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Factors Affecting Initiation of Voice Therapy for Paradoxical Vocal Fold Motion Disorder
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Factors Affecting Initiation of Voice Therapy for Paradoxical Vocal Fold Motion Disorder *Kevin Pasternak, and †Susan L. Thibeault, *yMadison, Wisconsin Summary: Objective. To investigate patient-level predictors of initiation of voice therapy for paradoxical vocal fold motion disorder (PVFM). Study Design. Prospective outcomes database study. Methods. Patients consented to the University of Wisconsin Voice and Swallow Clinics Outcomes Database between March 2010 and November 2016 who were diagnosed with PVFM and recommended for voice therapy were eligible. Patients who attended at least one voice therapy session were considered to have initiated therapy. Analyzed variables included age, gender, distance to the clinic, insurance status, socioeconomic factors, comorbidity score, spirometry results, presence of asthma and/or dysphonia diagnoses, length of evaluation and evaluation model, and patient scores on the Voice Handicap Index and Generalized Anxiety Disorder 7-item scale. Results. One-hundred seventy-eight patients met inclusion criteria. Of these, 118 initiated voice therapy as recommended (66.29%). The majority of patients were female (n = 127; 71.35%). Age was the only factor significantly associated with therapy initiation in both univariate (P = 0.0359) and multivariable (P = 0.0295) analyses, with patients aged 30−39 least likely to attend compared with other age groups. Multivariable analysis also showed that patients evaluated by a speech-language pathologist alone were an estimated three times as likely to initiate therapy compared to patients evaluated by speech-language pathologist and otolaryngologist (ENT) together (P = 0.0407). Other variables were not statistically significant for prediction of therapy initiation. Conclusions. This study suggests that age group and evaluation model are associated with initiation of voice therapy for PVFM. Further study is needed to investigate social-cognitive and quality-of-life factors in predicting therapy initiation. Key Words: Paradoxical vocal fold motion (PVFM)−Vocal cord dysfunction (VCD)−Therapy adherence−Therapy initiation−Voice therapy.
INTRODUCTION Adherence to a prescribed or recommended therapy, either medical or behavioral, is critically important for patients to attain positive health outcomes and decrease health care costs. Attempts to improve adherence must be patienttailored and disease-specific, with an understanding of influencing factors.1 While the predictors of poor adherence in voice therapy for dysphonia have been explored, similar predictors have not yet been investigated for paradoxical vocal fold motion disorder (PVFM), an episodic laryngeal breathing disorder in which the vocal folds adduct partially or completely during inhalation and/or exhalation.2 Care of the patient with PVFM typically involves behavioral treatment provided by a speech-language pathologist (SLP),2,3 yet the level of adherence to this recommended treatment is unknown. Though voice therapy for dysphonia and PVFM are both provided by an SLP, the disorder populations are distinct. For instance, the population of treatment-seeking individuals Accepted for publication December 20, 2018. This research was supported by funding from the Diane M. Bless Endowed Chair in Otolaryngology, Head and Neck Surgery, UW Madison. From the *Voice and Swallow Clinics, University Hospital, Madison, Wisconsin; and the yDivision of Otolaryngology, Head and Neck Surgery, Department of Surgery, University of Wisconsin-Madison, Madison, Wisconsin. Address correspondence and reprint requests to Kevin Pasternak, Voice and Swallow Clinics, University Hospital, 600 Highland Ave., G3/2 Clinical Science Center, Madison, WI 53792. E-mail: [email protected] Journal of Voice, Vol. &&, No. &&, pp. &&−&& 0892-1997 © 2019 The Voice Foundation. Published by Elsevier Inc. All rights reserved. https://doi.org/10.1016/j.jvoice.2018.12.013
with dysphonia skews older compared to the treatment-seeking population with PVFM.4,5 These disorders also differ fundamentally in the nature of the patient's impairment: dysphonia affects communication, while PVFM affects breathing. With these differences in mind, the factors known to affect adherence in voice therapy for dysphonia have thus far served as a proxy in the absence of disease-specific predictors for PVFM voice therapy adherence. In the dysphonia literature, several studies have shown that a significant proportion of patients fail to initiate voice therapy after it has been recommended by an otolaryngologist (ENT), between 38% and 44%.6,7 Initiation of voice therapy is not predicted by demographic factors such as gender and age group,6 although younger age and female gender are associated with successful completion of the clinician's plan of care.7 Other factors predictive of poor adherence include lower employment rate, greater number of comorbid health issues, greater severity of voice disorder, and higher patient-rated voice handicap or quality-of-life score at the time of evaluation.7,8 In follow-up interviews, patients have offered reasons for treatment deferral, including travel distance to the clinic and spontaneous symptom resolution.6 Evaluation model is also known to affect voice therapy adherence: patients evaluated in the same visit by both an ENT and SLP have nearly double the rate of therapy initiation compared to those evaluated separately.9 Qualitative analysis has revealed additional factors serving as either facilitators or barriers to adherence, including the patient's level of motivation, therapeutic alliance between clinician and patient, social support, the perception
ARTICLE IN PRESS 2 of voice therapy exercises as silly or embarrassing, and the perceived difficulty or speed of the therapy process.10 Finally, it has been hypothesized that patients are more likely to attend voice therapy if they achieve a level of self-efficacy in the initial evaluation, fostered through a so-called “mastery” experience.11 Adherence is defined by the World Health Organization as “the extent to which a person's behavior . . . corresponds with agreed recommendations from a health care provider.”1 Prior studies in voice therapy adherence have measured this concept in two ways, either as therapy initiation (ie, attendance in at least one session6,12) or completion of a plan of care.7,9 We chose therapy initiation as our adherence outcome measure because this information was known for all potential participants, and other outcomes, such as therapy discharge, were not known for all potential participants. Thus, the purpose of this study was twofold: to calculate a rate of initiation and determine predictive factors for initiating voice therapy for PVFM. METHODS Study sample This study used data collected from patients consented to the UW Madison Voice and Swallow Outcomes Database, which includes the health information of more than 6000 patients of the UW Health Voice and Swallow Clinics. Establishment of and access to this data has been granted by the UW Madison School of Medicine and Public Health Institutional Review Board. All patients in this database who were diagnosed with PVFM and recommended to return for therapy were included in our study. Patients with primary complaint of cough were excluded, as dyspnea was our focus population. The inclusion criterion for PVFM diagnosis was paradoxical movement of the vocal folds during laryngeal examination. In addition, patients with a negative laryngeal exam and strong clinical symptoms, such as stridor, throat tightness, and quick onset/offset, were diagnosed with PVFM and recommended to attend trial therapy. These patients were also included in our study. Two comparison groups were identified, a therapy group (T) and a no therapy group (NT), based on whether patients had initiated voice therapy.
Variables Patient-level variables were retrieved directly from the UW Madison Voice and Swallow Outcomes Database or calculated based on data obtained there. All patients consented to the database completed a medical intake form at their initial evaluation, from which patient age at clinic visit, gender, and insurance status were taken. Patient responses to the Voice Handicap Index (VHI) and Generalized Anxiety Disorder 7-item scale (GAD-7) were also gathered. The VHI is a validated instrument to assess the psychosocial impact of voice disorders. It consists of three subscales: functional, physical, and emotional. Each subscale has a
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possible score of 0−40, with a possible total score of 0−120. Higher scores indicate higher perceived vocal handicap.13 The GAD-7 is a validated measure used to screen for generalized anxiety. A score of 5−9 indicates a mild level of anxiety, 10−14 indicates a moderate level, and 15−21 indicates a severe level.14 Socioeconomic information was gleaned from the US Census Bureau's American Community Survey based on patient zip code and included median income in dollars and percentage of residents with a bachelor's degree.15 American Community Survey 5-year estimates (2011−2015) were considered more reliable than 1-year and 3-year estimates because of this study's largely rural sample.16 Distance to the clinic was also determined based on patient zip codes. An electronic calculator based on the Charlson Comorbidity Index (CCI) was used to assess the significance of comorbidity.17 This instrument was originally developed to determine the effect of 19 medical conditions on 1-year mortality rate. Each condition is weighed from 1 to 6 points, with a higher number indicating increased risk of mortality (eg, asthma equals 1 point; metastatic solid tumor equals 6 points). The CCI has a possible total score of 0−37.18 Patients’ voice quality within the database was rated by the evaluating SLP using a skilled auditory-perceptual rating tool, the GRBAS. These ratings were used to determine presence or absence of dysphonia. Presence or absence of an existing asthma diagnosis was taken from the database. Also noted was length of the patient's evaluation and evaluation model. Patients were seen for 60- or 90-minute SLP appointments and evaluated by either an SLP alone or an interdisciplinary team of SLP and ENT, typically in the same visit. To determine presence or absence of obstructive airway disease, such as asthma or chronic obstructive pulmonary disease (COPD), we took pulmonary function testing (PFT) results from the database. Obstructive airway disease was determined using the Global Initiative for Chronic Obstructive Lung Disease system (GOLD standard), following the criterion of forced expiratory volume in 1 second/forced vital capacity ratio (FEV₁/FVC) of less than 70%.19 Our selected measures identify an obstructive pulmonary process but do not consider bronchodilator reversibility for the purpose of differential diagnosis between asthma and other diseases, such as COPD.20 Abnormality of the inspiratory flow volume loop (FVL) has been previously associated with extrathoracic breathing restriction, including PVFM.21 Inspiratory FVL shape can be described as normal, absent, flat, or truncated, and is commonly rated subjectively by the interpreting provider.22 These descriptions were found within the database, and a binary interpretation (normal shape vs. abnormal shape) was included in our analysis.
