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date: 27 May 2017

Types of Explanations in Health and Risk Messaging

Summary and Keywords

Explanations designed to teach, rather than to support scientific claims in scholarly works, are essential in health and risk communication. Patients explain why they think their symptoms warrant medical attention. Clinicians elicit information from patients and explain diagnoses and treatments. Families and friends explain health and risk concerns to one another. In addition, there are websites, brochures, fact sheets, museum exhibits, health fairs, and news stories explaining health and risk to lay audiences. Unfortunately, research on this important discursive goal is less extensive than is research on persuasion, that is, efforts to gain agreement. One problem is that explanation-as-teaching has not been carefully conceptualized. Some confuse this communication goal and discursive type with its frequent verbal and visual features, such as simple wording or diagrams. Others believe explanation-as-teaching does not exist as a distinctive communication goal, maintaining that all communication is solely persuasive: that is, designed to gain agreement.

Explanation-as-teaching is a distinct and important health communication goal. Patient involvement in decision making requires that both clinicians and patients understand options underlying health-care choices. To explore types of explanation-as-teaching, research provides (a) several ways of categorizing health and risk explanations for lay audiences; (b) evidence that certain textual and graphic features overcome predictable confusions, and (c) illustrations of each explanation type. Additionally, explanation types succeed or fail in part because of the social or emotional conditions in which they are presented so it is important to note research on conditions that support patients, families, and clinicians in benefiting from explanations of health and risk complexities and curricula designed to enhance clinicians’ explanatory skill.

Keywords: explanation-as-teaching, risk, risk communication, health literacy, numeracy, shared decision making, communication, instruction giving, elucidating explanation, quasi-scientific explanation, transformative explanation, informal science education, health communication instruction, health communication education, health and risk message design and processing

It’s Saturday afternoon. The Bakers are sitting at the kitchen table. The nephrologist’s office calls saying Mrs. Baker needs to get to the hospital immediately. Speaking to the nurse on the phone, Mrs. Baker asks, “Why do I need to go to the hospital? Nothing hurts.”

Nurse Your potassium is very high. Your kidneys are not working well.

Mrs. Baker But I feel fine.

Nurse Mrs. Baker, kidneys don’t hurt.

Definition

The nurse’s statements saying Mrs. Baker’s potassium level is high and that kidneys “don’t hurt” are brief explanatory messages. In the sense intended in this entry, “explanatory discourse” refers to health and risk messages motivated by a desire to teach or deepen understanding, rather than to provide evidence for a scientific claim or change attitudes and behavior (Martin, 1970; Rowan, 1988, 1995, 2003). A scholarly article published in an academic journal succeeds if it presents evidence for its core claim, evidence satisfactory to subject-matter experts (Kinneavy, 1971; Martin, 1970). In this telephone interaction, the nurse is not trying to establish a scientific claim to the satisfaction of expert reviewers but rather to deepen a specific patient’s understanding of her medical condition. The nurse’s account is accurate for Mrs. Baker’s situation, chronic kidney disease, but not for kidney ailments that are painful, such as infections or kidney stones.

Explanatory discourse is essential to health and risk communication. This message type is found in informal conversations (e.g., Kline, 2011), patient-provider interaction (e.g., Laidsaar-Powell, Bu, & McCaffery, 2014; Martin & DiMatteo, 2014; Thompson, 2000; Thompson, Parrott, & Nussbaum, 2011; Whaley, 2000), fact sheets, encyclopedia entries, social and traditional news, Internet teaching materials, textbooks, science centers, and entertainment (e.g., Bell, Lewenstein, Shouse, & Feder, 2009; Rowan, 1988, 2000, 2003). Explanations-as-teaching are generated by health-care professionals, patients, families, friends, journalists, and scriptwriters.

Academic and Professional Literatures Analyzing Health and Risk Explanations for Nonexperts

Because of the importance and frequency of explanatory or “teaching” messages, research on the nature, types, and effectiveness of these messages is found in many fields. In medical literatures, work may be found on the many explanatory challenges specific to a specialty area such as explaining illness to children or with the elderly (e.g., Whaley, 2000a; Wolf, Gazmararian, & Baker, 2005). Research on effective explaining is available in health psychology (e.g., Martin & Dimatteo, 2014), health literacy (e.g., Doak, Doak, Friedell, & Meade, 1998; Friedman & Hoffman-Goetz, 2006), and health communication (Thompson, 2000; Thompson, Parrott, & Nussbaum, 2011; Whaley, 2000). Relevant work on explanation-as-teaching is also available in instructional design (Merrill & Tennyson, 1977; Tennyson, Dijkstra, & Schott, 1997), science and psychology education (Hewson & Hewson, 1983, 1984; Kawalski, & Taylor, 2009; Mayer, 1983), informal science education (Bell et al., 2009), and linguistics (Halliday & Martin, 2003; Zacadoolas, Pleasant, & Greer, 2009). Additionally, there is practical wisdom on explanatory journalism in texts on health and science reporting (e.g., Blum, Knudson, & Henig, 2006), as well as curricula on effective health communication skills for clinicians (e.g., Kurtz, Silverman, Benson, & Draper, 2003; Schirmer et al., 2005).

Unfortunately, there are reasons why explanatory communication may not be well understood.

