clinical application of the sadl scale in private practice ...€¦ · culty, pure-tone average,...

J Am Acad Audiol 12 : 15-36 (2001)

Clinical Application of the SADL Scale in Private Practice 11 : Predictive Validity of Fitting Variables Holly Hosford-Dunn* Jerry Halpern'

Abstract

Predictive validity of 44 independent variables and their interactions with Satisfaction with Amplification in Daily Life (SADL) scores was assessed . SADL scores were influenced by patient age, years of hearing aid experience, hours of use per day, perceived hearing diffi-culty, pure-tone average, hearing aid style, processor type, and manufacturer's invoice cost . The relative importance of these variables to SADL measures was complex and very small, but the variables and their squares and interactions improved r2 predictions of SADL Global and subscale scores in a separate stepwise multiple linear regression procedure by 12 to 33 percent compared to SADL norms alone. More research with additional variables is needed to develop a clinically useful model for predicting wearer satisfaction . Clinically, SADL scores yield subscale-specific patterns of satisfaction and dissatisfaction that help in intervention planning and serve as graphic "snapshots" of satisfaction status . A series of patient profiles are presented illustrating the potential usefulness of the SADL in predicting hearing aid sat-isfaction. With its good construct and psychometric properties, the SADL could serve as a gold standard for satisfaction outcomes and a basis for development of a predictive model of hearing aid fitting success.

Key Words : Hearing aids, outcome, satisfaction, Satisfaction with Amplification in Daily Life, validity

Abbreviations: ANOVA = analysis of variance, BTE = behind the ear, CIC = completely in the canal, DSP = digital signal processing, ITC = in the canal, ITE = in the ear, PP-SADL = private practice SADL group, PTA = pure-tone average, SADL = Satisfaction with Amplification in Daily Life

P art I of this study verified that the Sat-isfaction with Amplification in Daily Life (SADL) scale quantifies hearing aid

users' responses in content domains that con-tribute to SADL scores in predictable ways (Hos-ford-Dunn and Halpern, 2000) . The SADL's sound construct validity and psychometric prop-erties enable its use as an outcome measure of hearing aid satisfaction in a variety of settings, with a wide range of patients, over periods of months to years postfitting (Cox and Alexander, 1999 ; Hosford-Dunn and Halpern, 2000).

The SADL profiles satisfaction domains in

four subscales containing a total of 15 items. The

*Tai Inc ., Tucson, Arizona ; tDepartment of Biostatistics, Stanford University, Stanford, California

Reprint requests : Holly Hosford-Dunn, TAI, Inc ., PO Box 32168, Tucson, AZ 85751

most important, and heaviest weighted, sub-scale is Positive Effect, which is complemented by the Service/Cost subscale . Together, these two subscales contain nine items that address benefit/value content areas. The remaining sub-scales are Negative Features, which quantifies problems of patient-technology mismatch, and Positive Image, which combines cosmetic and stigmatizing concerns . These two subscales have lesser weighting in the SADL because they rep-resent content areas that are important to some, but not all, patients . However, both subscales contain one item each that is highly important

to satisfaction . Telephone use and appearance are elements that influence satisfaction for almost all users.

A number of variables affect satisfaction in one or more domains (Hosford-Dunn and Baxter, 1985 ; Smedley, 1990 ; Dillon et al, 1997 ; Humes, 1999) in ways that remain unclear. Humes (1999)

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Journal of the American Academy of Audiology/Volume 12, Number 1, January 2001

concluded that satisfaction "may depend on a complex combination of severity of hearing loss, perceived handicap . . ., aided sound quality, reli-ability . . .of the instruments, and the personality of the wearer" (p . 38). With that shopping list in mind, the SADL may be a candidate for ferreting out complex relationships of psychological, demo-graphic, and technical variables with satisfac-tion domains. No data are published relating SADL elements to these classes of independent variables. For instance, statistically higher Neg-ative Features subscale scores in a private prac-tice population (Hosford-Dunn and Halpern, 2000) may be due to the conservative estimate pro-vided by Cox and Alexander (1999) or may rep-resent effects of environmental, patient, or technology variables (e.g ., practice procedures, degree of hearing loss, multichannel processing) .

The importance of identifying relations between variables and SADL scores lies in the idea of developing tools and techniques to improve preassessment needs and predict treat-ment outcomes . By knowing which variables affect satisfaction in what ways, it might be possible to predict hearing aid user satisfaction with some degree of certainty prior to fitting while using the SADL to verify satisfaction at periodic intervals subsequent to treatment.

The sequential goals of Part II of this study were to

represented a wide range of ages, degrees of hearing impairment and disability, hearing aid use, and hearing aid experience . Patients also completed four multiple-choice items on the SADL regarding years of hearing aid experi-ence, daily hearing aid use, and perceived degree of unaided hearing difficulty. These demographics were treated as subjective independent vari-ables in the analyses .

Procedures were incorporated into the patients' regular office visits to encourage par-ticipation . Hearing aids were selected and fitted in a series of appointments in which individual participants received services from one of three audiologists employed in the private practice (including the first author). The evaluation and fitting appointment were 90 minutes each . Follow-up appointments were 30 minutes each . The first follow-up was between 48-hours to 1-week postfitting, depending on hearing aid style (e .g., completely-in-the-canal [CIC1 fittings were scheduled for two appointments in the first week, the first at 48-hours postfitting and the sec-ond at 1-week postfitting) . Weekly follow-up appointments continued until the patient expressed satisfaction with amplification in daily life . Subsequent follow-up appointments were scheduled quarterly or biannually. Patients were scheduled for annual appointments to test hear-ing and review hearing aid fittings .

Identify effects of a select group of indepen-dent variables, and their interactions, on SADL scores ; Evaluate SADL scores for different hearing aid types, if significant hearing aid influences were discovered in the first goal, and compare these scores to interim norms proposed by Cox and Alexander (1999) ; and Investigate the possibility of using the rela-tionships identified in goal 1 to start developing fitting profiles that could serve eventually as generalized predictors of positive hearing aid outcome in a variety of dispensing settings .

0

METHOD

S ubjects, materials, and procedures were described in detail in Part I (Hosford-Dunn and Halpern, 2000). To summarize, all patients fitted with hearing aids in 1996 and 1997 at a sin-gle private practice were asked to complete the 15-item SADL scale at 1-year postfitting. Those who complied (referred to as "the PP-SADL group") constitute the subjects in Parts I and II of this study. Subjects in the PP-SADL group

Instrument Selection

Hearing aid recommendations used a client-centered approach of "consultative selling" (Sweetow, 1999) in which audiologists used a tiered technology chart illustrating three levels of technology (conventional, analog program-mable, and digital), which were described in terms of circuitry, style, application, and price range. Tier assignments were made according to the following operational definitions :

Tier I. Single-channel linear or compres-sion instruments that were not adjustable using Noah-based manufacturers' software modules.

Tier IL Analog instruments that included multichannel or multimemory processing and/or were adjusted using Noah-based fitting tech-nology.

Tier III. Instruments with digital signal processing (DSP).

Four styles were defined: behind the ear (BTE), in the ear (ITE), in the canal (ITC), and CIC.

The tier chart was updated frequently dur-ing 1996 and 1997 to reflect technology changes

16

SADL Validation II/Hosford-Dunn and Halpern

and additions . A typical tier chart is shown in Appendix A. Appendix B lists the instruments used in the study, grouped by technology tier . Audiologists used the technology tier chart for sequential purposes : (1) to explain which hear-

ing aid styles were available in each technol-ogy level (e.g ., DSP CIC hearing aids were not

available until June 1997) ; (2) to advise patients

on which devices and styles matched their

hearing and listening needs best ; (3) to dis-

cuss the pros and cons of selections at each technology level, including performance and price considerations associated with monau-

ral and binaural fittings ; and (4) to ensure that patients' expectations were in line with selected

technologies, styles, costs, and monaural/

binaural fitting recommendations . Hearing aid selection proceeded by estab-

lishing whether the fit should be binaural or monaural and then by indicating particular instruments at different levels of the tier sheet and rank ordering them according to "best fit" styles . The technology tier chart served as a selection guide, with the patient making an edu-cated purchase based on the audiologist's rec-ommendations . Patients did not always choose the top-ranked recommendation, usually due to cosmetic or financial reasons, nor did they always allow a binaural fitting when it was rec-ommended . The tier sheet was inserted in each patient's chart in case original recommenda-tions needed to be revisited during subsequent fitting and follow-up appointments .

were extracted from patients'responses to demo-graphic questions on the SADL and from patient records. They were categorized as intrinsic or extrinsic, as shown in Table 1. Intrinsic variables described characteristics of the patients, and extrinsic variables were specific to the instru-ments and fitting histories . Two conventions were adopted in the Results and Discussion sec-tions for purposes of clarity : (1) intrinsic variables are referred to as intrinsic or patient related; extrinsic variables are referred to as extrinsic or hearing aid related; and (2) because the statis-tical analyses included so many comparisons that some might be significant by chance, we elected to refer to a correlation as "significant" only if the associated p value was less than .005 .

