Real-Time Development from Theory to Practice


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Simulation Modelling Practice and Theory

Development and implementation of data structures, algorithms and tools for model-checking, testing, performance analysis and synthesis for embedded systems focusing on real-time, probabilistic and hybrid aspects. Applications to communication protocols, control programs and planning and scheduling. Methodologies for specification, analysis and testing of embedded systems.

Modelling and analysis of industrial case studies. Component-based development of embedded and hybrid systems. Analysis and construction of services and protocols for computer networks, including grid computing, high-performance computing and software defined networks. Real-time and embedded operating systems. Developing efficient design and inference methods for graphical models; in particular, frameworks for representing and solving complex decision problems under uncertainty. Learning from data for knowledge discovery and design of intelligent systems. The focus is on the use of probabilistic and statistical methods, as well as the use of logic-based methods for modeling complex, structured data.

Center for Embedded Software Systems, CISS, aims at strengthening industrial competence, research and education within the area of embedded software systems. Particular attention will be given to products and devices whose individual components must typically be able to communicate and cooperate with other systems over networks. All involved research groups have significant experience with industrially collaboration on utilization and development of technology. Kim Guldstrand Larsen, Professor. Jiri Srba , Associate Professor. The Distributed, Embedded and Intelligent Systems unit is running regular seminars where both local speakers as well as external visitors give talks on a wide range of topics from the concurrency theory and practice.

The seminars are not only aimed at the local audience but also to any interested visitors from outside of the unit or the department. You can read about our usage of your data and how to block cookies in the AAU cookie policy. So while some analysts may characterize our professions and academic training systems as percolating with potential with a thousand blooming flowers, a sober analysis based in the realities of imperfect communication, information overload, and bounded rationality is more suggestive of systems where innovations rapidly blossom and die in an insidious redundant cycle without much accumulated system-level learning.

Much goes in, but little comes out. Ironically, Archie Cochrane contributed to this structural imbalance with publication of his influential monograph, Effectiveness and Efficiency. His was an eloquent and timely call for better evidence of intervention effect to improve the British National Health Service, an objective interpreted by his many followers to require rigorous study of intervention efficacy.

The subsequent focus on establishing the effects of new treatments, protocols, and programs meant that questions of how to spread the relatively few effective health services interventions were not the object of much study. The topic is one of increasing dedicated interest by social science researchers.

The present task is to clarify, albeit in brief form, diffusion of innovation concepts that have been used to affect rates of adoption of voluntary-choice interventions, along with those concepts that have not been the object of many tests but which I believe to be promising for intervention development. This challenge is not one of basic science, nor applied science, but of dissemination science. A worldwide science of dissemination is emerging, driven by new communication technologies, the interests of philanthropies and the needs of government agencies, and the persistent and growing applied problems that have been addressed but not solved by the dominant research paradigms in disciplines such as psychology, sociology, and political science.

Dissemination science is being shaped by researchers in the professional and applied fields of study, including public health, health services, communication, marketing, resource development, forestry and fisheries, education, criminal justice, and social work. Research about dissemination is a response to a general acknowledgment that successful, effective practices, programs, and policies resulting from clinical and community trials, demonstration projects, and community-based research as conducted by academicians very often do not affect the services that clinical staff, community service providers, and other practitioners fashion and provide to residents, clients, patients, and populations at risk.

In any one societal sector populated, for example, by food-based micro-entrepreneurs, or city-level transportation and parkway planners, or nursing home owners and staff , the state of the science what researchers collectively know and the state of the art what practitioners collectively do coexist more or less autonomously, each realm of activity having little effect on the other.

Dissemination science is the study of how evidence-based practices, programs, and policies can best be communicated to an interorganizational societal sector of potential adopters and implementers to produce effective results. This definition means that dissemination embeds the objectives of both external validity , the replication of positive effects across dissimilar settings and conditions, and scale-up , the replication of positive effects across similar settings and conditions Moffitt, A potential adopter is someone targeted for making a decision about whether to invest resources in an innovation.

