The health care field has adopted many process improvement methodologies from other disciplines and industries to ensure quality and patient safety. However, there is still a great need for a well-structured and easy-to-follow methodology that focuses on changing health care professionals’ (HCPs) behaviors. Using hand hygiene among intensive care unit HCPs as an illustrative example, the authors provide a practical guideline for such a methodology. Based on Fishbein and Ajzen¹ theory of planned behavior and Hornik and Woolf ² message design strategy, this methodology identifies key factors, determines their intention for the behavior at hand, runs a cross-sectional survey on the beliefs and behavioral intention, and uses statistical analysis to identify a manageable number of target beliefs that will be the basis for program development. In addition, we introduce ways to develop a successful program that is based on this information.

Keywords: healthcare provider behavior, theory of planned behavior, statistical approach to program development, quality of care, patient safety, hand hygiene

In order to improve quality and patient safety, health care organizations around the world have launched an immeasurable number of projects. To expedite this improvement, many of them have borrowed well-recognized techniques from other industries or fields, so-called “translocational research.” For instance, the policy of limiting the number of consecutive work-hours was adopted from the airlines and trucking industries.³ Moreover, for more complicated and large-scale projects like clinical process redesign, more comprehensive methodologies such as Lean Six Sigma or Total Quality Management have been borrowed from business, management and even manufacturing, and proven effective in health care.^{4 ,5}

However, such translocational application of methodologies customarily targets system or process improvement; few are intended to change the behavior of individual health care professionals (HCPs). This is regrettable because several simple but critical behaviors can enhance quality and safety, such as verbal order read back, double-checking patient ID when administering medication, and having a timeout before beginning a surgery. Even a large systems improvement contains several parts that require HCPs’ behavioral changes. To illustrate, a hospital-wide implementation of Computerized Prescriber Order Entry system requires physicians to change their behavior, something that is expected to take quite a long time. Indeed, there is a huge unmet need for a proven methodology to tap into HCPs’ minds and expedite their behavioral modification.

In search of such a methodology, we must keep in mind that each organization or work unit possesses its own culture and behavioral pattern, which must be factored into any behavioral change program; simply trying to replicate the ‘best practice’ or ‘success story’ of other organizations is likely to be ineffective at best and a failure at worst.⁶

This article, introduces a methodology, drawn from the fields of social psychology and communication that is designed to effect HCPs’ behavioral change. It also offers how to identify the underlying beliefs on the behavior held by each HCP and even social pressure from the culture where they work.

In order to keep this guide easy to follow, we have refrained from describing the theoretical background and the statistical analysis techniques in detail. Instead we suggest step-by-step activities intended to solve a fictional but highly plausible problem—low compliance in hand hygiene behavior of resident physicians working in the Intensive Care Units (ICUs) of a hospital (see Box 1).

Reveal te salihent beliefs

The first step is defining the target behavior. The more specific it is, the more accurately this step will identify beliefs that will change the behavior. The definition should incorporate action, target, context and time.¹⁰ Based on the case in box 1, we define the target behavior as “Residents washing hands using alcohol-based rub or soap and water before and after seeing a patient in ICUs in the next week.” A precise description of behavior is crucial since we will collect beliefs related to that behavior.

With the defined behavior, we run a series of elicitation interviews to learn what relevant beliefs the target population possesses. An elicitation interview is semi-structured (Table 1) and open-ended, usually conducted on at least 15 to 20 respondents. However, the absolute number of interviews is of not too much importance. The purpose of the interviews is to reveal all the salient beliefs until more new beliefs emerge. From the authors’ experience, beliefs among a limited population like HCPs working in an ICU require only 10-12 interviews until reaching belief saturation. It is desirable to have about half of the interviewees having already performed or intending to perform the behavior, and the other half having not performed well.¹¹ The decision of who should be interviewed should be left to the discretion of the project manager, with input from people in the best position to have observed behavior or the target population; in this case, nurses and senior physicians. The rationale for the intender vs. non-intender mix will be described in the next step.

Though the focus group interview is known to be efficient and time-saving, the one-on-one setting is suggested to prevent any group dynamics effect and to facilitate the interviewees to express underlying beliefs. Table 1 shows some sample questions. Asking probing questions is a good way to elicit beliefs that are not readily accessible but may still be influential.

