Real-Ear Measurement and Its Impact on Aided Audibility and Patient Loyalty

By Amyn M. Amlani, PhD, John Pumford, AuD, and Erich Gessling

Sep 22, 2017

This article looks at how differences in the level of audibility provided by each fitting approach—REM vs Quick Fit—impacts speech understanding and, indirectly, patient loyalty towards the provider. Audibility improvement is, without question, a key consideration, given the realities of increased competition in the form of new product distribution and service delivery models. To that end, we provide the reader with data that supports the impact of REM on patient loyalty towards the provider and practice.

The primary objective of a traditional hearing aid fitting is to ensure that appropriate aided acoustic information (ie, desired output across frequencies at different input levels) is being delivered to the tympanic membrane of the wearer in order to maximize the potential benefit of amplification. The use of a probe-microphone, or real-ear measurement (REM), system is the only way to confirm the appropriateness of hearing aid gain and resulting output across frequencies for a range of input levels at the tympanic membrane. Yet, despite the documented benefits of conducting REM during hearing aid fittings^1,2 and best-practice recommendations by a number of professional bodies,^3,4 REM is one aspect of audiological servicety delivery that has not been consistently embraced as a part of the profession’s standard of care.

For example, professional survey data gathered by Kirkwood⁵ has indicated that 57% of respondents own REM equipment, yet a mere 34% of respondents reported using the equipment consistently. To put this in perspective, assume that 100 practitioners dispense hearing aids and only 57 of this sample owns a REM system. Further, of the 57 practitioners who own a REM system, only 19 (ie, 34%) perform this service routinely. These data conclude that 81 hearing aid fittings, out of a possible 100, likely do not provide optimal audibility and sound quality to the hearing aid user. Similar findings have been reported by Mueller⁶ in 2005 and Mueller and Picou⁷ in 2010. This lack of service delivery, we believe, lends to the inappropriateness of the hearing aid fitting, especially related to audibility, and is a leading cause of stigma—a primary catalyst for the low adoption rates in our industry.

Findings such as those outlined above suggest that many dispensers are relying on manufacturers’ first-fit or Quick-Fit, algorithms to provide appropriate aided gain and output. Yet, the literature indicates that the Quick-Fit methodology results in increased likelihood of inadequate aided gain and, correspondingly, insufficient aided audibility. Aazh and colleagues,⁸ for example, reported on 51 hearing aid fittings programmed to the manufacturer’s NAL-NL1⁹ targets using the Quick-Fit approach. Of these fittings, 71% (36 of 51) resulted in gain deviating from target, both below and above, by 10 dB or more. More recently, Sanders et al¹⁰ compared real-ear aided response (REAR) measures for the premium hearing aids of five major manufacturers that had been quick fitted to the NAL-NL2¹¹ targets of an independent REM system. These authors found that, in general, the manufacturer’s NAL-NL2 quick fits offered less aided gain and, inherently, reduced audibility, as measured by the Speech Intelligibility Index (SII),¹² compared to the NAL-NL2 prescriptive target provided in the REM system, especially at soft-input levels. While speech understanding was not directly measured, findings generally revealed lower aided SII scores for devices quick fitted to either NAL-NL2 or the manufacturer’s proprietary formula relative to the aided SIIs that would be obtained from a precise fit to NAL-NL2 targets.

Research further suggests that the reduced audibility provided by the Quick-Fit approach results in reduced speech understanding in background noise. For example, Leavitt and Flexer¹³ fit individuals with six premier pairs of hearing aids with advanced features enabled (eg, directional microphones, noise reduction) using each manufacturer’s Quick-Fit approach along with a pair of 10-year old, analog, single-channel, omnidirectional device with no noise-reduction features fit using REM to NAL-R targets. Aided performance was measured using the QuickSIN in a randomized fashion. Results revealed that all of the premier devices yielded poorer performance compared to the analog device. Only after subsequent refitting of the premier devices using REM to NAL-R targets did the performance potential of the new technology reveal itself, with 5 of the 6 premium hearing aids yielding QuickSIN scores superior to those obtained with the older analog devices.

Likewise, Abrams and colleagues¹⁴ fit listeners with new hearing aids programmed with either a verified prescription to NAL-NL1 targets or the manufacturer’s Quick-Fit to NAL-NL1 targets. Initial REMs revealed a significant difference between the measured REARs obtained for each fitting method, with the Quick-Fit approach providing less gain than the verified prescription. Listeners wore their devices with a given fitting method for a trial period of 4-6 weeks in a counterbalanced fashion before being subsequently refit via the alternative method for an additional 4-6 week trial period. After each trial period, the listeners reported their self-perceived hearing aid benefit, as measured by the APHAB.¹⁵ Results revealed statistically significant improvement in three APHAB subscales (ease of communication, reverberant environments, background noise) with the verified prescription to NAL-NL1 targets approach compared to the Quick-Fit approach.   Further, at the conclusion of the study, 68% (15 of 22 participants) indicated they preferred the hearing aid fitting programmed to the verified prescription.

In addition to the aforementioned benefits of REM as it relates to ensuring appropriate levels of audibility, we published an article in the December 2016 issue of The Hearing Review revealing that REM improves patient psychology towards audiology services and technology.¹⁶ We assessed the patient’s perspective towards audiology services and hearing aid technology by quantifying patient satisfaction and perceived benefit in three groups of listeners fit with REM and Quick-Fit approaches. Overall, findings suggested that the provision of REMs positively improved patient psychology towards: 1) the practitioner; 2) the standard of care provided by the profession; and 3) and self-perceived benefit towards the hearing aid through increased confidence with the product.

The present article follows-up on our earlier findings and addresses the potential impact of audibility on outcomes for both the hearing aid user and the provider. From the perspective of the hearing aid user, we capture how differences in the level of audibility provided by each fitting approach—REM relative to Quick Fit—impacts speech understanding and, indirectly, loyalty towards the provider. From the perspective of the provider, audibility improvement is, no doubt, a consideration, particularly given the realities of increased competition, new product distribution channels, and new service delivery models. To that end, we provide the reader with data that supports the impact of REM on patient loyalty towards the provider and practice.

Methods

The participants and hearing aids reported in this study are the same as that in our initial Hearing Review article.¹⁶ Thus, only a brief overview of the methods is provided here.

Participants. We recruited a total of 60 participants, with a sample size of 20 listeners in each of three groups. Participants of the “Experienced” group consisted of experienced hearing aid users (ie, >1 year of use, devices use >8 hours/daily). Participants of the “In-the-Drawer” group consisted of listeners who had previously adopted hearing aids, but were not using their devices regularly (ie, hearing aids purchased within the past 24 months, but used less than 8 hours weekly). Participants of the “First-Time” group consisted of listeners who experience hearing difficulties, yet had never attempted a trial period with hearing aids. Each participant was recruited from the greater Dallas-Fort Worth (DFW) metropolis. Study participation across groups was based on the following criteria:

1) Aged between 50 and 75 years;

2) Exhibited a symmetrical, bilateral, mild-to-moderate sensorineural hearing loss;

3) Reported a <$42,000 annual household income; and

4) Passed a cognitive screening task (ie, Mini-Mental State Exam).¹⁷

The mean age of participants was 66.8 years (SD = 5.2; 8 males, 12 females), 66.2 years (SD = 4.9; 13 males, 7 females), and 68.5 years (SD = 7.3; 10 males, 10 females), for the Experienced, In-the-Drawer, and First-Time groups, respectively. Mean audiometric data for each respective group are shown in Figures 1a-c.

Hearing aid. Each participant was fit binaurally with a commercially-available, premium model receiver-in-the-canal (RIC) hearing aid from one manufacturer. This multi-memory hearing aid provided digital wide dynamic range compression (WDRC), along with speech enhancement, omni- and directional-microphone listening, feedback management, and noise reduction processed in 15 channels. Manufacturer specifications indicated a high-frequency average (HFA) maximum power output and gain of 110 and 58 dB SPL, respectively, for this device. During the study, all advanced features (eg, directionality, noise reduction) were disabled and target gain was predicted using the NAL-NL2 prescriptive approach⁸ in a single memory.

Loyalty survey. We assessed loyalty to the service provider using the RAPID Loyalty Survey.¹⁸ This survey consists of 10 questions and identifies three components: retention (ie, degree to which consumers remain consumers to the same business), advocacy (ie, positive perceptions that lead to advocacy of the business), and purchasing (ie, degree to which consumers will increase purchase behavior). Respondents were asked to provide a categorical response ranging from 1 (very likely) to 10 (not likely). Response ratings closer to 1 indicated increased loyalty, while responses closer to 10 indicated decreased loyalty.

Speech Intelligibility Index (SII). We assessed the potential impact of each fitting approach on speech understanding using the SII which is a measure, between 0 and 1, that captures the proportion of speech cues that are audible. Following the completion of each REM, the Verifit2 calculated and displayed the aided SII for each input level evaluated, which we subsequently entered into a database for analysis.

Procedures

Each potential participant was provided a University of North Texas Institutional Review Board (UNT-IRB)-approved consent form prior to participation. After consenting, each participant underwent audiometric testing (ie, air- and bone-conduction thresholds, immittance measures, word-recognition performance) and the cognitive screening task. Once a participant met the requirements for participation, he/she was placed into one of the three groups assessed in this study: Experienced, In-the-Drawer, and First-Time. Figure 2 depicts the procedures used in this study for the Experienced and In-the-Drawer groups (Panel A/B), and the First-Time group (Panel B).

Pre-study. Ten (10) participants within a given group were selected randomly to receive clinical services and amplification programmed using the Quick-Fit (ie, hearing aid manufacturer first-fit) target approach, while the remaining 10 participants within the same given group received clinical services and amplification programmed based on the real-ear measurement approach (REM via Verifit Speechmap¹⁹). For participants in the Experienced and In-the-Drawer groups, who had previously experienced professional services related to amplification, we obtained their loyalty towards their previous experience. Assessing these subjective measures prior to the experiment provided us with each group’s predisposed psychological attitude and intention towards professional services.

Hearing aid programming. Participants within each group who received the Quick-Fit target approach had the experimental hearing aids programmed with the manufacturer’s fitting software to predicted NAL-NL2 target gain for experienced listeners, based only on audiometric thresholds. On the other hand, participants within each group who received the REM approach were provided clinical services where the investigator measured the listener’s real-ear-to-coupler difference (RECD) bilaterally, using the methodology included in the Audioscan manual. The RECD measurement, along with audiometric threshold data, was entered into the manufacturer’s software for the REM group resulting in an individualized NAL-NL2 prescriptive target, also designated for experienced listeners. This individualized prescriptive target was then saved to the experimental hearing aids.