Statistical analysis Patient characteristics were compared using Statistical Analysis Software (version 9.4, SAS Institute Inc, Cary, NC). Differences between the T and NT groups were
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compared using Fisher's exact tests for categorical variables and pooled t tests for continuous variables with equal variances or Satterthwaite t tests for continuous variables with unequal variances. Additionally, logistic regression models were fit in order to estimate odds ratios associated with each factor of interest. Those variables with P values <0.2 were included in the multivariable logistic regression model, with commencement of voice therapy as the outcome. This criterion was chosen to include more variables in the multivariable model and to increase confidence that we were not omitting a potentially important factor. For all analyses, P < 0.05 was considered statistically significant. RESULTS Patient characteristics One hundred seventy-eight patients who were consented to the UW Madison Voice and Swallow Outcomes Database between March 2010 and November 2016 were eligible for inclusion in this study. Of these, 118 attended at least one voice therapy session (66.29%), while 60 did not initiate voice therapy (33.71%). Of those patients who initiated voice therapy, the mean number of sessions attended was 2.09. The mean number of days between initial evaluation and the first therapy session was 22. Table 1 contains summary statistics of the study sample. The majority of patients were women (n = 127, 71.35%). The mean age was 44 years. Mean distance to the clinic was 23 miles. Four outliers with addresses greater than 500 miles from the clinic were excluded from this analysis, as these patients were university students whose medical records reflected their hometown addresses in other states and did not accurately represent distance traveled to the clinic. An additional SLP diagnosis of dysphonia was made in nearly 22% of patients (n = 39). Overall level of comorbidity as measured by the CCI was low, with mean of 1.2 (standard deviation = 1.27) out of a possible 37 points. Self-reported measure of generalized anxiety using the GAD-7 revealed a mean of 5.1 (standard deviation = 5.49), falling in the range of mild anxiety. Forty-one percent of the cohort carried an existing diagnosis of asthma upon presentation to the clinic (n = 73). Of the 119 patients who had PFT completed, only 17.65% met the GOLD standard for pulmonary obstruction (n = 21). Roughly two-thirds of the patients with an available interpretation of FVL shape showed abnormality of the inspiratory limb (n = 47, 68.12%).
Predictors of voice therapy initiation Descriptive statistics comparing predictive factors between the T and NT groups are found in Table 2. Univariate analysis showed that the only variable significantly associated with initiation of voice therapy was age group (P = 0.036). Results by age group are found in Table 3. Patients aged 40−49 initiated therapy at a rate of 81%, compared with an initiation rate of just 42% for those aged 30−39. Patients in all other age groups had a voice therapy initiation rate
TABLE 1. Characteristics of Patient Cohort (n = 178) Characteristic Therapy (n, %) Yes 118, 66.29 No 60, 33.71 Gender (n, %) Female 127, 71.35 Male 51, 28.65 Age groups (n, %) <30 47, 26.40 30−39 33, 18.54 40−49 27, 15.17 50−59 34, 19.10 60−69 21, 11.80 70+ 16, 8.99 Distance to the clinic 23.28 § 35.04 (miles) (mean § SD)* Insurance status (n, %)† Insured 160, 91.43 Uninsured 15, 8.57 ACS—median income ($) 63114.31 § 17791.59 (mean § SD) ACS—bachelor’s degree (%) 46.27 § 18.28 (mean § SD) CCI comorbidity score (mean § SD) 1.20 § 1.27 GAD-7 anxiety score (mean § SD) 5.09 § 5.49 17.81 § 21.85 VHI total score (mean § SD)‡ Abnormality of inspiratory FVL (n, %)§ Yes 47, 68.12 No 22, 31.88 Pulmonary obstruction (n, %)║ Yes 21, 17.65 No 98, 82.35 Length of evaluation (minutes) (n, %) 60 59, 33.15 90 119, 66.85 Evaluation model (n, %) SLP only 157, 88.20 SLP + ENT 21, 11.80 Asthma diagnosis (n, %) Yes 73, 41.01 No 105, 58.99 Dysphonia diagnosis (n, %) Yes 39, 21.91 No 139, 78.09 * Distance was not calculated in four outliers with distance >500 miles. † Insurance status was missing in three patients. ‡ VHI total score was missing in 11 patients. § Inspiratory FVL interpretation was missing in 109 patients. ║ Pulmonary function tests (PFTs) were missing in 59 patients. Abbreviations: ACS, American Community Survey; CCI, Charlson Comorbidity Index; FVL, flow volume loop; GAD-7, Generalized Anxiety Disorder-7; SD, standard deviation; VHI, Voice Handicap Index.
between 65% and 76%. Other variables did not demonstrate any significant predictive value for voice therapy initiation, though several notable differences were found between the T and NT groups. Female patients initiated therapy at a
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TABLE 2. Comparison of the Study Groups, Therapy (T) and No Therapy (NT) Therapy (T)
No Therapy (NT)
P Value*
88, 69.29% 30, 58.82% 24.39 § 39.31
39, 30.71% 21, 41.18% 21.08 § 24.73
0.2200
107, 66.88% 8, 53.33% 63282.79 § 18716.88 46.94 § 18.71 1.28 § 1.27 5.44 § 5.36 19.45 § 22.34
53, 33.13% 7, 46.67% 63195.17 § 16120.03 44.82 § 17.36 1.03 § 1.29 4.38 § 5.73 14.47 § 20.60
0.3935
28, 59.57% 17, 37.78%
19, 40.43% 5, 20.83%
0.1829
15, 71.43% 64, 65.31%
6, 28.57% 34, 34.69%
0.7996
39, 66.10% 79, 66.39%
20, 33.90% 40, 33.61%
1.0000
108, 68.79 10, 47.62
49, 31.21 11, 52.38
0.0829
51, 69.86 67, 63.81
22, 30.14 38, 36.19
0.4246
29, 76.32 88, 63.31
9, 23.68 51, 36.69
0.1468
Characteristic Gender (n, %) Female Male Distance to the clinic (miles) (mean § SD) Insurance status (n, %) Yes No ACS—median income ($) (mean § SD) ACS—bachelor’s degree (%) (mean § SD) CCI comorbidity score (mean § SD) GAD-7 anxiety score (mean § SD) VHI total score (mean § SD) Abnormality of inspiratory FVL (n, %) Yes No Pulmonary obstruction (n, %) Yes No Length of evaluation (minutes) (n, %) 60 90 Evaluation model (n, %) SLP only SLP + MD Asthma diagnosis (n, %) Yes No Dysphonia diagnosis (n, %) Yes No
0.4931
0.9191 0.4240 0.2202 0.2440 0.1674
* Fisher’s exact tests were used for categorical variables. Two sample t tests were used for continuous variables. Abbreviations: ACS, American Community Survey; CCI, Charlson Comorbidity Index; FVL, flow volume loop; GAD-7, Generalized Anxiety Disorder-7; SD, standard deviation; VHI, Voice Handicap Index.
higher rate (69% vs. 58% for males), though this finding was not significant (P = 0.220). Other demographic variables gleaned from census data yielded essentially no differences between the groups in median income (P = 0.919) or percentage of residents with a Bachelor's degree (P = 0.424).