Scholarship on Health Explanation Designed to Teach

Scholarly analyses of effective communication in public life date to at least the 4th century bce (e.g., Aristotle, 1954/350 bce), but most researchers analyze messages designed principally to persuade, that is, to change attitude and behavior, not mainly to deepen understanding of some topic. Some argue that distinguishing persuasive messages from informative or explanatory messages is a distinction without a difference (e.g., Berlo, 1960; Lum, Parvanta, Maibach, Arkin, & Nelson, 2002). These scholars note that a single message may be motivated by multiple goals, such as both teaching and encouraging agreement. However, some messages are principally designed to deepen understanding or teach, without having an additional goal of gaining agreement. A surgeon may talk with a patient contemplating elective surgery about the benefits and limitations of partial versus full knee replacement. The surgeon may tell the patient that the choice of partial or full is his to make, assuming surgery does not reveal a clear case that full replacement is mandatory. In this case, the surgeon’s goal is to assist the patient in making a decision, not necessarily to gain agreement that one option is better than the other. Distinguishing explaining-as-teaching from persuasion is especially important given that high-quality health care does not assume patients must or will passively accept health-care professionals’ recommendations but rather casts health communication as a process of shared or collaborative decision making (Charles, Gafni, & Whelan, 1997; O’Connor, Légaré, & Stacey, 2003; Politi & Street, 2011; Thompson et al., 2011a).

Still another reason to study types of explanatory health communication is that contemporary health communication is increasingly focused on management of chronic rather than acute illnesses and conditions (e.g., Yach, Hawkes, Gould, & Hofman, 2004). Since ongoing conditions such as hypertension, diabetes, chronic kidney disease, cancers, arthritis, and recovery from stroke are handled by teams of patients, families, and health professionals, both at home and within health-care facilities, there is a continual need for awareness of procedures (e.g., following knee replacement, does the patient descend stairs on the “good” leg or the “bad” one?) as well as explanation-as-teaching (why do you ascend on the “good” and descend on the “bad” leg?). Therefore, given the importance and frequency of this message function, it’s important to analyze myths associated with it.

Myths

Myth 1: Effective Explanation-as-Teaching Is Solely a Matter of Organization

In the 1700s, George Campbell offered an analysis of “expository” speech and writing where organizational strategies such as narration, chronology, and spatial order were cast as natural processes through which the mind reasons (Campbell, 1988/1776). Campbell’s analysis, and that of others who followed his approach, still guides many contemporary composition and public speaking textbook chapters devoted to “expository writing” or informative speaking (e.g., Connors, 1981; Rowan, 1995). That is, many textbooks imply that there is little strategy in explaining except for selecting an organizational format for one’s speech or essay. The problem here is that in everyday life people do not think about explaining mainly as an organizational challenge. Whaley (2000a) describes a 5-year-old girl who was told her knee was “inflamed,” a message that caused her to worry that her entire leg would soon be on fire (p. 200). Whaley’s chapter summarizes child development research that says young children are often unaware that words can have multiple meanings. Someone trying to explain to this child that, no, her leg is not going to go up in flames, would not conceptualize his or her challenge as a problem of putting sentences into chronological or spatial order. Instead, the challenge in that explanatory context would be to determine and address the reason for the child’s confusion, and to alleviate her distress. The strategy underlying explanatory discourse involves identifying and overcoming likely confusions, not selecting organizational frameworks.

Myth 2: Effective Explanation-as-Teaching Is Solely a Matter of Word Choice

Another view suggests that use of simple, familiar, short words and conversational language will inevitably enhance the understandability of any message. Certainly efforts to use accessible language are helpful in explanation-as-teaching. Keller and associates (2014) describe practices that assist low health literacy audiences, and prominent among them is the use of accessible language. Parrott (1995) identifies text features that encourage audiences to pay attention to health messages. However, research suggests that there are multiple ways in which wording affects the accessibility of explanations-as-teaching. For example, Halliday and Martin (2003) argue that it is the density of noun strings (i.e., multiple nouns used to name a newly studied entity, such as glass crack growth rate), along with syntactic choices such as passive voice, that can make scientific writing difficult to comprehend. A single key term, well explained, is unlikely to harm a passage’s accessibility (see also Davison, 1984; Shuy & Larkin, 1978).

Scholars have studied the impact of word choice, sentence structure, layout, white space, and graphics on the accessibility of health and risk communications (e.g., Davis, Williams, Branch, & Green, 2000; Zarcadoolas et al., 2009). The U. S. government’s Plain Language initiatives are informed by these efforts (e.g., Clinton, 1998). While efforts to simplify wording are generally helpful in explaining complexities, it is important to note that hard-to-interpret words are only one of several possible sources of confusion for audiences. Audiences may struggle to visualize a complex structure, like a larynx, or fail to understand why those who do not have a family history of cancer may still be susceptible to it. Plain or simple language may not address these sources of confusion.

