The effects of vestibular dysfunction on balance and self-concept in children with cochlear implants

Abstract

OBJECTIVES:

Children with cochlear implants (CCI) have an increased rate of vestibular dysfunction. Vestibular dysfunction is associated with decreased balance and dynamic visual acuity ability. Hearing loss alone is associated with reduced speech perception and vocabulary in children. In adults, vestibular dysfunction is associated with reduced quality of life; however, similar relationships have not been studied in children with vestibular dysfunction. Therefore, the objective of the present study was to evaluate the effect of hearing loss and vestibular dysfunction on self-concept in CCI (n = 33) compared to children with normal hearing (CNH, n = 38). It was hypothesized that children with vestibular dysfunction would have reduced self-concept beyond that from hearing loss, secondary to the presence of balance and visual acuity deficits.

METHODS:

The Piers-Harris Children’s Self-Concept Scale – 2, speech perception, vocabulary, video head impulse test (vHIT), rotary chair, balance using the Bruininks-Oseretsky Test of Motor Proficiency (BOT-2), and dynamic visual acuity (DVA) testing were completed on all participants.

RESULTS:

In the 34 CCI, 24 had normal vestibular function, 6 had unilateral vestibular dysfunction, and 4 had bilateral vestibular dysfunction. There were no significant mean differences in the Piers-Harris Children’s Self-Concept Scale – 2 between groups. A Principal Component Analysis (PCA) was conducted on the predictor variables (average horizontal canal vHIT gain, BOT-2 score, DVA, speech perception, and vocabulary) resulting in two factors; factor 1 represented “vestibular” components (vHIT, BOT-2, and DVA) and factor 2 represented “auditory-language” components (speech perception and vocabulary). In addition to age and gender, the 2 PCA factors were analyzed using multivariate regression with stepwise selection to determine which factors best predicted self-concept. The PCA auditory-language factor was the only significant predictor of self-concept.

CONCLUSIONS:

Auditory-language, not vestibular related factors, contribute to the self-concept of CCI. While adults with vestibular dysfunction have reduced quality of life, it could be that children with vestibular dysfunction have some psychosocial resilience.

1. INTRODUCTION:

Children with hearing loss are at risk for having vestibular dysfunction. This risk increases as the degree of hearing loss increases [1]. Specifically, children with audiometric thresholds greater than 66 dB have a higher likelihood of having vestibular dysfunction [1]. Thus, it is not surprising that approximately 50% of children with hearing loss who require a cochlear implant have some degree of vestibular dysfunction with 20 – 30% of children having bilateral vestibular dysfunction [2-4].

While the spectrum of consequences associated with pediatric vestibular dysfunction have not been fully defined, pediatric vestibular dysfunction has been associated with significant reductions in balance and dynamic visual acuity ability. Specifically, children with vestibular dysfunction hold their head upright, sit, stand, and walk later than their age-matched normal hearing peers [1,5,6]. Reductions in overall balance have been found to persist into childhood as school-age children with vestibular dysfunction continue to demonstrate reduced performance on standardized tests of gross motor function [7-12]. Additionally, children with vestibular dysfunction show reduced dynamic visual acuity performance, in that they cannot see clearly when their head is in motion [3,7,11,13-15]. When congenital in nature, children with vestibular dysfunction do not have the perspective to know that their balance and visual deficits are abnormal, and therefore, may not overtly report symptoms. Thus, it is also unknown if these balance and visual acuity deficits have additional cascading effects.

There is reason to believe the presence of vestibular dysfunction may result in additional consequences beyond imbalance and reduced visual acuity. First, imbalance and reduced visual acuity can result in the inability to perform activities of daily living, which can in turn result in reduced quality of life. While reduced quality of life has been documented in adults with vestibular dysfunction [16-19], similar studies have not been completed to determine if vestibular dysfunction results in similar reductions in the quality of life of children. Additionally, poor motor performance has been associated with peer relationship and emotional difficulties in children with hearing loss[20]. More specifically, 62% of children with a cochlear implant (CCI) rated their athletic competence to be low; further, peer acceptance was related to athletic competence suggesting that participation in activities facilitates peer interactions [21].