Hearing aid fitting. For participants who received the Quick-Fit approach, programming adjustments to the hearing aid were made based on anecdotal responses provided by the listener. Programming adjustments ceased when the patient verbally indicated that the devices provided him/her with comfort and clarity ratings of 8 on a 10-point scale (ie, 1 = lowest, 10 = highest) while listening to passages of the Connected Speech Test (CST).²⁰ The CST passages were presented from a personal computer (PC) connected to a loudspeaker positioned directly in front of the listener at a distance of 1 meter at a presentation level of 68 dB SPL. No REMs were made for this subgroup during this portion of the study. The participant was then asked to complete both surveys and provide responses based on the clinical services received. The surveys were counterbalanced across participants, and provided by and returned to a secondary investigator who had not provided the professional services, to reduce bias.

Participants experiencing the REM approach had a probe-tube inserted in their ear canal following manufacturer’s guidelines. Specifically, the subject was informed of the purpose of the procedure and what was to occur, otoscopy was conducted, and the probe housing was attached to the patient. The probe-tube was positioned within 5 mm of the eardrum using the visually assisted positioning technique. The hearing aids were placed in the ear and programming adjustments to the hearing aids were made until the real-ear aided response (REAR) was within ±3 dB of the generated NAL-NL2 targets on the Verifit2 across frequencies for each input level. Anecdotal responses were also obtained, where each participant verbally indicated that the devices programmed to the NAL-NL2 targets provided him/her with comfort and clarity ratings of 8 on a 10-point scale (ie, 1 = lowest, 10 = highest) while listening to CST passages. The CST passages were presented at the same distance, azimuth, and presentation level as described in the Quick-Fit approach. Slight adjustments (ie, within ±5 dB) were made relative to the NAL-NL2 targets in 17 of the 30 (ie, 57%) participants tested in this study.

After the hearing aids were adjusted, final REAR responses were obtained for Verifit2-generated speech signals (standard Male) at input levels of 55- (soft speech), 65- (average speech), and 75- (loud speech) dB SPL, as well as MPO. The participant was then asked to complete the loyalty survey, providing responses based on the clinical services received. The survey was provided by and returned to a secondary investigator—not associated with those providing professional services—to reduce bias.

Post-fitting. At the conclusion of the study, participants who received the Quick-Fit approach were retested, this time receiving the same REM approach provided to their within-group counterparts. Each participant also completed the loyalty survey a second time, this time based on the REM services they received at this stage of the study.

RESULTS AND DISCUSSION

Fitting to Target

Figures 3-5 demonstrate the REAR deviations by input level for each group between the REM and Quick-Fit approaches compared to the NAL-NL2 target (ie, represented as 0 dB on the y-axis). The orange and blue bars represent aided deviations for the REM and Quick-Fit approaches, respectively, plotted for the right ear. The dashed and solid lines represent left-ear aided deviations from target for the REM and Quick-Fit approaches, respectively. The results are plotted individually for the inputs of 55-, 65-, and 75-dB SPL.

For the Experienced group (Group A, Figure 3), results revealed that the Quick-Fit approach (ie, blue bars = right ear, solid lines = left ear) provided roughly 8.9, 8.7, and 10.2 dB less gain when averaged across both ears at inputs of 55-, 65-, and 75-dB SPL across frequencies, respectively, compared to the prescribed NAL-NL2 targets. Conversely, the REM approach (orange bars = right ear, dotted line = left ear) approximated targets more closely, underfitting targets by roughly 1.6, 1.9, and 2.0 dB when averaged across both ears. The results reveal consistency in findings across ears (right ear = bars, left ear = lines), showing symmetrical deviation trends from target across frequencies for each intensity for each fitting method. Similar trends are seen for the In-the-Drawer (Group B) and First-Time (Group C) groups. For the In-the-Drawer group, the Quick-Fit approach provided 7.2 and 6.2 dB less gain when averaged across both ears at 55- and 65-dB SPL, respectively, and 9.4 dB less gain when averaged across both ears at 75-dB SPL, compared to the NAL-NL2 target (Figure 4). Conversely, for the REM approach, mean REARs, when averaged across ears, deviated from target by 1.2, 1.3, and 1.6 dB at 55-, 65-, and 75-dB SPL respectively.

For the First-Time group, the Quick-Fit approach provided 8.6 and 9.3 dB less gain when averaged across ears at 55- and 65-dB SPL, respectively, and 10 dB less gain across ears at 75-dB SPL, compared to the NAL-NL2 targets (Figure 5). In comparison, the REM approach (orange bars = right ear; dotted line = left ear) deviated from targets by an average of 1.5 to 2 dB across ears for the three input levels. For both groups, REAR data was symmetrical between ears for each input level for each fitting method.

Author’s note: Findings with the REM condition revealing relatively small deviations from target were anticipated given that several participants requested small programming changes (~±5 dB from target) based on their sound quality preference, as previously described in the fitting procedure protocol. The audiological values for all three groups (Figures 3-5) are also provided in tables in the online version of this article at hearingreview.com.

Audibility Assessment with the SII

Following each REAR measurement, the Verifit2 calculated the speech intelligibility index (SII).¹² The SII is a measure of the proportion of speech information that is audible to the listener, ranging between 0.0 and 1.0, where higher values represent a greater proportion of audible speech cues. There is also a monotonic relationship between SII (ie, audibility) and speech understanding; that is, as the SII is increased, speech understanding is also expected to increase.

Figures 6-8 show the mean amount of audibility (per the SII) within a 95% confidence interval (CI₉₅) for the: 1) NAL-NL2 target, as displayed on the Verifit2; 2) REAR based on the Quick-Fit approach, and 3) REAR based on the REM approach, as a function of intensity level (ie, 55-, 65-, 75-dB SPL) and across groups.

At an input level 55-dB SPL, mean audibility per the SII for the NAL-NL2 target (gray bars in Figure 6) ranged between .57 and .61 across the three groups. Results for the Quick-Fit approach revealed a decrease in mean audibility compared to the NAL-NL2 target, ranging from .10 to .16 (black and white dotted bars). This decrease for the Quick-Fit approach compared to the NAL-NL2 target was statistically significant (t(1) = 4.11, p < .05). Conversely, mean audibility for the REM approach per the SII (black and white downward striped bars) deviated from target by < .02, which was not statistically significant (p > .05). An exact match to NAL-NL2 target SII values was not expected given that several participants requested small programming changes (~±5 dB from target) based on their sound-quality preferences as previously described.

Figures 7 and 8 depict mean audibility re: SII across the same conditions and groups, but at input levels of 65- and 75-dB SPL, respectively. Note that, as input level is increased, audibility as represented by the SII also increases for all three conditions. Regardless, data trends continue to reveal that the Quick-Fit approach results in SII scores that are ~.10 less than the REM approach, which was found to be statistically significant in nearly every comparison.

Speech in Babble Performance

We also employed the CST in its intended format: for quantifying speech understanding performance in background noise. During the task, participants were tested individually in a sound-treated room while wearing the experimental hearing aids binaurally. Four loudspeakers were positioned at an equal distance (1 meter) relative to the center-head position of the participant. The participant was seated in the center of the room, facing a loudspeaker positioned at 0° azimuth. CST passages were presented from this loudspeaker at an overall RMS level of 75 dB SPL. Three additional loudspeakers were positioned at 90°, 180°, and 270° relative to the loudspeaker at 0° azimuth. The CST multi-talker babble was presented individually from these loudspeakers at 66.23 dB SPL, resulting in a combined overall RMS level of 71 dB SPL, or a signal-to-noise ratio (SNR) of +4 dB. Performance scores were transformed from percent-correct to rationalized arcsine units (rau).²¹ Percent and rau scores are similar between 15% and 85%, but the rau conversion is necessary to normalize the variance in performance at the two extreme ends.

Results from the aided testing is shown in Figure 9. For listeners in the Experienced and In-the-Drawer groups, mean speech understanding in noise performance was statistically better (p < .05) for the REM approach (striped bars) compared to the Quick-Fit approach (solid bars). For the First-Time group, mean speech understanding in noise performance showed a similar trend to the more-experienced aided listeners, but was found not to be statistically significant (p > .05) given large performance variability in this small sample size.

Relationship Between Audibility and Speech Understanding Performance

A core component for real-ear measurement is to ensure that the user is receiving appropriate amplification (ie, audibility) that would lend itself to an improvement in the user’s speech understanding performance. To that end, we undertook a correlational analysis that plotted SII as a function of CST performance. Specifically, we plotted the SII data for 75 dB SPL against the CST, where the speech passage was also presented at 75 dB SPL.

The outcomes for the data from each group are shown in Figures 10a-c. Within each panel, the black filled circles represent data plotted for the Quick-Fit approach, while the blue, filled diamonds represent data plotted for the REM approach. For all three groups, trends suggest that, as audibility increased, speech-intelligibility performance also increased.

While a broadband noise signal is presented from the REM loudspeakers, the spectrum of sound within the ear canal is repeatedly sampled, analyzed, and input into a model of probe tube depth developed from a previously measured set of in-ear recordings. These recordings were gathered with normal adult ear canals as the probe tube was advanced to the correct location relative to the tympanic membrane.¹⁴ The machine-learning algorithm was “trained” to estimate probe tube depth from a sequence of input spectra, resulting in a software system that detects correct probe placement in real time.

A typical next step in machine-learning tool development is to test the trained system on a new dataset to evaluate whether the trained system works on new patients. Therefore, the purpose of the following collaborative study was to validate the performance of Probe Guide on a new set of ears. Our goal was to determine the performance of this new tool by comparing measured probe tube insertion depths between Probe Guide and a clinician-appraised depth, the adequacy of REMs made with Probe Guide, and the presence of any procedural issues (eg, eardrum contact) obtained with Probe Guide (PG) versus an experienced audiologist using a traditional visually assisted (VA) method of probe tube placement.

For the Experienced group who received the Quick-Fit approach, CST performance based on this fitting approach showed a moderate (r = 0.47) positive relationship between audibility and speech-intelligibility performance. This finding was not statistically significant (p > .05) and yielded a R² of 0.21, indicating large variability between the variables. One reason for this outcome may be related to the fact that the Quick-Fit approach provided less gain in the high-frequency region compared to the NAL-NL2 target, as shown in Figure 3, thus compromising the listeners’ perception of consonant sounds. For listeners in the Experienced group who received the REM approach, CST performance based on this fitting approach showed a large (r = 0.89) positive relationship between audibility and speech-intelligibility performance. This outcome was statistically significant (p < .05) and yielded an R² of 0.78, suggesting that as audibility improved, so did speech-intelligibility performance. Data analysis for the In-the-Drawer group yielded similar outcomes to the Experienced Group.