Myth 3: There Is a Direct Connection Between Message Comprehension and Attitude Change Concerning Health and Risk

A third reason why explanation-as-teaching may not get the theoretical and empirical analysis this communication goal deserves is that there is a sense that this approach has already been tried and found deficient. In the early days of empirical study concerning attitude change, this research was guided by learning theory (e.g., Hovland, Janis, & Kelley, 1953; Suls & Bruchman, 2014). For Hovland and colleagues (1953), the success of a persuasive appeal rested on the extent to which a message received attention, comprehension, acceptance, and storage in memory. Additionally, research on health communication began as the study of health education, not the more-encompassing phenomenon, health communication (Thompson et al., 2011a). But as Suls and Bruchman (2014) note, the relationship between comprehension of a message and attitude change is complex. There are many reasons why, for example, physicians and patients may disagree about changing the dosage on a medication. Further, when a scientific topic such as vaccination is politicized, scholars such as Kahan (2012) have shown that individuals may be able to state the views expressed in a health message accurately—such as the benefits of vaccination for children—without endorsing the recommended view or getting their children vaccinated.

Myth 4: Explanation-as-Teaching Is an Inevitable Component of Persuasive Messaging Addressing Health Threats

In many models of health and risk perception, such as Witte’s Extended Parallel Process model (1992; Witte & Allen, 2000), there are several steps where an explanatory message might be included. However, models like Witte’s do not include steps that say “explain why the threat or harm occurs” or “explain the research that shows why and how the treatment works.” Instead, Witte’s model says that people are more apt to address a health threat if they are exposed to messages that establish a threat is (a) severe, (b) likely to harm them, and (c) effectively addressed with the recommended response. Additionally, Witte’s model says that an effective response establishes that those being asked to enact some response, such as taking a medication regularly, are capable of doing so, which is called an appeal to their self-efficacy. Such messages may explain the science underlying these messages and deepen audiences’ understanding of a disease or treatment, but, again, such steps are not explicitly stated in the model. Nevertheless, research has established that exposure to explanatory messages is associated with enhanced problem solving capacity (e.g., Mayer, 1983, 1992; Mautone & Mayer, 2001; Mayer & Anderson, 1992; Mayer, Bove, Bryman, Mars, & Tapangco, 1996) and that those with low health literacy are hampered in their capacity for health decision making (e.g., Davis et al., 2000). Therefore, it seems reasonable to devote attention to explanatory messaging.

Types of Health and Risk Explanations

Frequent Questions Approach

First, some study explanation-as-teaching by identifying frequently asked questions and effective responses. Billings-Gagliardi, Mazor, and Belanger (2001) follow this approach when examining medical students’ responses to a hypothetical patient with Bell’s palsy. Bell’s palsy causes a weakening in facial muscles, which makes half the face appear to droop. The cause of this condition is not known, but it may be inflammation of a facial nerve or reaction to a viral infection (Mayo Clinic, n.d.). In the scenario tested, the patient had not recovered motor function in his face. He wanted to understand what was happening in his nerve, why his recovery was slow, and how his condition might improve (Billings-Gagliardi et al., 2001, p. S39). A group of lay readers was asked to evaluate medical students’ responses to this patient. The readers rated more highly those explanations that provided information about the disease, this patient’s prognosis, and his likely course of recovery, as well as emotionally supportive messaging, than they did messages that failed to pursue these goals or did not offer these types of information.

Clinician-Patient Interaction Approach

A second approach is to view clinician-patient interaction as the principal context in which explanatory efforts occur and to classify each of the explanation types needed for that context. For example, Keller and colleagues (2014) describe four types of information elicitation and explanation frequent in a physician office visit. They are (a) questions clinicians ask about barriers to enacting the recommended treatment in the past; (b) questions the clinician asks to establish nature and severity of disease state (e.g., “How does your shortness of breath keep you from doing things you want to do?”); (c) explanation of the diagnosis (“When fluid collects in your body, your legs can get swollen . . . you feel more short of breath . . . Your water pill (i.e., diuretic) helps to get rid of the excess fluid and can help you feel better”); and (d) explanation of treatment (“Take your water pill two times a day so you can feel better. If you are going to be out in the afternoon, it’s okay to take the water pill when you get home so you can be near the bathroom”; Keller et al., 2014, p. 26). Thompson (2000) notes that physicians may underestimate patients’ desires for information.

The strength of these approaches is that they provide in-depth accounts of explanations on particular topics and of a key context: interaction with physicians during an office visit. A limitation, however, is that health communication occurs in a wide array of settings, the office visit being only one. Therefore, another approach is to identify the principal goals pursued when people teach about health and risk concerns. This approach also identifies obstacles to deepening understanding of complexities and evidence-based approaches for overcoming these obstacles. Rowan presents this approach in a series of papers (e.g., Rowan, 1988, 1990, 1991, 1995, 2000, 2003; Rowan, Sparks, Pecchioni, & Villagran, 2003).

Strategic Approach to Categorizing Health and Risk Explanations

Kinneavy (1971) categorizes all discourse into four fundamental and inferable strategic goals. These are self-expression, persuasion, entertainment, and “reference.” Kinneavy says that reference discourse is chiefly designed to represent some aspect of reality to some audience. Following Kinneavy, Rowan (1988, 2003) identifies several types of reference communication. There is scholarly discourse, which offers evidence that a scholarly finding is illuminating (i.e., explanation-as-proof); informatory discourse, which creates awareness of new information about a topic already understood (e.g., instructions on how frequently to take a prescribed medication); and explanatory discourse, which deepens understanding of topics about which audiences have some awareness but lack deep understanding or have misunderstood (e.g., why something labeled “natural” can count as a medicine; why taking “water pills” makes one less likely to be short of breath; or how the rare disease, amyloidosis, differs from cancer, despite both often being treated with chemotherapy). This entry describes one type of informatory discourse, instruction giving, and three types of explanatory discourse.

