CHAPTER 8
Translating a Professional Practice Model Into Everyday Practice: Adoption
KEY WORDS
Adoption, meaningful work, milestones, uptake
OBJECTIVES
By the end of this chapter, readers will be able to:
1. Describe the process of individual adoption of new behaviors
2. Analyze tipping points and milestones to adoption
3. Describe the relationship between the uptake of professional practice models (PPMs) and meaningful work
INDIVIDUAL ADOPTION OF PROFESSIONAL PRACTICE MODELS
Adoption of new behaviors is a complex process that takes into account individuals’ intention, decision to accept, and ultimately, alters their actions related to trying out or performing new ways of being or doing in a certain setting. Thus, the environment plays a key role in the process. Greenhalgh, Robert, MacFarlane, Bate, and Kyriakidou (2004) characterized the adoption process as a series of steps: preadoption (e.g., awareness of innovation), peri-adoption (e.g., continuous access to innovation information), and established adoption (e.g., adopters’ commitment to the adoption decision). Individual adoption, in the context of embracing new ways of practicing nursing, is analogous to the adoption-of-innovation (change) process that has been described by several theorists.
In this light, innovation is considered an “idea, practice or project that is perceived as new” (Rogers, 2003, p. 12) and that spreads (or diffuses) at different rates among individuals throughout an organization. Common to this notion is that adoption is a process that requires the acquisition of new knowledge, skills, and attitudes; the testing out of new ideas or behaviors in a specific context; comparing them to present practice; developing an attitude or intention toward the new behaviors; and finally, deciding whether or not to implement them (Clarke, 1996; Rogers, 1995; Wisdom, Chor, Hoagwood, & Horwitz, 2014). The various theoretical frameworks on individual adoption have different disciplinary origins (e.g., psychology, business, communication, sociology, etc.), are complementary, and add to the understanding of the adoption process; yet empirical research has not shown benefits of one over the other. Briefly, highlighted in the following text are several such frameworks from which to consider individual adoption of a professional practice model (PPM).
Prochaska and DiClemente’s (1983) transtheoretical model (aka stages of change model) evolved through studies of smokers who quit on their own. The model focuses on the decision making (or intentional change) of individuals and assumes that they change behavior, especially habitual behavior, continuously through a cyclical process. The transtheoretical model suggests that individuals move through six stages of change: precontemplation, contemplation, preparation, action, maintenance, and termination. For each stage of change, different intervention strategies are most effective at moving the person to the next stage and subsequently through the model to maintenance, the ideal stage of behavior. To progress through the stages of change, individuals apply cognitive, affective, and evaluative approaches that help them make and maintain the change.
Prochaska, DiClemente, and Norcross (1992) identified five characteristics of an innovation that influence adoption: its relative advantage, compatibility, complexity, “trialability,” and observability. Although this model has been used to explain health-related behavior change and encourages assessment of individuals’ stage of change, it does not address the social context in which change occurs or the time requirements needed for each stage.
The social cognitive theory (SCT), initiated as the social learning theory (SLT) in the 1960s (Bandura, 1969), speculates that learning occurs in a social context that is dynamic and that reciprocal interaction between the person and his or her environment influences behavior. The emphasis on social influence, including social reinforcement, reflects how individuals acquire and perform certain behaviors. The theory takes into account a person’s past experiences as an influencing factor that helps to explain how people regulate their behavior. This framework speaks to essential knowledge and skills required; modeling observed behavior; likely reinforcements that affect the continuance of the behavior; and expectations, or the anticipated consequences of a person’s behavior. Finally, self-efficacy, the level of a person’s confidence in his or her ability to successfully perform a behavior, is unique to the theory. Although this framework has been used by many in nursing, especially related to health-related behavior change (health promotion), it is loosely organized and based solely on the dynamic interplay among person, behavior, and environment. The theory also focuses heavily on processes of learning, disregarding other factors (such as biological or emotional) that may influence behaviors.