Hearing loss alone is also associated with its own related deficits. In children with hearing loss, auditory, speech, and language have been linked to quality of life and social development [22-24]. Specifically, better auditory and pragmatic language skills are associated with better quality of life [22] while better language has been associated with better social development [24]. Additionally, word recognition ability is a good predictor of hearing-related quality of life, with word recognition scores less than 72 – 76% associated with reduced quality of life [23]. In addition to quality of life, self-concept (i.e., how children feel about themselves) has also been measured in children with hearing loss, but with conflicting findings. Children with hearing loss have been noted to have both lower [25,26] and normal [24,27,28] self-esteem/psychosocial development compared to normal hearing peers. Better self-concept/ psychosocial development has been associated with better speech and language outcomes [22,24,27] and better scholastic achievement [25], with differing effects of mainstream versus special education classroom settings on self-concept [25,27].

Given the relationship among vestibular dysfunction and reduced quality of life in adults, decreased balance performance and vestibular dysfunction in CCI and the negative relationship among motor control, athletic performance, and peer relationships in CCI, it was questioned whether the reductions in balance and visual acuity abilities associated with vestibular dysfunction would have a negative effect on the self-concept of CCI. Thus, the purpose of this study was to evaluate the effect of hearing loss and vestibular dysfunction on self-concept in CCI compared to children with normal hearing (CNH). It was hypothesized that children with vestibular dysfunction would have reduced self-concept beyond that from hearing loss likely secondary to the presence of balance and visual acuity deficits.

2. METHODS:

2.1. Participants:

Thirty-eight CNH (mean age: 12.2 years, range 7 - 18) and 37 CCI (mean age: 13.21, range 6 – 18) participated in the study; 3 CCI were excluded from analyses due to either inconsistent or biased responses on the Piers Harris and 1 CCI was excluded due to a low non-verbal intelligence score, as described below. As such, data from 33 CCI (mean age: 13.24, range 6 - 18) were analyzed. By case history, all CNH denied dizziness, imbalance, or other neurologic complaints; All CNH had air-conducted thresholds of 15 dB HL or better at all octave frequencies 250-8000 Hz, bilaterally. Data from these same participants has been published elsewhere[29].

Of the 33 CCI whose data were used for analysis, 23 had bilateral CI and 10 had unilateral CI (5 used a hearing aid and 5 used no form of amplification on the contralateral side). Average age of initial CI was 31.4 months (range 10 – 156 months). One child had progressive hearing loss; thus, had delayed implantation (156 months). Etiology of hearing loss in the CCI was unknown in 17, malformation (i.e., enlarged vestibular aqueduct, Pendred Syndrome, Mondini) in 3, Connexin/GJB2 in 5, auditory neuropathy in 2, Waardenburg Syndrome in 2, meningitis in 2, cytomegalovirus (CMV) in 1, and Usher Syndrome in 1. Five participants used a combination of Signing Exact English (SEE-II) and spoken language in their educational settings and required varying levels of sign support. Of these 5 participants, all utilized an interpreter for most of the measures, which involved simultaneous presentation of items in sign (SEE-II) and spoken language. All remaining participants used spoken English. Participants were recruited from the Human Research Subjects Core database at Boys Town National Research Hospital (BTNRH). All subjects provided informed consent for participation at BTNRH (protocol 12 – 13 – XP).