Instruction Giving

Farkas (1999) developed a model of effective “procedural discourse” or instruction. In his model, procedural discourse involves four “system states” (p. 42). They are the following:

  • “Desired state. The goal that is presented to the user.

  • Prerequisite state. The state that is a condition for moving toward the desired state. This is often specified at the beginning of the procedure so that the user can align his or her current state with the prerequisite state.

  • Interim states. States we enter as we move toward our goal. These are milestones and sub-goals. We create or reach these states through our actions.

  • Unwanted states. States we wish to avoid. These stem from errors, system malfunctions, and conflicts with interrelated systems” (Farkas, 1999, pp. 42–43).

Drawing from Farkas (1999), one can examine “streamlined” instructions offered in medical contexts. For example, a hospital sent a surgical patient home after knee replacement with a folder containing 11 pages of instructions. Most pages were cast as bullet points or skimmable reminders about what medications to take and when to take them, as well as discussion of what counts as overdependence on narcotics for pain. The text below provides lines of instruction regarding wound care.

“Incision care

  • Remove the Ace wrap and dressing 2 days after surgery, then do daily dressing changes.

  • Check the incision daily for redness, tenderness or drainage.

  • Don’t be alarmed if there is some bruising, slight swelling of the knee or a small amount of blood on the bandage” (INOVA Health System, 2016).

This set of instructions is a type Farkas names “streamlined” texts, which are designed to be skimmed. These brief bullet points assume some understanding of surgical wound dressing and provide highlights of steps about which one should be aware. Importantly, the surgeon’s office puts a request in bold at the bottom of these instructions alerting patients to “Notify Dr. [name] for any increased bleeding, redness, drainage, swelling, worsening pain, calf pain or swelling, or any other concerning symptoms.” Clearly, these are “unwanted states” requiring quick action.

As Farkas notes, streamlined instructions are ineffective in contexts where users have many decisions to make or must be taught to recognize a variety of interim states before taking a key step. Even with the surgeon’s recommendation to contact his office if any condition is worrisome, a surgery patient and her caregivers may wonder, when given these instructions, what constitutes “increased bleeding” or what sorts of “dressing changes” are needed?

Rather than “streamlined” text, another approach to instructions is to use a “text rich” version (Farkas, 1999). Farkas says that instructions for treatment for frostbitten skin should not be provided in a streamlined format because users may need assistance in making many decisions. They must know how to identify skin that is frostbitten, how frostbitten skin will look in individuals with differing skin colors, how to treat the patient as the skin moves from a frozen state to a thawing state, and what important missteps to avoid that could cause undue pain or injury to the patient.

Clearly, a challenge in instruction giving is determining whether to use streamlined text or text rich instruction. Usability testing with sample audiences could answer these questions (e.g., MacFarlane, Sim, & Horton, 2005; Rubin, 1994). Research with low health literacy audiences shows that instructions are helpful on how to, for example, count pills, especially when large numbers of pills must be taken at differing times of the day. In one instance, a nurse sat with a patient and her caregiver for an hour teaching them to put 20 daily medications in the slots of a plastic pill box labeled for major times of the day (morning, noon, afternoon, evening). This sort of one-on-one instruction giving using a pill box is likely to increase the chances that patients and their loved ones follow instructions precisely (e.g., Keller et al., 2014). Another helpful step is to convert the dosages that appear on prescription labels in milligrams into numbers of whole and half pills.

Explanatory Discourse

Instructions assume one understands a phenomenon (e.g., medication and its purpose) but would like specific information about the types of medications to take or when to take them. In contrast, explanatory communication assumes some awareness of a topic, but addresses the need for deeper understanding (Martin, 1970; Rowan, 1988, 2003). Instances of explanatory discourse include paper-and-pencil drawings by surgeons to help patients visualize body parts and surgical procedures, fact sheets explaining why chronic kidney disease can be fatal, games teaching forensic science to lay audiences, or news features discussing common misconceptions about mental illness. Explanatory discourse includes oral, written, interactive, and graphic efforts aimed at teaching nonexperts about the physical and social world.

According to Rowan (1988, 1991, 1995, 2003), there are many reasons why subject matter may be difficult to understand, but research has identified three principal ones. These are difficulties in (a) distinguishing essential from associated meanings of key terms (e.g., what counts as medicine; the difference between low vision and blindness); (b) difficulties in visualizing complex, unseen, or unfamiliar phenomena (e.g., the periodic table of elements; how hearing works); and (c) obstacles in understanding ideas that seem counterintuitive to lay audiences such as the fact that one may be ill without feeling bad, or that natural foods such as potatoes contain naturally present pesticides (National Research Council, 1996).