An implementer is someone who will actually change his or her behavior to put an innovation into use. Often in complex organizations, the users are not the choosers of innovations. Implementers often subvert or contradict the intentions of adopters. Moreover, in complex organizations for the consideration of consequential innovations, adopters are usually higher than implementers in formal authority and thus not very accurate in knowing about the extent or quality of implementation or of the response by clients or constituents to what is implemented.

Thus for dissemination, unlike for diffusion in which broad-based adoption is the main dependent variable, the extent and quality of implementation and client or constituent responses to it become additional dependent variables of study just as important as adoption. Dissemination science merges the study and objectives of diffusion intervention with implementation intervention.

Many adopters are targeted, with implementation quality a key objective. It can be argued that dissemination science represents the most important type of diffusion study. It is a way of not forgetting our roots. Diffusion is the process through which an innovation is communicated through certain channels over-time among the members of a social system Rogers, For example, Barker reports on three international development efforts in relation to diffusion concepts. In Haiti, a United States Agency for International Development effort to conduct HIV prevention education in rural villages identified and recruited village voodoo practitioners, who are almost always considered credible and trusted sources of advice by Haiti villagers, to encourage villagers to participate in village meetings with USAID change agents.

In Nepal, where vitamin A deficiency contributes to very high rates of infant and maternal mortality, the innovation of kitchen gardens was diffused among households through neighbor social modeling, resulting in heightened knowledge, positive attitudes, increased vegetable and fruit growing and consumption, and improvements in vitamin A nutrition. In Mali in , a study of Malian youth evaluated their information-seeking behavior and perceptions of source credibility concerning reproductive health.

A lack of accurate knowledge among youth was attributed to their most trusted sources of information being friends and siblings; youth did not consider credible information sources including health agents and teachers to be accessible enough or trustworthy. Many studies have shown a predictable over-time pattern when an innovation spreads, the now familiar S-shaped cumulative adoption curve. The generalized cumulative curve that describes the curvilinear process of the diffusion of innovations.

When social work practitioners themselves are targeted for behavior change, such as to adopt new evidence-based interventions to in turn offer them to populations at risk, then they are potential adopters within a client system. Diffusion occurs through a combination of a the need for individuals to reduce personal uncertainty when presented with new information, and b the need for individuals to respond to their perceptions of what specific credible others are thinking and doing, and c to general felt social pressure to do as others have done.

Uncertainty in response to an innovation typically leads to a search for information and, if the potential adopter believes the innovation to be interesting and with the potential for benefits, a search for evaluative judgments of trusted and respected others informal opinion leaders. Needs or motivations differ among people according to their degree of innovativeness earliness in adoption: When all is said, the promise of the history of diffusion scholarship and diffusion practice is a promise of efficiency in intervention: Communicating an innovation to a special small subset of potential adopters so that they, in turn, will influence the vast majority of other potential adopters to attend to, consider, adopt, implement, and maintain the use of worthy innovations.

Diffusion paradigm concepts are not new. The French judge cum sociologist Gabriel Tarde explained diffusion as a societal-level phenomenon of social change in his book, The Laws of Imitation , including the identification of an S-shaped curve in cumulative adoptions over time and the importance of opinion leadership in promulgating that distribution. As a judge, Tarde had taken note of the way people coming before the bench used new slang and wore new clothing fashions as if on cue. In Germany at the same time, Georg Simmel, a political philosopher, was writing about how individual thought and action was structured by the set of interpersonal relations to which a person was subject.

The Web of Group Affiliations , was the forerunner for understanding how social network position affects what individuals do in reaction to innovations, and when. Together, these perspectives provided the micro-macro explanation for much about diffusion processes: How system-level effects pressured the individual to adopt new things; and how individuals, linked in social networks, contributed to and mostly resisted system change.

Following Tarde and Simmel, European anthropologists seized on diffusion theory as a means to explain the continental drift of people, ideas, means of social organization, and primitive technologies. American anthropologists also conducted historical studies but they confined their analyses to more discrete innovations in smaller social systems such as a community or a region of the country.