RESULTS

A ge, gender, and audiometric characteris-tics of the cohort and PP-SADL group are

described in Part I of this study (Hosford-Dunn and Halpern, 2000). The PP-SADL group (68.7% of the cohort) was similar to the population in most respects but differed according to some hearing aid-related variables . The PP-SADL participants used higher priced (t = -2 .92), higher tier technology (t = -2.87), binaural fit-tings (t = -3 .05) more than the total cohort (p < .005 for each). They also returned for more hearing aid follow-up checks (t =-6.01, p < .005).

Data Analysis

Data were stored and analyzed on the Stan-ford University Sun Sparc Ultra II computer, Solaris 2 .6 Operating System, using programs from the Statistical Analysis System . Cross-correlation, analysis of variance (ANOVA), step-wise multivariant analyses, and logistic regression procedures analyzed data .

The PP-SADL group consisted of patients in the cohort who returned usable SADL scales . Cri-teria for acceptable SADL questionnaires were described in Part I (Hosford-Dunn and Halpern, 2000). Of 282 returned scales, 257 were used for Global scores, 275 for the Positive Effect sub-scale, 274 for Service/Cost, 271 for Negative Features, and 270 for Positive Effect .

Dependent variables were Global, Positive Effect, Service/Cost, Negative Features, and Positive Image SADL scores, as well as scores on the 15 SADL items. The independent vari-ables selected for examination in this study

Table 1 Summary of Dependent Variables

Type

Intrinsic

Extrinsic

Description

Patient-related variables Gender Age Total hearing aid experience (yr) Daily use (hr) Perceived hearing difficulty (unaided) Pure-tone average (four frequency, left and

right ears averaged) Monaural/binaural status

Hearing aid-related variables Hearing aid style (BTE, ITE, ITC, CIC) Technology tier (conventional,

programmable, DSP) Number of processing channels (1, 2, or 3) Invoice cost Retail price Number of repairs (in first year) Total visits (number of clinical appointments) Total time (sum of clinical appointments in

minutes

17


Table 2 Number of Patients Fit in Each Instrument Category (N = 374)

Conventional Programmable DSP Total (%)

BTE 12 56 29 97 (26) ITE 35 30 17 82 (22) ITC 58 47 31 136 (36) CIC 21 20 18 59 (16) Total 126(34%) 153(41%) 95(25%) 374 (100)

Hearing Aid Selections

The distribution of fittings for different com-binations of hearing aid technology and styles are shown in Table 2 for the cohort . Proportions were similar whether the data were viewed as total instruments or total fittings (Fig . lA and 1B), indicating that binaural or monaural fittings did not occur disproportionately in any tech-nology or style category. One-third of the instru-ments fitted in this study were conventional (Tier 1), 41 percent were programmable (Tier II), and one-quarter were DSP (Tier III) . Fittings were fairly evenly distributed among styles . The most common style was ITC (38%). Almost half of the instruments were BTE or ITE. Sixteen per-cent of the instruments were CIC.

Table 3 and Figure 2 summarize PP-SADL group response rates according to hearing aid style and technology categories . Logistic regres-sion analysis showed a statistical difference (p = .016) in response rates among the three tech-nology levels, indicating that the response rate of DSP users was significantly higher than that of patients who wore conventional aids . However, there was no strong evidence of true differences between the conventional and programmable or between the programmable and DSP response rates.

ables in Table 4 correlated significantly (p < .005 or . 001) with one another except age, which cor-related only with four-frequency pure-tone aver-age (PTA) (500, 1000, 2000, 3000 Hz).2,3 These intrinsic correlations indicated that patients with greater hearing loss reported more hear-ing difficulty, more years of hearing aid use, and greater daily wearing time .

Extrinsic variables were uncorrelated, with a few predictable exceptions : (1) higher tech-nology tiers had higher invoice costs and (2) smaller, more expensive instruments had more first-year repairs. Style and technology were unrelated, implying that technology selec-tion did not drive style selection or vice versa. The number of hearing aid changes during the trial period did not differ for different hearing aid styles or technology tiers.

The only variable that linked patients to instrumentation was style, which correlated significantly and negatively with all intrinsic variables. The correlations with style in Table 4 indicate that smaller instruments were fitted on younger patients with less hearing loss and hearing aid experience, who reported less hear-ing difficulty and used their instruments fewer hours per day. The relationship between age and repairs is due to style: older patients tended to wear larger hearing aids, which had fewer first-year repairs.

Variable Influences on SADL Scores

Univariate Analyses

Significant correlation coefficients between dependent and independent variables are shown in Tables 5 and 6. One-way ANOVA procedures

Relation of Intrinsic and Extrinsic Variables

Correlation analyses were performed for all dependent variables in Table 1. The following variables were excluded from subsequent analy-ses because they did not correlate significantly with any dependent variables in the study (p > .005): gender, monaural/binaural status,' number of independent processing channels (i .e ., one to three), retail price, number of repairs, total visits, and total time .

Table 4 examines the relationships of the remaining variables to each other. Intrinsic vari-

'Kochkin (2000) has reported a 3 percent improve-ment in overall satisfaction for binaural wearers, based on national survey results . Our variable is not directly com-parable and undoubtedly underestimates the effect of a binaural effect because it is based on the number of aids fitted, so that binaural users who purchased one instru-ment were coded as monaural fittings .

2 PTA was selected as the variable of choice for hear-ing loss because hearing loss effects were not frequency dependent when audiometric thresholds at 500 to 4000 Hz were correlated with other study variables .

'Functional gain at 500 to 4000 Hz also correlated with these patient variables, independent of test frequency, but did not influence SADL scores systematically and was not used as an extrinsic variable in this study. Similarly, Beamer et al (in preparation) found no predictive value of National Acoustic Laboratories' target gain match on perceived hearing aid benefit .

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A

# Aids

B

# Aids

# Fittings

Tier I Tier I I Tier III

# Fittings

BTE ITE ITC

~_ CIC

Figure l Distribution of hearing aids (n = 608) and hearing aid fittings (n = 374) by technology tier (A) and style (B).

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Table 3 Distribution of Hearing Aid Fittings for Patients Who Returned SAM Scales

Conventional Programmable DSP Total (51o)

BTE 4 37 26 67(69) ITE 25 24 15 64(78) ITC 42 36 26 104(76) CIC 16 17 14 47(80) Total 87(69%) 114(75%) 81 (85%) 282(75%)

Percent response rate for each aid category shown in parentheses.

were performed when appropriate and indi-cated. ANOVA results are described in the text.

Global Scores

Global satisfaction correlated with age . Age had small negative effects on Global and Posi-tive Effect scores (see Table 5) and on telephone use (see Table 6) . These effects were not artifacts of the skewed age distribution of subjects because t-tests of Global and subscale scores for older (>59 years old, n = 253) and younger (<60 years old, n = 22) subjects were not significantly dif-ferent (p > .29) . One-way ANOVA showed a sig-nificant effect of style on Global satisfaction

(F3,253 = 3.167, p = .025) in which smaller instru-ments were associated with higher Global scores (Figure 3) .

Subscale and Constituent Item Scores

Variables in this study affected SADL scores in a dichotomous manner, as shown in Table 5 by the arrangement of intrinsic variables in the top and extrinsic variables in the bottom portions of the chart. Intrinsic variables correlated with

Tier Style

Figure 2 Percentage of patients who completed the SADL, according to hearing aid technology tier and hear-ing aid style (n = 282 respondents) .

the Positive Effect subscale and extrinsic vari-ables correlated with the Personal Image sub-scale . Only the Negative Features subscale correlations reflected influences of both intrin-sic and extrinsic variables. The effects were not great: none of the correlations was large, and Service/Cost did not correlate with any vari-ables in the study.