Elucidating Explanations

Elucidating explanations are designed to help people understand the meaning and use of a key term. The name “elucidating” is used because this sort of discourse clarifies meanings. Frequently, when people clarify a confusing term, they do so by offering a substituted word or phrase, by giving an example, or by defining the term (Yule, 1997, pp. 80–81). Research shows that good elucidating explanations contain four steps. They offer (a) a definition that lists each of the concept’s essential features, often noting what the concept does not mean as well as what it does; (b) an array of varied examples indicating several ways a concept can be used; (c) a discussion of false examples and why they are false; and (d) opportunities to practice distinguishing examples from false examples (Merrill & Tennyson, 1977; Rowan, 1988, 1991, 2003; Tennyson et al., 1997; Tennyson & Cocchiarella, 1986).

The National Eye Institute offers a video on its website explaining “low vision.” The video script enacts several steps in a good elucidating explanation:

State key features of the concept’s meaning or definition: “Millions of Americans have low vision and cannot correct their vision with glasses, contacts, or surgery.”

Illustrate with a range of examples, rather than a single example: “Low vision can result from a variety of conditions. Age-related macular degeneration accounts for almost 45% of all cases. Many people with cataracts, glaucoma, or diabetic retinopathy, also have low vision.”

Discuss a false example or an erroneously inferred key feature of meaning and explain why it is false: “Mark Williams, OD, and specialist in low vision: “In the past, low vision was defined as vision 20/70 or less.”

Clarify essential meaning by noting what a concept does not mean as well as what it does: “The definition now is vision loss not corrected by glasses or contact lenses that affects a person’s functional abilities. So it’s not about a number now. It’s about reduced vision that’s affecting the quality of life of the individual and their functional abilities.”

(NEI, n.d.)

The NEI video begins by noting one aspect of the “essential meaning” for the term “low vision”: neither glasses, nor contacts, nor surgery can correct it. The specialist says this condition affects a person’s “functional abilities” and reduces quality of life. As Dr. Roxanne Parrott, who suffers from low vision, explains, “I cannot drive, and I require accommodations to do my work. I hate stairs painted or carpeted all one color. Movie theaters might as well be black holes” (Parrott, personal communication, 2016). Two steps that may make the video’s explanation even more clear would be an explicit discussion of the differences between low vision and blindness (an individual with low vision has more capacity for vision than someone with blindness) and an opportunity for learners to state this explanation themselves and share it with associates. Research from several fields shows that when learners explain concepts to themselves or to one another, they are more likely to master meanings than when this experience does not occur (e.g., Bell et al., 2009; Merrill & Tennyson, 1977). Consistent with this finding, health-care professionals are encouraged to use a method called “teach back” to verify patient understanding of complexities (e.g., Keller et al., 2014). To teach back, a physician might say, “I have just shared a lot of new information and want to make sure I explained things clearly. Can you tell me [how you might explain what I just said to a family member]?” (p. 30).

Elucidating explanations are especially important when it is difficult to interpret the way a familiar word is intended or understand the full range of its application. At medical appointments, clinicians often ask patients what medications they are taking. While this question sounds simple, what counts as medicine in such a context may not be obvious. Here is explanatory material available from the National Institute of Aging explaining what “medicine” includes:

“Medicine, often referred to as drugs, can be:

  • Prescriptions. What you can get only with a doctor’s order (for example, pills to lower your cholesterol or an asthma inhaler).

  • Over-the-counter pills, liquids, or creams. What you can buy without a prescription (for example, pills for headaches or chew tablets for heartburn).

  • Vitamins, eye drops, or dietary supplements” (NIA/NIH, n.d.).

One strength of this explanatory text is the range of examples provided. One may not automatically assume that medicine not delivered in pill form (e.g., asthma inhalers, creams, eye drops) counts as medicine. Further, the passage uses bullet points to highlight two types of entities that should be reported: prescriptions and over-the-counter items. For some reason, though, there are three bullet points.

A limitation to this explanation is that it does not define medicine. It does not indicate the common quality or qualities shared by each entity listed. It may be that medicine is any substance taken principally to relieve disease or symptoms, not mainly for nourishment or recreation. On the other hand, coffee and caffeine might be taken to relieve symptoms. Should coffee be reported as a medicine? The fact that there is no definition of medicine offered in this passage weakens its effectiveness. Further, discussion of a clear false example, perhaps scrambled eggs, might make what counts as medicine more clear—medicines are substances taken principally to address disease or symptoms, not principally to nourish the body, as scrambled eggs are, nor principally for recreation or abuse. Knowing the features of elucidating explanations can guide patients and clinicians in improving their explanatory efforts.

Quasi-Scientific Explanations

Quasi-scientific explanations are so named because, like scientific explanations, they offer an illuminating, often simplified, visualization or model of some structure or process. The difference is that quasi-scientific explanations use these visualizations to teach science rather than to provide evidence for scientific claims (e.g., Rowan, 1988, 2003). A quasi-scientific explanation, or effective visualization, is needed when the key source of confusion facing nonexperts is not unfamiliar words but rather the complexity of some structure or process. Research by Mayer and associates has shown verbal and visual signaling helps audiences understand key points and their relationships (e.g., Mautone & Mayer, 2001; Mayer, 1983, 1992; Mayer & Anderson, 1992; Mayer, Bove, Bryman, Mars, & Tapangco, 1996). Verbal signaling includes previews (“There are three types of hearing loss”), titles, headings, analogies, captions, and connectives such as first, second, third, if, and because. Graphic signals include diagrams, cartoons, conceptual models, decision trees, animations, and white space (Mayer, 1989).