For the First-Time group who received the Quick-Fit approach, results revealed a statistically significant (p < .05) positive relationship (r = 0.65) between audibility and speech-intelligibility performance. For the REM approach, the data also indicated a statistically significant (p < .05) yet similar association (r = 0.65) between audibility and speech-intelligibility performance as the Quick-Fit approach. This finding is somewhat expected, given that increasing audibility should increase speech-intelligibility performance. The degree of improved speech-intelligibility, as a function of audibility, however, is not captured by this analysis. To illustrate, note that the First-Time group demonstrated smaller increases in speech-intelligibility compared to the Experienced and In-the-Drawer groups, even though audibility was similar among all three groups.

Consumer Loyalty: Advocacy

Consumer loyalty occurs when an individual consistently adopts a product or service from the same company over an extended period. In the hearing aid market, loyalty to the provider is roughly 50%, and reportedly stems from a lack of a standardized clinical protocol that includes REM as a professional service.^22,23 In this study, we quantified the degree to which hearing aid service provision (ie, Quick-Fit vs REM) influenced patient perception towards the provider in three areas: advocacy (ie, positive perceptions that lead to advocacy of the business), purchasing (ie, degree to which consumers will increase purchase behavior), and retention (ie, degree to which consumers remain consumers of the same business). These areas were assessed using the previously described loyalty survey, and each participant was asked to provide a categorical response ranging from 1 (very likely) to 10 (not likely).

Figure 11 displays the mean responses for advocacy, a measure of emotional attachment towards the provider and practice as considered by the respondent. An increase in advocacy often coincides with an increase in overall satisfaction, referrals, and repurchase intent.

Overall, results revealed that participants in the Experienced group would not positively advocate for their previous provider given a mean response of 3.4 (ie, gray bar). The Quick-Fit approach, which was performed as part of this study, did not positively impact advocacy to any great extent (black and white dotted bar). Participants who received the REM approach during the study (black and white vertically striped bar), on the other hand, indicated a mean response of nearly 7.5. This finding, when compared to the Quick-Fit, was found to be statistically significant (Krusal-Wallis test; ?2(1) = 14.37, p < .001) and indicated increased patient advocacy towards the provider when REM was provided. When the participants who originally received the Quick-Fit approach were re-fit using the REM approach (ie, black and white diagonally striped bar), their ratings increased significantly (p < .05) by an average of 4.7—or from a mean of 3.4 to a mean of 8.1. 

For the In-the-Drawer group, mean responses were mostly lower compared to that of the Experienced group. Advocacy responses to their previous provider tallied a mean of 1.8 (gray bar), while the Quick-Fit approach yielded a mean of 3.3 (black and white dotted bar). These differences were not statistically significant (p > .05). Participants who received the REM approach provided a mean response of 5.9 (black and white vertically striped bar), which was not perceived as a statistical improvement (Krusal-Wallis test; ?2(1) = 2.89, p > .05) compared to the Quick-Fit approach. Lastly, participants who originally received the Quick-Fit approach were re-fit using the REM approach and subsequently provided a mean of 6.4 (black and white diagonally striped bar), which was a statistical improvement over the Quick-Fit approach and similar to the participants who initially received the REM approach. An interesting observation about the In-the-Drawer group is the large variability in their responses. This observation highlights an empirical need to better understand the psychological make-up of this subpopulation as it relates to their previous hearing aid experiences.

Participants in the First-Time group provided mean advocacy scores of 4.8 and 7.2 for the Quick-Fit and REM approaches, respectively. The differences in these mean responses were found to be statistically significant (Krusal-Wallis test; ?2(1) = 16.09, p < .001). Listeners who received the Quick-Fit protocol and later were re-fit using the REM approach (black and white vertical striped bar), provided mean responses of 8.5, which was consistent (p < .05) with responses provided by listeners who received the REM protocol at the study’s outset.

Consumer Loyalty: Purchasing

Purchasing behavior, shown in Figure 12, was the second factor of loyalty that we assessed. This scale documents the consumer’s intention to increase their purchasing behavior, either through increased willingness to pay or the purchase of additional products or services.

For the Experienced and In-the-Drawer groups, purchasing results revealed mean responses of 5.4 and 2.3 towards their previous provider (gray bars), respectively. Interestingly, mean responses for the Quick-Fit approach (black and white dotted bar) were found to be similar to previous experiences (gray bars) reported by these two groups. However, mean responses for the REM approach (black and white vertically striped bar), compared to the Quick-Fit approach resulted in an improvement by 2.9 and 3.3 for each group, respectively. This later finding was statistically significant (p < .05). Lastly, there was no statistically significant difference (p > .05) in mean responses between the REM approach performed at the outset of the study and the REM approach performed after the Quick-Fit approach for both groups. There is, however, a statistically significant difference (p < .05) between the Quick-Fit and REM approaches for both groups, indicating that the REM protocol increased the likelihood of hearing aid uptake (ie, purchasing intent) compared to the Quick-Fit approach. Similar trends were noted for the First-time group.

Together, these data support our earlier findings related to willingness-to-pay.¹⁶ Specifically, the REM approach, compared to the Quick-Fit approach, resulted in an enhanced perceived value towards the provider that lends itself to an increase in the acquisition of product and services offered.

Consumer Loyalty: Retention

The final component of the loyalty scale is retention (Figure 13), the psychological assessment of value that compares the services and products rendered by one provider to the same services and products offered by the competition.

For all three groups, the data suggests that the REM approach (black and white vertically striped bars and black and white diagonally striped bars) provides a significant (p < .05) increase in retention compared to the Quick-Fit approach (ie, black and white dotted bar). In addition, the mean REM procedure yielded significant (p < .05) mean increases of 3.9 and 4.3 compared to previous experiences perceived by participants in the Experienced and In-the-Drawer groups, respectively. Lastly, there was no statistically significant difference (p > .05) in mean responses between the listeners who received the REM approach at the outset of the study (black and white vertically striped bar) and those who received the REM approach after the Quick-Fit approach (black and white diagonally striped bar).

CLINICAL IMPLICATIONS

This article expands on a previously reported study¹⁶ investigating the potential benefits of clinical services that include the use of real-ear measurements (REM). In this follow-up report we have captured:

1) The amount of audibility provided by the Quick-Fit and REM approaches and how this audibility correlates with speech understanding; and

2) The user’s corresponding loyalty to the provider and practice based on the hearing aid fitting method experienced (ie, Quick-Fit vs REM).

Findings revealed that the Quick-Fit approach differed significantly from NAL-NL2 targets, under-fitting by roughly 7-10 dB across input levels despite being selected as the “experienced” fitting formula of choice in the programming software. Conversely, the REM approach provided gain within 1.5 to 2.5 dB across input levels from the NAL-NL2 prescriptive target, even with programming allowances to address participant listening preferences. The differences in gain between the approaches yielded statistically significant (p < .05) differences in audibility. This overall result as it relates to meeting targets as a function of Quick-Fit versus a verified REM approach is consistent with various reports in the literature.^4,8,14 As expected, these differences in audibility were reflected in the resulting aided SII scores and behaviorally via the CST task, where speech understanding performance in background noise was statistically better for the REM approach compared to the Quick-Fit approach.

Secondly, we assessed the relative impact of fitting method (ie, REM and Quick-Fit) on patient loyalty, an important issue for practitioners. Results suggested that the REM approach enhanced all three aspects (ie, advocacy, purchasing, and retention) compared to the Quick-Fit approach.

The outcomes from this undertaking are noteworthy in that they support the perspective that providing evidence-based hearing healthcare improves the perceived value of the provider in the eyes of the hearing aid user. This increase in perceived value lends itself to increased purchase and repurchase intent of services and products—not to mention increased referrals through patient recommendation.^24,25

Together, the simple act of providing REM can serve to enhance a practice’s reputation and brand, while reducing the time and expenses associated with marketing. In this time of disruptive innovations and evolving service and product delivery models, the clinician would be well served to consider the integration of clinical services that will enhance their perceived value and highlight the important role they have to play in hearing healthcare delivery. It is our belief that the findings presented in this article, along with those illustrated in our previous report highlight the positive role that REM has to play in supporting the needs of both the patients we serve and the hearing healthcare profession at large.

References

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2. Kochkin S. MarkeTrak VIII: Reducing patient visits through verification and validation. Hearing Review. 2011;18(6):10-12.

3. American Academy of Audiology. Guidelines for the Audiological Management of Adult Hearing Impairment. Audiology Today. 2006;18(5):32-37.

4. American Speech-Language-Hearing Association. Guidelines for Hearing Aid Fitting for Adults. 2015. Available at: http://www.asha.org/PRPSpecificTopic.aspx?folderid=8589935381&section=Key_Issues

5. Kirkwood DH. Survey: Dispensers fitted more hearing aids in 2005 at higher prices. Hear Jour. 2006;59(4):40-50.doi: 10.1097/01.HJ.0000286695.28587.f5

6. Mueller GH. Probe-mic measures: Hearing aid fitting’s most neglected element. Hear Jour. 2005;58(10): 21-30. doi: 10.1097/01.HJ.0000285782.37749.fc

7. Mueller HG, Picou EM. Survey examines popularity of real-ear probe-microphone measures. Hear Jour. 2010;63(5):27-32.doi: 10.1097/01.HJ.0000373447.52956.25

8. Aazh H, Moore BCJ, Prasher D. The accuracy of matching target insertion gains with open-fit hearing aids. Am J Audiol. 2012;21(2):175-180. doi:10.1044/1059-0889(2012/11-0008)

9. Byrne D, Dillon H, Ching T, Katsch R, Keidser G. NAL-NL1 procedure for fitting nonlinear hearing aids: Characteristics and comparisons with other procedures. J Am Acad Audiol. 2001;12(1):37-51.

10. Sanders J, Stoody TM, Weber JE, Mueller HG. Manufacturers’ NAL-NL2 fittings fail real-ear verification. Hearing Review. 2015;21(3):24-30.

11. Keidser G, Dillon HR, Flax, M, Ching T, Brewer S. The NAL-NL2 prescription procedure. Audiol Res. 2011;1(1):e24. DOI: http://doi.org/10.4081/audiores.2011.e24

12. Acoustical Society of America (ASA). ANSI/ASA S3.5-1997 (R2012)–American National Standard Methods for Calculation of the Speech Intelligibility Index. ASA: New York City;1997.

13. Leavitt RJ, Flexer C. The importance of audibility in successful amplification of hearing loss. Hearing Review. 2012;19(13):20-23.