A further dichotomy was that intrinsic vari-ables correlated with either Positive Effect or Negative Features subscales, but not both . Those patients who reported more daily use and greater perceived hearing difficulty also reported higher Positive Effect, manifest by significant correla-tions of these variables with most items in that subscale (see Table 6) . Patients who reported more years of hearing aid use and had greater audiometric hearing loss reported lower Nega-tive Features scores due to increased dissatis-faction with feedback and background noise.

Table 4 Spearman's Rho Correlation Coefficients Between Study Variables

ge

Total Hearing Aid

Experience Hours/ Day

Age - Total hearing aid experience Hours/day - 0.25** - Perceived hearing difficulty - 0.20* 0.41 ** Pure-tone average 0.22** 0.42** 0.26** Style -0.16* -0.25** -0.28** Technology tiers - - - Invoice - Repairs -0.15* - Aid changes - - -

Perceived Pure- Hearing Tone Technology Difficulty Average Style Tiers Invoice

0.52** --0.41** -0.46**

0.75** 0.26** - 0.18**

*p < .005 ; **p < .001 .

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SADL Validation ll/Hosford-Dunn and Halpern

Table 5 Spearman's Rho Correlation Coefficients Between SADL Subscales and Related Variables

Variables

Intrinsic

Global Positive Effect Service/Cost Negative Feature Personal Image

Age -0.18* -0.22* Total hearing aid experience -0.23* Hours/day 033* Perceived hearing difficulty 0 .25* Pure-tone average -0.29**

Extrinsic Style 0.31** 0.25** Technology tiers Invoice 0.19*

*p < 005; **p < .001 .

Style emerged as the key extrinsic variable for predicting SADL scores, manifest in the Neg-ative Features and Personal Image subscales. Five of the six items in these two subscales showed small but significant correlations with style (see Table 6), and item 4 barely missed sig-nificance (p = .006) by the criterion of this study. The meaning of these relationships is illustrated in Figure 4, showing less dissatisfaction with Negative Features and more satisfaction with

Personal Image for smaller instrument designs. The relationship of size with satisfaction in these subscales was confirmed by one-way ANOVAs (Negative Features : F,, 267 = 9 .49, p = .0001 ; Positive Image: F,, 266 = 729, p = .0001).

Figure 5 shows the effects of style on items in the Negative Features and Positive Image sub-scales, where larger instruments (BTE and ITE) produced lower satisfactions than smaller instru-ments (ITC and CIC) on all items. One-way

Table 6 Spearman's Rho Correlation Coefficients Between Study Variables and SADL Items, Organized by Subsale

ge

Total Hearing

Aid Experience

Hours/ Day

Perceived Hearing Loss

Pure- Tone

Average it nvoice epairs Aid

Changes

Positive Effect Item 1 -0 18* 0 .22* -0.19* Item 3 0 .32** 0.31** 0.21** Item 5 -0.24** - Item 6 0.33** 0.31 ** 0.20** Item 9 - 0.25** 0.3** 0.30** 0.27** Item 10 -0.17* 0.21 **

Service/Cost Item 12 Item 14 Item 15 -0.32**

Negative Features Item 2 - -0.20** 0.24** - Item 7 0.30** -0.27** -0.28** 0.20* - Item 11 -0.21 * - - 0.25** 0.18*

Personal Image Item 4 Item 8 0.20* -0.20* Item 13 0.19* -

*p< .005 :**p< .001 .

21


5.4 +1SE Mean

2 L 5 1SE .

O v N

5 0 .

O 0 4.8

4.6 45 4;r CK

4~V ~~' ~~~

Figure 3 Mean SADL Global scores and standard errors for four hearing aid styles (n = 257 SADL scores).

ANOVAs for each item, classified by style, were significant (p < .05 or less), but the main effects were due to one item in each subscale . Both telephone use (item 11) and appearance (item 8) were rated significantly higher by CIC users than users of ITC, ITE, or BTE instruments

(F3,251 = 5.97, p = .0006 ; F3,264 = 5.11, p = .0019) . Technology tiers did not correlate with SADL

scores or item scores, nor were one-way ANOVAs between technology tiers and SADL subscales

BTE (n=64.66) 0 ITE.(n=62-63)

ITC (n=99-100)

. G ~ Wr ' ~ ^"~ mt ; OC

Q02 Q ~~

Figure 4 Mean SADL subscale scores for four hearing aid styles .

OCi V0

J 0 ~a1 ®

` ~0

significant . Invoice cost, number of repairs, and number of hearing aid changes had small but sig-nificant effects on subscale scores . Higher-cost instruments were associated with higher Posi-tive Image subscale scores (see Table 5) and more satisfaction with telephone use (see Table 6) . The only other significant correlations were in areas that are predictable from clinical expe-rience . Patients who had more hearing aid repairs were less impressed with the depend-ability of their instruments (item 15). Patients who exchanged their instruments for other styles or technology tier types during their trial peri-ods expressed less satisfaction with the appear-ance of their instruments (item 8) .

Multivariate and Factor Analyses

A principal research question was whether combinations of the independent variables in our study affected SADL scores in measurable ways . As a first step in this direction, we looked at the isolated effects of style and technology tiers to see if the lack of effect of technology tiers in univariant analyses was due to a confounding of size and circuitry. Two-way ANOVA for tech-nology tiers X style without interaction paral-leled the findings reported in the previous section for style alone, indicating that size influenced sat-isfaction more than processing on SADL mea-sures. Significant relationships due to style, but not technology tiers, were found for Global

(F5,251 = 3 .51, p = .01) and Negative Features (F5,265 = 10 .11, p = .0001) scores . Despite the independence of style, the two-way ANOVA did show a secondary effect of technology tiers on Personal Image scores, which were significantly better for DSP and programmable instruments (Tiers III and II) compared with conventional (Tier I) instruments (F test for style F3,264 = 8.36, p < .0001; F test for technology tiers: F5,264 = 2.95, p = .05; omnibus F test for the model: F5,264 = 5.71, p = .0001) .

A separate stepwise multiple linear regres-sion procedure was used in the following man-ner to determine whether selected variables contributed to satisfaction in more complex ways . Ideally, the procedure should use all variables to produce a predictive equation that explains how the variables, their squares, and their interac-tions may be used in a predictive mode . However, preliminary work showed that using all of the variables in the model produced results that served to confuse, rather than clarify, the clini-cal picture provided by the SADL. Therefore, we limited the model to specific variables that came

22


Item 2 Item 7 Item 11

Figure 5

E BTE (n=51-67) ITC (n=78-101) ITE (n=52-63) / CIC (n=32-46)

Item 4 Item 8 Item 13 BTE (n=56-64) ITC (n=93-101)

C1 ITE (n=58-61) / CIC (n=39-44)

Mean scores for four hearing aid styles on Negative Feature items (A) and Personal Image items (B) .

to our attention as the result of the lower-order, single-variant analyses (see Tables 5 and 6) . We also excluded aid changes and repairs because these variables represented rare events . The intent was to get an idea of which universal vari-ables remained important in the presence of the other variables (i .e ., gave information in addition to the others). The model for the stepwise back-ward selection procedure contained the eight variables from Table 5, their linear and qua-dratic combinations including squares, for a total of 44 variables.' The model was as follows:

Global = age, PTA, perceived hearing diffi-culty, daily use, total hearing aid experi-ence, style, technology tiers, invoice, and the squares and pairwise products (interac-tions) of these eight variables.

Table 7 gives the results of the procedure for

Global and SADL subscores . In each case, no

more than seven variables remained when the

criterion for remaining in the model was p < .05 .

All eight of the original variables selected for the

model contributed to the results-as a linear

term, its square, or in combination with other

linear terms . RI values were too small to develop

a predictive model, but some observations about the data are worth noting. As Table 7 shows, the

'Our goal in pursuing this analytic approach was to try to understand contributions by allowing variables and their squares and interactions . We did not require a hier-archical model with linear terms but allowed quadratic variables to appear without their linear constituents .

relative importance of the variables to SADL measures was complex and very small. However, the significance of the p values is strong evidence that there are relationships and that it is worth-while to investigate the nature of the relation-ships further.

Age and its square were the most important variables for three SADL measures . Age exer-cised an exponential and negative effect on Global and Positive Effect scores and a linear negative effect on Service/Cost . It also had a positive effect on these scores when combined with invoice and perceived hearing difficulty.