People need to visualize the links between symptoms and treatments. The National Safety Foundation’s Ask Me 3 campaign says patients and health-care professionals should be asking one another three main questions. They are the following:

  1. 1. “What is my main problem?

  2. 2. What do I need to do?

  3. 3. Why is it important to do this?” (Keller et al., 2014, p. 30)

As Keller and associates (2014) note, encouraging both patients and clinicians to ask these questions can enhance the quality of health care by deepening patients’ involvement and understanding.

To analyze a written quasi-scientific explanation, consider the brochure Smith and colleagues (2007) developed to persuade lawn care workers and farmers to wear hearing protection. The brochure contains several explanatory passages. Here is one:

Hearing loss can occur from a single loud, explosive noise or from prolonged daily exposure to noise . . . The recommended response to stop hearing loss is to fix the noise source. If this is not practical, then you need to use earplugs or ear muffs whenever . . . you have to shout to be heard.

(Smith et al., 2007, figure 2)

Smith and her colleagues established that this brochure was effective in several important ways. It increased lawn care workers’ and farmers’ perceptions that (a) they were at risk for hearing loss when operating heavy machinery, (b) wearing hearing protection would reduce this risk, and (c) they were capable of using this protection. It would be interesting to see if additional explanatory material would deepen audiences’ understanding of why they are at risk for hearing loss and perhaps enhance their ability to solve problems related to hearing protection, problems such as knowing in what situations they are at risk. Here is an analogy explaining hearing loss that could be added to the brochure:

Most hearing loss results from damage to hair cells [inside the inner ear]. [These cells] have been likened to shag carpet fibers. Walk around on them and they will spring back with a quick vacuuming. But leave a heavy piece of furniture on them for a long time and they may never rebound.

(Myers, 2012, p. 140)

Myers’s analogy, which appears in a psychology text, may help lay readers develop a mental model of how human hearing works and can be damaged. Analogies work by linking familiar knowledge (how carpet looks when trod upon or when heavy furniture rests on it) with new knowledge (how hearing works and can be damaged).

To test the power of analogy-based quasi-scientific explanations for deepening understanding of complexities, one might assess the effectiveness of several analogies and captioned diagrams. Research published in the journal Nature offers another powerful analogy. Scientists x-rayed the protein structure of the “tips” on the ends of hair cells or cilia. These “hair cells” transform mechanical stimuli into electrical signals, crucial for human hearing. For human hearing to work properly, these researchers found that there must be a “firm molecular handshake between two proteins critical for hearing and balance” (Centrum Hearing, n.d.; Sotomayor, Weihofen, Gaudet, & Corey, 2012). This molecular handshake or, more precisely, this “force-conveying bond” is “strong enough to withstand normal sound, but the connection is likely the first to break under loud noises” (Centrum Audiology, n.d.). The molecular handshake analogy and a diagram of how loud noise can break this “handshake” might be one of several quasi-scientific explanations to assess.

Envisioning Numerical Risk

Research has identified steps that support lay persons in making connections between numerical information and health. First, pictographs (graphics such as those seen on “do not walk” street signs) are helpful in many contexts. One study assessed the effectiveness of a pictograph indicating when to take medicine (one hour before eating) with low health literacy patients (Barros et al., 2014). Second, diagrams are more effective than line or bar graphs in helping lay audiences to consider probabilities. A “wall of balls” diagram is used in the public summary of a National Academy of Science consensus report on risk of cancer from exposure to low levels of ionizing radiation (see Figure 1). Ionizing radiation comes from the cosmos, Earth, and from humanly developed sources such as x rays. The diagram presents a set of circles in several rows. Its caption says this:

In a lifetime, approximately 42 (solid circles) of 100 people will be diagnosed with cancer. Calculations in this report (Monson et al., 2006) suggest that approximately one cancer (star) per 100 people could result from a single exposure to 0.1 Sv of low LET radiation above background [i.e., above the ionizing radiation normally received from the cosmos, the Earth, and other natural sources].

(Monson et al., 2006, p. 7)

Types of Explanations in Health and Risk MessagingClick to view larger

Figure 1. Risk of cancer occurring because of exposure to low levels of ionizing radiation

(Source: Monson et al., 2006). Available at http://www.nap.edu/read/11340/chapter/2.

The “wall of balls” diagram plus its caption may be more clearly understood than an account that said simply that the risk of cancer from exposure to low levels of ionizing radiation exists, but is slight.

A third finding about assisting lay audiences with envisioning numerical risk is that often such risks are presented in a way that makes it hard to judge their relevance. For example, organizations may say females have a “1 in 1,000” chance of dying from disease x.” This sort of sentence does not make the implications of the risk clear to those most affected. To make these implications more clear, Woloshin, Schwartz, and Welch (2002) designed health risk “decision aids.” For example, they asked U.S. women who never smoked to imagine 1,000 women like them. Then, on large charts or decision aids, they list ages and likely deaths in each age range over 10 years for nonsmoking women from each chronic disease. Here is an illustration:

Age

Vascular Disease

Lung Cancer

Breast Cancer

45

3

1

4

65

40

7

9

85

307

8

12

This chart helps users see that vascular disease (heart attack, stroke) is a health risk as one ages, a fate more likely than that of lung or breast cancer, on average, for nonsmoking females.