14. Abrams HB, Chisolm TH, McManus M, McArdle R. Initial-fit approach versus verified prescription: comparing self-perceived hearing aid benefit. J Am Acad Audiol. Nov/Dec, 2012;23(10):768-778.

15. Cox RM, Alexander GC. The abbreviated profile of hearing aid benefit. Ear Hear. April, 1995;16(2):176-186.

16. Amlani AM, Pumford J, Gessling E. Improving patient perception of clinical services through real-ear measurements. Hearing Review. 2016;23(12):12-21.

17. Folstein MF, Folstein SE, McHugh PR. Mini-mental state. A practical method for grading the cognitive state of patients for the clinician. J Psych Res. 1975;12(3):189-198.  DOI: http://dx.doi.org/10.1016/0022-3956(75)90026-6

18. Hayes BE. Lessons in loyalty.  Quality Progress. March, 2011.

19. Smriga, D. Speechmap as a counseling and fitting tool.  May 26, 2015. Available at: https://www.audiologyonline.com/ce/audioscan/events/details/42821/audioscan-42821

20. Cox RM, Alexander GC, Gilmore C. Development of the Connected Speech Test (CST). Ear Hear. October, 1987;8[Suppl 5]: 119S-126S.

21. Studebaker GA. A “rationalized” arcsine transform. J Sp Hear Res. September, 1985;28(3):455-462.

22. Kochkin S. MarkeTrak VIII: 25-year trends in the hearing health market. Hearing Review. 2009;16(11):12-31.

23. Kochkin S. A comparison of consumer satisfaction, subjective benefit, and quality of life changes associated with traditional and direct-mail hearing aid use. Hearing Review. 2014;21(1):16-26.

24. Jiang L, Jun M, Yang Z. Customer-perceived value and loyalty: How do key service quality dimensions matter in the context of B2C e-commerce? Service Business. February 27, 2015;10(2):301-317.

25. Trasorras R, Weinstein A, Abratt R. Value, satisfaction, loyalty, and retention in professional service. Marketing Intelligence and Planning. 2009;27(5): 615-632. DOI: https://doi.org/10.1108/02634500910977854

Improving Patient Perception of Clinical Services Through Real-ear Measurements

By Amyn M. Amlani, PhD, John Pumford, AuD, and Erich Gessling

Nov 22, 2016

REM builds patient loyalty and is viewed as valuable to a wide range of patients

Verification, namely probe-microphone or real-ear measures (REMs), is one aspect of service delivery that has not been consistently embraced as a part of the profession’s standard of care. In fact, surveys on the clinical use of REMs range between 20% and 50%,^1-3 despite evidence-based recommendations from audiology professional organizations.^4,5

Mueller,⁶ for example, reported that 78% of audiologists who dispensed hearing aids routinely programmed the devices to either the NAL or DSL prescriptive method. Of this group, only 44% routinely used REMs to verify gain and output at the listener’s eardrum. This finding assumes that the remaining 56% trust the manufacturer’s software (ie, Quick-fit) to provide accurate information. Unfortunately, several studies have shown that the Quick-fit approach does not mimic the prescriptive taget,^7,8 with gain differing by as much as ±10 dB at a given frequency.

This disparity between what the hearing aid is providing via Quick-fit and what the hearing aid should be providing when REMs are performed is likely a primary factor for the low adoption rate and increased stigma towards hearing aid use. In fact, it could be reasoned that the lack of REM use as a standard clinical procedure is a catalyst for the recent recommendations by the President’s Council of Advisors on Science and Technology (PCAST)⁹ and the National Academy of Sciences, Engineering, and Medicine (NAS)¹⁰ to establish a new category of over-the-counter, wearable devices.

In the present study, we evaluated the impact of REMs on consumer satisfaction and, indirectly, loyalty as a means to learn whether consumers perceived REMs as a key service component during the hearing aid fitting process. To achieve this objective, we quantified the perceived value of fitting to manufacturer’s Quick-fit specifications with no additional service provision versus an individualized hearing aid fitting accompanied by the service provision of REMs in three different groups of patients commonly seen in the clinic. The study findings are remarkably positive and bear serious consideration by those clinicians still unconvinced of the merits of REMs.

Methods

Participants. Three groups of participants were recruited, with each group consisting of 20 listeners:

1) “Experienced” group consisted of experienced users of amplification (ie, >1 year of use, device use exceeds 8 hours/daily).

2) “In-the-Drawer” group who had previously purchased amplification, but did not use their devices (ie, hearing aids purchased within the past 2 years, but used less than 8 hours weekly).

3) “First-time” users of amplification, who experience hearing difficulties, yet had never attempted a trial period with amplification.

Each participant was recruited from the greater Dallas-Fort Worth (DFW) metropolis. Study participation across groups was based on the following criteria: 1) Aged between 50 and 75 years; 2) Exhibit a symmetrical, bilateral mild-to-moderate sensorineural hearing loss; 3) Annual household income of less than $42,000; and 4) Pass a cognitive screening task (ie, Mini-Mental State Exam).¹¹

The mean age of participants was 66.8 years (SD = 5.2; 8 males, 12 females), 66.2 years (SD = 4.9; 13 males, 7 females), and 68.5 years (SD = 7.3; 10 males, 10 females), for the Experienced, In-the-Drawer, and First-Time groups, respectively. Mean audiometric data for each respective group are shown in Figure 1.

Hearing Aid. To control for electroacoustic differences between hearing aid brands and models, each participant was fit binaurally with a commercially available premium model receiver-in-the-canal (RIC) hearing aid from one manufacturer. This multi-memory hearing aid provides digital wide-dynamic range compression (WDRC), along with speech enhancement, omni- and directional-microphone, feedback management, and noise reduction processed in 15 channels. During the study, all advanced features (eg, noise reduction) were disabled, and target gain was generated using the NAL-NL2 prescriptive approach¹² in a single memory.

Surveys. Participant responses regarding the service provision of hearing aid verification were quantified using two surveys: 1) Willingness-to-pay (WTP), and 2) SERVAL, a modified version of the PERVAL¹³ that quantifies the perceived value of service provision.

WTP. WTP is a one-item question that indicates the maximum dollar amount an individual is willing to exchange to obtain a product or service. Prior to administering this survey, we provided each participant with a price anchor of $250 for professional services. The $250 anchor was derived from a pilot study indicating that this value was the average hourly rate in a US audiology clinic.

SERVAL. Each respondent’s perceived value towards verification was measured using the PERVAL-Service Scale (SERVAL). SERVAL is a modified version of the PERVAL Measurement Scale, previously used by Amlani,¹³ and also includes dimensions reported by Petrick.¹⁴ SERVAL, as used in this study, is a 14-item scale that measures attitude and behavior toward perceived value in five dimensions: emotion, perceived quality, price, perceived value, and behavioral intent. During the experiment, participants were asked to provide a categorical response ranging from 1 (strongly agree) to 7 (strongly disagree) for each question item. Response ratings closer to 1 indicated a positive perceived value, while responses closer to 7 indicate a negative perceived value. Questions 2, 4, 5, 7, and 10 were reversed (ie, 1 = strongly disagree; to 7 = strongly agree) to reduce response bias.

Procedures

Each potential participant was provided a University of North Texas Institutional Review Board (UNT-IRB) approved consent form prior to participation. Each consenting participant was tested for air- and bone-conduction thresholds, immittance measures, word-recognition performance, and the cognitive screening task. Once participants met the study requirements, they were placed into one of the three groups (Experienced, In-the-Drawer, and First-Time). Figure 2 shows the procedures used in this study for the Experienced and In-the-Drawer groups (Figure 2a), and the First-Time group (Figure 2b).

Pre-study. A total of 10 participants within a given group were selected randomly to receive clinical services and amplification programmed using the Quick-fit (ie, hearing aid manufacturer first-fit) protocol, while the remaining 10 participants within the same given group received clinical services and amplification programmed using the probe-microphone real-ear measurements protocol (ie, Verifit Speechmap protocol).¹⁵ For participants in the Experienced and In-the-Drawer groups, who had previously experienced professional services related to amplification, we obtained their WTP towards their previous experience. Assessing these subjective measures prior to the experiment provided us with each group’s predisposed attitude and intention towards professional services. Table 1 demonstrates the previous “verification” experience encountered by participants in the Experienced and In-the-Drawer groups.

Hearing aid programming. Participants within each group who received the Quick-fit protocol had the experimental hearing aids programmed with the manufacturer’s fitting software to predicted NAL-NL2 target gain for experienced listeners, based only on audiometric thresholds. On the other hand, participants within each group who received the REM protocol were provided clinical services where the investigator measured the listener’s real-ear-to-coupler difference (RECD) bilaterally, using the methodology described in the Audioscan Verifit2 manual. The RECD and audiometric threshold data, was subsequently entered into the manufacturer’s software for the REM group resulting in an individualized NAL-NL2 prescriptive target, also designated for experienced listeners. This individualized target was then saved to the experimental hearing aids.

Hearing aid fitting. For participants who received the Quick-fit protocol, programming adjustments to the hearing aid were made based on anecdotal responses provided by the listener. Programming adjustments ceased when the patient verbally indicated that the devices provided him/her with comfort and clarity ratings of 8 on a 10-point scale (ie, 1 = lowest, 10 = highest) while listening to passages of the Connected Speech Test (CST).¹⁶ The CST passages were presented from a personal computer (PC) connected to a loudspeaker positioned directly in front of the listener at a distance of 1 meter at a presentation level of 68 dB SPL. No REMs were made for this subgroup during this portion of the study. The participant was then asked to complete both surveys and provide responses based on the clinical services received. The surveys were counterbalanced across participants, and provided by and returned to a secondary investigator who had not provided the professional services to reduce bias.

Participants experiencing the REM protocol had testing conducted following manufacturer’s guidelines. Each participant was informed of the purpose of the procedure and what was to occur, otoscopy was conducted, and the probe module was attached to the outer ear. The probe-tube was positioned within 5 mm of the eardrum using the visually assisted positioning technique. Participants were positioned directly in front of the REM loudspeaker (0° azimuth), facing the measurement screen at a distance of 0.5-1.0 m. The hearing aids were placed in the ear and programming adjustments to the hearing aid were made until the real-ear aided response (REAR) was within ±3 dB of the generated NAL-NL2 targets on the Verifit2 across frequencies for each input level. Participants were counseled regarding the meaning of the various measurement curves and symbols on the Speechmap® screen. As with the Quick-fit protocol group, anecdotal responses were also obtained, where each participant verbally rated the comfort and clarity of devices programmed to NAL-NL2 targets on a 10-point scale (ie, 1 = lowest, 10 = highest) while listening to CST passages. The CST passages were presented at the same distance, azimuth, and presentation level as described in the Quick-fit protocol. Slight adjustments (within ±5 dB) were made relative to the NAL-NL2 targets in 17 of the 30 (i.e., 57%) to obtain comfort/clarity ratings of 8/10 for participants in this study.