Perceived hearing difficulty and its square had a negative effect on Service/Cost and Per-sonal Image scores . However, perceived hearing difficulty in combination with other variables (age, daily use, PTA, and style) exercised posi-tive effects on all SADL measures except Neg-ative Features .

Daily use was an important but compli-cated variable, which affected all SADL scores except Service/Cost . Daily use x style had a positive effect on Global scores . Daily use alone had an exponential, negative effect on Nega-tive Features but affected that subscale positively in interactions with style or technology tier . Daily use x total hearing aid experience and x PTA increased Personal Image scores, but daily use x PTA reduced Positive Effect scores .

Total hearing aid experience had an expo-nential and positive effect on Negative Features but a linear and negative effect on Personal Image. When combined with PTA or technol-ogy tiers, the effect on Negative Features was

23


Table 7 Results of Stepwise Backward Selective Procedure for Global and Subscale Scores, Using Eight Variables,Their Squares and Interactions (44 Variables Total)

Variable Parameter Estimate Probability > F

Global (n = 230) r2 = .117 Age 2 -0 .00014 0001 Daily use x style 0.04224 0018 Perceived hearing difficulty x PTA 0.00324 0036 Age x invoice 0.000 .0073 PTA x invoice -0.000 0221

Positive Effect (n = 243) r2 = .33 Age2 -0.00059 0001 Daily use x PTA 0.00749 0001 Age x perceived hearing difficulty 0.01929 0021 Style x invoice 0.00010 .0109 Perceived hearing difficulty' -0.21586 .0118 PTA x invoice 0.00010 0109

Service/Cost (n = 244) r2 = .17 Age -0.06211 0019 Age x perceived hearing difficulty 0.01884 0056 Perceived hearing difficulty' -0.20041 .0246

Negative Features (n = 240) r2 = .187 Daily use x style 0.09503 .0004 Daily use' -0.13838 0009 Total hearing aid experience x PTA -0.00631 0019 Daily use x technology tiers 0.30100 0057 Total hearing aid experience' 0.12598 .0144 Total hearing aid experience x technology tiers -0.28429 0152

Personal image (n = 239) r2 = .140 Daily use x PTA -0.01671 0002 Total hearing aid experience x daily use 0.24800 0005 Perceived hearing difficulty x style 0.07631 0006 Perceived hearing difficulty x PTA 0.01520 .0008 Total hearing aid experience -0.72887 0025 Age x invoice -0.72887 .0025 Perceived hearing difficulty -0.73282 .0040

negative . When combined with daily use, the effect on Personal Image was positive .

PTA had mixed effects on all SADL scores except Service/Cost in interactions with per-ceived hearing difficulty, invoice, daily use, or total hearing aid experience .

Style interacted with daily use, invoice, and perceived hearing difficulty to positively affect all SADL scores except Service/Cost. Positive effects indicated increased satisfaction with smaller instruments .

Technology tiers affected only the Negative Features subscale. In combination with daily use, the effect was positive . In combination with total hearing aid use, the effect was negative .

Invoice x age or x PTA had positive and negative effects on Global, Positive Effect, and Personal Image scores. Invoice x style increased Positive Effect scores .

We further limited the scope of our inquiry to the effect of intrinsic variable combinations on Global scoring. Using the model

Global = age, PTA, perceived hearing diffi-culty, daily use, total hearing aid experi-ence, and their square and interactions, age was the only variable selected .

After age was entered, no further variable in the model was significant (p < .05), but the daily use x perceived hearing loss interaction was borderline significant (p = .059). In real-world terms, even this very limited model emphasized the small effect of age on over-all satisfaction : for every decade of increased age in our cohort, Global SADL scores decreased by -0 .12 points on the 7-point scale.

24

DISCUSSION

Effects of Independent Variables on SADL Scores

As conceptualized by Cox and Alexander (1999), an important part of the clinical success of the SADL lies in the correspondence of its sub-scales to domains that reflect wearer satisfac-tion, underscoring the multidimensional nature of the satisfaction construct. When the SADL is used clinically, the different patterns of scores that emerge quickly make it apparent that sev-eral factors contribute to satisfactory hearing aid fitting outcomes, with each factor affected by variables that interact in complex and unique patterns depending on the individual patient.

According to the theory of its construction, the SADL score should meet or exceed norms whenever a patient's needs are surmised cor-rectly, appropriate counseling is provided (and heeded by the patient), and a patient is fitted and maintained with optimal instrumentation . In such a theoretical world, score deviations below SADL norms reflect a failure in the fitting process due to one or more variables that were improperly weighted during the counseling, selection, fitting, or follow-up . Due to the clini-cal nature of our study, the audiologists strove to ensure "best match" fittings by assessing and treating patient- and hearing aid-related vari-ables over 1-year intervals . To the extent that they succeeded with each fitting, none of the study variables should have reduced satisfaction measures below norms . Likewise, if no study variables are associated with inherently more satisfaction, none should increase satisfaction measures above norms . Therefore, the effects of our study variables on SADL scores in the pre-sent data reflect variances that were unan-ticipated or poorly addressed in fitting and treatment (e.g ., cosmetic concern) or are due to inherent satisfaction differences associated with the variables (e.g ., age, style) .

Overall, the results of this study reinforce the observations that objective measures of hearing disability (e .g., PTA) and hearing aid fitting (e .g ., functional gain) and subjective measures of ben-efit (e .g ., Positive Effect) do not account for some important aspects of wearer satisfaction with hearing aids in daily life. Our attempts to iden-tify other predictors of wearer satisfaction met with only slight success. Although some vari-ables are almost certainly related to long-term satisfaction with hearing aid use, the data make it clear that additional variables and interac-


tions must be analyzed before we can hope to pre-dict satisfaction a priori . The results of this study identify some areas of variance in SADL data as a first step toward describing and codifying com-plex interactions of variables that affect long-term hearing aid user satisfaction . At the same time, we recognize that there are many complex vari-ables such as personality, psychosocial adjust-ment to hearing loss, and overall health that are weighed in clinical decision making that were not included in our study.

Using univariate analyses, we dropped out variables that did not affect satisfaction accord-ing to any SADL measures but kept other vari-ables that appeared relevant to specific domains of user satisfaction . In particular, five patient-related variables correlated with benefit mea-sures and three technology-related variables affected cosmetic concerns . The only domain in which both types of variables convened was Negative Features, where style and patient vari-ables made differences in satisfaction .

Although design differences prevent direct comparisons, the same-direction correlation trends reported in other research (cf., Schum, 1992 ; Dillon et al, 1999 ; Kochkin, 2000; Beamer et al, 2000) support the validity of our observa-tions (e.g ., negative correlation of PTA with Neg-ative Features, positive correlation of daily use with Positive Effect and with degree of hearing loss). Thus, the first-order analyses encouraged pursuit of a predictive model of satisfaction based on the eight consequential variables shown in Table 5. However, it became clear from higher-level analyses that variables that affected satisfaction domains did so in the presence of other influen-tial variables and higher-order interactions, so that satisfaction outcomes were affected in extremely complex ways . Although we were able to use the variables to improve outcome estimates over those provided by SADL mean scores, the improvements were not sufficient to develop a model for clinical predictions.

The present data encourage further research to complete a predictive model. They also allow some speculation as to the paths that such research might take . A few variables affected SADL scores in patterns that suggest predictive fitting profiles . Their recurrent significance in relation to different SADL measures, as demon-strated by a variety of statistical analyses, strongly suggested that the relationships are important. The following discussion looks at the effects of those variables and their interactions on the SADL and the profiles that are suggested by these effects.

25


Age

As patients aged, their hearing losses increased but their impressions of hearing dif-ficulty did not. They tended to use larger instru-ments, but their daily wearing times did not increase . Their satisfaction with acoustic aspects of hearing aid benefit decreased to the point that Global satisfaction and Positive Benefit scores declined as an exponential effect of age. Indirectly, the inverse relation of age and acoustic benefit is consistent with well-documented reports in the literature of the deleterious effects of age on speech understanding, due to cognitive slowing or auditory processing deficits (Jerger et al, 1990 ; Pichora-Fuller et al, 1995 ; Gordon-Salant and Fitzgibbons, 1999). More directly, negative relationships have been reported for age and hearing aid benefit (Beamer et al, in prepa-ration) and for age and hearing aid user satis-faction (Smedley, 1990).

