) age of the respondents was 61.5 (12.3) years (range, 24-86 years). The mean (SD) time since cancer diagnosis was 8.4 (8.1) years (range, 0-45 years). Most participants were male (121 [61.4%]), which is consistent with HNC prevalence data.1 Additional demographic information is shown in Table 3.

Predictors of Communicative Participation

The mean logit score for communicative participation in this sample was 0.330 (SD, 0.948). The range was −2.503 to 2.607 logits, suggesting a broad range of experiences across the participants. The mean (SD) summary score for cognitive function in this sample was 35.2 (4.9), with a range of 16 to 40. Descriptive results for categorical variables included in this study are described in Table 1.

Initial analysis with backward stepwise linear regression resulted in a model containing only self-rated speech severity and cognitive function (R2 = 0.425). A histogram of the residuals approximated a normal distribution, showing random distribution of the residuals. A scatterplot comparing Cook’s distance and centered leverage values revealed 3 potential outliers. These 3 data points were removed, and the regression analysis was repeated. During the subsequent analysis, variables were removed from the model in the following order: educational level, cancer location, physical activities, pain, fatigue, sex, use of speech, employment, living situation, swallowing problems, emotional distress, age, and hearing loss. The resulting model contained 4 variables: self-rated speech severity, self-rated cognitive function, laryngectomy status, and time since diagnosis (R2 = 0.462) (Table 4). A histogram of the residuals again approximated a normal distribution. Consistent with the initial analysis, better communicative participation was associated with less severe speech and cognitive problems; together, these 2 variables composed 42.0% of the variance in the model, as shown in Table 4: self-rated speech severity change in R2 = 0.227 and cognitive function change in R2 = 0.193 (0.227 + 0.193 = 0.420 = 42% variance explained). To a lesser extent, but still statistically significant, better communicative participation was also associated with not having undergone a total laryngectomy surgical procedure and longer time since diagnosis.

Discussion

The results of this study suggest that communicative participation in adults with HNC is associated with self-rated speech severity, self-rated cognitive function, time since diagnosis, and whether or not a person has undergone a total laryngectomy surgical procedure. Of these variables, 3 were hypothesized a priori as being potential predictors of communicative participation. First, self-rated speech severity and laryngectomy status are directly linked to speech function and quality, and prior research showed that speakers with increased speech difficulties have worse communicative participation in other patient populations.8 In HNC, speech and voice difficulties are commonly encountered because of surgical resection or radiation effects on the function of structures in the vocal tract.9 Several researchers also have noted lower levels of function after total laryngectomy for voice-related quality of life when compared with laryngeal preservation or partial laryngectomy procedures, which is consistent with the present results (laryngectomy status as the final, albeit weak, predictor).21,22 Second, self-rated difficulties in speech and voice have been more strongly associated with communicative participation than clinician-rated severity.5 Thus, results from the present study are consistent with prior research and show the direct association between speech severity and communicative participation, predicting 22.7% of the variance in scores (change in R2 = 0.227; b = 0.551 [SE, 0.065]; P < .001).

Beyond speech and voice impairments, we also predicted that time since diagnosis would be associated with communicative participation outcomes. Prior research supports the idea that quality of life improves over time as people adapt to a new normal.23 This variable also has been positively associated with other outcomes in HNC.23

Finally, it is notable that self-reported cognitive function emerged as the second strongest predictor of communicative participation, with 19.3% of the variance predicted (change in R2 = 0.193; b = 0.063 [SE, 0.011]; P < .001). This variable was not hypothesized to be an a priori predictor because cognitive symptoms have not traditionally been considered in HNC. To date, and to our knowledge, only 1 study24 has investigated and found objective evidence of cognitive dysfunction in this population.

Cognitive changes associated with HNC are not well understood but have been well established in other cancer populations. For example, in women with breast cancer, the most commonly reported cognitive deficits occur in the areas of memory, attention, executive function, and processing speed.25 Together, these deficits compose the phenomenon that patients and survivors frequently refer to as “chemo brain.”26 Although commonly attributed to adverse effects of various chemotherapeutic agents, cognitive deterioration has been reported in patients with various types of cancer who did not receive chemotherapy, suggesting that cognitive changes may be caused by irradiation, a surgical procedure, and even the body’s natural response to the cancer.27,28 Because of this, the term cancer-related cognitive impairment has emerged. Deficits in memory, word finding, and processing speed may lead to difficulty participating in conversations, particularly in groups, and may result in avoidance of conversations in multiple contexts.8,29,30 This avoidance can create a substantial barrier for survivors as they return to work and participate in other activities posttreatment. The possibility of the struggle with cognitive symptoms is also of considerable importance for the rehabilitation process after HNC. Patients often are managing complex medical routines and are provided with considerable information to understand and remember without concern for cognitive status because HNC is not typically associated with cognitive problems. The results of this study, however, suggest that patients may indeed be struggling with cognitive issues more than previously appreciated.

Because HNC is most commonly diagnosed in people older than 55 years,31 it may be difficult to differentiate cancer-related cognitive impairment from typical age-related cognitive changes. Although the mean age of participants in this study (61.5 years) is consistent with population data reported by the National Cancer Institute,31 the rate of HNC associated with human papillomavirus continues to multiply in an increasingly younger population.32 No inferences should be made from the summary scores reported here regarding population norms of cognitive function. Further study is needed, including measures before and after treatment, to explore the nature and prevalence of cognitive change in this population.