2.2. Vestibular and Balance Function Testing:

Video Head Impulse Test (vHIT):

vHIT was measured use an ICS Otometrics Impulse unit (Natus, Taastrup, DK). Participants were seated one meter from a visual target at eye level and were instructed to keep their eyes on the target as the clinician stood behind the participant and performed head impulses in the plane of the horizontal (lateral) semicircular canal. For each head impulse, the head was displaced 10 to 20° at a peak head velocity between 120 – 300°/s and peak head acceleration between 1000°/s² and 2500°/s². During head impulses, the infrared camera measured eye velocity while the gyroscope measured head velocity. The main outcome parameter was gain, which was calculated by dividing eye velocity from head velocity.

Rotary Chair:

Rotary chair testing was completed in a motorized rotational chair (Micromedical Technologies, Chatham, IL). Sinusoidal harmonic acceleration (SHA) was completed at the following frequencies and velocities: 0.02 Hz (70°/sec), 0.08 Hz (50°/sec), 0.16 Hz (40°/sec), and 0.32 Hz (30°/sec). Eye movements were measured with either an infrared video camera or electrodes. For each frequency of rotation, the outcome parameters were gain (eye velocity/chair velocity), phase, and symmetry. Rotary chair was used to confirm whether participants had normal vestibular function, unilateral vestibular dysfunction (UVD), or bilateral vestibular dysfunction (BVD). Participants were considered to have BVD if gain was < .1 and phase was > 68° at .01 Hz and UVD if gain was abnormal according to manufacturer normative data and phase lead < 68° at .01 Hz[30].

2.3. Nonverbal Intelligence:

The block design and matrix reasoning subtests of the Wechsler Abbreviated Scale of Intelligence-II (WASI-II[31]) were used to assess nonverbal intelligence. In the block design subtest, two-color blocks are used to recreate a two-dimensional pattern within a specified amount of time. In the matrix reasoning subtest, participants select the picture item that completes a matrix. The block design and matrix reasoning subtests comprise the Perceptual Reasoning Index (PRI) composite score. Participants with a PRI composite score less than 1.5 SD below the mean (< 77) were excluded (n = 1 CCI).

2.4. Additional Metrics:

Bruininks-Oseretsky Test of Motor Proficiency (BOT-2):

All participants completed the balance subtest of the BOT-2, which is a standardized test of motor proficiency. The balance subtest consists of 9 tasks which include: 1) standing with feet apart on a line, 2) walking on a line, 3) standing on one leg, 4) standing with feet apart on a line, eyes closed, 5) walking heel-to-toe, 6) standing on one leg, eyes closed, 7) standing on one leg, on a balance beam, 8) standing heel-to-toe on a balance beam, and 9) standing on one leg on a balance beam, eyes closed. If the maximum score is not achieved on the first trial, a second trial is attempted. Each task has a maximum score of 4, except for the 9^th task, which has a maximum score of 5, for a total possible score of 37. Using participant age, a scaled score was also determined (range = 1 – 35, mean = 15, SD = 5) [32].

Dynamic Visual Acuity (DVA):

Participants were seated 12.5 feet from the computer monitor, which was adjusted to individual eye level. Use of glasses and contact lenses was permitted during testing. Visual targets were the letters, C, D, H, K, O, N, S, R, V, A, and Z, presented randomly. Letters were reviewed with the participants prior to testing. Participants wore a head mounted rate sensor (O-Navi, Vista, CA, USA), which detected head velocity in the plane of the horizontal canal. Visual targets were presented when head velocities were between 120 – 180 degrees/second with the examiner passively moving the subject’s head to the left and right (15 - 20° excursions). Software was modified from the NIH Toolbox DVA test [33,34].

Speech Perception:

Speech perception was assessed using adult AZBio sentences[35], or when the adult lists were too difficult for an older child or a child was under the age of 13 years, pediatric AZBio sentence lists were used [36]. The sentence lists were presented in sound field in quiet at 65 dB SPL. When requested, presentation level was increased to the most comfortable loudness for CCI. The number of words repeated correctly for each sentence was used to calculate a percent correct score for each participant.