TABLE 3. Univariate Comparison of Attendance by Age Group Age (years)
Therapy (T) (n, %)
No Therapy (NT) (n, %)
Total (n)
<30 30−39 40−49 50−59 60−69 ≥70
31, 65.96 14, 42.42 22, 81.48 24, 70.59 16, 76.19 11, 68.75
16, 34.04 19, 57.58 5, 18.52 10, 29.41 5, 23.81 5, 31.25
47 33 27 34 21 16
P Value 0.0359
Nearly all patients had insurance (n = 160), and this small comparison group of uninsured patients (n = 18) did not reveal any significant predictive value (P = 0.394). Distance to the clinic was slightly higher for the T group (24.39 § 39.31 vs. 21.08 § 24.73 miles for the NT group; P = 0.493). Overall comorbidity as reflected by CCI score was slightly higher in the T group (1.28 § 1.27 vs. 1.03 § 1.29 for the NT group; P = 0.22), but the means were relatively low for both groups given a possible total score of 37 points. Patient self-reported measures showed nonsignificant association with initiation of voice therapy, with the T group having both higher GAD-7 scores (5.44 § 5.36 vs. 4.38 § 5.73 for the NT group; P = 0.244) and higher VHI total scores (19.45 § 22.34 vs. 14.47 § 20.60 for the NT group; P = 0.167). The diagnosis of dysphonia was also associated with initiation of voice therapy, with 76% of those with dysphonia initiating voice therapy compared to 63% of those without dysphonia, though this finding was not significant (P = 0.147). Length of evaluation (60 vs. 90 minutes) had no association (P = 1.00) with voice therapy initiation. There
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was a nonsignificant association related to which provider(s) conducted the evaluation (SLP only vs. SLP and ENT). Sixty-nine percent of patients evaluated only by an SLP-initiated therapy, while only 48% of those patients evaluated jointly by SLP and ENT did so (P = 0.083). Existing diagnosis of asthma was not significantly associated with voice therapy initiation rate (69.86% vs. 63.81% for those without asthma; P = 0.425). Those patients with evidence of pulmonary obstruction on PFTs initiated therapy at a rate of 71.43%, compared with a similar rate of 65.31% for those with no pulmonary obstruction (P = 0.799). Greater difference was found among the subset of patients with an interpretation of their inspiratory FVL (n = 69). Patients with abnormality of the inspiratory FVL initiated therapy at a rate of 59.57%, compared with only 37.78% of patients with inspiratory FVL interpreted as normal (P = 0.183).
Multivariable analysis Variables with P values <0.2 were included in a multivariable logistic regression model, shown in Table 4. This included age group, presence of dysphonia diagnosis, and evaluation model (SLP only vs. SLP and ENT). Two additional variables, VHI total score and rating of the inspiratory FVL, were within the inclusion threshold but were not included in the multivariable model because the data points were incomplete, missing from 11 and 109 patient records, respectively. As in the univariate analysis, age group was shown to have statistically significant association with therapy attendance (P = 0.0295). Other age groups were compared with the 30−39 age group, which had the lowest initiation rate. Compared to this age group, each of the other age groups was estimated to be between two and six times as likely to initiate voice therapy, with the highest odds ratio for the group aged 40−49 (odds ratio [OR] 6.250; confidence interval [CI] 1.893−21.239). Dysphonia diagnosis was not statistically significant, with presence of this diagnosis leading to an estimated rate of initiation that was two times higher than for those without dysphonia diagnosis (OR 2.292; CI 0.939−5.596; P = 0.0685). Patients who were seen by SLP only were estimated to be three times as
TABLE 4. Multivariable Analysis
Age 20 vs. 30 40 vs. 30 50 vs. 30 60 vs. 30 70 vs. 30 Dysphonia MD + SLP visit
Odds ratio
95% CI
2.704 6.250 3.254 4.726 4.960 2.292 3.082
1.045−6.998 1.839−21.239 1.138−9.309 1.308−17.073 1.251−19.671 0.939−5.596 1.049−9.054
P Value 0.0295
0.0685 0.0407
likely to initiate voice therapy as those seen in an initial evaluation by SLP and ENT (OR 3.082; CI 1.049−9.052; P = 0.0407). DISCUSSION In this study, we aimed to establish a voice therapy initiation rate for patients with PVFM and examine factors predictive of voice therapy initiation for eligible subjects in an established, disease-specific outcomes database. Roughly two-thirds of our cohort initiated therapy after it had been recommended, which compares similarly with previous voice therapy initiation rates for dysphonia.6,7 Consistent with previous literature on PVFM,23 a greater than twothirds majority of patients in our study were women. Our results suggest that age group and evaluation model are associated with initiation of voice therapy for patients with PVFM. Association of age group Age group was the only factor significantly associated with voice therapy initiation in both univariate and multivariable analyses. Patients in their 30s initiated voice therapy at roughly half the rate of patients in their 40s (42.42% vs. 81.48% for those in their 40s), and at generally lower rates than all other age groups (Table 3). This finding is curious, as it does not correspond to any trend observed in the clinical setting or to data previously published in the voice therapy adherence literature. Prior investigation has revealed limited influence of age on adherence to voice therapy. In one retrospective analysis, the most successful patients, or those discharged from therapy with complete resolution of their voice problem, were also the youngest. However, these results were not statistically significant.7 Several other studies also found no significant difference in attendance by age group.6,9,12 The effect of age on attendance in other behavioral therapies is unclear. In physical therapy, a systematic review found conflicting evidence that age had any effect, with several studies supporting better attendance or improved participation from younger patients.24 Much of this literature focused on adherence to home physical therapy plans rather than therapy attendance. A small study investigating attendance in occupational therapy found drop-out rates were similar in a group over 35 years of age compared with a group under 35 years of age.25 Association of evaluation model Perhaps the most surprising finding in our study was the association of therapy initiation with evaluation model. Patients seen by SLP alone were an estimated three times likelier to initiate voice therapy than patients evaluated in an interdisciplinary clinic by SLP and ENT. This finding is contrary to those from previous studies suggesting that interdisciplinary evaluation with SLP and ENT leads to increased likelihood of completing a voice therapy plan of care.9,26 To date, there has not been any investigation of
ARTICLE IN PRESS 6 voice therapy adherence following evaluation only by SLP. Given the unique nature of PVFM as a functional, or physiologic, disorder, patients are routinely evaluated and treated in our clinic by SLP alone. A small portion of the study cohort was triaged to an interdisciplinary evaluation with SLP and ENT (n = 21; 11.8%), which occurs in our clinic when patients are referred for dysphonia as well as dyspnea complaints. Analyzed as separate variables, neither the clinical diagnosis of dysphonia nor VHI total score was predictive of voice therapy initiation. Notably, this subgroup of 21 patients evaluated in an interdisciplinary clinic was composed of nearly 43% men, a greater proportion than in our larger study cohort (28%). Though no statistically significant difference was found, men did initiate therapy at a lower rate than women overall (58.82% vs. 69.29% for women). As previously stated, there are no published data showing difference in adherence rates between men and women in voice therapy. Previous study of the effect of gender on attendance in medical appointments has revealed conflicting findings. A Swiss study investigating an attendance intervention program in an urban primary care clinic found men were an estimated 1.72 times as likely to miss a medical appointment as women.27 Conversely, a study of attendance among four British primary care practices found women were an estimated 1.4 times as likely to miss appointments as men.28 Other investigations have shown no difference between men and women in missed appointment rates in primary care practice.29,30 Difference in evaluation length was anticipated to be another possible factor affecting voice therapy initiation, which is related to the evaluation model. A longer, 90-minute evaluation is given in the SLP-only model to allow greater time for symptom provocation as well as education about the diagnosis and immediate introduction of therapy techniques. In comparison, patients seen for interdisciplinary evaluation spend 60 minutes with the SLP before then seeing the ENT. Additionally, patients evaluated at a satellite clinic by SLP-only are seen for 60-minute appointments based on clinic scheduling needs. We hypothesized that a longer evaluation time, allowing for introduction of therapy techniques and opportunity for a so-called “mastery” experience, would lead to a higher initiation rate. Nevertheless, our results showed length of evaluation had no predictive value for voice therapy initiation for PVFM. One confounding possibility, given the relatively low mean number of sessions for patients who did initiate therapy (2.09), is that patients experienced symptom improvement following a relatively brief intervention. The longer evaluation duration could be considered to have elements of “intervention,” including education, counseling, and introduction of therapy techniques, thus making further therapy unnecessary for some patients. Both possibilities are simply hypotheses, and further study would be needed to determine their accuracy. It is possible that the authority conferred on the SLP as the independent evaluating clinician may have played a role in
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the higher voice therapy initiation rate. The recommended treatment for all patients in this cohort was behavioral treatment with an SLP, regardless of evaluation model. Having this recommendation come directly from the same clinician who was anticipated to deliver the treatment may have increased patients’ confidence in their skill. Also, the manner in which patients are educated about their disorder may affect their adherence to recommended treatment. There are demonstrated impacts to patients’ medication adherence based on the quality of the prescribing physician's communication.31 Although not yet explored in the literature, there are possibly differences in the education provided by physicians and SLPs regarding the pathophysiology and rationale for behavioral treatment of PVFM. Presumably, patients evaluated in an interdisciplinary clinic would receive education from both SLP and ENT. Our finding of higher therapy initiation rate amongst patients seen by SLP alone compared with SLP and ENT should not be used independently to suggest an ideal evaluation model for PVFM. There are many other factors to consider in such a decision, including provider experience level, resource allocation, cost of assessment, and legality in each jurisdiction.