The dam broke in with publication of an article by Bryce Ryan and Neil C. This seminal article set the paradigm for many hundreds of future diffusion studies by emphasizing individuals as the locus of decision, adoption as the key dependent variable, the key role of a centralized change agency that employed change agents, and the importance of different communication channels for different purposes at different times in the individual innovation-decision process. The Ryan and Gross article propelled diffusion study to center stage among rural sociologists and made the practice of diffusion a primary toolbox in the day-to-day work of agricultural extension agents.

Distributed, Embedded and Intelligent Systems

Soon, many scholars in general sociology, medical sociology, organizational studies, education, journalism, communication, and public health began diffusion research. The hottest intellectual concept studied was innovativeness time of adoption relative to others and its correlates. These studies often focused on sociodemographics and beliefs, both abiding scholarly interests in larger sociology and marketing research paradigms. Unfortunately, this emphasis steered diffusion scholarship away from the study of interpersonal, group, and relational influence on adoption behavior.

This development became most clear in the fascination with innovativeness as a means to understand organization-level diffusion. Many management and organizational scholars conducted correlational studies of organizational innovativeness and a variety of organization-level characteristics size, market share, bureaucratic structure, industry type, centralization, etcetera , a paradigmatic burst of activity that contributed little to an understanding of diffusion of innovations across organizations.


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One positive development of this organization-level focus on adoption as a dependent variable of study was general agreement that adoption could mean very little given the political and social machinations inside organizations. Implementation, not the decision to adopt, was the more important process of study, and innovation and reinvention rather than innovativeness of the whole organization the more revealing research focus. Trained as a rural sociologist, Everett Rogers, too, conceptualized rural communities as the social systems of study Rogers grew up on an Iowa farm watching his father not adopt innovations, so trying to explain this regressive behavior and in turn perhaps helping to improve farming conditions among poverty-stricken farmers came naturally.

Rural sociologists focused on community-level phenomena, on interpersonal networks, and on the boundedness of such social systems. The reference groups of community members functioned as very effective filters and gatekeepers, what the prominent sociologist and early diffusion scholar Elihu Katz labeled interpersonal selectivity.

Emotional Intelligence: From Theory to Everyday Practice

If diffusion is about change and destruction and uncertainty, then interpersonal networks and opinion leaders were about stability, normative influence, and the measured appraisal of new ideas. Understanding the social dynamics of community-level systems was a main objective. To spread agricultural, public health, and educational innovations—and many innovations were a combination of the three—diffusion systems had to be put into place to interact with rural communities.

The s, s, and s were decades of huge growth in U. Thus the diffusion systems were centralized in both administrative control and substantive expertise. Knowledge flowed from this core to the periphery with the objective of lessening the problems of farmers, social workers, public health officers, and teachers. The main model for these systems was the agricultural Cooperative Extension Service that at the time was heralded for its international successes in crop production increases the so-called Green Revolution.

But the extension service model was expensive. There was not enough money to send change agents to regularly meet with all public health officers and teachers. The agricultural rural sociology lesson about finding and using opinion leaders to influence the decisions of their near-peers got lost at the same time that new information technologies promised so much.

So the classical diffusion paradigm found widespread application both among academicians interested in different types of innovations and among practitioners who perceived the paradigm as a means for spreading solutions to real-world problems, yet it was also changed as it was adapted from agriculture to public health and education and as more efficient dissemination possibilities arose.

Backlashes against these large investments, partly based in knowledge utilization studies showing little effect on the decisions of practitioners, focused on what seemed to be the advocacy of innovations that were the products of commercial firms. This broadcast model of diffusion was also put into place without attendant strategy on interpersonal influence, implementation support, or behavioral or organizational maintenance.

Application by government agencies of diffusion concepts was pursued on a large scale but usually only concerned one or two concepts. A notable exception has been the U. Cooperative Extension Service which has long applied multiple diffusion concepts in concert to affect change. For every commendable application of diffusion theory concepts that accurately operationalizes certain of the empirical results from the collective of diffusion research, there are many examples of the diffusion literature being operationalized in ways that a diffusion scholar might not recognize.