Vocabulary:

The Peabody Picture Vocabulary Test – 4 (PPVT-4) was used to assess receptive vocabulary. The test requires the child to select the correct picture from a set of four choices when the target word is spoken by the examiner. Results are reported as standard scores based on the child’s age. The research team developed guidelines for aligning PPVT-4 items with established SEE-II signs; items with no corresponding sign or items that were highly iconic were presented in fingerspelling. Finger-spelled items were also presented in print to ensure that measurement of vocabulary was not confounded by processing of fingerspelling.

2.5. Self-Concept:

The Piers-Harris Children’s Self-Concept Scale – 2 (Piers-Harris – 2) was given to assess self-concept [37]. The Piers Harris – 2 is a self-report questionnaire comprised of items that express how people may feel about themselves. Participants are asked to choose yes or no to indicate whether a statement applies to them. Most participants were easily able to read and understand the statements presented. When participants indicated difficulty reading or understanding items, the examiner read and/or explained items as necessary. The Piers Harris – 2 yields an overall self-concept score (TOT) and the following domain scales; behavioral adjustment (BEH), intellectual and school status (INT), physical appearance and attributes (PHY), freedom from anxiety (FRE), popularity (POP), and happiness and satisfaction (HAP). Higher scores indicate a more positive self-evaluation in the domain being measured.

An Inconsistent Responding Index (INC) is calculated to detect random response patterns. Participants with an INC raw score > 4 were excluded (n = 1 CCI). Additionally, a Response Bias (RES) score is calculated to detect whether a participant tended to provide a response of YES or NO regardless of the question. Thus, participants with a raw RES score > 40 or < 18 were also excluded (n = 2 CCI). All remaining methods have been reported elsewhere [29].

2.6. Statistical Analyses:

To determine if there were significant differences between groups, a one-way ANOVA was applied on each analytic metric. When needed, post hoc testing was completed using Tukey’s honest significant difference (HSD). Multiple regression analyses were then performed to determine which independent variable(s) best predict the total self-concept score. Considering that predictor variables may be correlated, we calculated the Pearson correlations among these predictors and the variance inflation factor (VIF) for each independent variable to detect any potential multicollinearity in multiple regression. A principal component analysis (PCA) with Varimax rotation was also conducted on all predictor variables (average horizontal canal vHIT gain, BOT-2 score, DVA, speech perception, and vocabulary). PCA is a statistical technique for reducing the dimensionality of a large dataset (usually with a list of correlated variables) by transforming a large set of variables into a smaller one (usually called “PCs”) while preserving the maximum amount of information. The PC factors generated from PCA analyses still contain most of the information of predictor variables, but were orthogonal (i.e., independent) and thus no longer results in multicollinearity problems in multiple regression. The PC factors were analyzed using multiple regression to determine which factors best predicted self-concept while adjusting for age and gender as predictor variables.

3. RESULTS:

3.1. Vestibular and Balance Function Testing:

Degree of vestibular dysfunction:

All participants completed vHIT and rotary chair testing. CNH had normal vHIT gains (horizontal canal mean: 0.96, SD = 0.065). CCI were considered to have BVD if vHIT gains were < 0.6, bilaterally (n = 3)[30] and UVD if vHIT gains were < 2 SDs below the normal control group mean (2 SD = 0.82), unilaterally. For both BVD and UVD, compensatory saccades had to be present in greater than 80% of head impulses and exceed 50° in amplitude (n = 6) [38]. One subject did not complete vHIT testing; however, did not generate nystagmus in response to rotation; therefore, was categorized as having BVD (n = 1). This resulted in the following subject groups: CNH (n = 38, mean age: 12.2 years, range 7 - 18), CCI with normal vestibular function (CCI-NV; n = 23, mean age: 13.7 years, range 7 - 18), CCI-UVD (n = 6, mean age: 12.9, range 7 – 19) and CCI-BVD (n = 4, mean age: 11.3, range 7 – 18).