Association with spirometry results Spirometry results yielded an interesting and possibly clinically significant difference between patients who initiated therapy and those who did not. Those with abnormality (eg, truncation, blunting, etc) of the inspiratory FVL initiated voice therapy at a rate nearly 20% greater than those with normal inspiratory FVL. This finding was not statistically significant (P = 0.183). This is possibly due to the relatively small subset of our total cohort with an available interpretation of their FVL (n = 69 patients, 38.76%), because FVL shape was not consistently interpreted by the performing medical providers. Regardless, it is not immediately clear why spirometry results would have any effect on therapy initiation, though there are several possibilities. Abnormal inspiratory FVL has long been associated with PVFM.21 One possibility is that patients with the finding of abnormal inspiratory FVL are likely educated about PVFM by their referring provider, typically a pulmonologist or allergy/asthma specialist, thus priming their expectation for the diagnosis and likely treatment (ie, voice therapy). It is tempting to hypothesize that patients demonstrating truncation of the inspiratory FVL have a more severe manifestation of the disorder and are thus more likely to follow treatment recommendations. This suggestion is tenuous, though, given that the relationship of FVL to PVFM is not well understood and somewhat controversial. To date, the predictive value of FVL in diagnosis of PVFM has not been established in any prospective study. Only 28% of patients with PVFM have an abnormality of the inspiratory or expiratory FVL.23 Another challenge in using FVLs diagnostically is that PVFM is episodic and dynamic. Even in patients with endoscopically confirmed PVFM during exertion, only 20% were found to have
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abnormality of the inspiratory FVL because the spirometry was administered when patients were asymptomatic.32
Limitations It is important to keep in mind several limitations inherent to our use of an outcomes database. It is unknown whether patients may have chosen to undergo therapy at an alternate location. The literature describes various patient-provided reasons for seeking treatment elsewhere, including insurance denial, spontaneous resolution of symptoms, and distance to the clinic.6,33 Our study controlled only for distance and did not allow for follow-up with patients to investigate these other factors. Our analysis did not consider any subgroups within the PVFM population, which is an important distinction. Based largely on clinical observation, PVFM is increasingly understood as a heterogeneous disorder with different etiologies, leading some to propose several phenotypes based on triggers.33 One such phenotype is the irritable larynx syndrome, where hyper-responsiveness to environmental stimulants can cause episodic dyspnea, cough, globus, and/or voice changes.34 A separate phenotype includes patients with dyspnea largely or solely induced by exercise and may involve supraglottic collapse and/or glottic closure during inspiration, so-called exercise-induced laryngeal obstruction.35 There is also a subset of patients who report both triggers.33 Limited study has been done comparing patient-level characteristics between these phenotypes. One interesting distinction between them is the predominance of young athletes who present with the exerciseinduced laryngeal obstruction phenotype. For instance, a large study of breathing in elite athletes aged 16−37 years found a PVFM prevalence rate of 5%.36 A retrospective investigation of adolescent and young adult athletes with breathing complaints showed a PVFM diagnosis rate of 70%.37 Our results pointed to an initiation rate curiously lower for the age group in their 30s compared to the age group of 18−29 years. Our clinic location, at a university medical center located on a NCAA Division I campus, may have populated the study cohort with a large number of young, elite athletes. It is possible that the specialized demands of this subgroup led to an increased therapy initiation rate among that age group. Unfortunately, it was difficult to determine with certainty to which phenotypes patients may have best fit. These differing phenotypes were thus examined as a single group under the overarching diagnosis of PVFM, and future studies should take aims to investigate them as different subgroups. Understanding why a patient adheres to a recommended treatment involves more than just patient demographics. The WHO describes several factors that influence adherence: the relationship between clinician and patient, characteristics of the disease, specifics of treatment, patient characteristics, and socioeconomic factors.1 Aligning with this framework, several social-cognitive barriers to adherence have been identified in the voice therapy literature, including therapeutic alliance and readiness for change,10
as well as not understanding the purpose of therapy or not seeing the potential benefit for improvement.5 Our analysis did not allow for investigation into these factors. Additionally, the self-perceived impact of the disorder on patient quality of life was not considered. Our clinic does not routinely collect a patient-reported quality-of-life measure for PVFM, as there is not currently a validated instrument specific to the disorder. Future studies should include patient self-reported measures as possible. Finally, adherence in behavioral therapy relies not only on initiation, but also on regular attendance and independent practice of learned skills. These additional factors are beyond the scope of our study. It should be noted that for patients who initiated therapy, the mean number of total sessions was only two. We were unable to determine whether patients completed their plan of care. It is therefore difficult to propose whether this relatively low number of therapy sessions was influenced by discharge due to quick achievement of treatment goals, patient drop-out, or some other factor(s). CONCLUSIONS This study provides a foundation for understanding the important issue of nonadherence for PVFM treatment, a unique breathing disorder that is addressed primarily through voice therapy. Our results suggest that age and evaluation model may influence initiation of voice therapy for PVFM. This understanding has implications not only for improved patient care, but also for better clinical efficiency and productivity. Future prospective investigation should focus on factors related to clinician-patient interaction, effects of the disorder on quality of life, and patient motivation for change. Ultimately, understanding these patient-related factors does not negate the responsibility of healthcare providers to tailor evaluation, education, and treatment to each specific patient.
Acknowledgments The authors wish to thank Glen Leverson, PhD and Xing Wang, PhD for their statistical assistance, and Eileen Peterson, BS for her writing assistance. REFERENCES 1. Sabate E. Adherence to Long-Term Therapies: Evidence for Action. World Health Organization. 2003. 2. Mathers-Schmidt BA. Paradoxical vocal fold motion: a tutorial on a complex disorder and the speech-language pathologist's role. Am J Speech Lang Pathol. 2001;10:111–125. https://doi.org/10.1044/10580360(2001/012). 3. Patel RR, Venediktov R, Schooling T, et al. Evidence-based systematic review: effects of speech-language pathology treatment for individuals with paradoxical vocal fold motion. Am J Speech Lang Pathol. 2015;24:566–584. https://doi.org/10.1044/2015_AJSLP-14-0120. 4. Hartley NA, Petty BE, Johnson B, et al. Comparative analysis of clinical profile: chronic cough vs paradoxical vocal fold motion. Respir Med. 2015;109:1516–1520. https://doi.org/10.1016/j.rmed.2015.10.007.
ARTICLE IN PRESS 8 5. Misono S, Marmor S, Roy N, et al. Multi-institutional Study of voice disorders and voice therapy referral. Otolaryngol Head Neck Surg. 2016;155:33–41. https://doi.org/10.1177/0194599816639244. 6. Portone C, Johns MM, Hapner ER. A review of patient adherence to the recommendation for voice therapy. J Voice. 2008;22:192–196. https://doi.org/10.1016/j.jvoice.2006.09.009. 7. Smith BE, Kempster GB, Sims SH. Patient factors related to voice therapy attendance and outcomes. J Voice. 2010;24:694–701. https:// doi.org/10.1016/j.jvoice.2009.03.004. 8. Santos L, Almeida L, Teixeira L, et al. Adherence of the dysphonic teachers in speech therapy. CoDAS. 2013;25:135–140. 9. Starmer HM, Liu Z, Akst LM, et al. Attendance in voice therapy. Ann Otol Rhinol Laryngol. 2014;123:117–123. https://doi.org/10.1177/ 0003489414523708. 10. van Leer E, Connor NP. Patient perceptions of voice therapy adherence. J Voice. 2010;24:458–469. https://doi.org/10.1016/j.jvoice.2008.12.009. 11. Bonilha HS, Dawson AE. Creating a mastery experience during the voice evaluation. J Voice. 2012;26:665.e1−7. https://doi.org/10.1016/j. jvoice.2011.09.004. 12. Hapner E, Portone-Maira C, Johns MM. A study of voice therapy dropout. J Voice. 2009;23:337–340. https://doi.org/10.1016/j.jvoice.2007.10.009. 13. Jacobson BH, Johnson A, Grywalski C, et al. The Voice Handicap Index (VHI): development and validation. Am J Speech Lang Pathol. 1997;6:66–70. https://doi.org/10.1044/1058-0360.0603.66. 14. Spitzer RL, Kroenke K, Williams JB, et al. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med. 2006;166:1092–1097. https://doi.org/10.1001/archinte.166.10.1092. 15. U.S. Census Bureau American Community Survey: 2011-2015 5-year estimates. Available at: https://www.census.gov/acs/www/data/datatables-and-tools/. 2016. Accessed 2016. 16. U.S. Census Bureau American Community Survey: guidance for data users. Available at: https://www.census.gov/programs-surveys/acs/ guidance/estimates.html. 2016. Accessed 2016. 17. Hall WH, Ramachandran R, Narayan S, et al. An electronic application for rapidly calculating Charlson comorbidity score. BMC Cancer. 2004;4:1–8. https://doi.org/10.1186/1471-2407-4-94. 18. Charlson ME, Pompei P, Ales KL, et al. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373–383. 19. Vestbo J, Hurd S, Agustí A, et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Resp Clin Care. 2013;187:347–365. 20. Johnson JD, Theurer WM. A stepwise approach to the interpretation of pulmonary function tests. Am Fam Physician. 2014;89:359–366. 21. Miller R, Hyatt R. Evaluation of obstructing lesions of the trachea and larynx by flow-volume loops. Am Rev Respir Dis. 1973;108:475–481. https://doi.org/10.1164/arrd.1973.108.3.475.
