Patient Surveys and the Six Sources of Influence

At Crucial Dimensions, we provide a lot of training to the Healthcare sector. We were recently asked by an attendee at our training how they could use the Six Sources of Influence to improve patient satisfaction scores at their hospital.

At their hospital, they were finding that the patient satisfaction scores were coming back significantly lower than what the patients were telling the staff. Patients were always singing the praises of the hospital, yet when it came to completing the satisfaction surveys, the feedback was seemingly disappointing. So could the Six Sources of Influence actually improve patient satisfaction scores?   

First, let’s consider the survey and assume that the purpose of your survey is to gather reliable data. Reliable data is uncorrupted, which means it’s free of errors and bias.

Second, let’s consider the Six Sources of Influence. They are personal, social, and structural levers that can be used to affect motivation and ability.

So, there’s some irony in how you can influence people in a situation where, if you want reliable data, they shouldn’t be influenced at all—unless it is to tell the truth as they see it.

So we want patients to report their feedback honestly but we also want to improve patient satisfaction scores using influence, if possible. Hmmm? Let’s break this down.


There’s nothing wrong with having an assumption—a hypothesis. But remember it’s a hypothesis only.

We can hypothesize that patients are more satisfied with treatment than they’re reporting. We have two data sources: the verbal feedback, and the numerical feedback.

Given that they don’t match, it’s natural to conclude one source doesn’t accurately reflect patient perspectives. We assume the faulty data is the numerical feedback, and it may be. But let’s for a moment, consider the possibility that the faulty data is the verbal feedback.

Could this be possible? Why might a patient tell a nice healthcare professional his or her staff is wonderful and then complete an anonymous survey with a low score?


Given the nature of this exercise, the end goal is both reliable data and better scores. But when it comes to the survey, the only goal should be reliable data.

The cardinal sin of any survey is bias. And while that’s obvious on paper, it’s not always clear in practice. Surveys should be used to gather data that allow us to make a reasonable inference about a population, but frequently they are used to gather data to support a belief or proposition, which results in bias.

So, commit to improving the survey, not the survey results. Truth in the data makes it possible to do the work of improving results.


One of the key principals of philosophy is “define your terms.” The point of all communication is to convey meaning. We only confirm whether meaning is accurately conveyed through feedback. And, when it isn’t, that feedback can be anything from a scrunched eyebrow to a survey anomaly.

The fact that we encounter discrepancies between verbal and numerical feedback could mean our survey questions are unclear. For example, for some patients a 10 may mean “medical care provided without error by qualified healthcare professionals.” For some of your patients, a 10 may mean “attractive nurses, plenty of morphine, and 100 channels on a big-screen TV.”

So, define your terms. This is particularly important with ratings. Make it clear what you mean by an 8 or a 10 or a 5 by providing examples of the care those ratings represent. In your definitions, avoid interpretations like “timely care” and provide factual examples like “nurses responded to calls within 10 minutes on average.”

In short, your respondents should never feel confused. You might add a question to your survey: “Did you find any questions in this survey confusing or difficult to answer? If so, please explain.” Use that feedback to continually improve the clarity of your survey and your respondents’ ability to answer accurately.


Remind patients of the personal and social value of complete and reliable data. You might do so on the survey itself and verbally when administering it.

“While this survey is optional, your honest and anonymous feedback help us provide quality care for the community. When you take the time to answer objectively, you help us provide better care for you and other patients.”


Finally, consider hiring an agency. We sometimes do so with our own surveys. Professionals in survey design and analysis understand how various factors can contribute to discrepancies or bias, from wording to question types, to the order of the questions themselves.

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