3.2. Nonverbal Intelligence:

Nonverbal Intelligence:

There were no significant group differences in the WASI-II PRI composite scores (F (3, 67) = .656, p = .582, ES = .17; Table 1).

Table 1.

Mean scores per group for all outcome measures.

Outcomes	Group p-value	Group
		CNH (n = 38)	CCI-NV (n = 23)	CCI-UVD (n = 6)	CCI-BVD (n = 4)
Non-Verbal Intelligence
WASI – PRI Score	p = .582	109.3	104.5	103.8	105.3
Piers Harris
Total Score	p = .169	56.0	52.0	51.0	58.5
Behavior Adjustment	p = .625	56.9	55.1	54.3	58.0
Intellectual Status	p = .086	54.7	50.3	52.0	55.8
Physical Appearance & Attributes	p = .137	51.4	49.7	48.8	59.8
Freedom from Anxiety	p = .374	55.2	52.3	49.7	54.3
Popularity	p = .219	51.5	48.2	46.3	54.3
Happiness & Satisfaction	p = .729	54.7	53.8	51.7	55.0
Balance and Vestibular Outcomes
BOT-2 – Total Raw Score	p < .001	32.5	30.8	24	16.7
BOT-2 – Scaled Score	p < .001	13.4	11	5.8	3.7
Horizontal Canal vHIT gain average	p < .001	0.96	0.96	0.63	0.29
Passive Dynamic Visual Acuity	p < .001	0.27	0.25	0.41	0.67
Speech Perception
AZBio	p < .001	99.6	87.2	70	95.1
Language / Vocabulary
PPVT-4	p < .001	118.7	99.3	95.2	107.8

WASI – PRI = Wechsler Abbreviated Scale of Intelligence-II, Perceptual Reasoning Index; BOT-2 = Bruininks-Oseretsky Test of Motor Proficiency; vHIT = video head impulse test; PPVT-4 = Peabody Picture Vocabulary Test – 4; CNH = children with normal hearing; CCI = children with cochlear implant, NV = normal vestibular; UVD = unilateral vestibular dysfunction; BVD = bilateral vestibular dysfunction.

3.3. Additional Metrics:

Balance:

There was a significant group difference in balance ability using both the BOT-2 total raw score (F (3, 63) = 28.9, p < .001, ES = .76) and scaled score (F (3, 63) = 11.07, p < .001, ES = .59). Post hoc testing for the raw score using Tukey’s HSD demonstrated no significant difference in mean performance between CNH and CCI-NV (p = .236), CCI-UVD performed significantly worse than CNH (p < 0.001) and CCI-NV (p < 0.001), and CCI-BVD performed significantly worse than all the groups (CNH, p < .001, CCI-NV, p < .001, CCI-UVD, p = .015; Table 1). Post hoc testing for the scaled score using Tukey’s HSD demonstrated a similar pattern; however, there was no significant difference in performance between CCI-UVD and CCI-BVD groups (p = .863, Table 1).

Dynamic Visual Acuity (DVA):

There was a significant group difference in dynamic visual acuity ability (F (3, 61) = 11.51, p < .001, ES = .6; Table 1). Post hoc testing for the raw score using Tukey’s HSD demonstrated that CCI-BVD performed significantly worse than all the groups (CNH, p < .001, CCI-NV, p < .001, CCI-UVD, p = .025; Table 1) and that CCI-UVD performed significantly worse than CCI-NV (p = .04), but not CNH (p = .089).

Speech Perception:

There was a significant group difference in speech perception ability using the AZBio Sentences (F (3, 67) = 8.698, p < .001, ES = .53; Table 1). Post hoc testing using Tukey’s HSD demonstrated that CNH had better speech perception than CCI-NV (p = .011) and CCI-UVD (p < .001), but not CCI-BVDL (p = .939). Among the CCI, there was no significant difference between CCI-NV and either CCI-UVD (p = .069) or CCI-BVD (p = .71); however, CCI-UVD had significantly worse speech perception compared to CCI-BVD (p = .047).