Journal of Voice, Vol. &&, No. &&, 2019 22. Sterner JB, Morris MJ, Sill JM, et al. Inspiratory flow-volume curve evaluation for detecting upper airway disease. Respir Care. 2009;54:461–466. 23. Morris MJ, Allan PF, Perkins PJ. Vocal cord dysfunction: etiologies and treatment. Clin Pulm Med. 2006;13:73. https://doi.org/10.1097/01. cpm.0000203745.50250.3b. 24. Jack K, McLean SM, Moffett JL, et al. Barriers to treatment adherence in physiotherapy outpatient clinics: a systematic review. Man Ther. 2010;15:220–228. 25. Green A. An audit of occupational therapy outpatient attendance. Br J Occup Ther. 1997;60:384–388. 26. Litts JK, Gartner-Schmidt JL, Clary MS, et al. Impact of laryngologist and speech pathologist co-assessment on outcomes and billing revenue. Laryngoscope. 2015;125:2139–2142. https://doi.org/10.1002/ lary.25349. 27. Perron N, Dao M, Kossovsky MP, et al. Reduction of missed appointments at an urban primary care clinic: a randomised controlled study. BMC Fam Pract. 2010;11:79. 28. Neal RD, Lawlor DA, Allgar V, et al. Missed appointments in general practice: retrospective data analysis from four practices. Br J Gen Pract. 2001;51:830–832. 29. Kaplan-Lewis E, Percac-Lima S. No-show to primary care appointments: why patients do not come. J Prim Care Community Health. 2013;4:251–255. 30. Giunta D, Briatore A, Baum A, et al. Factors associated with nonattendance at clinical medicine scheduled outpatient appointments in a university general hospital. Patient Preference Adherence. 2013;7:1163. 31. Zolnierek KB, DiMatteo MR. Physician communication and patient adherence to treatment: a meta-analysis. Med Care. 2009;47:826. 32. Morris M, Deal L, Bean D, et al. Vocal cord dysfunction in patients with exertional dyspnea. Chest. 1999;116:1676–1682. 33. Shembel AC, Sandage MJ, Abbott K. Episodic laryngeal breathing disorders: literature review and proposal of preliminary theoretical framework. J Voice. 2017;31:125.e7−125.e16. https://doi.org/10.1016/j. jvoice.2015.11.027. 34. Morrison M, Rammage L, Emami A. The irritable larynx syndrome. J Voice. 1999;13:447–455. 35. Røksund OD, Olin J, Halvorsen T. Working towards a common transatlantic approach for evaluation of exercise-induced laryngeal obstruction. Immunol Allergy Clin N Am. 2018;38:281–292. https://doi.org/ 10.1016/j.iac.2018.01.002. 36. Rundell KW, Spiering BA. Inspiratory stridor in elite athletes. Chest. 2003;123:468–474. 37. Hanks CD, Parsons J, Benninger C, et al. Etiology of dyspnea in elite and recreational athletes. Physician Sports Med. 2012;40:28–33. https://doi.org/10.3810/psm.2012.05.1962.
Factors Affecting Initiation of Voice Therapy for Paradoxical Vocal Fold Motion Disorder *Kevin Pasternak, and †Susan L. Thibeault, *yMadison, Wisconsin Summary: Objective. To investigate patient-level predictors of initiation of voice therapy for paradoxical vocal fold motion disorder (PVFM). Study Design. Prospective outcomes database study. Methods. Patients consented to the University of Wisconsin Voice and Swallow Clinics Outcomes Database between March 2010 and November 2016 who were diagnosed with PVFM and recommended for voice therapy were eligible. Patients who attended at least one voice therapy session were considered to have initiated therapy. Analyzed variables included age, gender, distance to the clinic, insurance status, socioeconomic factors, comorbidity score, spirometry results, presence of asthma and/or dysphonia diagnoses, length of evaluation and evaluation model, and patient scores on the Voice Handicap Index and Generalized Anxiety Disorder 7-item scale. Results. One-hundred seventy-eight patients met inclusion criteria. Of these, 118 initiated voice therapy as recommended (66.29%). The majority of patients were female (n = 127; 71.35%). Age was the only factor significantly associated with therapy initiation in both univariate (P = 0.0359) and multivariable (P = 0.0295) analyses, with patients aged 30−39 least likely to attend compared with other age groups. Multivariable analysis also showed that patients evaluated by a speech-language pathologist alone were an estimated three times as likely to initiate therapy compared to patients evaluated by speech-language pathologist and otolaryngologist (ENT) together (P = 0.0407). Other variables were not statistically significant for prediction of therapy initiation. Conclusions. This study suggests that age group and evaluation model are associated with initiation of voice therapy for PVFM. Further study is needed to investigate social-cognitive and quality-of-life factors in predicting therapy initiation. Key Words: Paradoxical vocal fold motion (PVFM)−Vocal cord dysfunction (VCD)−Therapy adherence−Therapy initiation−Voice therapy.
INTRODUCTION Adherence to a prescribed or recommended therapy, either medical or behavioral, is critically important for patients to attain positive health outcomes and decrease health care costs. Attempts to improve adherence must be patienttailored and disease-specific, with an understanding of influencing factors.1 While the predictors of poor adherence in voice therapy for dysphonia have been explored, similar predictors have not yet been investigated for paradoxical vocal fold motion disorder (PVFM), an episodic laryngeal breathing disorder in which the vocal folds adduct partially or completely during inhalation and/or exhalation.2 Care of the patient with PVFM typically involves behavioral treatment provided by a speech-language pathologist (SLP),2,3 yet the level of adherence to this recommended treatment is unknown. Though voice therapy for dysphonia and PVFM are both provided by an SLP, the disorder populations are distinct. For instance, the population of treatment-seeking individuals Accepted for publication December 20, 2018. This research was supported by funding from the Diane M. Bless Endowed Chair in Otolaryngology, Head and Neck Surgery, UW Madison. From the *Voice and Swallow Clinics, University Hospital, Madison, Wisconsin; and the yDivision of Otolaryngology, Head and Neck Surgery, Department of Surgery, University of Wisconsin-Madison, Madison, Wisconsin. Address correspondence and reprint requests to Kevin Pasternak, Voice and Swallow Clinics, University Hospital, 600 Highland Ave., G3/2 Clinical Science Center, Madison, WI 53792. E-mail: [email protected] Journal of Voice, Vol. &&, No. &&, pp. &&−&& 0892-1997 © 2019 The Voice Foundation. Published by Elsevier Inc. All rights reserved. https://doi.org/10.1016/j.jvoice.2018.12.013
with dysphonia skews older compared to the treatment-seeking population with PVFM.4,5 These disorders also differ fundamentally in the nature of the patient's impairment: dysphonia affects communication, while PVFM affects breathing. With these differences in mind, the factors known to affect adherence in voice therapy for dysphonia have thus far served as a proxy in the absence of disease-specific predictors for PVFM voice therapy adherence. In the dysphonia literature, several studies have shown that a significant proportion of patients fail to initiate voice therapy after it has been recommended by an otolaryngologist (ENT), between 38% and 44%.6,7 Initiation of voice therapy is not predicted by demographic factors such as gender and age group,6 although younger age and female gender are associated with successful completion of the clinician's plan of care.7 Other factors predictive of poor adherence include lower employment rate, greater number of comorbid health issues, greater severity of voice disorder, and higher patient-rated voice handicap or quality-of-life score at the time of evaluation.7,8 In follow-up interviews, patients have offered reasons for treatment deferral, including travel distance to the clinic and spontaneous symptom resolution.6 Evaluation model is also known to affect voice therapy adherence: patients evaluated in the same visit by both an ENT and SLP have nearly double the rate of therapy initiation compared to those evaluated separately.9 Qualitative analysis has revealed additional factors serving as either facilitators or barriers to adherence, including the patient's level of motivation, therapeutic alliance between clinician and patient, social support, the perception
ARTICLE IN PRESS 2 of voice therapy exercises as silly or embarrassing, and the perceived difficulty or speed of the therapy process.10 Finally, it has been hypothesized that patients are more likely to attend voice therapy if they achieve a level of self-efficacy in the initial evaluation, fostered through a so-called “mastery” experience.11 Adherence is defined by the World Health Organization as “the extent to which a person's behavior . . . corresponds with agreed recommendations from a health care provider.”1 Prior studies in voice therapy adherence have measured this concept in two ways, either as therapy initiation (ie, attendance in at least one session6,12) or completion of a plan of care.7,9 We chose therapy initiation as our adherence outcome measure because this information was known for all potential participants, and other outcomes, such as therapy discharge, were not known for all potential participants. Thus, the purpose of this study was twofold: to calculate a rate of initiation and determine predictive factors for initiating voice therapy for PVFM. METHODS Study sample This study used data collected from patients consented to the UW Madison Voice and Swallow Outcomes Database, which includes the health information of more than 6000 patients of the UW Health Voice and Swallow Clinics. Establishment of and access to this data has been granted by the UW Madison School of Medicine and Public Health Institutional Review Board. All patients in this database who were diagnosed with PVFM and recommended to return for therapy were included in our study. Patients with primary complaint of cough were excluded, as dyspnea was our focus population. The inclusion criterion for PVFM diagnosis was paradoxical movement of the vocal folds during laryngeal examination. In addition, patients with a negative laryngeal exam and strong clinical symptoms, such as stridor, throat tightness, and quick onset/offset, were diagnosed with PVFM and recommended to attend trial therapy. These patients were also included in our study. Two comparison groups were identified, a therapy group (T) and a no therapy group (NT), based on whether patients had initiated voice therapy.