Both of these commendable efforts developed clear change models that the authors identify as being based in diffusion of innovation theory, yet they do not obviously use prior knowledge from diffusion research about why innovations spread in ways that reflect diffusion research results. Efforts such as these may suggest that there are more ways to affect change than is represented in the diffusion literature; they may also suggest the ease with which the translation of generalized lessons can result in misunderstanding and misapplication.

Based solely on my working with the diffusion literature and with organizations that seek to spread evidence-based practices, I list in Table 1 common ways in which what is done in practice can work against diffusion. Such strategic application need not only affect adoption rate; strategies can be differentially applied to segments of target adopters so that those persons or organizations that would typically adopt innovations late in a diffusion process become early adopters, thus working to close inequities and inequalities in a societal sector, bringing the have-nots closer to the haves see Figure 2.

The over-time process of diffusion can be accelerated by using validated concepts from the diffusion of innovation literature to heighten the likelihood that an innovation and messages about it will be positively perceived by potential adopters, and by identifying and recruiting influential potential adopters to help in communicating the innovation to other potential adopters. Disadvantaged population service providers who would typically be late adopters of an innovation can also be proactively targeted for early adoption of an innovation, thus addressing inequities within social systems.

Here, I discuss seven concepts based in the prior empirical results of diffusion and innovation research that have utility for social work intervention development. I do not review all the concepts from this literature with applicability to intervention development. The concept of innovativeness has, for example, contributed to the creation of many behavioral interventions that rely on stage models of readiness for change by tailoring messages to the time-dependent receptivity of potential adopters. Here, I focus on less-used concepts with high potential for affecting rates of diffusion.

An attribute is a perceived characteristic of an innovation. The other two attribute categories he distinguishes, observability and trialability , are not as consistently important across innovation types for producing adoption, though it is reasonable to assume that for high-risk, expensive, and obtrusive innovations, trialability should be especially important, while for complex innovations with many process steps and those innovations that embed high degrees of ambiguity or tacit knowledge in their operation, visibility of the innovation in process and observability of outcomes should be especially important.

Other diffusion researchers have identified similar attributes. Attribute categories can be applied in the design of interventions, for example, so that they are not too complex or too costly. They can also be used in the design of communication messages and images about interventions, so that viewers or readers will be more likely to perceive that one can readily see the results of using the intervention, or to communicate to readers that an intervention, while sophisticated, is not difficult to understand.

Attribute categories can be used as a basis for training demonstration hosts who will tour visitors around an intervention site so that they do not, for example, overly emphasize data about effectiveness while underplaying cost-effectiveness and the ease of implementing the intervention. Attribute categories can be used as a basis for structuring formative evaluation questionnaires to measure potential adopter perceptions about an intervention so that the intervention, and the materials describing it and portraying it, can be altered prior to introduction to heighten its likelihood of a positive reception.

Rather than communicating and advocating adoption of a single intervention, a change organization can group interventions together. A cluster is a logically-related set of interventions that are constructed either on the basis of the interventions being complementary to one another, or being logical alternatives to one another, and whose grouping increases adoption. Adopters may eventually select and implement all of the interventions in a complementary intervention cluster; in an alternative intervention cluster, they are unlikely to ever adopt more than one intervention except in cases of displacement.

Yet, for either type of cluster, choice should positively affect implementation quality. Adopters are more likely to select an intervention that is readily compatible with their organizational context and thus needs fewer adaptations of less magnitude to successfully implement. One decision begets another, and another. In effect, the first decision embeds a number of sunk costs that then make subsequent decisions about related interventions relatively easy.

Psychology reactance theory offers another rationale for why clustering innovations makes sense. Individuals cherish their ability and consider it a right to choose. When deprived of choice, they react negatively Brehm, ; Eagly and Chaiken, But in the construction of choice options or menus, the objective is the likely right amount of choice rather than unlimited selection. Having a delimited set of choices—a few logical alternatives—as a basis for decision making is cognitively appealing. Too many choices, and people often will not decide anything; not having a ready comparison similarly decreases the likelihood of making a selection Schwartz, The relationship between adoption and choice is curvilinear.