Vocabulary:

There was a significant group difference in vocabulary ability using the PPVT-4 (F (3, 67) = 9.037, p < .001, ES = .54; Table 1). Post hoc testing using Tukey’s HSD demonstrated that CNH had better vocabulary than CCI-NV (p < .001) and CCI-UVD (p = .007), but not CCI-BVD (p = .558). Among the CCI, there was no significant difference in vocabulary between CCI-NV and either CCI-UVD (p = .939) or CCI-BVD (p = .763) and no significant difference between CCI-UVD and CCI-BVD (p = .611).

3.4. Self-Concept:

Self-Concept:

There were no significant group differences in the Piers Harris overall self-concept Total Score (F (3, 67) = 1.729, p = .169, ES = .27; Figure 1, Table 1) or any of the sub domain scales (p = .086 - .729, Table 1). The average range for the overall self-concept total score is 40 – 59 while the average range for the sub domain scales is 40 – 55. As noted in Table 1, the average for each of the groups is within these average ranges. In looking at the raw individual data, few children scored within the low average range for overall self-concept total score (CNH = 1, CCI = 1) or the subdomains (BEH: CNH = 0, CCI = 2; INT: CNH = 0, CCI = 0; PHY: CNH = 1, CCI = 2; FRE: CNH = 2, CCI = 2; POP: CNH = 3, CCI = 4; HAP: CNH = 1, CCI = 1) and with the exception of 1 CNH in the Physical subdomain, none of the remaining children had scores in the very low range (≤ 29), consistent with a serious emotional or behavioral disorder.

Figure 1:

Mean Piers Harris scores by group. There were no significant differences in overall scores. Of note, the group with bilateral vestibular dysfunction (n = 4) demonstrated normal scores with little variability. CNH = children with normal hearing; CCI = children with cochlear implant, NV = normal vestibular; UVD = unilateral vestibular dysfunction; BVD = bilateral vestibular dysfunction.

Self-concept Total Score was investigated between the CNH and the CCI group as a whole and there were no mean differences in overall self-concept Total Score between CNH (mean: 55.97 (7.89)) and CCI (mean 52.58 (9.04); t = 1.69, p = .095). Additionally, Self-concept Total Score was investigated between the CCI-NV (n = 23) and CCI-VL groups combined (n = 10) and there were no significant group differences in the overall self-concept Total Score between CCI-NV (mean: 51.96 (8.8)) and CCI-VL (mean: 54 (9.9); t = −.591, p = .559) or any of the sub domain scales (p = .265 - .813).

Multiple regression was then completed to determine which factors (if any) best predicted the total self-concept score. Age, gender, average horizontal canal vHIT gain, BOT-2 score, DVA, speech perception, and vocabulary were entered into the model using stepwise selection and produced R² = .348, F (1, 65) = 8.846, p = .004. The correlation matrix is provided in Table 2. The only factor that significantly contributed to the model was vocabulary score, suggesting that children with higher vocabulary scores had better self-concept.

Table 2.

Correlation matrix of all predictor variables. Significant correlations are bolded

Predictor Variables	AZ Bio	PPVT-4	BOT-2 Total	Mean vHIT gain	Passive DVA
AZ Bio	--	.491	.302	.158	−.079
PPVT-4	.491	--	.139	.113	.018
BOT-2 Total	.302	.139	--	.691	.48
Mean vHIT gain	.158	.113	.691	--	−.601
Passive DVA	−.079	.018	.48	−.601	--

BOT-2 = Bruininks-Oseretsky Test of Motor Proficiency; vHIT = video head impulse test; DVA = dynamic visual acuity; PPVT-4 = Peabody Picture Vocabulary Test – 4