Rogers’s Diffusion of Innovation Theory (1962) is well known to leaders of organizational change, and can be easily applied in the context of integrating a PPM in a health system. In this framework, there are five stages of adoption: awareness, persuasion (attitude), decision making (accept/reject), implementation (trial), and confirmation (adoption). Understanding the target population and the factors influencing their rate of adoption facilitates new behaviors. For example, according to Rogers (2003), innovators easily embrace new ideas and are followed by early adopters and then the early majority, late majority, and finally, the laggards, who are the last to adopt. According to Rogers (2003), earlier adopters tend to have different characteristics compared with later adopters. These characteristics offer a means of identifying individuals who could then be targeted to influence and engage others who are less eager to change.
For example, an innovation champion is often an early adopter who displays a certain charisma that facilitates adoption of the innovation, even overcoming resistance to it by others (Rogers, 2003).
Leadership’s understanding of the characteristics of their employees generates a profile of potential champions that helps to identify those who can easily facilitate the adoption of new behaviors, in this case, the behaviors associated with operationalizing a professional practice model.
In a study of nurses using genetics in practice, early adopters had an overall interest in genetics, were familiar with certain genetic issues and resources, and felt a greater expectation from others to be “genetically literate” (Andrews, Tonkin, Lancastle, & Kirk, 2014). The authors concluded that knowing the characteristics of early adopters may facilitate adoption. Rogers’s theory has been used successfully in many fields, including communication, information technology, agriculture, public health, criminal justice, social work, and marketing. However, it was not created for the health care environment and it lacks attention to individuals’ resources or the social support necessary to adopt new behaviors. More research using the theory in the health care environment is warranted.
The theory of planned behavior (TPB; Ajzen, 1985) originated as the theory of reasoned action to predict an individual’s intention to engage in a behavior at a specific time and place (Ajzen, 1991). The theory explains behaviors over which individuals have the ability to exert self-control. The key concept of the model is behavioral intent, which is influenced by the likelihood that the behavior will have the expected outcome and the subjective evaluation of the risks and benefits of that outcome. The TPB states that behavioral achievement depends on both motivation (intention) and ability (behavioral control). The TPB is composed of six constructs that collectively represent a person’s actual control over the behavior. They are attitudes, behavioral intention, subjective norms, social norms, perceived power, and perceived behavioral control. The TPB has been used successfully to predict and explain a wide range of health behaviors and intentions, including smoking, drinking, health services utilization, breastfeeding, and substance use, among others. However, it assumes individual opportunities and resources, and it does not account for the environment, emotions, or past experiences that might influence behavioral intention.
Social network theory or social network analysis (SNA), derived from sociology, assumes that individuals, groups, or companies (nodes) are connected (linked) through relationships (Wasserman & Faust, 1994). All together, these various nodes (individuals) and links (connections) can be represented by a map or a network. Social networks emphasize the importance of peer-to-peer relationships in one system or explain how several companies interact with each other in a region. They help expose the channels of communication and information flow, collaborations, and disconnects among people and departments. The shape and size of social networks often influence their utility, providing explanations for behavior. For example, in systems with tighter networks, strong ties exist that encourage sharing of information and values, but limit creativity. In larger networks, nodes are more likely to present and embrace new ideas. The theory espouses that individual traits matter less than relationships between nodes in a network. SNA is most widely used in commercial organizations and only recently has been applied to health systems. In fact, in one systematic review, few studies could be found that used SNA (Chambers, Wilson, Thompson, & Harden, 2012); thus, its application in health care is limited.
Other change or transformation theories and translational models (such as the PARiHS [Promoting Action on Research Implementation in Health Services] framework; Kitson et al., 2008) can also help to describe the mechanisms whereby individuals, groups, and organizations adopt innovation. However, individual adoption is influenced by a number of interacting variables and much more empirical evidence is needed to better understand it.
Nonetheless, when reflecting on individual adoption from a leadership perspective, it is readily apparent that over time, individuals move from attitudes of indifference toward the new practice to increasingly more interest and ultimately to actively engaging with it, even, in some cases, trying to make it work better. At a system level, however, the adoption process is more complex and organizations, like individuals, can be classified as low, medium, or high adopters. Frambach and Schillewaert (2002) discussed two stages associated with system-level adoption: the organization’s decision to pursue adoption and the staff’s acceptance and initiation of their individual processes of accepting the innovation.