Variables Patient-level variables were retrieved directly from the UW Madison Voice and Swallow Outcomes Database or calculated based on data obtained there. All patients consented to the database completed a medical intake form at their initial evaluation, from which patient age at clinic visit, gender, and insurance status were taken. Patient responses to the Voice Handicap Index (VHI) and Generalized Anxiety Disorder 7-item scale (GAD-7) were also gathered. The VHI is a validated instrument to assess the psychosocial impact of voice disorders. It consists of three subscales: functional, physical, and emotional. Each subscale has a
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possible score of 0−40, with a possible total score of 0−120. Higher scores indicate higher perceived vocal handicap.13 The GAD-7 is a validated measure used to screen for generalized anxiety. A score of 5−9 indicates a mild level of anxiety, 10−14 indicates a moderate level, and 15−21 indicates a severe level.14 Socioeconomic information was gleaned from the US Census Bureau's American Community Survey based on patient zip code and included median income in dollars and percentage of residents with a bachelor's degree.15 American Community Survey 5-year estimates (2011−2015) were considered more reliable than 1-year and 3-year estimates because of this study's largely rural sample.16 Distance to the clinic was also determined based on patient zip codes. An electronic calculator based on the Charlson Comorbidity Index (CCI) was used to assess the significance of comorbidity.17 This instrument was originally developed to determine the effect of 19 medical conditions on 1-year mortality rate. Each condition is weighed from 1 to 6 points, with a higher number indicating increased risk of mortality (eg, asthma equals 1 point; metastatic solid tumor equals 6 points). The CCI has a possible total score of 0−37.18 Patients’ voice quality within the database was rated by the evaluating SLP using a skilled auditory-perceptual rating tool, the GRBAS. These ratings were used to determine presence or absence of dysphonia. Presence or absence of an existing asthma diagnosis was taken from the database. Also noted was length of the patient's evaluation and evaluation model. Patients were seen for 60- or 90-minute SLP appointments and evaluated by either an SLP alone or an interdisciplinary team of SLP and ENT, typically in the same visit. To determine presence or absence of obstructive airway disease, such as asthma or chronic obstructive pulmonary disease (COPD), we took pulmonary function testing (PFT) results from the database. Obstructive airway disease was determined using the Global Initiative for Chronic Obstructive Lung Disease system (GOLD standard), following the criterion of forced expiratory volume in 1 second/forced vital capacity ratio (FEV₁/FVC) of less than 70%.19 Our selected measures identify an obstructive pulmonary process but do not consider bronchodilator reversibility for the purpose of differential diagnosis between asthma and other diseases, such as COPD.20 Abnormality of the inspiratory flow volume loop (FVL) has been previously associated with extrathoracic breathing restriction, including PVFM.21 Inspiratory FVL shape can be described as normal, absent, flat, or truncated, and is commonly rated subjectively by the interpreting provider.22 These descriptions were found within the database, and a binary interpretation (normal shape vs. abnormal shape) was included in our analysis.
Statistical analysis Patient characteristics were compared using Statistical Analysis Software (version 9.4, SAS Institute Inc, Cary, NC). Differences between the T and NT groups were
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compared using Fisher's exact tests for categorical variables and pooled t tests for continuous variables with equal variances or Satterthwaite t tests for continuous variables with unequal variances. Additionally, logistic regression models were fit in order to estimate odds ratios associated with each factor of interest. Those variables with P values <0.2 were included in the multivariable logistic regression model, with commencement of voice therapy as the outcome. This criterion was chosen to include more variables in the multivariable model and to increase confidence that we were not omitting a potentially important factor. For all analyses, P < 0.05 was considered statistically significant. RESULTS Patient characteristics One hundred seventy-eight patients who were consented to the UW Madison Voice and Swallow Outcomes Database between March 2010 and November 2016 were eligible for inclusion in this study. Of these, 118 attended at least one voice therapy session (66.29%), while 60 did not initiate voice therapy (33.71%). Of those patients who initiated voice therapy, the mean number of sessions attended was 2.09. The mean number of days between initial evaluation and the first therapy session was 22. Table 1 contains summary statistics of the study sample. The majority of patients were women (n = 127, 71.35%). The mean age was 44 years. Mean distance to the clinic was 23 miles. Four outliers with addresses greater than 500 miles from the clinic were excluded from this analysis, as these patients were university students whose medical records reflected their hometown addresses in other states and did not accurately represent distance traveled to the clinic. An additional SLP diagnosis of dysphonia was made in nearly 22% of patients (n = 39). Overall level of comorbidity as measured by the CCI was low, with mean of 1.2 (standard deviation = 1.27) out of a possible 37 points. Self-reported measure of generalized anxiety using the GAD-7 revealed a mean of 5.1 (standard deviation = 5.49), falling in the range of mild anxiety. Forty-one percent of the cohort carried an existing diagnosis of asthma upon presentation to the clinic (n = 73). Of the 119 patients who had PFT completed, only 17.65% met the GOLD standard for pulmonary obstruction (n = 21). Roughly two-thirds of the patients with an available interpretation of FVL shape showed abnormality of the inspiratory limb (n = 47, 68.12%).
Predictors of voice therapy initiation Descriptive statistics comparing predictive factors between the T and NT groups are found in Table 2. Univariate analysis showed that the only variable significantly associated with initiation of voice therapy was age group (P = 0.036). Results by age group are found in Table 3. Patients aged 40−49 initiated therapy at a rate of 81%, compared with an initiation rate of just 42% for those aged 30−39. Patients in all other age groups had a voice therapy initiation rate
TABLE 1. Characteristics of Patient Cohort (n = 178) Characteristic Therapy (n, %) Yes 118, 66.29 No 60, 33.71 Gender (n, %) Female 127, 71.35 Male 51, 28.65 Age groups (n, %) <30 47, 26.40 30−39 33, 18.54 40−49 27, 15.17 50−59 34, 19.10 60−69 21, 11.80 70+ 16, 8.99 Distance to the clinic 23.28 § 35.04 (miles) (mean § SD)* Insurance status (n, %)† Insured 160, 91.43 Uninsured 15, 8.57 ACS—median income ($) 63114.31 § 17791.59 (mean § SD) ACS—bachelor’s degree (%) 46.27 § 18.28 (mean § SD) CCI comorbidity score (mean § SD) 1.20 § 1.27 GAD-7 anxiety score (mean § SD) 5.09 § 5.49 17.81 § 21.85 VHI total score (mean § SD)‡ Abnormality of inspiratory FVL (n, %)§ Yes 47, 68.12 No 22, 31.88 Pulmonary obstruction (n, %)║ Yes 21, 17.65 No 98, 82.35 Length of evaluation (minutes) (n, %) 60 59, 33.15 90 119, 66.85 Evaluation model (n, %) SLP only 157, 88.20 SLP + ENT 21, 11.80 Asthma diagnosis (n, %) Yes 73, 41.01 No 105, 58.99 Dysphonia diagnosis (n, %) Yes 39, 21.91 No 139, 78.09 * Distance was not calculated in four outliers with distance >500 miles. † Insurance status was missing in three patients. ‡ VHI total score was missing in 11 patients. § Inspiratory FVL interpretation was missing in 109 patients. ║ Pulmonary function tests (PFTs) were missing in 59 patients. Abbreviations: ACS, American Community Survey; CCI, Charlson Comorbidity Index; FVL, flow volume loop; GAD-7, Generalized Anxiety Disorder-7; SD, standard deviation; VHI, Voice Handicap Index.