Due to concern regarding collinearity among the predictor variables, a PCA was conducted on the predictor variables (average horizontal canal vHIT gain, BOT-2 score, DVA, speech perception, and vocabulary) with varimax rotation. One CCI-BVDL did not have vHIT or BOT-2 completed and 1 CCI-BVD did not have DVA completed. Therefore, these participants were given the average score in the CCI-BVD group for vHIT (0.29), BOT-2 (16.7) and DVA (0.67). The Kaiser-Meyer-Olkin measure verified the sampling adequacy for the analysis, KMO = 0.633, which is above the acceptable limit of 0.5[39]. Two factors had Eigenvalues over Kaiser’s criterion of 1 and in combination explained 74% of the variance; thus, these 2 factors were retained. Table 3 shows the factor loadings after rotation and Figure 2 shows the Scree Plot. Unsurprisingly, factor 1 represents “vestibular” and factor 2 represents “auditory-language” components.

Table 3.

PCA Predictors and Component Structure

Predictors	Component
	1	2
	“Vestibular”	“Auditory Language”
BOT-2 – Total Raw Score	.856
Mean HC vHIT gain	.860
Passive DVA	−.729
AZBio		.730
PPVT-4		.801

BOT-2 = Bruininks-Oseretsky Test of Motor Proficiency; HC = horizontal canal; vHIT = video head impulse test; DVA = dynamic visual acuity; PPVT-4 = Peabody Picture Vocabulary Test – 4

Figure 2:

Eigenvalue Scree Plot. The first two components have eigenvalues greater than 1 and explain 74% of the variance, thus were retained. Factor 1 represents “vestibular” and factor 2 represents “auditory-language” components.

In addition to age and gender, the 2 PCA factors were analyzed using multiple regression with stepwise selection to determine which factors best predicted self-concept. Models with higher order interactions were not significant. The multiple regression model produced R² = .119, [F (1,64) = 8.674, p = .004]. The PCA auditory-language factor was the only significant predictor of self-concept (unstandardized coefficient (B) = 2.489).

4. DISCUSSION

The purpose of this study was to evaluate the effect of hearing loss and vestibular dysfunction on self-concept (i.e., how children feel about themselves) in CCI compared to CNH. It was hypothesized that children with vestibular dysfunction would have reduced self-concept beyond that from hearing loss. This hypothesis was generated from trends seen in adults with vestibular dysfunction who report reduced quality of life [16-18] and the negative correlation noted between motor performance, peer acceptance and athletic competence [20,21]. In the current study, children with vestibular dysfunction demonstrated reduced balance and dynamic visual acuity performance, as expected; however, contrary to our hypothesis, results suggest that auditory-language related factors (e.g., speech perception and vocabulary) rather than vestibular-related factors (e.g., average horizontal canal vHIT gain, BOT-2 score, and DVA) are better predictors of self-concept. The lack of an effect of vestibular dysfunction may be from 2 factors: 1) self-concept is a different underlying construct compared to quality of life, and/or 2) that children with vestibular dysfunction may have some degree of resiliency not seen in adults regarding the psychological effects of vestibular dysfunction.

The current study evaluated self-concept, which is distinguishable from quality of life. Quality of life is a combination of an “individual’s perception of health status, psychosocial status, and other aspects of life” [40]. Additionally, the psychosocial aspect can be further separated into psychological and social relationships. Alternatively, self-concept is only a dimension of an individual’s psychological development [22]. Therefore, it could be that like adults, children with vestibular dysfunction exhibit reductions in quality of life, but their self-concept is unaffected. Future studies are planned to investigate whether vestibular dysfunction results in reduced quality of life in children.