Nonprofit organizations and commercial businesses rely heavily on demonstrations. Yet, it is federal governments that have the most impressive histories of support for the demonstration of new technologies, programs, and practices, partly because what is demonstrated often represents radical new ways to conceive of providing a service that requires risks too large for single firms or single nonprofit organizations to assume.

Demonstrations of innovations exist for one of two reasons. A demonstration is either an experiment of a promising intervention, or a showcase of a proven intervention Myers, Being clear about demonstration purpose is important. An experimental demonstration is a field test carried out for the purpose of assessing the external validity of an intervention by varying the setting, the participants, resource availability, implementation protocol, or the methods by which outcomes are measured.

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The purpose of an experimental demonstration is data collection. Once this type of external validity an acceptable degree of innovation robustness has been established, a second type of demonstration is warranted. An exemplary demonstration is a persuasive event calculated to influence adoption decisions and thus increase the likelihood of diffusion. An exemplary demonstration is not staged for the purpose of merely disseminating information; rather, the objective is to showcase an intervention in a convincing manner Baer et al.

Exemplary demonstrations increase the likelihood of diffusion partly by making a costly, worrisome, and complex intervention more understandable through visibility of its processes and observability of its outcomes.

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A disconfirmed hypothesis that leads to a design improvement is a positive result in an experimental demonstration; in an exemplary demonstration, such an outcome is noise that will lead to perceptions of higher, not lower, uncertainty among potential adopters. A societal sector is a collection of focal organizations operating in the same domain without respect to proximity, as identified by the similarity of their services, products, or functions, together with those organizations that critically influence the performance of the focal organizations.

City social work agencies can be conceptualized as constituting a societal sector. I emphasize a targeting of societal sectors as the social systems for change because of the reach and organizational identification they make possible through professional associations that often tie them together, job mobility that often leads to people across organizations knowing one another, and common attendance at professional conferences.

For intervention purposes, this means that common messages can be developed and communicated with desired effect among organizational representatives. All these factors contribute to the creation and maintenance of dense social networks. Where a social network exists, an intervention developer or change organization can learn of it and tap into it. These efficiencies, together with the related concept of opinion leadership, are at the heart of applying diffusion of innovation concepts for the spread of effective social work innovations. Sometimes the types of organizational employees who one wants to affect will not be integrated by informal communication.

The focal organizations in a societal sector may exhibit mere functional similarity with an absence of direct or indirect ties, or occasional integration via one or more professional associations, to regular integration via direct ties such that representatives of focal organizations know one another via their communication together in a social network.

The more integrated, the faster the rates of decision about innovations. Understanding the degree to which a societal sector is integrated is a key to subsequent dissemination intervention to know whether influence flows through relational ties or through mediated specialty channels on the basis of structural similarity of potential adopters Burt, This knowledge can then be used in intervention development to inform potential adopters about one or more innovations.

In the United States, arguably the greatest public health success has been the decrease in smoking of tobacco since the s. The California experience, in particular, is illustrative of a multipronged dissemination system of mutually-reinforcing messages, opportunities, regulations, incentives, and social pressure for normative, attitude, and behavior change Green et al. This approach to change, while not a priori managed as a coordinated strategy, exhibits the holistic combination of centralized technical expertise, distribution and access, and decentralized participation and community incentives that private foundations have supported in communities.

The experience in California also demonstrates system interdependency; California and its residents, while early relative to others, were not alone in smoking behavior change. Federal efforts, mass media messages, and a broader normative readiness for change likely affected and were affected by what happened in California. The lessons for dissemination science are two. First, dissemination effort can be effective via a complex mutually-reinforcing intervention system even when that intervention is not strategically designed and coordinated by a centralized source.

Complexity and, hence, indeterminancy, in intervention may be precisely the point with causal attribution not the scholarly objective Hornik, Diffusion, after all, is about spread.

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In a push-pull-capacity model Green et al. There is none, at least, that is apparent. This complex process is exactly what many analysts refer to as naturalistic diffusion. Mass media are key to this cumulative effect, providing what Harold D. Lasswell referred to as a correlational function in helping to suggest what issues are deserving of attention and when. Social work researchers can monitor media and policy attention to reinforcing and competing issues to best time the introduction of clusters of social work interventions to potential adopters.