between 65% and 76%. Other variables did not demonstrate any significant predictive value for voice therapy initiation, though several notable differences were found between the T and NT groups. Female patients initiated therapy at a
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TABLE 2. Comparison of the Study Groups, Therapy (T) and No Therapy (NT) Therapy (T)
No Therapy (NT)
P Value*
88, 69.29% 30, 58.82% 24.39 § 39.31
39, 30.71% 21, 41.18% 21.08 § 24.73
0.2200
107, 66.88% 8, 53.33% 63282.79 § 18716.88 46.94 § 18.71 1.28 § 1.27 5.44 § 5.36 19.45 § 22.34
53, 33.13% 7, 46.67% 63195.17 § 16120.03 44.82 § 17.36 1.03 § 1.29 4.38 § 5.73 14.47 § 20.60
0.3935
28, 59.57% 17, 37.78%
19, 40.43% 5, 20.83%
0.1829
15, 71.43% 64, 65.31%
6, 28.57% 34, 34.69%
0.7996
39, 66.10% 79, 66.39%
20, 33.90% 40, 33.61%
1.0000
108, 68.79 10, 47.62
49, 31.21 11, 52.38
0.0829
51, 69.86 67, 63.81
22, 30.14 38, 36.19
0.4246
29, 76.32 88, 63.31
9, 23.68 51, 36.69
0.1468
Characteristic Gender (n, %) Female Male Distance to the clinic (miles) (mean § SD) Insurance status (n, %) Yes No ACS—median income ($) (mean § SD) ACS—bachelor’s degree (%) (mean § SD) CCI comorbidity score (mean § SD) GAD-7 anxiety score (mean § SD) VHI total score (mean § SD) Abnormality of inspiratory FVL (n, %) Yes No Pulmonary obstruction (n, %) Yes No Length of evaluation (minutes) (n, %) 60 90 Evaluation model (n, %) SLP only SLP + MD Asthma diagnosis (n, %) Yes No Dysphonia diagnosis (n, %) Yes No
0.4931
0.9191 0.4240 0.2202 0.2440 0.1674
* Fisher’s exact tests were used for categorical variables. Two sample t tests were used for continuous variables. Abbreviations: ACS, American Community Survey; CCI, Charlson Comorbidity Index; FVL, flow volume loop; GAD-7, Generalized Anxiety Disorder-7; SD, standard deviation; VHI, Voice Handicap Index.
higher rate (69% vs. 58% for males), though this finding was not significant (P = 0.220). Other demographic variables gleaned from census data yielded essentially no differences between the groups in median income (P = 0.919) or percentage of residents with a Bachelor's degree (P = 0.424).
TABLE 3. Univariate Comparison of Attendance by Age Group Age (years)
Therapy (T) (n, %)
No Therapy (NT) (n, %)
Total (n)
<30 30−39 40−49 50−59 60−69 ≥70
31, 65.96 14, 42.42 22, 81.48 24, 70.59 16, 76.19 11, 68.75
16, 34.04 19, 57.58 5, 18.52 10, 29.41 5, 23.81 5, 31.25
47 33 27 34 21 16
P Value 0.0359
Nearly all patients had insurance (n = 160), and this small comparison group of uninsured patients (n = 18) did not reveal any significant predictive value (P = 0.394). Distance to the clinic was slightly higher for the T group (24.39 § 39.31 vs. 21.08 § 24.73 miles for the NT group; P = 0.493). Overall comorbidity as reflected by CCI score was slightly higher in the T group (1.28 § 1.27 vs. 1.03 § 1.29 for the NT group; P = 0.22), but the means were relatively low for both groups given a possible total score of 37 points. Patient self-reported measures showed nonsignificant association with initiation of voice therapy, with the T group having both higher GAD-7 scores (5.44 § 5.36 vs. 4.38 § 5.73 for the NT group; P = 0.244) and higher VHI total scores (19.45 § 22.34 vs. 14.47 § 20.60 for the NT group; P = 0.167). The diagnosis of dysphonia was also associated with initiation of voice therapy, with 76% of those with dysphonia initiating voice therapy compared to 63% of those without dysphonia, though this finding was not significant (P = 0.147). Length of evaluation (60 vs. 90 minutes) had no association (P = 1.00) with voice therapy initiation. There
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was a nonsignificant association related to which provider(s) conducted the evaluation (SLP only vs. SLP and ENT). Sixty-nine percent of patients evaluated only by an SLP-initiated therapy, while only 48% of those patients evaluated jointly by SLP and ENT did so (P = 0.083). Existing diagnosis of asthma was not significantly associated with voice therapy initiation rate (69.86% vs. 63.81% for those without asthma; P = 0.425). Those patients with evidence of pulmonary obstruction on PFTs initiated therapy at a rate of 71.43%, compared with a similar rate of 65.31% for those with no pulmonary obstruction (P = 0.799). Greater difference was found among the subset of patients with an interpretation of their inspiratory FVL (n = 69). Patients with abnormality of the inspiratory FVL initiated therapy at a rate of 59.57%, compared with only 37.78% of patients with inspiratory FVL interpreted as normal (P = 0.183).
Multivariable analysis Variables with P values <0.2 were included in a multivariable logistic regression model, shown in Table 4. This included age group, presence of dysphonia diagnosis, and evaluation model (SLP only vs. SLP and ENT). Two additional variables, VHI total score and rating of the inspiratory FVL, were within the inclusion threshold but were not included in the multivariable model because the data points were incomplete, missing from 11 and 109 patient records, respectively. As in the univariate analysis, age group was shown to have statistically significant association with therapy attendance (P = 0.0295). Other age groups were compared with the 30−39 age group, which had the lowest initiation rate. Compared to this age group, each of the other age groups was estimated to be between two and six times as likely to initiate voice therapy, with the highest odds ratio for the group aged 40−49 (odds ratio [OR] 6.250; confidence interval [CI] 1.893−21.239). Dysphonia diagnosis was not statistically significant, with presence of this diagnosis leading to an estimated rate of initiation that was two times higher than for those without dysphonia diagnosis (OR 2.292; CI 0.939−5.596; P = 0.0685). Patients who were seen by SLP only were estimated to be three times as
TABLE 4. Multivariable Analysis
Age 20 vs. 30 40 vs. 30 50 vs. 30 60 vs. 30 70 vs. 30 Dysphonia MD + SLP visit
Odds ratio
95% CI
2.704 6.250 3.254 4.726 4.960 2.292 3.082
1.045−6.998 1.839−21.239 1.138−9.309 1.308−17.073 1.251−19.671 0.939−5.596 1.049−9.054
P Value 0.0295
0.0685 0.0407
likely to initiate voice therapy as those seen in an initial evaluation by SLP and ENT (OR 3.082; CI 1.049−9.052; P = 0.0407). DISCUSSION In this study, we aimed to establish a voice therapy initiation rate for patients with PVFM and examine factors predictive of voice therapy initiation for eligible subjects in an established, disease-specific outcomes database. Roughly two-thirds of our cohort initiated therapy after it had been recommended, which compares similarly with previous voice therapy initiation rates for dysphonia.6,7 Consistent with previous literature on PVFM,23 a greater than twothirds majority of patients in our study were women. Our results suggest that age group and evaluation model are associated with initiation of voice therapy for patients with PVFM. Association of age group Age group was the only factor significantly associated with voice therapy initiation in both univariate and multivariable analyses. Patients in their 30s initiated voice therapy at roughly half the rate of patients in their 40s (42.42% vs. 81.48% for those in their 40s), and at generally lower rates than all other age groups (Table 3). This finding is curious, as it does not correspond to any trend observed in the clinical setting or to data previously published in the voice therapy adherence literature. Prior investigation has revealed limited influence of age on adherence to voice therapy. In one retrospective analysis, the most successful patients, or those discharged from therapy with complete resolution of their voice problem, were also the youngest. However, these results were not statistically significant.7 Several other studies also found no significant difference in attendance by age group.6,9,12 The effect of age on attendance in other behavioral therapies is unclear. In physical therapy, a systematic review found conflicting evidence that age had any effect, with several studies supporting better attendance or improved participation from younger patients.24 Much of this literature focused on adherence to home physical therapy plans rather than therapy attendance. A small study investigating attendance in occupational therapy found drop-out rates were similar in a group over 35 years of age compared with a group under 35 years of age.25 Association of evaluation model Perhaps the most surprising finding in our study was the association of therapy initiation with evaluation model. Patients seen by SLP alone were an estimated three times likelier to initiate voice therapy than patients evaluated in an interdisciplinary clinic by SLP and ENT. This finding is contrary to those from previous studies suggesting that interdisciplinary evaluation with SLP and ENT leads to increased likelihood of completing a voice therapy plan of care.9,26 To date, there has not been any investigation of