While the spectrum of consequences associated with pediatric vestibular dysfunction have not been fully defined, results to-date suggest that children with vestibular dysfunction have similar consequences to those reported in adults. Namely, children exhibit similar reductions in overall balance, visual acuity, and increased falls [1,3,5-13]; however, findings of the current study suggest that children with vestibular dysfunction and poorer balance and visual acuity may not exhibit the same psychosocial effects of vestibular dysfunction. Molnar et al. (2021) report that as many as 86.4% of adult patients with complaints of vertigo have reduced quality of life and 42.3% with symptoms of depression [19]. However, in the current study, the small cohort of children with BVD (n = 4) had particularly normal self-concept (Figure 1) with scores in the high range of normal (normal range = 40 – 59). This could be because they are unaware that the symptoms or life experiences related to their vestibular dysfunction are different from others. Whereas adults can compare their life experiences and capabilities prior to and following the onset of a vestibular impairment and thus perceive a reduction in their quality of life. Additionally, the small cohort of children with BVD (n = 4) also noted speech recognition and language scores that were just below their normal hearing counterparts (Table 1).

Findings from the current study demonstrated that there were not significant differences in self-concept between CCI and CNH. This is consistent with Boerrigter et al. (2021) who also noted positive self-concept in CCI [27]. Additionally, speech perception and vocabulary significantly contributed to children’s overall self-concept, which is consistent with others who have noted a relationship between psychological constructs and auditory-language factors [22,27,41]. In our cohort, most children demonstrated speech perception scores greater than 72% (Table 1), which is consistent with these findings. In looking at the raw data, only 5 children demonstrated speech scores < 72%. Additionally most children in the study demonstrated self-concept in the normal range (i.e., scores > 40) highlighting the usefulness of a cochlear implant, which allows better access to speech, increased likelihood of participating in mainstream classrooms and higher self-concept [27,42]. Lastly, similar to Mekonnen et al (2016), gender and age had no significant effect on overall self-concept [25].

4.1. Strengths and Limitations:

This was the first study to investigate whether vestibular dysfunction significantly contributes to the self-concept of CCI. While previous studies have focused on the functional effects of pediatric vestibular dysfunction, this is one of the first studies investigating whether vestibular dysfunction results in psychosocial deficits in children. Overall, it is reassuring that the cohort of CCI demonstrated normal self-concept. When investigating the effects of vestibular dysfunction in children, children with vestibular dysfunction are more likely to have severe to profound sensorineural hearing loss. Because hearing loss alone has its own effects, a control group with matched hearing loss is needed to isolate the effects of vestibular dysfunction. This work highlights the necessity of a control group with matched hearing loss when studying the effects of vestibular dysfunction. An additional strength of the study is that the data represent the children’s perceptions of themselves as parents have a tendency to rate children higher than they rate themselves [21].

There are some limitations to the current work. First, there was a small number of children with vestibular dysfunction (10/34 [29%]) reflected in the present cohort; although this is an accurate reflection of the number of children with severe-to-profound sensorineural hearing loss expected to have vestibular dysfunction, it represents a small number of children. Future work is needed on a larger cohort of children with vestibular dysfunction. Second, this study focused on self-concept and did not investigate quality of life. Third, educational setting (i.e., mainstream vs special education setting) and age of implant has been shown to affect overall self-concept. Children in the special education setting have lower self-concept compared to children in the mainstream setting [27] and children who receive their implant at an earlier age have better self-concept/self-esteem compared to children who receive their CI later [26,43]; however, educational setting and age of CI were not investigated as a factors contributing to self-concept in the present study. Lastly, one potential bias is that the participants willing to participate in research may have higher self-concept.

5. CONCLUSIONS:

This study found that on average, the self-concept scores of CCI were like those of CNH. Auditory-language factors (i.e., speech perception and vocabulary) predicted self-concept. Vestibular dysfunction was not a significant contributor to self-concept in CCI. This could be because children with vestibular dysfunction are unaware that their related symptoms are abnormal.

Highlights.

• Auditory-language factors contribute to children with CI’s self-concept.

• Vestibular dysfunction did not contribute to children with CI’s self-concept.

• Children may have psychosocial resilience regarding vestibular dysfunction.