The second lesson for dissemination science is one of timing. Change in California, just as in other states, did not occur randomly in time. In relation to smoking, California changed within a specific time-frame and exhibited considerable over-time grouping with what happened in other states. There may always remain a role for centralization of certain knowledge in planned change for the purpose of efficiency Stetler et al.

The diffusion of consequential innovations always has been understood to be a social process. Although knowledge is often gained through the largely one-way communication of information especially with the increased information search capabilities of new communication technologies, persuasion occurs through the two-way communication of social influence, most commonly in the form of local informal opinion leaders who are embedded in social networks. For innovations perceived to be high in risk or uncertainty, information alone in one-on-one counseling, training workshop, practice guideline, presentation, Web site, brochure, etc.

Opinion leaders are the reason why diffusion can be a very efficient process to jump-start: An innovation source or sponsor can concentrate on identifying and convincing a special small subset of all possible adopters Castro et al. Existing influence and the extent to which followers monitor the attitudes and behaviors of opinion leaders can do the rest as long as a opinion leader attitudes are favorable toward the new practice, and b others positively identify the opinion leader with the innovation, and c the larger environment supports change of that type at that time Wejnert, The concept of opinion leadership, when translated for use to spread interventions, is often misoperationalized.

The concept is also operationalized too broadly as earliness in adoption. Although it is true that opinion leaders, whether operationalized as individuals or aggregates thereof, do make decisions about innovations early relative to others, it is also true that not all early adopters are opinion leaders. So while time of adoption can be used as an indicator of state leadership relative to other states, it should not be a sole indicator.

The broader diffusion literature demonstrates that the motives for adoption differ, in general, according to time of adoption. A key determinant of the likely success in intervention development is the sophistication of change agents who work on behalf of a change agenc y. If a change agent correctly identifies which organizational leaders serve as sources of example, modeling, and advice for the leaders of other organizations in a societal sector, change agent time can be spent interacting with that subset of opinion leaders who will in turn affect other leaders in the course of their normal conversations with those peer-followers Rogers, In dissemination intervention, opinion leaders are especially effective when they are not asked to do too much.

Asking opinion leaders to advocate, persuade, promote, or educate in ways they normally would not with their colleagues is asking them to risk their status within the system in question by formalizing what is an informal role Pereles et al. Opinion leaders are perceived as expert and trustworthy precisely because of their relative objectivity regarding innovations. Indeed, most of their judgments about innovations are negative. One implication of this tendency is that innovations perceived as radical are especially likely to be rejected by opinion leaders and, thus, are better targeted first to innovators who are sources of information for the opinion leaders in question.

In organizations, the choosers of innovations are often not users. What it is that organizational implementers do with innovations has been viewed as a dichotomy. Either they put the innovation into practice as is, or they change it in the belief that the new iteration will better fit their current workplace or client conditions. Adherents of program fidelity believe that working to insure that adopters make as few modifications as possible is key to retaining the success of the original program.

If the program is changed, how does one know if it is still effective? On the other hand, adherents of the program adaptation perspective counter that it is only through allowing adopters to change a program to suit their needs that the likelihood of sustainability is increased. If adopters do not feel ownership of the program, how can we insure its persistence in practice? There is great incentive, often well-intended, at the individual or single organizational level to customize, to partly adopt, and to combine innovation components from multiple sources to create a best fit in the user context.

For every adopting organization, truth be told, is unique von Hippel, Studies of the creation and implementation of interventions suggest that user involvement is positively related to adoption, implementation, and sustainability of change Douthwaite, Reinvention of innovations is more norm than exception, especially with wider availability of technology such that more and more adopters can participate in the creation of innovations themselves von Hippel, So while strict fidelity to an established process of implementation can make good sense in very complex behavioral interventions such as substance abuse treatment and recovery programs Fixsen et al.