There were a few limitations to this study. It should be noted that 122 (62%) of the participants indicated that they had undergone a total laryngectomy surgical procedure. Although this number may limit the ability to generalize these results to the larger HNC population, laryngectomy status made up only 3.5% of the variance in the final model (change in R2 = 0.035; b = 0.285 [SE, 0.117]; P = .02). In addition, cancer site did not enter as a significant predictor variable. Together, these results suggest that, at least among the current participants, results were representative. Another limitation of this study is that speech severity, along with several other potential predictor variables, was measured using a single item. In all cases, these single items were global items that correlate with multi-item scales. These items evaluate function in broad yet essential terms. They provide insight into the participants’ core perceptions, but further research is needed to examine the nature of these perceptions and identify potential therapeutic targets. This study used only self-reported data. Future research should investigate the association between communicative participation and variables, such as speech or cognitive severity, when measured objectively or using other perspectives, such as clinician-directed measures, and how these modalities compare. In addition, other variables that predict communicative participation need to be identified. These variables could include severity of comorbid ailments or even social factors. For example, whereas living alone did not emerge as a predictor in the present study, other factors associated with the environment, such as social support, are important for HNC survivors.7 In addition, personal factors, such as coping strategies, may be stronger predictors of communicative participation than age or sex, as explored in the present study. All of these factors warrant further consideration in future research.

Conclusions

The results of this study highlight the importance of speech function and quality in communicative participation outcomes after HNC. These results also show an association between cognitive function and communicative participation in this population. Clinicians can use these results to inform their practice in pretreatment counseling, patient education, and rehabilitation for survivors of HNC. Future research may lead to the development of new interventions to maximize communication outcomes and help survivors of HNC achieve their life goals.

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Article Information

Accepted for Publication: May 23, 2016.

Corresponding Author: Susan Bolt, MSP, Department of Speech and Hearing Sciences, University of Washington, Seattle, 1417 NE 42nd St, Eagleson Hall, PO Box 354875, Seattle, WA 98105 (bolts@uw.edu).

Published Online: July 21, 2016. doi:10.1001/jamaoto.2016.1198

Author Contributions: Dr Baylor and Ms Bolt had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Eadie, Yorkston, Baylor, Amtmann.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Bolt, Eadie, Baylor.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Baylor, Amtmann.

Obtained funding: Eadie, Yorkston, Baylor, Amtmann.

Administrative, technical, or material support: Baylor, Yorkson.

Study supervision: Eadie.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.

Funding/Support: This study was supported by grants R03CA132525 and R01CA177635 from the National Institutes of Health, National Cancer Institute and grant R03DC010044 from the National Institute on Deafness and Other Communication Disorders and the University of Washington Speech & Hearing Sciences Vocal Function Laboratory. No other disclosures were reported.

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Previous Presentation: This study was presented at the American Head & Neck Society Ninth International Conference on Head and Neck Cancer; July 18, 2016; Seattle, Washington.

References
1.
American Cancer Society.  Cancer Facts & Figures 2015. Atlanta, GA: American Cancer Society; 2015.
2.
Karnell  LH, Funk  GF, Hoffman  HT.  Assessing head and neck cancer patient outcome domains.  Head Neck. 2000;22(1):6-11.PubMedGoogle ScholarCrossref
3.
Eadie  TL, Lamvik  K, Baylor  CR, Yorkston  KM, Kim  J, Amtmann  D.  Communicative participation and quality of life in head and neck cancer.  Ann Otol Rhinol Laryngol. 2014;123(4):257-264.PubMedGoogle ScholarCrossref
4.
Eadie  TL, Yorkston  KM, Klasner  ER,  et al.  Measuring communicative participation: a review of self-report instruments in speech-language pathology.  Am J Speech Lang Pathol. 2006;15(4):307-320.PubMedGoogle ScholarCrossref
5.
Eadie  TL, Otero  D, Cox  S,  et al.  The relationship between communicative participation and postlaryngectomy speech outcomes.  Head Neck. 2016;38(suppl 1):E1955-E1961.PubMedGoogle ScholarCrossref
6.
Chen  SC, Yu  PJ, Hong  MY,  et al.  Communication dysfunction, body image, and symptom severity in postoperative head and neck cancer patients: factors associated with the amount of speaking after treatment.  Support Care Cancer. 2015;23(8):2375-2382.PubMedGoogle ScholarCrossref
7.
Nund  RL, Rumbach  AF, Debattista  BC,  et al.  Communication changes following non-glottic head and neck cancer management: the perspectives of survivors and carers.  Int J Speech Lang Pathol. 2015;17(3):263-272.PubMedGoogle ScholarCrossref
8.
Baylor  C, Yorkston  K, Bamer  A, Britton  D, Amtmann  D.  Variables associated with communicative participation in people with multiple sclerosis: a regression analysis.  Am J Speech Lang Pathol. 2010;19(2):143-153.PubMedGoogle ScholarCrossref
9.
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