Transformative Explanations

The third type of explanation is called transformative. Transformative explanations help audiences understand ideas difficult to comprehend because they are counterintuitive (Rowan, 1988, 1991, 2003). That is, some scientific notions can be expressed with simple words and involve structures or processes that are easy to envision, but they are still profoundly difficult to understand. For instance, people struggle to understand why they get cancer if there is no family history of cancer, why colds are not caused by cold weather, or how it could be that humans routinely emit radiation from their bodies In these cases, powerful lay theories are the principal source of confusion—not unfamiliar words or complex structures and processes. People have their own theories—often implicit or unstated notions—that say cancer occurs only when this disease “runs” in the family, that colds are associated with cold weather, and that radiation is something humans engineer or are exposed to, not something emitted by natural bodily processes (for more lay theories, see, e.g., Burgoon & Hall, 1994; Parrott et al., 2004; Sharf, Stelljes, & Gordon, 2005; Whaley, 2000a). Research in science education shows that, like scientists, people are reluctant to give up their tacit theories until given good reasons to do so (Anderson & Smith, 1984; Hewson & Hewson, 1983, 1984; Hughes, Lyddy, & Lambe, 2013; Kawalski & Taylor, 2009; Richards, 1996). Consequently, to help audiences recognize, test, and overcome lay theories, one can use a form of text called transformative explanation.

The Four Essential Features of Effective Transformative Explanations

Given the obdurateness of lay notions, and the extent to which they are often apparently supported by daily experiences and everyday language, communicators should take certain steps to overcome them. Effective explanations of counterintuitive ideas surprise audiences by helping them see that they have a lay theory and then causing them to become dissatisfied with it, before they consider the more-accepted account. Good transformative explanations treat audiences like scientists: Scientists do not give up their theories until they receive compelling reasons to do so. Similarly, people do not give up lay notions simply because someone says they are wrong. Good transformative explanations help audiences overcome lay theories when they (a) state the lay theory; (b) acknowledge its apparent merit; (c) create dissatisfaction with it, and (d) show how a more orthodox notion better explains the phenomenon in question (Anderson & Smith, 1984; Hewson & Hewson, 1983, 1984; Rowan, 1988, 1991, 2003; Shymansky & Kyle, 1988).

Here is text illustrating the features of a transformative explanation. This example was created to provide an extended account of the nurse’s brief explanation that began this entry, the explanation for why Mrs. Baker needed to get to the hospital.

State the lay theory and acknowledge its apparent plausibility: Mrs. Baker, it’s normal to assume that if you feel well, there is no reason to go to the hospital.

Create dissatisfaction with the lay view: You were hospitalized a few weeks ago. Part of your diagnosis while hospitalized was chronic kidney disease. You probably remember that when kidneys lose their capacity to filter impurities from the blood, most patients do not experience symptoms. Potassium is one of the substances diseased kidneys do not filter properly. People need some potassium for good health, but not excessive amounts. An indication of the danger of excess potassium is that in executions, where death occurs by lethal injection, potassium chloride is used to stop the heart.

State the established science: According to Medline Plus, a service of the U.S. National Library of Medicine, there are often no symptoms with a high level of potassium. When symptoms do occur, they include “nausea, slow, weak, or irregular pulse, and sudden collapse, when the heartbeat gets too slow or even stops” (National Library of Medicine, n.d.). We don’t want you to collapse, or worse, from excess potassium. That’s why you need to get to the hospital.

In this transformative explanation, the patient’s lay view or belief that she does not need to go to the hospital is addressed and acknowledged first. Next, some information needs to be given that helps the lay person reflect on inadequacies in the lay view. In the text above, the patient is encouraged to remember that a form of potassium is used to stop the heart in executions and that eventual “collapse” is one symptom of excess potassium. Only after the lay theory is described and reflection about it is encouraged is the established science presented.

One context where transformative explanation can be found is that of science and health news. Good writers know that a compelling way to cast a feature story is to begin by reminding readers of a widespread assumption or lay theory, explore reasons why it persists, create dissatisfaction with it through evocation of experiences inconsistent with it or other surprising information, and then present sound science. In this excerpt from a story by Jane Brody of The New York Times, Brody begins by reminding readers of a lay theory about anemia, suggests why it developed and why anemia is underestimated, and then explains why anemia is a serious health problem, one that should not be underestimated:

State the lay theory: “Thanks to advertisements for the once-popular tonic Geritol, most people of a certain age know about ‘tired blood,’ a disorder more accurately called anemia, involving a shortage of healthy red blood cells to carry oxygen to body tissues . . .”

Explain the lay view’s inadequacy: “It is not really the blood of people with anemia that is ‘tired.’ Rather, it is anemic people themselves who commonly experience chronic fatigue. Other symptoms may include weakness, shortness of breath, impaired athletic performance, rapid heartbeat, irritability, apathy, dizziness, pale skin, headache and numb or cold hands and feet.”

Acknowledge understandability of lay view and reasons for lack of attention to problem: “But in many people the symptoms are too mild to be recognized, and the anemia goes undetected for years. Anemia is the most common blood disorder in the United States. Statistics indicate that 3.4 million Americans are anemic, but experts say that this is a gross underestimate and that anemia has been viewed for far too long as an ‘innocent bystander,’ considered almost normal in certain groups, like menstruating women and the elderly.”