Age also reduced satisfaction with Service/Cost . Interestingly, these negative effects of age alone were offset somewhat by increases in Global, Positive Effect, and/or Service Cost scores for those older patients who perceived more hearing difficulty and/or purchased higher cost instruments. The latter almost certainly reflects higher technology tier fittings, given the high correlation of invoice cost with tech-nology tiers. The former suggests an apprecia-tion of services that may be tied to a heightened awareness of disability in some older patients .

Clinically, one could speculate from these results that hearing aid satisfaction in older patients might be improved with a sequential, twofold aural rehabilitation program empha-sizing needs-matched technology applications prior to purchase and systematically raising expectations for hearing performance in post-fitting aural rehabilitation sessions . This approach is in line with data from Schum (1999) indicating that prefitting expectations and post-fitting perceived benefit operate as separate domains.

Age-related dissatisfaction focused on the four auditory benefit items on the SADL : speech understanding (item 1), reduced repetitions (item 5), naturalness of sound (item 10), and tele-phone help (item 11). However, satisfaction with value aspects of hearing aid benefit did not decline with age, so that older patients felt that their instruments were "worth it" or "in their best interest" even though they felt that the instru-ments were only partially successful in restor-ing auditory function. This may suggest that

older patients have lowered expectations for amplification, perhaps because they have grad-ually grown used to their disability and per-ceive proportionally less handicap associated with their hearing loss (cf., Gatehouse, 1999).

An example is illustrated in Figure 6. This 85-year-old man rated his hearing difficulty as "moderate" in the presence of 60 dB PTA and 70 dB HL thresholds at 2000 Hz bilaterally. He reported lower than average benefit on all audi-tory benefit items, including telephone use (hence, the low Negative Features score) . Yet, he expressed satisfaction with value, cost, benefit, and appearance with his bilateral, full-shell, multichannel, programmable instruments.

Daily Use

Patients who wore their instruments the most every day had more hearing loss at all fre-quencies, had more years of hearing aid experi-ence, reported more perceived hearing difficulty, and wore larger instruments. In univariant analyses, those patients' SADL scores reflected more benefit in the Positive Benefit subscale and more problems with feedback (item 7). Daily use was not significantly related to Global sat-isfaction but had the highest correlation with Pos-itive Effect (r = .33; see Table 5) . Other studies using different outcome measures and analyses also have found small but significant correla-tions between routine use and benefit (Schum, 1992 ; Dillon et al, 1997 ; Beamer et al, in prepa-ration). Daily use did not influence other subscale scores independently. Patients who did not use their instruments (<1 hour/day reported on the SADL) accounted for only 5.7 percent of the

Figure 6 SADL score sheet for elderly patient with low auditory benefit and good psychological benefit, as reported on Positive Effect subscale .

26

group, notably less than the 16 percent reported in MarkeTrak V (Kochkin, 1999).

Higher-order analyses allowing variable interactions showed a negative, exponential effect of daily use on Negative Features . Oth-erwise, daily use had complicated interactions with other variables, which affected most SADL domains. Patients who wore smaller hearing aids or higher technology tier instruments a lot each day reported higher Global and Negative Features scores, perhaps due to fewer problems with feedback . Patients with greater hearing loss and/or longer histories of hearing aid use who wore their instruments a lot each day were less concerned with stigma and appearance, but those with greater hearing loss also were less sat-isfied with Positive Effect . Clinical speculation from these data suggests two profiles for pre-dicting and manipulation satisfaction, based on daily use:

0 Patients with significant and long-term hear-ing loss who have grown accustomed to and dependent on amplification over the years, even in the presence of less than satisfactory negative features . These patients run the risk of settling into inertia by accepting instru-ments because they have worn them before and because they have a great need for ampli-fication . In order to improve satisfaction with future fittings, counseling could be aimed at educating these patients to ways in which benefit, feedback, and background noise might be improved by technological applications . Patients with milder losses and smaller hear-ing aids who encounter few or no wearing obstacles (e.g ., feedback on the phone) . This is an ideal profile . The daily use results serve to remind clinicians of the importance of exam-ining even "easy" fittings in terms of this variable to undercover overt or covert obsta-cles that may discourage patients from incor-porating their hearing instruments into full-time daily use and therefore may reduce wearer satisfaction .

0

In the literature, daily use is a frequently reported measure of hearing aid fitting success that is considered independent of but somehow related to satisfaction (Dillon et al, 1997 ; Humes, 1999). Our findings concur with this assess-ment and suggest that daily use itself is a mul-tidimensional construct, influenced by other variables, that exercises a variety of effects on satisfaction . Daily use is an important patient outcome measure that affects satisfaction but


does not capture the full spectrum of satisfaction dimensions .

The patient profiled in Figure 7 demon-strates an example of the limitations of daily use as a satisfaction outcome variable . As Humes (1999) points out, "It is not at all clear . . . that higher hearing aid satisfaction will lead to higher hearing aid use ." The patient in Figure 7 is very

satisfied but uses her instruments only a few hours a day. She has a bilateral, mild high-frequency sensorineural hearing loss and pur-chased DSP instruments for one purpose : to improve understanding of evening television . This patient was made aware of infrared systems for this purpose but wanted the communication flexibility provided by amplification . One year later, she reported daily use of 1 to 4 hours and

expressed higher than average satisfaction on all SADL scales .

Total Hearing Aid Experience

Patients with longer histories of hearing aid use had greater audiometric hearing losses, had greater perceived hearing difficulty, and wore their instruments more . Univariate analy-ses with SADL measures showed that patients with longer total hearing aid experience reported greater dependence on amplification (item 9) . They also reported significantly more feedback problems (item 7) and lower satisfaction in the Negative Features subscale . Higher-order analy-ses confirmed that this variable alone had a negative, exponential effect on Negative Features scores . Patients with long histories of hearing aid use who had greater hearing loss and/or wore higher-technology instruments were more likely to report Negative Features problems. Con-versely, the long-time wearers who had greater

Figure 7 SADL score sheet for satisfied patient with low daily use of amplification .

27


hearing loss and/or used smaller instruments were less likely to voice Personal Image concerns .

Clinical speculation suggests a profile of long-term hearing aid users who have few stigma or cosmetic concerns but who are inherently more difficult to satisfy because their degrees of hearing loss or gain preferences push the tech-nological envelope . Counseling for satisfaction in this group needs to stress the importance of technological applications to control negative features but simultaneously stress the limita-tions of even the most sophisticated technologies in high-gain fittings .

Figure 8 is an example of a long-term user with bilateral severe hearing loss who is fitted with multichannel, directional, dual-receiver power aids with manual volume controls . He has no measurable speech discrimination under earphones and does not use the telephone . According to the SADL, the fitting is successful except for feedback problems that prevent the patient from turning both aids to maximum vol-ume. The patient and his family were made aware of the fitting challenge and counseled that periodic replacement of his ear molds would help, but not alleviate, the problem.

Hearing Loss and Perceived Hearing Difficulty

The relation between degree of hearing loss and degree of perceived hearing difficulty man-ifest in our data is well documented in the lit-erature (Cox and Alexander, 1999; Kochkin, 2000). Perceived hearing difficulty was posi-tively correlated with audiometric hearing loss, independent of frequency, and both variables correlated with all intrinsic variables except age.

Figure S SADL score sheet for long-time hearing aid user with severe hearing loss .

First-order analyses showed that these two variables affected SADL scores in different but predictable ways : the greater the perceived hear-ing difficulty, the greater the satisfaction with benefit, as reported in other studies (cf., Schum, 1999). The greater the hearing loss was, the less satisfaction there was with Negative Fea-tures due to increased problems with feedback and background noise.

Higher-order analyses showed a more com-plicated picture in which both variables inter-acted with a number of other variables and with each other to influence satisfaction in most SADL domains. Notably, patients with greater hearing loss who reported greater perceived dif-ficulty had higher Global SADL scores . Per-ceived hearing difficulty, alone or as an interaction, affected all SADL domains except Negative Features . PTA did not emerge as an independent variable, but its interaction with other variables affected all SADL domains except Service/Cost .

To some extent, the complexity of PTA effects is probably related to the hearing losses of the sample population, as discussed in Dillon et al (1999) . The lack of correlation in univariant analyses between PTA and Positive Effect par-allels their comment that "the use of average hearing loss as a predictor of likely benefit appears to be totally without support" (p . 40). The interactive influences of PTA on satisfaction domains further support their suggestion that stronger correlations between hearing loss and hearing benefit should emerge in sample groups that include more patients with hearing in the normal and profound regions.

