By Dennis Van Vliet, AuD
The car I have driven since late 2004 is a simple red Prius. I chose it because California had an incentive at the time that allowed solitary drivers to be in the carpool lanes if they purchased a vehicle that had fuel economy that met certain criteria. I appreciated the fuel economy, and really appreciated the ability to use the carpool lanes when traffic was heavy. That perquisite lasted a few years and expired, but I liked the car well enough to keep driving it.
One of the distinctive features of the car is that there is no mistaking that it is a Prius. Initially, I also liked that the car’s buyers spanned a variety of socioeconomic lines, so there was no way to guess why I drove it. Even in a car that was unmistakably a Prius, I could be somewhat anonymous with few expectations from others. What I have found recently, however, is that people apparently form an opinion about my car, or me, because of what it is. If I’m traveling along with traffic at uncongested freeway speeds, typically between 68 and 75 miles per hour, I find that a good number of drivers work very hard to tailgate and get around me, apparently assuming that I must be going too slow. Their reward is to gain a car length or two, but not to gain any additional speed, since I’m traveling with the flow of traffic.
Instead of being anonymous, I’m apparently the slowest car in the lane, no matter how fast I am going. I understand the efficiency of assumptions and profiling when we are trying to make decisions and navigate through life, and I suppose that just seeing an old hybrid on the road falls into that category when one is in a hurry, but it isn’t a correct assumption.
The Dangers of Assumptions
Think about the assumptions we may make when confronted by a 69-year-old new hearing aid user candidate. Do we assume that she is in denial, withdraws at parties and family events, is depressed, and has formed a strong negative opinion about hearing aids? We might be right on some of the attributes, but our assumptions are based on what we might think is commonly seen, not on the behavior and beliefs of the person we are working with.
Take my assumption that the potential candidate is 69. That may fit the MarkeTrak findings based on the National Family Opinion panel’s balancing method that selects participants based on US census data in an effort to reflect a demographic profile similar to that of the United States as a whole. It cannot represent the patient in front of us, however. A recent 2013 issue of Seminars in Hearing, guest edited by Jason Galster, PhD, is dedicated to the variability in individual aided outcomes.1 Larry Humes succinctly sums up the core message:
Ultimately, individual differences research has the potential to be of the greatest benefit to practicing clinicians; professionals who always deal with individual patients rather than the “average” or “typical” patient.2
In the same publication, Recker and Edwards point out: “These results also highlight the importance of analyzing data on an individual basis.”3
The fact is that our patients are individuals, and we treat them as such to personalize their care. Why, then, do we hold on to routines that are based on averages of group data? We do because we need to start somewhere, and it is more likely that we are near a successful fitting if we use group data to guide us to that starting point. The key is for us to remember that it is likely that the starting point is unlikely to be optimal for a given individual. The fittings that get us to optimal are arrived at by asking questions, listening carefully, and responding to the individual answers with adjustments and counseling as appropriate.
I recently had an interesting conversation with a fourth year AuD student who was disappointed with probe microphone methods in his professional community. He relayed an incident where a patient he had fit and subsequently followed had visited another clinic for a second opinion. The clinic sent him probe microphone data for this patient, with areas that the fitting didn’t match up with average targets highlighted, not unlike red marks on a quiz from a teacher. He was disappointed because he had fit the patient to target, then worked with the patient over time to make adjustments for comfort and clarity. He didn’t see how the probe targets helped in the fitting other than to give someone else a method for critiquing his work.
Since I know only what I learned from the AuD student, I can only comment that probe microphone results are best used as guidelines for audibility and comfort of aided speech, and targets only show us where a number of successful users end up with their fittings. Gain and targets are just guidelines to steer us toward the more important goal of audibility. As long as the patient in front of us has audibility and comfort for a bandwidth that is appropriate for them, we can be satisfied that we have a good starting point. The best way to verify that is by objectively measuring it. Beyond verification, we still need to be clinicians and respond to other individual factors that are in play for the patient.
The Final Word? Patients are individuals, and we need to analyze their individual results and preferences to determine an acceptable, optimal fitting. Group average data are helpful to shape the direction we need steer, but the end point of the fitting needs to match individual needs.
|
References
1. Galster J (Guest editor). Individual variability in aided outcomes. Seminars in Hearing. 2013;34(2).
2. Humes L. Individual differences research and hearing aid outcomes. Seminars in Hearing. 2013;34(2):67-73.
3. Recker K, Edwards B. The effect of presentation level on normal-hearing and hearing-impaired listeners’ acceptable speech and noise levels. J Am Acad Audiol. 2013;24(1):17-25.