After the hearing aids were adjusted, final REARs were obtained for Verifit2 generated speech signals (standard Male) at input levels of 55- (soft speech), 65- (average speech), 75- (loud speech) dB SPL and MPO. The participant was then asked to complete both surveys, providing responses based on the clinical services received. The surveys were counterbalanced across participants, and provided by and returned to a secondary investigator—not associated with providing professional services—to reduce bias.

Post-fitting. At the conclusion of the study, participants who received the Quick-fit protocol were re-tested, this time receiving the same REM protocol provided to their within-group counterparts. Each participant also completed both surveys, using the same protocol that their counterparts received.

Results and Discussion

Willingness-to-pay. A multivariate analysis of variance (MANOVA) was performed to determine whether the independent variables of protocol (ie, Quick-fit, REM) and professional experience (ie, previous user, new user) had an effect on participants’ WTP. Recall that a price anchor of $250 was provided to all participants.

For the Experienced and In-the-Drawer groups, results revealed that listeners were willing-to-pay a maximum of $95.00 (95% confidence interval [CI95] ±$25.85) and $80.00 (CI95 ±$27.26), respectively, for their previous hearing aid fitting experience. As shown in Figure 3, these findings are not statistically different (p > .05) and fall significantly (p < .05) below the $250 anchor, suggesting that the average Experienced and In-the-Drawer participant perceived that they received similar, yet unacceptable professional services prior to participating in this study.

When participants were dichotomized into receiving either the Quick-fit or REM protocol, results for the Experienced group revealed a WTP of $125 (CI95 ±$47.32) for the Quick-fit protocol and $332.50 (CI95 ±$47.32) for the REM protocol, shown in Figure 3. The difference in WTP between protocols was statistically significant (F2,17 = 20.04, p < .001). A post-hoc analysis revealed that only the REM protocol was statistically improved (p < .05) compared to the average participant’s perception of the previous professional services they received, by a margin of $237.50 ($332.50 – $95.00).

For the 10 participants in the Experienced group who received the Quick-fit protocol initially, we re-tested them using the REM protocol in the latter portion of the test session. Figure 3 indicates that participants who initially experienced the Quick-fit and then experienced the REM protocol provided a statistically significant (t(9) = 11.50, p < .001) increase in WTP. Here, mean responses appreciated by $230.00 compared to the Quick-fit procedure (ie, $355.00 – $125.00). No difference (p > .05) in mean WTP was noted between participants who initially received REM and participants who received REM after the Quick-fit protocol. Together, these findings support the notion that the lack of a standardized clinical protocol that employs REMs could be one reason why experienced users only return to their previous provider around 50% of the time.19

WTP results for the in-the-Drawer group, displayed in Figure 3, revealed a mean response of $190.00 (CI95 ±$41.21) and $265.00 (CI95 ±$41.21) for the Quick-fit and REM protocols, respectively. The difference in WTP between protocols was statistically significant (F2,17 = 4.16, p < .005), and both the Quick-fit and REM protocols were statistically improved (p < .05) compared to the average participant’s perception of the professional services they received prior to entering the study (Table 1).

Figure 3 also displays the WTP initially provided by In-the-Drawer group participants who received the Quick-fit protocol and then later experienced the REM protocol. Results were statistically significant (t(9) = 4.64, p = .001). Here, mean responses improved by $115 compared to the previously experienced Quick-fit procedure ($305 – $190). No difference (p > .05) in mean WTP was noted between participants who initially received REM and participants who received REM after the Quick-fit protocol. While our study is confounded by an order effect (ie, Quick-fit always precedes REM protocol), the findings revealed that the average Experienced and In-the-drawer group participant found the REM protocol provided greater perceived value than the Quick-fit protocol.

Participants in the First-time group provided responses solely regarding the experimental session, as this group had no previous experience with hearing aids. Results yielded a statistically significant difference (F1,18 = 20.16, p < .001) in WTP, where the Quick-fit protocol yielded a mean of $195 (CI95  ±$46.32) and the REM protocol yielded a mean of $335 (CI95 ±$46.32), as shown in Figure 3.

Figure 3 further displays the difference in mean WTP for those First-time group participants who initially received the Quick-fit protocol and then later experienced the REM protocol. Mean WTP responses for the REM protocol significantly improved (t(9) = 4.61, p < .001) by $165 compared to the Quick-fit procedure (ie, $360 – $195). No difference (p > .05) in mean WTP was noted between First-time group participants who received only REM and participants who received REM after the Quick-fit protocol.

Lastly, the difference in mean WTP between protocols pooled across groups revealed that listeners—both experienced and inexperienced hearing aid users—observed differences in perceived value between the types of verification services provided by the practitioner. Verification services that are comprehensive enhance:

1) The average participant’s psychology towards the amplification process, as determined in this study;

2) Their self-perceived benefit towards the device,¹⁷ and

3) Satisfaction towards the practitioner.¹⁸

Authors’ Note: The impact of the Quick-fit vs REM protocols on audibility will be discussed in a future article.

Clinical Implications

The primary purpose of this study was to assess the impact of REMs on consumer satisfaction as a service component during the hearing aid fitting process. For the SERVAL scale, overall results revealed that the REM protocol reduced emotional distress, and improved perceived quality of service and value of the hearing aid fitting experience compared to the Quick-fit protocol in all three groups of participants. Together, the improvement in these areas is expected to be correlated with increased behavioral intent, resulting in an increased positive perception of hearing aid provision services that include REM.

The findings of the SERVAL were validated by the results obtained from the WTP scale, which indicated an improved perception of the clinician when REM services were provided. For the participants in the Experienced and First-time groups, larger improvements were noted between the REM and Quick-fit protocols for SERVAL responses, while smaller improvements were observed for the In-the-drawer group. For participants in the First-time group, research has shown that decreasing emotional distress improves their perceived value of amplification.^13,20

The SERVAL results revealed smaller differences between the REM and Quick-fit protocols for the In-the-Drawer group, suggesting that this group has greater resistance to the amplification process. This resistance, however, could be reduced through implementation of a REM protocol. While we did not test the influence of counseling in this study, we conjecture that the In-the-Drawer group might have yielded improved SERVAL responses had we utilized a different, more holistic counseling approach.

Overall, findings in this study suggest:

1) Satisfaction of hearing aid users can be linked to the type of verification services offered;

2) REM can enhance patient psychology of the amplification process, self-perceived benefit of their amplification device, satisfaction with the practitioner, and by association, patient loyalty;

3) The lack of a standardized protocol that employs REMs may be one reason why patients do not return to their previous provider;

4) The provision of REM can positively impact the user’s confidence with, and perception of, their hearing aid, and

5) REM was deemed as a worthwhile expense—a finding that bodes well for clinicians who are considering itemizing (unbundling) and listing REM as a provided service.

The findings reported in this study also address, indirectly, aspects of the recent PCAST and NAS reports, namely the need to:

1) Develop and promote best practices and measures to assess and improve quality of hearing health care services, and

2) Empower consumers and patients in their use of hearing health care.

The REM protocol promotes an evidence-based assessment that allows the clinician to provide a more transparent hearing healthcare experience than the Quick-fit protocol used in this study. This increased transparency enlightens patients about the value of the services they are being provided, and also provides clinicians with the opportunity to itemize services. To the extent that participants in this study reported a willingness to pay more for a service experience that included REM (vs Quick-fit), the potential for increased revenue should also be considered by clinicians when deciding on which services to offer their patients. Clearly, the inclusion of REM in clinical practice improves the hearing healthcare experience for both patients and clinicians.

Acknowledgments

Audioscan provided funding for this study. Portions of this paper were presented at AudiologyNOW! in Phoenix, Arizona, April 13-16, 2016.

References

1. Beck D. Hearing aids, real-ear measures, FM technology, and more: An interview with Michael Valente, PhD. Dec 18, 2008. Available at: http://www.audiology.org/news/hearing-aids-real-ear-measures-fm-technology-and-more-interview-michael-valente-phd

2. Mueller HG, Picou EM. Survey examines popularity of real-ear probe-microphone measures. Hear Jour. 2010;63(5):27-32.

3. Sanders J, Stoody T, Weber J, Mueller HG. Manufacturers’ NAL-NL2 Fittings Fail Real-ear Verification. Hearing Review. 2015;21(3):24.

4. American Academy of Audiology. Guidelines for the Audiological Management of Adult Hearing Impairment. Audiology Today. 2006;18(5):32-37.

5. American Speech-Language-Hearing Association. Guidelines for Hearing Aid Fitting for Adults. 2015. Available at: http://www.asha.org/PRPSpecificTopic.aspx?folderid=8589935381&section=Key_Issues

6. Mueller HG. Probe-mic measures: Hearing aid fitting’s most neglected element. Hear Jour. 2005;57(10): 33-41.

7. Aazh H, Moore BC, Prasher D. The accuracy of matching target insertion gains with open-fit hearing aids. Am J Audiol. 2012;21(2):175-180. doi: http://dx.doi.org/10.1044/1059-0889(2012/11-0008)

8. Mueller HG. 20Q: Real-ear probe-microphone measures—30 years of progress? January 13, 2014. Available at: http://www.audiologyonline.com/articles/20q-probe-mic-measures-12410

9. President’s Council of Advisors on Science and Technology. Oct 23, 2015. Available at: http://www.hearingreview.com/2015/10/pcast-report-hearing-loss-raises-concerns

10. National Academy of Sciences, Engineering, and Medicine. June 2, 2016. Available at: http://www8.nationalacademies.org/onpinews/newsitem.aspx?RecordID=23446

11. Folstein MF, Folstein SE, McHugh PR. Mini-mental state. A practical method for grading the cognitive state of patients for the clinician. J Psych Res. 1975; 12(3): 189–98.

12. Keidser G, Dillon, H, Flax, T, Ching T, Brewer S. The NAL-NL2 prescription procedure. Audiology Research. 2011;10(1):e24. Available at: http://doi.org/10.4081/audiores.2011.e24

13. Amlani AM. Influence of perceived value on hearing aid adoption and re-adoption intent. Hearing Review Products. 2013;20(3):8-12.

14. Petrick J. Development of a multi-dimensional scale for measuring the perceived value of a service. Journal of Leisure Research. 2002;34:119-134.

15. Smriga D. Speechmap as a counseling and fitting tool. May 26, 2015. Available at: https://www.audiologyonline.com/ce/audioscan/events/details/42821/audioscan-42821

16. Cox RM, Alexander GC, Gilmore C. Development of the Connected Speech Test (CST). Ear Hear. 1987;8 [Suppl 5]:119S-126S.