Because individual adoption occurs in the context of an organization, the interaction between individual and organizational factors most likely affects the rate and comprehensiveness of adoption. Thus, even if the individual is motivated, ready, and capable, if the organization itself presents barriers, adoption may not be the result.
It is particularly challenging to promote change in routine practice when the decision to adopt is complicated by organizational factors such as a long-standing culture, deficient resources, and ineffective leadership. However, some drivers of adoption (facilitators) have been identified that can move organizations from medium or low adopters to high adopters. For example, organizational resources, training, positive social networks, and evidence of efficacy have been shown to be positively associated with adoption (Greenhalgh et al., 2004; Oldenburg & Glanz, 2008). In fact, in a synthesis paper, Wisdom et al. (2014) compared constructs related to organizational adoption of innovation and found several factors that favored adoption: positive sociopolitical external influences; leadership support and experience; research infrastructure; resources; positive social interactions (climate); easy-to-use innovations that were viewed as better than current practice, cost-effective, adaptable to the organization, and evidence-based; employees’ positive attitudes toward change and other characteristics; frequent feedback; and system readiness for change. Contrarily, innovation adoption was limited in systems in which the innovation was perceived as complex, top-down hierarchical leadership situated in formal organizational structures was used, a poor climate persisted, innovation evidence was lacking, negative individual characteristics of employees persisted, lack of skills continued, and job tenure endured. Although this literature synthesis organized various frameworks, the relative lack of evidence available to clearly point out which factors facilitate system-level adoption was a major limitation.
TIPPING POINTS AND MILESTONES
Tipping Points
Over time, critical points in the evolving PPM integration lead to new and irreversible changes—these can be positive (manifested as progress) or negative (status quo). Often, it is a small detail, such as a certain nurse, or a particular unit, or a specified number of units, that get inspired by the model and can have the largest effect on the rest of the system. In Malcolm Gladwell’s book, The Tipping Point: How Little Things Can Make a Big Difference (Gladwell, 2002), he likens tipping points to epidemics. In other words, in epidemics one or a few individuals become infected with contagious organisms and then transmit them in certain environments. Epidemics, then, are a function of a few people who transmit the organism or disease itself, and the environment in which it is operating. When an epidemic tips, it is jolted out of equilibrium, because of a change in one or all three of these areas.
When applied to an innovation, for example, Gladwell’s law of a few (a tiny percentage of the people who do the most work), the stickiness factor (the degree to which a message [e.g., PPM] attaches and makes an impact), and the power of context (the situation or circumstances) strongly influences ongoing implementation and ultimate integration. Certain influential individuals whom Gladwell called the “mavens,” are the recognized experts on a subject. Their adoption of a new innovation could influence colleagues who know them to consider adopting that innovation as well, but, on their own, these mavens are often so focused on their small world of expert knowledge that they fail to make the innovation real. “Connectors” are those who spread the word of the innovation to the broader world, linking influential people and ideas to create the interest and curiosity that attract early adopters like honey. Finally, the “salesmen” take the ideas spread by the connectors and persuade their acquaintances to actually try out an innovation. Like Rogers’s (2003) Diffusion of Innovation Theory, Gladwell’s underlying model explains that an innovation spreads rapidly when the right combination of these factors is present.
Identifying early who these few key people are (mavens, connectors, and salesmen), harnessing their energy, and relying on their knowledge and resources facilitate adoption. In terms of the stickiness factor, relatively simple changes in the PPM diagram or the presentation and structuring of information about a PPM can make a big difference. For example, including essential components of the underlying theory in the PPM image; using the model to explain existing policies and procedures; and applying small, focused skills-acquisition forums to present the model can force the model to “stick,” pivoting (or tipping) the implementation toward advancement. Instead of a huge rollout, concentrating resources in a few key people and areas and helping to identify what is in it for the stakeholders, including how the change will impact their reality, may be more effective.