Once we have reached saturation, it is time to analyze the interview results to identify the most common beliefs held by the interviewees. The interviews are usually audio-recorded with participants’ consent, so typing them into computer is preferred. Either content analysis software or even a simple spreadsheet with manual analysis suffices to organize the interviewees’ beliefs. A researcher can group different terms and expressions that refer to the same outcome (e.g., “makes skin sore” and “skin irritation”). Then, beliefs are ranked by their frequency of mention, until the chosen beliefs account for at least 75% of responses.¹ Through interview and content analysis, we generated a list of the 12 beliefs about hand washing that were held by residents working in ICUs⁹ (Table 2).

The beliefs elicited through the interviews and following content analysis will be fed into formative survey in the next step, so that quantitative information on the associations among behavior, behavioral intention, and the underlying beliefs will be analyzed.

Identify key beliefs by formative survey

While we revealed the 12 most frequently mentioned beliefs, designing a program that covers all the beliefs will be likely to fail because of a lack of focus. Furthermore, if elicitation interviews revealed tens of salient beliefs, it would be impossible to develop a program addressing all of them. This step therefore describes how we can identify key beliefs that must be addressed in program development.

First, we develop a survey whose main items to be measured are intention to perform the behavior, and the beliefs we found in step 1. Intention is measured on a four-point Likert-type scale from “definitely will not” (1) to “definitely will” (4), because we will dichotomize the respondents into intenders and non-intenders. Beliefs are commonly measured on a five-point Likert-type scale from “strongly disagree” (-2) to “strongly agree” (2)¹² For example, “Washing my hands before and after seeing a patient, using alcohol-based rub or soap and water in ICUs in the next week will protect patients from infection” (behavioral belief); “Other residents think that I should wash my hands before and after seeing a patient, using alcohol-based rub or soap and water in ICUs in the next week” (normative belief); “I will experience an emergency situation” (control belief). We must reverse the scoring scheme for beliefs that are expected to have deterred the target behavior. To illustrate, for an item like “Washing my hands before and after seeing a patient, using alcohol-based rub or soap and water in ICUs in the next week makes my skin dry and sore” the answer “strongly disagree” should be considered as if “strongly agree,” and scored -2 rather than +2 in analysis, so that high score consistently indicates beliefs favorable toward the target behavior.

In a small-scale project targeting a certain population (ICU working residents), a survey could ideally be administered to the entire target population. However, even at a single ICU, administering survey to all HCPs is practically impossible, considering that their work hour is already overloaded. Therefore, in reality we would naturally gather survey data from a sample of the whole target population.

After all surveys have been returned, we can calculate the sample correlation coefficients between each belief strength (measured on a scale of -2 to +2) and behavioral intention (measured on a scale of 1 to 4). We have 12 beliefs, so that 12 correlation coefficients in total will be calculated (so called zero-order correlation coefficients). We would also focus on the percentage of people who strongly agreed (belief score +2) with each belief between intenders (intention score 3 or 4) and non-intenders (intention score 1 or 2). Table 3 displays these information; as mentioned earlier, the dataset shown in the table is an illustrative example. Although the authors have used both STATA and Microsoft Excel in our analyses and they produced the same zero-order correlation coefficients, any other appropriate software can be used to obtain these statistics.

a. Using Table 3, we select a few target beliefs to be used in program development by utilizing the criteria suggested by Hornik and Woolf²: The belief should be significantly related to the behavioral intention (significant correlation)
b. There should be enough “room for change” for beliefs. In Table 3, the larger the difference in percentage of whom answered “strongly agree” with a belief between intenders and non-intenders, the more room for change is expected
c. Whether a belief can be modified through the program we will develop; if not, the beliefs should not be chosen.

Lastly, all the control beliefs are significantly correlated with intention, and held by significantly fewer non-intenders than intenders, which makes all those beliefs meet the first two criteria. The third criterion is whether a selected belief can be used in developing a program. We will use the control belief about “emergency situations” as an example. It is understandable that it may be almost impossible to adhere to hand hygiene guidelines in an emergency. Moreover, ICU is one of the units where emergency situations occur the most frequently in a hospital. It would be impossible to design a program that would reduce the number of emergency situations in ICU, and it would be unrealistic to expect residents to make hand hygiene a higher priority than saving a patient’s life. Therefore, while this belief has met the first two criteria, it will not be a good basis for a program.