17. Kochkin S, Beck DL, Christensen LA, Compton-Conley C, Kricos PB, Fligor BJ, McSpaden JB, Mueller HG, Nilsson MJ, Northern JL, Powers TA, Sweetow RW, Taylor B, Turner RG. MarkeTrak VIII: The impact of the hearing healthcare professional on hearing aid user success. Hearing Review. 2010;17(4):12-34.

18. Abrams HB, Chisolm TH, McManus M, McArdle R. Initial-fit approach versus verified prescription: Comparing self-perceived hearing aid benefit. J Am Acad Audiol. 2012;23(10):768-778.

19. Petrick J. First timers and repeaters perceived value. Journal of Travel Research. 2004;43:29-38.

20. Cobelli N, Gill L, Cassia F, Ugolini M. Factors that influence intent to adopt a hearing aid among older people in Italy. Health Society Care Community. 2014;22(6):612-622.

21. Du Plessis L. Customer relationship management and its influence on customer loyalty at Liberty Life in South Africa. University of Johannesburg;2010.

22. Tam J. Customer satisfaction, service quality and perceived value. J Marketing Management. 2004;20:897-978.

23. Kochkin S. A comparison of consumer satisfaction, subjective benefit, and quality of life changes associated with traditional and direct-mail hearing aid use. Hearing Review. 2014;21(1):16-26.

24. Amlani AM. Application of the consumer decision-making model in assessing hearing aid adoption intent in first-time users. Seminars in Hearing. 2016; 37(2):103-119.

A Comparison of Automated Real-Ear and Traditional Hearing Aid Fitting Methods

By Paula Folkeard, AuD; John Pumford, AuD; Parvaneh Abbasalipour, MSc, Nicole Willis, and Susan Scollie, PhD

Oct 30, 2018

Several “autoREMfit” systems have been developed to assist in hearing aid fittings. This article evaluates a new fit-to-target platform, Audioscan’s VerifitLINK, that could be integrated into any manufacturer’s software, and documents its performance in target matching during hearing aid fitting.

Routine verification of aided hearing aid responses using real-ear measurements (REM) is part of recommended practice,^1-3 and failing to verify hearing aid fittings using this technique has been listed as the number one mistake made by clinicians.⁴ Research has revealed positive listening outcomes for patients fitted using best practice REM verification versus first-fit approaches in both lab-based and real-world environments.^5-8

Yet, despite professional guidelines and research evidence, REM is not routinely performed by clinicians.^9,10 This lack of use is attributed by some to the perceived complexity of the REM process and the limited time available to complete measurements on the part of the clinician.⁹

To address these concerns, a number of manufacturers have developed Closed Loop Fitting Systems (CLFS) or “autoREMfits.” While the details of each implementation may vary, at their core, these systems aim to automatically adjust hearing instrument parameter settings in the hearing aid fitting software to the supplied fitting formula targets via a comparison between measured and requested output levels across frequencies.^11,12 (For an excellent review, see Mueller and Ricketts’ article “Will AutoREMfit Move the Sticks? ¹³).

Recently, Audioscan developed the automated fit-to-target tool, VerifitLINK, which allows direct communication between manufacturer’s hearing aid fitting software and Verifit systems. VerifitLINK has the potential to be integrated into any hearing aid manufacturer’s fitting software to allow automatic adjustment of hearing aid settings to match the fitting formula targets supplied by the Audioscan equipment. VerifitLINK and hearing aid software (in this study, Oticon Genie 2) exchange data while real-ear measures are conducted and adjustments are automatically made to the gain settings in the device based on the output of the hearing aid as measured by the Audioscan Verifit.

In a collaboration between Audioscan and the National Centre for Audiology, a validation study of Audioscan VerifitLINK, as implemented into Oticon Genie 2 software, was conducted. The study investigated the efficiency and accuracy of VerifitLINK compared to a clinician-driven fitting approach and the manufacturer’s first-fit to DSL v5.0 adult targets using real-ear measures with the Audioscan Verifit2. It should be noted that, although not presented here, VerifitLINK can also be used with validated generic DSL v5 child, NAL-NL1, and NAL-NL2 targets supplied by the Verifit and that, when appropriate, can be used to fit hearing aids to target in the test box rather than on the ear. VerifitLINK is also available for use with the Audioscan Verifit1 (serial numbers 2070 or higher).

Study Methods

Binaural Oticon Opn 1 hearing aids were fitted to 22 adult participants using the Audioscan Verifit2 (software version 4.13.38). The participants had sensorineural hearing loss which fell within the fitting range of the Oticon Opn 85 and 100 receivers (Figure 1).

In this study, three fitting protocols were used: VerifitLINK, Clinician Fit, and the Manufacturer’s First Fit. For all three fitting protocols, the participant’s audiogram and measured HA-1 foam tip real-ear-to-coupler difference (RECD) values were entered into the Oticon Genie 2 Software (software version 2018.1-4.0.784.31). For the Clinician Fit and Manufacturer’s First Fit protocols, the audiogram and measured HA-1 foam tip RECD values were entered into the Audioscan Verifit2, as well. The DSL v5.0 adult fitting formula was chosen in the Genie 2 software, and participants were fitted with the dome type recommended by the fitting software dependant on their hearing loss. Relative to experience level, “experienced” was chosen for all participants. As recommended by the manufacturer, for all fitting protocols, the hearing aids were initially first-fit to the target being used (in this case DSL v5.0 adult) after the participant and acoustic information were entered.

VerifitLINK, as integrated in the REM AutoFit feature within Oticon Genie 2 software, is a three-stage procedure. Figure 2 shows the initial setup screen where the measurement method (ie, On ear, Test box), Fitting rationale (eg, DSL adult, DSL child, NAL-NL2), Signal Type (eg, Speech-ISTS, Speech-Std(F), Speech-Std(M)) and RECD source (ie, Genie 2, Verifit Measured, Verifit Average) can be chosen. In this study, the following setup parameters were used: On ear, DSL adult, Speech-ISTS, and the RECD which had been entered into Genie 2.

The participant was prepared for REM using Audioscan-recommended procedures, including placing the end of each probe tube within 5 mm of the tympanic membrane using otoscopy and the visually assisted positioning technique.¹⁴ Authors’ note: A review of probe-tube placement strategies for use with Audioscan equipment can be found on YouTube at: https://www.youtube.com/watch?v=m4VkK0OAbMw. 

To remove the confounding factor of probe-tube placement differences, once the probe tube and hearing aids were placed in the participants’ ears, all fitting types were completed without moving the probe tube or hearing aids. The fitting type order was counterbalanced across the 22 participants.

During the Manufacturer’s First-Fit and Clinician-Fit conditions, real-ear aided responses (REARs) at inputs of 50, 65, 75 dB SPL overall RMS using the ISTS signal, and MPO were completed using the binaural link feature of the Audioscan Verifit2. In cases of difficulty with binaural equalization, the hearing aids were measured monaurally. Each of the fittings were timed starting at the presentation of the first test signal and stopping at the completion of the final MPO test signal.

Fitting Specifics:

• Manufacturer’s First Fit: There were no adjustments made to the gain of the hearing aids based on the Verifit2 results following the Manufacturer’s First Fit to the DSL adult fitting formula.
• Clinician Fit: The gain of the hearing aids was manually adjusted by an experienced audiologist in the Genie 2 software to match the DSL adult targets shown on the Verifit2.
• VerifitLINK: VerifitLINK, as integrated in Genie 2, measured and adjusted the hearing aids through its automatic procedure to match the DSL adult targets shown on the Verifit2. This process consisted of a series of four automatic monaural measurements: 1) initial measurements left; 2) initial measurements right; 3) gain-adjusted measurements left; 4) gain-adjusted measurements right.

Each measurement group included REARs at 50, 65, and 75 dB SPL. The MPO was measured at the end of the series in the manual mode of VerifitLINK. Figure 3 shows a representative screenshot of the Genie 2 software after the VerifitLINK procedure was completed.

The Audioscan Verifit2 sessions were saved for each of the fitting types from all participants for analysis.  Fit-to-target accuracy, SII scores, as well as the time taken to complete the fitting were compared for the three fitting types. Because the gain adjustments of the automated real-ear (VerifitLINK) procedure implemented in Genie 2 software are based on target deviation calculations with the average (65 dB SPL) input signal, it was also of interest to evaluate the match-to-target impact with soft (50 dB SPL) and loud (75 dB SPL) speech inputs.

Results

Group data were analyzed for the 22 participants. Repeated Measures Analysis of Variance (ANOVA, GLM SPSS v24) was used to evaluate measurement differences between fitting types for: 1) Fit-to-target accuracy; 2) Speech Intelligibility Index (SII), and 3) Time to complete fitting. If significant differences were revealed, post-hoc paired comparisons were completed with Bonferroni corrections.

Fit-to-target accuracy. One method to determine how well hearing aids have been fitted is to calculate the root mean square error (RMSE) from target¹⁵ using the difference between the measured output at a defined group of frequencies and the target SPL at those frequencies. In this study, the RMSE from 500-6000 Hz was calculated for each of the three fitting types (Figure 4). Within-subjects variables of ear, test level, and fitting type were evaluated. Overall, the average Manufacturer’s First-Fit deviation was 6.7 dB RMS from target, which is outside the 5 dB recommendation found in the literature.¹⁵ VerifitLINK and Clinician-fitted conditions had 4.3 dB RMSE and 3.8 dB RMSE, respectively.

Of note, the ANOVA found that “test level” was not a significant factor, indicating an acceptable target match across multiple input levels. Thus, while the automated target match for this manufacturer’s implementation was based on the 65 dB SPL input, using the manufacturer’s recommended approach to first fit to the fitting formula that will be used in VerifitLINK resulted in the appropriate input/output function for the DSL adult prescription.

There was an overall effect of fitting type (F(1.647, 34.6)=.957, p<.001, ?²=.725). There was a significant interaction between test level and fitting type (F(1.089, 61.524)=3.978, p=.012, ?²=.159). Pairwise comparisons indicated a significant difference between the Manufacturer’s First Fit and both the Clinician Fit (p<.001) and VerifitLINK (p<.001), but no significant difference between the Clinician Fit and the VerifitLINK.

To illustrate the differences in average output for the three different fitting conditions evaluated in this study, the mean REARs for each of the three input levels (50, 65, and 75 dB SPL) for each of the fitting types are presented in Figure 5. In general, measurements show that the Manufacturer’s First Fit to DSL adult targets resulted in lower REARs across frequencies for each input level than both the Clinician Fit and VerifitLINK fittings, in addition to underfitting the DSL adult REAR targets.