State the orthodox science: “A growing body of research indicates that anemia can seriously compromise the quality of a person’s life, make sick people sicker and even speed deaths, said Dr. Allen Nissenson, a nephrologist and professor of medicine at the University of California, Los Angeles. It is time to take anemia much more seriously, he added, making sure people have routine blood tests and are treated to restore healthy supplies of red blood cells” (Brody, 2003).

In this news story, Brody begins with the lay theory to connect with readers’ experiences. Only after she has refreshed their memories concerning commercials for “Geritol,” does she explain several reasons why anemia is often an undetected and underestimated problem. Consider how less effective Brody’s article would have been had she begun, “A growing body of research indicates that anemia can seriously compromise the quality of a person’s life.” That statement is hard to appreciate until one has considered that it is still common to believe anemia is a normal state among menstrating women and the elderly.

Conditions That Support Effective Health and Risk Explanation

Research from several fields identifies social conditions under which explanation-as-teaching is most apt to be effective. One of these fields is health literacy. As noted earlier, Keller and associates (2014) report that “Ask Me 3” initiatives encourage patients to ask questions and to expect to understand their symptoms and treatments. Importantly, too, when patients and clinicians have earned one another’s trust because of consistently respectful and conscientious interaction, they are better able to understand one another’s explanations (e.g., Laidsaar-Powell, 2014; Politi & Street, 2011, Thompson et al., 2011).

Informal science education is another field that characterizes social and emotional conditions in which people benefit from explanation-as-teaching. Scholars in this field (e.g., Bell et al., 2009) examine learning in contexts where people voluntarily seek scientific information. These contexts include watching television, exploring the Internet, visiting a science center, hiking, cooking, after-school programs, and so forth. In their National Academy of Science consensus report, Bell and associates (2009) find that people benefit when these environments (a) are emotionally engaging; (b) provide explanations but also give learners opportunites to explain key concepts, structures, or processes to one another; (c) teach something about the scientific method, not just results; (d) cast scientists as fallible, or capable of error, but as having procedures such as peer review for overcoming error; (e) encourage participants to be active, not passive, by asking questions, using tools, touching objects, or playing educational games; and (f) encourage participants to view themselves as people who like science, even as people who might contribute to science. More work should be done to integrate evidence-based best practices for explanation-as-teaching by exploring research on informal science education, as well as relevant work in instructional design, educational psychology, human factors, linguistics, rhetoric, science education, interpersonal communication, patient-physician interaction, and health communication. These fields and curricula in health communication for clinicians can inform one another (e.g., Kurtz et al., 2003; Schirmer et al., 2005).

Further Reading

Keller, D. B., Sarkar, U., & Schillinger, D. (2014). Health literacy and information exchange in medical settings. In L. R. Martin & M. R. DiMatteo (Eds.), The Oxford handbook of health communication, behavior change, and treatment adherence (pp. 23–37). New York: Oxford University Press.Find this resource:

Laidsaar-Powell, R., Bu, S., & McCaffery, K. J. (2014). Partnering with and involving patients. In L. R. Martin & M. R. DiMatteo (Eds.), The Oxford handbook of health communication, behavior change, and treatment adherence (pp. 84–108). New York: Oxford University Press.Find this resource:

Rowan, K. E. (1988). A contemporary theory of explanatory writing. Written Communication, 5, 23–56.Find this resource:

Rowan, K. E. (2000). Mass media explanations of illness: The problem-solving perspective. In B. B. Whaley (Ed.), Explaining illness: Theory, research, and applications (pp. 69–100). Mahwah, NJ: Lawrence Erlbaum Associates.Find this resource:

Rowan, K. E. (2003). Informing and explaining skills: Theory and research on informative communication. In J. O. Greene & B. R. Burleson (Eds.), The handbook of communication and social interaction skills (pp. 403–438). Mahwah, NJ: Lawrence Erlbaum Associates.Find this resource:

Rowan, K. E., Sparks, L., Pecchioni, L., & Villagran, M. (2003). The “CAUSE” model: A research-supported guide for physicians communicating cancer risk. Health Communication: Special Issue on Cancer Communication, 15, 239–252.Find this resource:

Thompson, T. L. (2000). The nature and language of illness explanations. In B. B. Whaley (Ed.), Explaining illness: Theory, research, and applications (pp. 3–39). Mahwah, NJ. Lawrence Erlbaum Associates.Find this resource:

Thompson, T. L., Parrott, R., & Nussbaum, J. F. (Eds.). (2011). The Routledge handbook of health communication (2d ed). New York: Routledge.Find this resource:

Thompson, T. L., Whaley, B. B., & Stone, A. (2011). Explaining illness: Issues concerning the co-construction of explication. In T. L. Thompson, R. Parrott, & J. F. Nussbaum (Eds.), The Routledge handbook of health communication (2d ed., pp. 293–305). New York: Routledge.Find this resource:

Whaley, B. B. (Ed.). (2000). Explaining illness: Theory, research, and applications. Mahwah, NJ. Lawrence Erlbaum Associates.Find this resource:

Zarcadoolas, C., Pleasant, A., & Greer, D. S. (2009). Advancing health literacy: A framework for understanding and action. San Francisco: Jossey-Bass.Find this resource:

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