Beyond these basic observations, it seems as though PTA and perceived hearing diffi-culty are similar to daily use in that they func-tion as multidimensional outcome measures that overlap with satisfaction but fail to clar-ify its components .

Style

Smaller hearing aids were worn by younger patients with less hearing loss, who reported less perceived hearing difficulty, less daily use, and shorter hearing aid histories. On the SADL, smaller hearing aids were associated with higher Global, Negative Features, and Personal Image scores . Patients with small (ITC and CIC) instruments reported more satisfaction on these scales than did patients wearing larger instruments (ITE and BTE) . In both subscales, successively smaller instruments produced

28


incremental increases in satisfaction, particu-larly for CIC wearers in terms of satisfaction

with telephone use (item 11) and appearance (item 8) . Higher-order analyses confirmed that style was important but emphasized the posi-tive effects of style interactions with daily use and perceived hearing difficulty to promote higher Global, Negative Features, and Personal Image scores . Style and technology tiers also interacted at least weakly, with users of smaller Tiers II and III instruments scoring higher on the Personal Image subscale .

Clinical speculation for improving satisfac-tion based on this variable is clearly focused on

ways in which smaller, more sophisticated instru-ments can be fitted to more patients with greater hearing loss without inducing negative features (c£, Van Vliet, 2000) . The predictive profile is con-

stantly changing as processing chips and ear mold technology are developed to accommodate ear canal geometries and enhance signal-to-noise

ratios . Counseling for long-term satisfaction requires that the provider maintain in-depth

knowledge of emerging technologies and appli-

cations in order to optimize processor/packaging recommendations . When fitting patients with

larger instruments, the predictive profile under-

scores the importance of spending extra time

with patients prior to fitting to conduct needs-

based counseling and educate them on expecta-

tions . Postfitting training on telephone use and

assistive listening devices is also likely to improve

satisfaction scores for those patients using larger

instruments .

tion ratings on 60 percent of SADL items (includ-

ing cost) and on all SADL scores except Positive

Effect . However, Tier I instruments scored slightly higher than Tier 11 instruments on one subscale (Negative Features) and on several

SADL items, effectively reducing correlations in the statistics . The trends were not great because

t-tests for differences in means did not reach sig-nificance (p < .05) in any comparison . Never-theless, it seems likely that some other means

of describing instrumentation might reveal more

about its importance to satisfaction domains .

Exactly how this might be done is not clear

because our attempts to categorize the data in

different ways (e.g., number of processing chan-

nels, compression vs noncompression) did not result in higher correlations with SADL mea-sures . One possibility is to compare DSP versus

analog instruments or programmable versus linear instruments . For instance, Kochkin (1996) reported 13 percent higher overall satisfaction

ratings for programmable analog instruments compared with "typical product[s] in the mar-

ketplace ." Clinical speculation, supported less by sta-

tistical significance than by trends, suggests that DSP instrumentation with automatic, intel-ligent management of feedback and environ-mental nonspeech noise will reduce obstacles to full-time use and contribute to other satisfaction domains as well .

Comparison of Private Practice Scores to SADL Norms

Technology Tier and Invoice Cost

Increasing circuit sophistication usually raised the cost of instruments (based on manu-facturers' invoicing) but did not correlate with other independent variables or SADL measures . More sophisticated circuitry interacted with daily wearing time and years of hearing aid use, respectively, to produce increases and decreases in Negative Features satisfaction . Personal Image scores were higher for wearers of small programmable or DSP instruments.

Reviewing the data, it is clear that the inde-pendent contribution of technological sophisti-cation to satisfaction was underestimated by the statistical assumption of an ordered rela-

tionship between technology tiers and SADL scores . In our method, instruments were rank ordered according to their programmability and processing circuitry. By that categorization, DSP instruments (Tier IIl) had the highest satisfac-

The fact that the SADL isolates and quan-tifies satisfaction and dissatisfaction associated

with hearing aid style in the larger context of overall satisfaction is an important clinical

result . In Part I, we found that Negative Fea-

tures scores in the PP-SADL group were sig-nificantly higher than the conservative interim norms reported by Cox and Alexander (1999) . In Part II, we found that subscale patterns for PP-SADL patients differed according to hearing

aid style so that Negative Features and Per-sonal Image scores were higher for smaller aids, especially CICs . Comparisons of subscale norms

with subscale mean scores for CIC wearers in the

PP-SADL group (Table 8) show that CIC wear-ers in the present study were less dissatisfied

with Negative Features and more satisfied with Personal Image than subjects in the normative group. The differences shown in Table 8 are based on a small sample and need replication before it is determined that SADL norms require

29


Table 8 Comparison of Interim SADL Norms to SADL Statistics for CIC Wearers

Low Positive Benefit Subscale

Negative Features Personal Image

Norms CIC Scores Norms CIC Scores (n = 256) (n = 45) (n = 103) (n = 45)

Mean 3.6 4 .6 5 .6 6 .3 SD 1 .4 1 .2 1 .1 0 .7 20th percentile 2.3 3 .6 5 .0 6 .0 80th percentile 5.0 5 .7 6 .7 7 .0

adjustments for hearing aid type or for practice setting.

Clinical Applications of the SADL by Profiling

The SADL is a clinically useful outcome measure because its four subscales analytically and visually profile factors that reflect hearing aid fitting successes and failures, as shown in the following examples. Failure in a specific sub-scale shows up as a readily identified scoring pat-tern that can be used to document problems in a fitting, plan efficient intervention strategies, and quickly and flexibly redirect intervention . The patterns facilitate counseling and recom-mendations by including the patients in the process. Patients can see how they compare to other hearing aid wearers, and clinicians can use the patterns to isolate and translate dissat-isfactions into workable goals for improvement that are understandable to the patients . Exam-ples of subscale-specific profiles and their inter-pretations are discussed in the following sections .

A

~ Nvm

The patient in Figure 9A is a 90-year-old man with moderate hearing loss (PTAs of 40 and 45 dB HL) who is a first-time hearing aid user. He is fitted with binaural canal instru-ments of Tier I technology. His SADL pattern shows very low Positive Effect but satisfaction on other subscores. This pattern signifies low benefit, especially because telephone use is scored very low in the otherwise satisfactory Negative Features subscale . The pattern was rarely encountered in our data . Only three patients (all Tier I instruments; two ITC, one CIC) scored below the 20th percentile on Posi-tive Effect but at or above norms on the remain-ing subscales. One reason for this is the high correlation of Service/Cost and Positive Effect subscales so that these subscores usually moved in the same direction (as in Fig. 9B). The patient in Figure 9A was an exception because he remained pleased with the service and cost, even though he felt that the aids provided little, if any, acoustic or psychological benefit. Despite low benefit, Global satisfaction remains in the acceptable range, in large part because of the absence of technical problems with the fitting. One of the important values of the SADL is that satisfaction does not rely solely on a single index of satisfaction but reveals covert areas of dis-satisfaction that may be less obvious than overt problems such as feedback. The recurring pat-tern shown in Figure 9A and elsewhere of an acceptable Global score in the presence of sub-score dissatisfaction underscores the comment that "absence of problems with a hearing aid fit-ting should thus not be regarded as an indica-

B

Figure 9 SADL score sheets for two patients with low Positive Effect profiles . Service/Cost scores are high for the first patient (A) and low for the second patient (B).

30


tion of a successful hearing aid fitting" (Dillon et al, 1997).

Inadequate gain or instrument malfunc-tions are the first things to rule out when a low Positive Effect pattern appears. Assuming ade-quate gain and function, the low Positive Effect

pattern in Figure 9A is consistent with three sce-narios : (1) the patient's expectations for the selected amplification are too high, (2) the patient is not using the instruments regularly, and/or (3) the patient is not using the instruments effi-ciently (e.g ., setting volume control very low or failing to adjust for different environments) . Each scenario points to patient-related vari-ables that deserve counseling efforts . Also, all sce-narios open the possibility of recommending higher-technology instruments either to better match the patient's expectations or facilitate audibility and adjustment via automatic vol-

ume control. The pattern in Figure 9A is especially con-

ducive to effective counseling that is likely to

improve satisfaction because the patient remains

pleased with Service/Cost issues . The pattern in

Figure 9B was more common in the data set .