The normative belief that “mentally alerts patients think I should follow hand hygiene guideline” is in similar position. Residents would naturally feel more pressured to wash their hands when patients will know whether or not they do it. However in ICUs, most patients are not expected to be conscious and paying attention. Moreover, it is unacceptable for residents to wash their hands only when the patient is watching. Therefore, this belief is not a sound basis for a program. By testing each belief through these criteria, we arrive at seven key items to focus on in developing a program to improve residents’ compliance with hand hygiene behavior. The gray items in Table 3 are the items which will be used in the next step.

Develop an effective program using selected beliefs

Now, we develop a program, “Improving residents’ hand hygiene compliance in ICUs” focusing on the seven key beliefs found above. It can’t be stressed enough that while the way to find key beliefs are well established as shown above, developing a program is a highly creative task requiring program developer’s in-depth understanding on target place’s resource availability, general compliance to a quality and safety improvement program of the target population, even the overall culture of the place; the expected support level from senior physicians and executives should not be ignored.⁶

Here, we suggest a fictional example program by assuming that hospital and senior executives are willing to provide financial support to post reminders and to purchase more alcohol-based hand rubs and food for occasional lunch meetings. The following program example is derived from the above analysis; since one program components can cover several beliefs (and vice versa) the (Table 4) below is arranged to reflect that flexibility.

It is important to increase both self-efficacy (perceived ease of performing the target behavior) and response efficacy perceived effectiveness of the behavior Bandura¹³ among the target audience, here the residents regarding following hand hygiene guidelines. Once a program is developed shown as in Table 4, it is highly recommended to have a kick-off meeting, preferably at lunchtime, for everyone involved. In this example, hospital executives and senior staff physicians should attend and explain their expectations of the residents, and promise to support residents’ hand hygiene behavior. This meeting will dramatically improve residents’ self-efficacy. In terms of response efficacy, the belief that “(washing hands) consumes too much time when using soap and water” is noticeable. In addition to system changes that make alcohol-based rubs more available, providing persuasive messages that alcohol-based rubs are as effective as soap and water, and that they save time, will enhance response efficacy. Providing both self-efficacy and response efficacy messages along with programs handling environmental barriers will greatly enhance behavioral intention.

This simple step-by-step guide was prepared to develop any programs for HCPs’ behavioral change. People who are already familiar with the model used in this guideline may have questions. For example, we did not directly measure attitude, social norm and perceived behavioral control because identifying beliefs and following program development steps do not necessarily require them. Such thorough surveys usually take place for persuasive message development targeting a large population. In our case, and in many cases in health care field, the target audience has similar characteristics, especially when they are located in the same organization. They would share similar environment and cultural background. This would potentially result in much fewer behavior-relevant beliefs, which would make the statistical analyses manageable even when addressing all the key beliefs, without directly measuring attitude, social norm and perceived behavioral control and selecting one of the three before addressing each of the beliefs underlying those components. In addition we did not measure the residents’ self-reported behavior, because the principal investigator began with secret shopper methods on HCPs’ hand washing behavior. Therefore, the decision of success or failure of the project will rest on the next secret shopper measurement.

Though elicitation interview and calculating correlation between the belief and intention to perform the behavior are statistically clear processes, the step on “room for change” is based on the project manager’s experience and decision. Indeed there is no clear rule that governs whether or not we choose a certain belief. What matters is filtering out the less important beliefs and the beliefs upon which we cannot develop an effective program. You may think of this process as ranking the beliefs, and take a few beliefs (in our example, seven were chosen) and take them to the program development step. If would rather limit yourself to three beliefs, just choose the three with high correlation and most room for change.

As shown in Table 4, one single belief can lead the program manager to devise multiple components of the program, and vice versa. As such, when developing a program, in contrast to the previous steps, you should be creative, and brainstorming is highly recommended.

In addition, when you follow this guideline, you may feel overwhelmed by the beliefs that emerge from the elicitation interviews. However daunting they look, all you need to do is develop and administer a sound survey to the target population and filter the results until you reach the addressable number of beliefs.

In conclusion, this guideline presents the statistical and solid steps to take to identify the key items that will lead a target population to perform a certain behavior. More importantly, this method can bring to light HCPs’ highly relevant but latent beliefs. For example, many quality and patient safety leaders still believe that emphasizing “hand hygiene is important to save patients from infection” is crucial in improving HCPs’ hand hygiene compliance. Though this belief is absolutely true, everybody already believes this, so focusing on this knowledge and educating the residents will not be very effective. As specialists in quality and safety, and communication science, the authors therefore suggest applying this step-by-step guide to any behavior-related problems in health care organization. We expect that this framework will have the desired results, and surely save lives.

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