ARTICLE IN PRESS 6 voice therapy adherence following evaluation only by SLP. Given the unique nature of PVFM as a functional, or physiologic, disorder, patients are routinely evaluated and treated in our clinic by SLP alone. A small portion of the study cohort was triaged to an interdisciplinary evaluation with SLP and ENT (n = 21; 11.8%), which occurs in our clinic when patients are referred for dysphonia as well as dyspnea complaints. Analyzed as separate variables, neither the clinical diagnosis of dysphonia nor VHI total score was predictive of voice therapy initiation. Notably, this subgroup of 21 patients evaluated in an interdisciplinary clinic was composed of nearly 43% men, a greater proportion than in our larger study cohort (28%). Though no statistically significant difference was found, men did initiate therapy at a lower rate than women overall (58.82% vs. 69.29% for women). As previously stated, there are no published data showing difference in adherence rates between men and women in voice therapy. Previous study of the effect of gender on attendance in medical appointments has revealed conflicting findings. A Swiss study investigating an attendance intervention program in an urban primary care clinic found men were an estimated 1.72 times as likely to miss a medical appointment as women.27 Conversely, a study of attendance among four British primary care practices found women were an estimated 1.4 times as likely to miss appointments as men.28 Other investigations have shown no difference between men and women in missed appointment rates in primary care practice.29,30 Difference in evaluation length was anticipated to be another possible factor affecting voice therapy initiation, which is related to the evaluation model. A longer, 90-minute evaluation is given in the SLP-only model to allow greater time for symptom provocation as well as education about the diagnosis and immediate introduction of therapy techniques. In comparison, patients seen for interdisciplinary evaluation spend 60 minutes with the SLP before then seeing the ENT. Additionally, patients evaluated at a satellite clinic by SLP-only are seen for 60-minute appointments based on clinic scheduling needs. We hypothesized that a longer evaluation time, allowing for introduction of therapy techniques and opportunity for a so-called “mastery” experience, would lead to a higher initiation rate. Nevertheless, our results showed length of evaluation had no predictive value for voice therapy initiation for PVFM. One confounding possibility, given the relatively low mean number of sessions for patients who did initiate therapy (2.09), is that patients experienced symptom improvement following a relatively brief intervention. The longer evaluation duration could be considered to have elements of “intervention,” including education, counseling, and introduction of therapy techniques, thus making further therapy unnecessary for some patients. Both possibilities are simply hypotheses, and further study would be needed to determine their accuracy. It is possible that the authority conferred on the SLP as the independent evaluating clinician may have played a role in
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the higher voice therapy initiation rate. The recommended treatment for all patients in this cohort was behavioral treatment with an SLP, regardless of evaluation model. Having this recommendation come directly from the same clinician who was anticipated to deliver the treatment may have increased patients’ confidence in their skill. Also, the manner in which patients are educated about their disorder may affect their adherence to recommended treatment. There are demonstrated impacts to patients’ medication adherence based on the quality of the prescribing physician's communication.31 Although not yet explored in the literature, there are possibly differences in the education provided by physicians and SLPs regarding the pathophysiology and rationale for behavioral treatment of PVFM. Presumably, patients evaluated in an interdisciplinary clinic would receive education from both SLP and ENT. Our finding of higher therapy initiation rate amongst patients seen by SLP alone compared with SLP and ENT should not be used independently to suggest an ideal evaluation model for PVFM. There are many other factors to consider in such a decision, including provider experience level, resource allocation, cost of assessment, and legality in each jurisdiction.
Association with spirometry results Spirometry results yielded an interesting and possibly clinically significant difference between patients who initiated therapy and those who did not. Those with abnormality (eg, truncation, blunting, etc) of the inspiratory FVL initiated voice therapy at a rate nearly 20% greater than those with normal inspiratory FVL. This finding was not statistically significant (P = 0.183). This is possibly due to the relatively small subset of our total cohort with an available interpretation of their FVL (n = 69 patients, 38.76%), because FVL shape was not consistently interpreted by the performing medical providers. Regardless, it is not immediately clear why spirometry results would have any effect on therapy initiation, though there are several possibilities. Abnormal inspiratory FVL has long been associated with PVFM.21 One possibility is that patients with the finding of abnormal inspiratory FVL are likely educated about PVFM by their referring provider, typically a pulmonologist or allergy/asthma specialist, thus priming their expectation for the diagnosis and likely treatment (ie, voice therapy). It is tempting to hypothesize that patients demonstrating truncation of the inspiratory FVL have a more severe manifestation of the disorder and are thus more likely to follow treatment recommendations. This suggestion is tenuous, though, given that the relationship of FVL to PVFM is not well understood and somewhat controversial. To date, the predictive value of FVL in diagnosis of PVFM has not been established in any prospective study. Only 28% of patients with PVFM have an abnormality of the inspiratory or expiratory FVL.23 Another challenge in using FVLs diagnostically is that PVFM is episodic and dynamic. Even in patients with endoscopically confirmed PVFM during exertion, only 20% were found to have
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Kevin Pasternak and Susan L. Thibeault
abnormality of the inspiratory FVL because the spirometry was administered when patients were asymptomatic.32
Limitations It is important to keep in mind several limitations inherent to our use of an outcomes database. It is unknown whether patients may have chosen to undergo therapy at an alternate location. The literature describes various patient-provided reasons for seeking treatment elsewhere, including insurance denial, spontaneous resolution of symptoms, and distance to the clinic.6,33 Our study controlled only for distance and did not allow for follow-up with patients to investigate these other factors. Our analysis did not consider any subgroups within the PVFM population, which is an important distinction. Based largely on clinical observation, PVFM is increasingly understood as a heterogeneous disorder with different etiologies, leading some to propose several phenotypes based on triggers.33 One such phenotype is the irritable larynx syndrome, where hyper-responsiveness to environmental stimulants can cause episodic dyspnea, cough, globus, and/or voice changes.34 A separate phenotype includes patients with dyspnea largely or solely induced by exercise and may involve supraglottic collapse and/or glottic closure during inspiration, so-called exercise-induced laryngeal obstruction.35 There is also a subset of patients who report both triggers.33 Limited study has been done comparing patient-level characteristics between these phenotypes. One interesting distinction between them is the predominance of young athletes who present with the exerciseinduced laryngeal obstruction phenotype. For instance, a large study of breathing in elite athletes aged 16−37 years found a PVFM prevalence rate of 5%.36 A retrospective investigation of adolescent and young adult athletes with breathing complaints showed a PVFM diagnosis rate of 70%.37 Our results pointed to an initiation rate curiously lower for the age group in their 30s compared to the age group of 18−29 years. Our clinic location, at a university medical center located on a NCAA Division I campus, may have populated the study cohort with a large number of young, elite athletes. It is possible that the specialized demands of this subgroup led to an increased therapy initiation rate among that age group. Unfortunately, it was difficult to determine with certainty to which phenotypes patients may have best fit. These differing phenotypes were thus examined as a single group under the overarching diagnosis of PVFM, and future studies should take aims to investigate them as different subgroups. Understanding why a patient adheres to a recommended treatment involves more than just patient demographics. The WHO describes several factors that influence adherence: the relationship between clinician and patient, characteristics of the disease, specifics of treatment, patient characteristics, and socioeconomic factors.1 Aligning with this framework, several social-cognitive barriers to adherence have been identified in the voice therapy literature, including therapeutic alliance and readiness for change,10
as well as not understanding the purpose of therapy or not seeing the potential benefit for improvement.5 Our analysis did not allow for investigation into these factors. Additionally, the self-perceived impact of the disorder on patient quality of life was not considered. Our clinic does not routinely collect a patient-reported quality-of-life measure for PVFM, as there is not currently a validated instrument specific to the disorder. Future studies should include patient self-reported measures as possible. Finally, adherence in behavioral therapy relies not only on initiation, but also on regular attendance and independent practice of learned skills. These additional factors are beyond the scope of our study. It should be noted that for patients who initiated therapy, the mean number of total sessions was only two. We were unable to determine whether patients completed their plan of care. It is therefore difficult to propose whether this relatively low number of therapy sessions was influenced by discharge due to quick achievement of treatment goals, patient drop-out, or some other factor(s). CONCLUSIONS This study provides a foundation for understanding the important issue of nonadherence for PVFM treatment, a unique breathing disorder that is addressed primarily through voice therapy. Our results suggest that age and evaluation model may influence initiation of voice therapy for PVFM. This understanding has implications not only for improved patient care, but also for better clinical efficiency and productivity. Future prospective investigation should focus on factors related to clinician-patient interaction, effects of the disorder on quality of life, and patient motivation for change. Ultimately, understanding these patient-related factors does not negate the responsibility of healthcare providers to tailor evaluation, education, and treatment to each specific patient.
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