Assuming adequate gain, the scenarios sug-

gested by this pattern are the same as Figure 9A, involving mainly intrinsic variables, and the

approach revolves around counseling issues .

However, the likelihood of improving patient

satisfaction is lower because the credibility of the

provider and/or instruments is doubtful in these patients' minds .

Low ServicelCost Subscale

Correlation and factor analyses showed that the Service/Cost subscale was closely related to satisfaction with benefit. Service/Cost also correlated significantly with other sub-scales . It seems likely that almost all patients rate this subscale by calibrating it to their sat-isfaction with benefit and, to a lesser extent, with negative features and cosmetic/stigma concerns . There were no subjects who scored below the 20th percentile for Service/Cost if their satisfaction in the other subscales was at or above subscale means. The SADL in Figure 10 almost met criteria, but Positive Effect was just below the mean . This atypical pattern gives explicit information that the hearing aid's poor repair record reflects poorly on the clini-

cian . Unless decisive steps are taken to fix the repair problem, it seems likely that the patient will pursue new amplification with a different vendor.

Figure 10 SADL score sheet for patient with low

Service/Cost profile .

Low Negative Features Subscale

Figure 11 illustrates the SADL results from

an 87-year-old man with bilaterally symmetric hearing loss and an average PTA of 61 dB HL. His SADL scores meet or exceed norms except

for Negative Features, which shows almost com-plete dissatisfaction with all items in the sub-scale . His comments are informative : "I have

eliminated going to any meeting where there

may be several people talking at once, or where

there may be background noise." The low Neg-ative Features pattern signals a patient-technology mismatch, which may be addressed to the extent that technological applications

exist to correct the problems (e.g ., stronger t-coil, directional microphones, tighter earmold, hand-

held microphone, or personal fm system) .

Low Negative Features was the most com-mon of the single low subscale score patterns and

suggested some interesting findings related to

Figure 11 SADL score sheet for patient with low Neg-

ative Features profile .

31


hearing aid variables. Of the 10 outliers who comprised this group, 8 wore BTE instruments, 9 were fitted with Tier II technology instru-ments, and none wore CIC aids . Dissatisfaction with telephone use in this group is likely to be due to microphone location in the case of BTEs and degree of hearing loss for BTE, ITE, and ITC fittings . Dissatisfaction with feedback and back-ground noise is likely to be higher for Tier II instruments because those instruments in our study characteristically had wider dynamic ranges and frequency responses than most Tier I instruments, but less active control of feedback and gain than Tier III instruments (Appendix B) . Thus, when patients were given choices in sev-eral tiers during hearing aid selection, those who opted for higher technology at lesser cost by choosing programmable rather than DSP instru-ments may have obtained the benefit they wanted but at the price of more negative fea-tures. This "good news/bad news" aspect of Tier II selections may have confounded any direct relations between technology tiers and SADL sat-isfactions .

Clinically, the approach to the Figure 11 pattern centers on technology recommendations that are appropriate for the individual patient's hearing loss, hearing aid experience, and daily use. The SADL can be used to improve the patient's fitting, first by using the Positive Ben-efit score to reassure the patient that it is con-sistent with other wearers'reports and then by using the low Negative Features subscale to let the patient know that this much dissatisfaction is atypical . Discussion of Negative Features components allows education and recommen-dations on ways to reduce the negative aspects of the fitting by switching to a different hearing aid style or to higher-technology instruments for better control of feedback and reduced loudness intolerance of environmental noise. In the case of the patient in Figure 11, he had upgraded from programmable to DSP instruments and felt that the benefit was sufficiently improved that a fur-ther upgrade to directional DSP instruments was not warranted. Instead, he was fitted with new ear molds to reduce feedback, was given a handheld extension microphone for use in noise, and was instructed on the use of a speaker-phone. He declined other assistive listening device options.

Figure 12 SADL score sheet for patient with low Per-sonal Image profile .

problems . Nine patients scored Personal Image below the 20th percentile in the presence of scores in the other subscales that were at or above norms. None of these patients wore CIC instruments; otherwise, no particular pattern of technology and/or style was noted.

The patient in Figure 12 was a 66-year-old man with an asymmetric hearing loss with right and left PTAs of 61 and 35 dB HL, respectively. He was a first-time user. The fitting was monau-ral and right, with a multichannel BTE with automatic volume control. In contrast with patients who rated Personal Image low based on cosmetics (cf., Figs . 6C and 6D in Hosford-Dunn and Halpern, 2000), the patient in Figure 12 expressed strong dissatisfaction with the two stigma items in the subscale but was not unhappy with appearance .

The low Personal Image pattern telegraphs a need for counseling of patients regarding their expectations for those who want smaller instru-ments and information about hearing aid use in general for those who perceive stigma . The fact that these patients report good benefit is an important starting point. Appearance issues may be reduced if patients learn from the SADL that they meet or exceed the satisfaction of other hearing aid wearers who use the same styles of instruments. This pattern can also signal a need to re-evaluate the patient's fitting, in light of new technological advances that may allow more acceptable packaging of the processing features required for good benefit.

Low Personal Image Subscale

Figure 12 shows a low Personal Image pat-tern with good benefit and no negative feature

Reduced Scores on Multiple Subscales

As the single-subscale dissatisfaction pat-terns demonstrate, satisfaction in most areas is

32


sustainable only so long as instrumentation is appropriate to the patient's condition. Lower than average scores on Positive Effect and Neg-ative Features subscales should trigger discus-sion with the patient about expectations, listening situations, assistive devices, and appro-priateness of current amplification for the degree and type of hearing loss . For example, fitting a CIC instrument to satisfy a cosmetic concern in the presence of severe to profound hearing loss

runs the risk of provoking dissatisfaction in the benefit domain. Lower than expected Positive Effect scores with a cosmetically concerned patient may serve as a red flag to revisit the attributes of the fitting and counsel the patient accordingly. At the same time, the Negative Fea-tures subscale score may serve as the red flag by signalling problems with feedback and tele-phone use.

Figure 13 is a case in point. This patient was an 81-year-old man with a history of full-time ITC hearing aid use with recurrent feedback problems for many years. He had a stable, bilat-eral hearing loss with left and right PTAs of 50 and 60 dB HL. Over the years, he repeatedly resisted recommendations for a BTE or ITE fit-ting but was anxious to purchase DSP instru-ments in a canal style, despite obvious feedback and our negative recommendation . One-year postfitting, his SADL results are as shown in Figure 13. He reported lower than normal sat-isfaction in all SADL categories . Low benefit was the direct result of gain compromises dic-tated by persistent feedback in the fitting. Service/Cost followed Positive Effect, as was typical in our data . Negative Features reflected feedback problems in general and with the tele-phone. Personal Image showed the stigma expressed over the years by this patient, even

MX a aap

7aJX Z(M lo !M PercmYe

Figure 13 SADL score sheet for patient with dissat-

isfaction expressed on all scales .

though appearance of the instrument was satisfactory.

In this case, the SADL results dictated a counseling approach that focused on technol-

ogy and expectations because the patient's his-

tory made it likely that stigma would persist regardless of the fitting. The SADL results were

presented to the patient, with emphasis on the

low Positive Effect and Negative Features sub-scores, as support for our prior recommendation for appropriate BTE technology. The graphic representation of dissatisfaction in many cate-gories was a strong and convincing argument for this gentleman, who finally agreed to wear pro-grammable BTE instruments that have proven satisfactory in terms of reducing feedback and providing adequate gain .

CONCLUSIONS

P arts I and II of this study underscore Abrams and Hnath-Chisolm's (2000) obser- vation that satisfaction is a multidimensional construct requiring independent assessment .

The SADL probes domains of importance and satisfaction and scores those domains in a psychometrically sound manner (Cox and Alexander, 1999). In the absence of other mul-tidimensional outcome measures of satisfaction, and given the good construct and psychometric properties of the SADL, a case can be made for using the SADL as a gold standard for estab-lishing satisfaction outcomes . In that case, SADL scores enable a search for independent vari-ables that predict wearer satisfaction a priori .