Speech intelligibility (SII).The SII, which is shown on the Audioscan Verifit1 and Verifit2 Speechmap screen as a number between 0 and 100, is an indicator of the intelligibility of speech provided by the frequency gain response of the hearing aid fitting at that specific test level.¹⁶ Within-subjects variables of ear, level, and fitting type were evaluated (Figure 6). As expected, there was an overall effect of level (F(2,26.627)=347.77, p<.001, ?²=.943). In addition, there was an overall effect of fitting type (F(2, 22.699)=21.019, p<.001, ?²=.637), and an interaction between level and fitting type (F(1.518, 31.874)=44.16, p<.001, ?²=.678). Pairwise comparisons indicated a significant difference between the SII obtained using the Manufacturer’s First Fit and both the Clinician Fit (p<.001) and VerifitLINK (p<.001), but no significant difference between the SII obtained in the Clinician Fit compared to VerifitLINK.

The level by fitting type interaction was a result of significant differences between the Manufacturer’s First Fit and the other two fitting methods at all three levels. There was no significant difference in SII scores between the VerifitLINK and Clinician Fit at any of the three levels.

Test-retest. A total of 7 participants were run through the test protocol twice in order to measure the test-retest of the three different fitting types. Following the completion of the main protocol measures, the Verifit2 was restarted and the data within the system was erased. The probe tube was not moved out of the ear canal to ensure that probe-tube placement was not a variable in any measured differences between the initial and retest measures. The procedure was then repeated starting with the detection of the hearing aids. The real-ear aided response (REAR) differences between the first and second sets of measures were found at the audiometric frequencies between 250 and 8000 Hz for each of the three test levels for each of the fitting types. Test-retest values were below 2.5 dB for each of the fitting types across frequencies (Figure 7).

Time to complete the fitting. The time to complete REARs at 50 dB, 65 dB, 75 dB, SPL, and MPO inputs binaurally was measured for each of the fitting types, using simultaneous measurement whenever possible and sequential bilateral measurement otherwise. Durations were calculated in the following manner:

1) For the Manufacturer’s First Fit: When the fit-to-target icon was clicked until completion of all four REAR measures binaurally;

2) For the VerifitLINK: When the start button was clicked in Stage 2 of the VerifitLINK screen until completion of all four REAR measures binaurally; and

3) For the Clinician Fit: When the first stimulus was presented until completion of all four REAR measures binaurally.

As shown in Figure 8, mean times to achieve fit-to-target were: Manufacturer’s First Fit: 2 minutes and 2 seconds; VerifitLINK: 4 minutes 41 seconds; Clinician Fit: 7 minutes 16 seconds. The ANOVA revealed a significant overall effect of time(F(1.175,24.668)=74.296, p<.001, ?²=.780). Pairwise comparisons with Bonferroni corrections were completed and indicated the time to complete the fitting for each of the three methods were significantly different from each other (p<.001).

Example: On-Ear Fittings Using the Three Fitting Methods

Figure 9 shows a representative sample case in which both VerifitLINK and Clinician Fit provided closer fits-to-target and improved SII scores compared to the Manufacturer’s First Fit. RMSE deviation from target is calculated from 500-6000 Hz and is largest with the Manufacturer’s First Fit. The time-to-match target for the VerifitLINK was under 4 minutes 30 seconds. The time-to-match target during the clinician fitting was 9 minutes and 17 seconds for all four levels and both ears.

Summary

The current study investigated a recently developed automated match-to-target verification platform that integrates Audioscan Verifit systems with hearing instrument fitting software; in this case, Oticon Genie 2. As revealed in the findings above, this approach has the potential to provide multiple clinical benefits. In addition to being a timesaving method for target matching, these results are encouraging for those clinicians who may be unfamiliar with the process of adjusting hearing aids using REM. In the cases that have been evaluated, the VerifitLINK provides a fit to DSL v5.0 adult targets that is not significantly different than a fitting completed by an experienced audiologist in significantly less time. For these benefits to be realized, proper procedures for hearing aid fitting and real-ear measures (eg, appropriate probe tube placement in the ear canal) are required for accurate fitting results regardless of fitting method. Positive outcomes with amplification no doubt require a holistic (re)habilitative approach that considers multiple factors beyond simple target matching. As outlined above, the automated match-to-target approach provides clinicians with the opportunity to use their time for other aspects of clinical practice while supporting the use of best practice verification procedures during the hearing aid fitting process.

References

1. Valente M, Abrams H, Benson D, et al. Guidelines for the audiologic management of adult hearing impairment. American Academy of Audiology. https://audiology-web.s3.amazonaws.com/migrated/haguidelines.pdf_53994876e92e42.70908344.pdf. October 30, 2006.

2. College of Audiologists and Speech-Language Pathologists of Ontario (CASLPO). Practice standards for the provision of hearing aid services by audiologists.http://www.caslpo.com/sites/default/uploads/files/PS_EN_Practice_Standards_for_the_Provision_of_Hearing_Aid_Services_By_Audiologists.pdf. October 18, 2016.

3. Valente M, Bentler R, Kaplan HS, et al. Guidelines for hearing aid fittings for adults. Am J Audiol. 1998;7:5-13.

4. Kochkin S, Beck DL, Christensen LA, et al. MarkeTrak VIII: The impact of the hearing healthcare professional on hearing aid user success. Hearing Review. 17(4):12-34.

5. Valente M, Oeding K, Brockmeyer A, Smith S, Kallogjeri D. Differences in word and phoneme recognition in quiet, sentence recognition in noise, and subjective outcomes between manufacturer first-fit and hearing aids programmed to NAL-NL2 using real-ear measures.J Am Acad Audiol. 2018;29(8):706-721.

6. Amlani AM, Pumford J, Gessling E. Real-ear measurement and its impact on aided audibility and patient loyalty. Hearing Review. 24(10):12-21.

7. Abrams HB, Chisolm TH, McManus M, McArdle R. Initial-fit approach versus verified prescription: Comparing self-perceived hearing aid benefit. J Am Acad Audiol. 2012;23(10):768-778.

8. Leavitt RJ, Flexer C. The importance of audibility in successful amplification of hearing loss. Hearing Review. 2012;19(13):20-23.

9. Mueller HG. 20Q: Real-ear probe-microphone measures—30 years of progress? Lecture presented at: AudiologyOnline; January 12, 2014.

10. Mueller HG, Picou EM. Survey examines popularity of real-ear probe-microphone measures. Hearing Journal. 2010;63(5):27-32.

11. Koehler ED, Kulkarni S. Fast and easy fitting and verification with integrated real-ear measurement. Hearing Review. 2014;21(10):36-40.

12. Beck DL, Crowe N. Easy, fast, and accurate: Hearing aid fittings via an automated REM system using IMC 2. Hearing Review. 2017;24(4):30-31.

13. Mueller HG, Ricketts TA. 20Q: Hearing Aid Verification—Will autoREMfit move the sticks? Lecture presented at: AudiologyOnline; July 9, 2018.

14. American National Standards Institute (ANSI). Methods of measurement of real-ear performance characteristics of aids (ANSI/ASA S3.46-2013). https://webstore.ansi.org/Standards/ASA/ANSIASAS3462013.

15. McCreery RW, Bentler RA, Roush PA. Characteristics of hearing aid fittings in infants and young children. Ear and Hearing. 2013;34(6):701-710.

16. Scollie S. 20Q:Using the Aided Speech Intelligibility Index in hearing aid fittings. Lecture presented at: AudiologyOnline; September 10, 2018.

Evaluation Of Probe Guide: Software-assisted Probe Tube Placement In Hearing Aid Fittings

By Paula Folkeard, AuD; John Pumford, AuD; Jonathan Pietrobon, MESc, and Susan Scollie, PhD

Feb 13, 2020

A new software-assisted system for placement of the probe tube in real-ear measurement (REM) has been developed by Audioscan. This article describes the new Probe Guide tool and compares its performance with traditional methods for probe tube placement.

Research has highlighted the benefits of conducting real-ear measurements (REM) for both patients and clinicians. Routine verification of aided hearing aid responses using REM is also a part of recommended practice.^1,2 Yet, despite professional guidelines, best-practice statements, and research evidence, REM is not routinely performed by clinicians.^3,4 In fact, failing to verify hearing aid fittings using probe-microphone measurements has been listed as the number-one mistake made by clinicians.⁵

While various theories have been proposed, lack of REM use is attributed by some to the perceived complexity of the REM process, including proper positioning of the probe tube in the ear canal.⁴ The literature generally indicates that the end of the probe tube should be placed within 5 mm of the eardrum (while avoiding contact and any associated discomfort) to obtain accurate measurements, particularly in the high frequencies, given the influence of standing waves along the ear canal.^6-10

ANSI S3.46-2013¹¹ outlines various methods to obtain proper probe tube placement for REM including: visually assisted positioning using a standard probe tube insertion depth and otoscopy; geometrical positioning leveraging the lateral portion of an existing hearing aid or earmold⁸, and, two acoustical techniques which use standing waves in the ear canal to assist in probe tube positioning:

1) Acoustically assisted positioning using the stability of the REUR measurement at 4-6 kHz and

2) Acoustical positioning using a continuously presented 6 kHz narrow-band stimulus.

These probe tube placement methods can be used to generate clinically appropriate measurements that have good reliability;^7,8,10,12 however, they are arguably not always easy to execute or interpret, depending on the ear canal and experience of the clinician.

Training is commonly provided to develop clinical competency in probe tube placement and can include in-person training, the use of mannequin simulators,¹³ and software-assisted feedback systems such as the probe tube placement tool described in this paper.

Probe Guide

In an effort to increase the use of REM in clinical practice and to aid clinicians with obtaining proper probe tube insertion depth, Audioscan has developed Probe Guide. This clinically feasible, software-driven, acoustic-based tool was developed using a patent-pending machine-learning algorithm to guide probe tube placement in real time.

While a broadband noise signal is presented from the REM loudspeakers, the spectrum of sound within the ear canal is repeatedly sampled, analyzed, and input into a model of probe tube depth developed from a previously measured set of in-ear recordings. These recordings were gathered with normal adult ear canals as the probe tube was advanced to the correct location relative to the tympanic membrane.¹⁴ The machine-learning algorithm was “trained” to estimate probe tube depth from a sequence of input spectra, resulting in a software system that detects correct probe placement in real time.