This tendency is complicated by the fact that more than an innovation can be adapted during implementation. The organizational context, too, can change. And with process innovations, prior context can become indistinguishable from that which was new. If one only changes an adopted program and not the work environment—or visa versa—technical, delivery system, and performance criteria misalignments are more likely to characterize implementation.

How practitioners interpret the purpose and promise of a new program will interact with how they choose to make accommodation for it in the workplace. A key to successful implementation is to communicate why an innovation works, not just what it is. Guided adaptation through explicating both the underlying causal components of a program as well as examples for operationalizing those causal components in practice, and clarifying to implementers which aspects of a demonstrated program are central to its observed effect and which components are peripheral and more likely changeable without deleterious effects is a sensible approach to implementation that can recast adaptation as a property of implementation process and fidelity as a property of outcomes.

Practitioners should be encouraged to customize by making additions rather than just modifying an innovation. Adding local supplemental components is less likely to dilute effectiveness than is modification that includes the deletion of or alteration to core components Blakely et al. The pursuit of process adaptations to achieve positive outcomes is especially likely when both conceptual knowledge and examples are codified so that they are explicit rather than remaining tacit for subsequent implementers.

In organizations, resources in the form of staff time are often required for an innovation to be implemented. If senior management is not onboard, health care practitioners often cannot risk implementation Bradley et al. As it has increasingly been applied to agricultural, international development, public health, and educational interventions, classical diffusion of innovation theory is evolving into a science of dissemination. I have highlighted seven concepts from the diffusion literature that have been used or have the potential to be used to affect the rate at which social work interventions spread:.

Social work interventions range from innovations in human resource management to client counseling to technology deployment. The field exhibits a varied terrain for which narrow prescriptions for change may prove inadequate. Diffusion theory, with validated concepts that concern different aspects of personal, organizational, and social change, offers social work researchers a menu of concept combinations that may be quite adaptive to different social work innovations, different types of service providers and clients, and varied settings.

National Center for Biotechnology Information , U. Res Soc Work Pract. Author manuscript; available in PMC Oct Author information Copyright and License information Disclaimer. Correspondence may be addressed to James W. Box , Denver CO ; gro. The publisher's final edited version of this article is available at Res Soc Work Pract. See other articles in PMC that cite the published article. Abstract Few social science theories have a history of conceptual and empirical study as long as does the diffusion of innovations.

Gottlieb, and Guy S. Defining Dissemination Science A worldwide science of dissemination is emerging, driven by new communication technologies, the interests of philanthropies and the needs of government agencies, and the persistent and growing applied problems that have been addressed but not solved by the dominant research paradigms in disciplines such as psychology, sociology, and political science. The Classical Diffusion Paradigm Diffusion is the process through which an innovation is communicated through certain channels over-time among the members of a social system Rogers, Open in a separate window.

The innovation , and especially potential adopter perceptions of its attributes of relative advantage effectiveness and cost efficiency relative to alternatives , complexity how simple the innovation is to understand , compatibility the fit of the innovation to established ways of accomplishing the same goal , observability the extent to which outcomes can be seen , and trialability the extent to which the adopter must commit to full adoption ;. The social system , especially in terms of the structure of the system, its local informal opinion leaders , and potential adopter perception of social pressure to adopt;.

The individual adoption-process , a stage-ordered model of awareness, persuasion, decision, implementation, and continuation;. We assume that evidence matters in the decision making of potential adopters. Interventions of unknown effectiveness and of known ineffectiveness often spread while effective interventions do not. Evidence is most important to only a subset of early adopters and is most often used by them to reject interventions. Emphasize other variables in the communication of innovations such as compatibility, cost, and simplicity.

Inadequate and poorly performed formative evaluation is common as experts in the intervention topical domain engage in dissemination. Seek out and listen to representative potential adopters to learn wants, information sources, advice-seeking behaviors, and reactions to prototype interventions.

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Real-Time Development from Theory to Practice Real-Time Development from Theory to Practice
Real-Time Development from Theory to Practice Real-Time Development from Theory to Practice
Real-Time Development from Theory to Practice Real-Time Development from Theory to Practice
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