In this study, as in others, satisfaction was not well predicted by specific hearing aid tech-nologies, measures of hearing loss or hearing difficulty, hearing aid fitting, or benefit. However, the significance of five intrinsic and three extrin-sic variables in predicting SADL scores was strong evidence that these variables are related to SADL scores and that it is worth studying fur-ther the complex relationships of these variables on satisfaction . Patient-related variables that affected SADL scores were patient age, years of hearing aid experience, hours of use per day, perceived hearing difficulty, and combined-ear PTA (four frequency, 500 to 3000 Hz) . Hearing aid-related variables that affected SADL scores were hearing aid style, performance charac-teristics (as defined by three levels of circuit sophistication), and manufacturer's invoice cost . The patient- and hearing aid-related vari-ables, their squares and interactions, improved SADL subscore predictions by as much as 33

33


percent over that provided by SADL norms alone, based on the r2 values in Table 7 . How-ever, Global and other subscore predictions were improved by as little as 12 percent com-pared with norms alone, leading us to conclude that our endeavor encourages more research with additional variables before a clinically useful model can be developed.

Some clinically useful information and some potentially useful trends emerged from the study:

" For a ri t ti h t i f p va e prac ce co or , sat s action is greater with smaller instruments, especially in the Negative Features and Personal Image subscales and especially for telephone use in CIC wearers. It is fair to say that overall sat-isfaction with hearing aids would have been improved significantly if telephone use were satisfactorily addressed for non-CIC wearers in this cohort. If replicated, the differences may be sufficient to warrant separate norms for Negative Features and Personal Image subscales for CIC fittings . Technological sophistication of instruments did not affect satisfaction in a direct man-ner, at least for the three categories defined in our study. Due to the nature of our study, any interpretation from this finding that high-technology instruments are no more satis-factory than low-technology instruments is superficial and incorrect. Patients were fitted according to their needs and expressed wants,

0

with an end goal of tailoring recommendations to optimize individual satisfaction . To the extent that this goal was achieved, different-tiered instruments fitted by need and want should yield equivalent satisfaction . Never-theless, higher-tiered technologies in smaller instruments were associated with greater satisfaction on the Personal Image subscale. DSP (Tier III) technology ranked highest in satisfaction on a majority of items in this and other studies (Sandridge and Newman, 1998). These findings suggest that Tier III-type instruments are likely to prove more satis-factory in daily life, at least for private prac-tice patients who are fitted according to needs-based counseling.

" Satisfaction l f ld i was ower or o er pat ents, mainly due to reduced auditory benefit in general and with more difficulty using the tele-phone. Hours of daily use, degree of hearing loss, and perceived hearing difficulty were mea-sures that related to several SADL scores in

0

complex, overlapping ways, suggesting that these measures themselves are multidimen-sional outcome measures that are essential to satisfaction but do not capture its full essence.

0 SADL scores yield subscale-specific patterns of satisfaction and dissatisfaction that are useful graphic "snapshots" for the clinician and patient. In particular, the areas of dis-satisfaction are helpful in planning inter-vention. As Resnick (1998) comments, "identification of the variables contributing to an unsuccessful fitting [may be] as useful as identification of those giving rise to a suc-cessful one" (p . 133) . Different patterns of dissatisfaction suggest the efficacy of empha-sizing a counseling approach to change patient attitudes and behaviors or of pursuing a more action-oriented approach to change the hear-ing instruments, their components, or acces-sories, depending on the pattern. Patients easily understand the SADL patterns, which lend structure and credibility to the provider's counseling and recommendations.

Acknowledgments. Mary Gansheimer, MS, Nermana Hrustic, Judy Huch, MS, Alicia Hutzel, MS, Michael Irby, MS, Julie Leonard, MS, and Sherri MacMillan, MS, par-ticipated in data collection . Robyn Cox, PhD, Director of the Hearing Aid Research Laboratory, Memphis State University, provided SADL forms and the SADL scoring program. Drs. Harvey Abram, Robyn Cox, and Donald Schum reviewed the manuscript and offered helpful criticism.

REFERENCES

Abrams H, Hnath-Chisolm T. (2000) . Outcomes . In : Hosford-Dunn HL, Roeser R, Valente M, eds. Audiology Practice Management. New York : Thieme, 69-95.

Beamer SB, Grant KW, Walden BE. (2000) . Hearing aid benefit in patients with high-frequency hearing loss . J Amer Acad Audiol 11:429-437 .

Cox RM, Alexander GC . (1999) . Measuring satisfaction with amplification in daily life: the SADL scale . Ear Hear 20:306-319 .

Dillon H, James A, Ginis J. (1997). Client Oriented Scale of Improvement (COSI) and its relationship to several other measures of benefit and satisfaction provided by hearing aids . J Am Acad Audiol 8:27-43 .

Dillon H, Birtles G, Lovegrove R. (1999) . Measuring the outcomes of a national rehabilitation program: norma-tive data for the Client Oriented Scale of Improvement (COSI) and the HearingAid Users Questionnaire (HAUQ) . J Am Acad Audiol 10:67-79 .

Gatehouse S. (1999). Glasgow HearingAid Benefit Profile : derivation and validation of a client-centered outcome measure for hearing aid services . J Am Acad Audiol 10:80-103.

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Gordon-Salant S, Fitzgibbons PJ . (1999) . Profile of audi-

tory temporal processing in older listeners . J Speech Lang Hear Res 42:300-311 .

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of the Satisfaction with Amplification in Daily Life Scale

in private practice I: statistical, content, and factorial

validity. J Am Acad Audiol 11 :523-539 .

Huch JL, Hosford-Dunn H. (2000). Inventory of self-report outcome measures of hearing aid use. In : Sandlin R,

McCandless G, eds. Hearing and Amplification. 2nd Ed . San Diego: Singular, 489-555.

Humes LE . (1999) . Dimensions of hearing aid outcomes . J Am Acad Audiol 10:26-39 .

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of hearing instruments on quality of life . Hear Rev 7(1) :6-34.

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in noise. JAcoust Soc Am 97:593-608 .

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Washington, DC : Department of Veterans Affairs.

Sandridge SA, Newman CW. (1998) . Subjective Satisfaction Ratings for Digital Signal Processing Hearing Aids . Paper presented at the American Speech-Language-

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APPENDIX A

Typical Tier Sheet* Used in 1996/1997 for Hearing Aid Recommendations

The hearing aid industry has introduced many new and innovative products that greatly improve

hearing aid performance . These new products add to the options you have when choosing new hear-

ing aids . To help you decide which product best suits your needs, we have summarized their features :

Tier 1. Conventional Instruments Designed for: " Those whose main concern is hearing spouse and/or television in quiet environments

" Those who want to have a manual volume control

" Previous hearing aid wearers interested in upgrading a standard instrument

Tier II. High Performance and Programmable Analog Instruments

Featuring one or more of the following: computer based, multichannel, multimemory, remote

trolled, fully automatic, or manual volume control, multimicrophone. Designed for:

Active individuals People with poor speech intelligibility Previous hearing aid users looking to improve hearing in noise

Individuals who do not want to adjust their hearing aids at ear level

Those who are interested in advanced technologies

Tier III. DSP Instruments Designed for: " Enhanced speech and reduced noise

" High fidelity and natural sound reproduction

" Feedback cancellation " Quiet, distortion-free sound

con-

-Typical technology tier chart used during the period of this study. Charts were updated frequently to reflect changes

in available instruments (i .e ., DSP CICs were not available until July 1997) .

35


APPENDIX B

List of Manufacturers' Instruments Used in This Study, Categorized by Tier

Manufacturer Model (Descriptors)

Tier I Phonak Inca CIC (Class A or D ; linear or Super Compression) Rexton Miniprimo BTE Starkey CE 8 and 9 ITE (Class A or D)

Intra IV and V ITC (Class A or D) Secret Ear ITC (Class A or D) Sequel CIC (Class D, single channel, nonprogrammable) SM-AGC BTE

UHS Ultima III ITC and ITE Widex ES2-T BTE

Tier II Danavox Aura BTE Oticon Multifocus ITE and BTE

Microfocus ITC Primofocus ITC and ITE

Phonak Piconet AZ BTE Sonoforte AZ BTE

Resound BT2-E BTE ED3 and ED3-E ITE and BTE IE4 ITC (with and without remote)

Siemens Intelivenience CIC Music CIC

Starkey Interra BTE Sequel CIC Sequel 675 AV or AGC BTE

Widex L12T BTE

Tier III Oticon Digifocus ITE and BTE Widex Senso CIC, ITC, ITE, and BTE

clinical application of the sadl scale in private practice ...€¦ · culty, pure-tone average,...

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