A typical next step in machine-learning tool development is to test the trained system on a new dataset to evaluate whether the trained system works on new patients. Therefore, the purpose of the following collaborative study was to validate the performance of Probe Guide on a new set of ears. Our goal was to determine the performance of this new tool by comparing measured probe tube insertion depths between Probe Guide and a clinician-appraised depth, the adequacy of REMs made with Probe Guide, and the presence of any procedural issues (eg, eardrum contact) obtained with Probe Guide (PG) versus an experienced audiologist using a traditional visually assisted (VA) method of probe tube placement.

How to Use Probe Guide

Probe Guide can be accessed on any on-ear test screen on Audioscan Verifit2 (software version 4.18 and later) and Axiom (software version 1.24) by clicking the provided icon button (Figure 1). The guidance in probe tube placement is shown in Steps 1-3 below (Figures 2-4).

STEP 1: Setup

STEP 2: Preview

STEP 3: Measure

Probe Guide Validation Study

The current study investigated the performance of the software-assisted Probe Guide method as implemented on Verifit2 relative to an expert clinician’s probe tube placement using the traditional visually assisted positioning technique. The expert clinician had more than 20 years of experience placing probe tubes for both clinical and research purposes.

Evaluation measures for each placement method included absolute probe tube insertion depth, test-retest reliability of probe tube insertion depth, real-ear unaided responses (REUR), and the occurrence of any procedural concerns (eg, patient discomfort, visual acceptability of placement, reported eardrum contact). A total of 20 participants (10 males and 10 females, ages 25-81) completed the protocol. All subjects had normal middle ear and external ear canal status as determined by otoscopy and impedance measurements.

Probe tube placement was completed on 40 adult ears, twice using the visually assisted method, and twice using Probe Guide. The starting order was counterbalanced across ears and placement methods. A within-subjects design was used to measure these system performance variables at the individual level. The probe tube marker, typically used to aid with probe tube placement, was moved to the base of the probe tube so as not to influence insertion depth decision-making.

For the visually assisted method, the probe tube was placed considering anatomical markers that correspond to a distance of approximately 5 mm from the tympanic membrane. The clinician used otoscopy to monitor the probe tube location. For the software-assisted method, the probe tube was inserted until Probe Guide indicated the proper insertion depth had been achieved.

Following probe tube placement with either method, the REUR was measured using a 65 dB SPL pink noise following the standard ANSI S3.46-2013 REM procedure. Next, the probe tube was marked with a fine felt tip pen at the intertragal notch. The probe tube was then removed from the ear canal and the distance from the medial end of the probe tube to the marked line was measured to calculate the insertion depth in millimeters. The mark was removed and the procedure was repeated again to evaluate test-retest reliability. The procedure was completed twice in each ear canal resulting in 4 measurements for each participant (Figure 5).

Figure 5. Real-ear unaided response (REUR) measures for one participant. Four REUR measures were completed for each ear. (Test 1 – Visually assisted (VA); Test 2 – VA (second run for test-retest); Test 3 – Probe Guide (PG), and, Test 4 – PG for test-retest).

The Speechmap session files from the Verifit2 were saved and exported in .xml format and imported into a spreadsheet for further analysis. The acoustic differences between the visually assisted and Probe Guide methods were calculated at all 1/12th octave frequencies measured by the Verifit2.

Results

Real-ear unaided response (REUR) measurements.

Group data were analyzed for the 20 participants. All statistics were completed using SPSS v24. A repeated measure analysis of variance (ANOVA) was completed to evaluate differences between probe tube placement methods for: 1) Probe tube insertion depth, and 2) REURs. In addition, within each probe tube placement method, test-retest reliability was evaluated. If significant differences were revealed, post-hoc paired comparisons were completed with Bonferroni corrections.

The ANOVA was completed comparing the results from the two methods, with left and right ears and repetitions as within-subjects measures. Results indicated that frequency was significant (F(6.441, 978.975)=965.712, p=<.001>2 =.864). This result was expected because of the magnitude of the REUR changes across frequencies. Ear tested was not significant (p=.159, η²= .013), meaning results did not change whether we were testing the right or left ear.

For the purposes of this study, we were most interested in the significance of Placement Method. When the four sets of measures (ie, VA, VA-retest, PG, PG-retest) were compared, results indicated that placement method was not significant (p=.966, η²=.002) indicating that the measures within repetitions and between test methods did not differ. The average REUR difference at each frequency is presented in Figure 6 (PG-VA). Descriptively, these results show less than 1.6 dB difference between the visually assisted and Probe Guide measures out to 12,500 Hz. The 95% confidence interval shows that differences between the two placement methods were less than 2.5 dB up to 8,000 Hz, and less than 3 dB up to 12,500 Hz.

Probe tube insertion depth measurements. Probe tube insertion depths (Figure 7) relative to the intertragal notch for males ranged from 29-41 mm for both placement methods (mean = 33.9 mm using VA; mean = 33.7 mm using PG). For the female group, the probe tube depth ranged from 25.5-34.5 mm (mean = 30.2 mm) using the visually assisted and a range of 25-35 (mean = 30.0 mm) using Probe Guide. As expected, probe tube depth by gender was significantly different (F(1, 0.584)=5995.110, p<.001>2=.345). However, when the probe tube insertion depths for the 40 ears (20 left and 20 right) were compared across the four placement conditions (ie, VA, VA-retest, PG, PG-retest), the ANOVA results indicated Placement Method was not significant (F(2.447, 95.424)=.780, p=.485, η² =.020), nor was Method by Gender (F(2.467, 93.727)-.669, p=.545., η²=0.017).

Observational reporting of the probe tube placement methods. Of the 160 probe tube placements, there were no reported incidences of contact with the tympanic membrane or discomfort reported using either of the two placement methods. Following each use of Probe Guide, the experienced clinician viewed and commented on the resulting placement. Of the 80 software-assisted Probe Guide placements, one placement was deemed to be too far away from the tympanic membrane (3 mm farther than the visually assisted method) and 5 placements were deemed to be at an appropriate distance but likely too close to the tympanic membrane when inserting a hearing aid or foam tip (2-3 mm closer than the visually assisted method).

Summary

Proper probe tube placement is necessary for valid real-ear measurements, and is therefore an important aspect of verification. In an attempt to assist with this component, Audioscan developed an acoustic-based, software-driven probe tube placement tool called Probe Guide to evaluate the location of the probe tube in the ear canal.

As previous acoustic methods of probe tube placement have been criticized for being time-consuming and complex,¹⁵ Probe Guide was designed to be more easily incorporated into the clinical REM workflow. The current study evaluated the accuracy of probe tube placement using this new tool in adult ears with normal outer and middle ear status. Results indicated that Probe Guide provided probe tube insertion depths and resulting REURs that were not significantly different from those obtained by an experienced clinician using the traditional visually assisted probe tube placement method. Test-retest reliability was good for both probe tube placement methods. In addition, Probe Guide resulted in acceptable probe tube placement across the ears evaluated in this study as assessed by an experienced clinician with no reported contact with the tympanic membrane.

It is important to note that this project validated Probe Guide with adults presenting with normal outer and middle ear status, and outcomes with other clinical populations may vary. Further evaluation of this software-assisted probe tube placement tool is required to assess its performance with other patient groups, such as infants, children, and those with atypical outer and middle ear status. In addition, Probe Guide does not preclude the continued use of best-practice clinical protocols for probe tube placement with any patient, including otoscopy.

With these considerations in mind, the positive findings of this study suggest Probe Guide is a useful tool that can assist clinicians with probe tube placement when needed. To the extent that confidence and/or lack of experience with probe tube placement is an obstacle to conducting REM, the results of this study should encourage clinicians to use Probe Guide as a means to more routinely incorporate REM into their practice.

References

1. Valente M, Abrams H, Benson D, et al [American Academy of Audiology task force]. Guidelines for the Audiologic Management of Adult Hearing Impairment. Audiology Today.2006;18(5):1-44.

2. College of Audiologists and Speech-Language Pathologists of Ontario (CASLPO). Practice Standards for the Provision of Hearing Aid Services by Audiologists. http://www.caslpo.com/sites/default/uploads/files/PS_EN_Practice_Standards_for_the_Provision_of_Hearing_Aid_Services_By_Audiologists.pdf. Published October 18, 2016.

3. Mueller HG, Picou EM. Survey examines popularity of real-ear probe-microphone measures. Hear Jour. 2010; 63(5):27-32.

4. Mueller HG. 20Q: Real-ear probe-microphone measures–30 years of progress? January 12, 2014. Available at: https://www.audiologyonline.com/audiology-ceus/course/20q-real-ear-probe-microphone-23597. Published January 12, 2014.

5. Kochkin S, Beck DL, Christensen LA, et al. MarkeTrak VIII: The impact of the hearing healthcare professional on hearing aid user success. Hearing Review. 2010;17(4):12-34.

6. Dirks D, Kincaid G. Basic acoustic considerations of ear canal: Probe measurements. Ear Hear.1987;8(5):60S.

7. Storey L, Dillon H. Estimating the location of probe microphones relative to the tympanic membrane. J Am Acad Audiol.2001;12:150-154.

8. Bagatto MP, Seewald RC, Scollie SD, Tharpe AM. Evaluation of a probe-tube insertion technique for measuring the real-ear-to-coupler difference (RECD) in young infants. J Am Acad Audiol.2006;17:573-581.

9. Moodie S, Pietrobon J, Rall E, et al. Using the real-ear-to-coupler difference within the American Academy of Audiology pediatric amplification guideline: Protocols for applying and predicting earmold RECDs. J Am Acad Audiol.2016;27(3):264-275.

10. Vaisberg JM, Macpherson EA, Scollie SD. Extended bandwidth real-ear measurement accuracy and repeatability to 10 kHz. Int J Audiol.2016;55(10):580-586.

11. Acoustical Society of America. American National Standard: Methods of Measurement of Real-Ear Performance Characteristics of Hearing Aids, ANSI/ASA S3.46-2013. Melville, NY: Acoustical Society of America; 2013.

12. Sinclair ST, Beauchaine KL, Moodie KS, Feigin JA, Seewald RC, Stelmachowicz PG. Repeatability of a real-ear-to-coupler difference measurement as a function of age. Am J Audiol. 1996;5(3):52–56.

13. Koch RW, Moodie S, Folkeard P, et al. Face and content validity of a probe tube placement training simulator. J Am Acad Audiol.2019;30(3):227-234.

14. Pietrobon J, Pumford J, Folkeard P, McInerney C. Application of real time recurrent neural networks for estimating probe tube insertion depth. Poster presented at: The 2018 International Hearing Aid Research Conference (IHCON); August 15-19, 2018;Lake Tahoe, CA.

15. Searchfield GD, Purdy SC. Probe microphone placement for real ear measurement. Am J Audiol.1997;6(2):49-54.