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Comment on: Archibald M.M. & Clark A.M. (2014) Twitter and nursing research: How diffusion of innovation theory can help uptake. Journal of Advanced Nursing 70(3), e3-5. Doi: 10.1111/jan.12343

Comment on: Archibald M.M. & Clark A.M. (2014) Twitter and nursing research: how diffusion of
innovation theory can help uptake. Journal of Advanced Nursing 70(3), e35. doi:10.1111/jan.12343
In Archibald and Clark’s (2014) editorial, they provide an inter-
esting and intriguing examination of Twitter’s adoption by
nurses and researchers into the profession through the lens of
Rogers’ (2003) Diffusion of Innovations Theory. Although the
authors outline a variety of reasons as to why Twitter has failed
to take hold in nursing academic circles, we believe that their
editorial misses a few important considerations when exploring
the adoption of social media platforms such as Twitter.
Foremost, Twitter is a social technology. Correspondingly,
the modality of communication that Twitter enables is a trait
of the technology, and also co-created through the role and
value its users have inscribed onto the technology. In other
words, Twitter as an innovation is exceedingly mouldable, scal-
able and non-static. In this vein, both the innovation (i.e. Twit-
ter) and its users help to generate the current dynamic that is
the Twittersphere, and the inherent culture, attitudes and eti-
quette that are allowed to exist and operate on Twitter. As a
by-product of this continuously evolving relationship, some
nursing researchers have found value in using Twitter as a
means to distribute information related to research. Just as
Facebook is an ‘accidental health platform’ (Fox 2014), Twit-
ter too has become an accidental mechanism for distributing
information of all genres, including nursing research. There-
fore, as an accidental platform for nursing research dissemina-
tion, it is important to appreciate that the platform likely only
resonates with potential users (and nurses) who are able to
internalize both the technical competencies required to use the
platform, but more importantly, to also appreciate the larger
social implications and value of this communication modality.
From an ontological perspective, the Diffusion of Innova-
tion approach typically privileges the innovation in question
(i.e. Twitter), conceptualizing the innovation as an entity that
compels other elements in the surroundings to conform
around its presence. As outlined by Archibald and Clark, the
adoption of Twitter by nursing has not been comparable to
the adoption rates of adults in the general population, leading
them to question this ‘inertia’ from the perspective of the
profession (p. e3). As Twitter is an innovation that holds the
potential to exponentially amplify the social abilities of its
users, any person wishing to adopt and use Twitter in a sus-
tained fashion is subject to an array of complex socio-techni-
cal considerations, which may not be present in other types of
technical innovations that are less socially mediated. In an
effort to outline how social platforms (and their users) are
shaped by the networked nature of social media, Kietzmann
et al. (2011) outlined a ‘social media ecology’ (p. 241) as a
means of understanding a user’s audience and needs within
situations involving social technology. In this ecology, the
elements of presence, sharing, conversations, groups, relation-
ships, reputation and identity are outlined as potential factors
that influence engagement in social media dynamics. There-
fore, depending on the context, role and responsibilities of a
nurse (or researcher), the need or value of Twitter may not
resonate enough to support adoption, or sustain use. Inso-
much, the presence of the innovation itself is not sufficient to
drive adoption; rather, the depth of understanding of Twitter
and need of the potential user to undertake elements like iden-
tity building, maintenance of reputation, and sharing of infor-
mation in the user’s role and life are likely more important
predictors of adoption and sustained use in the postadoptive
Subsequently, it is not surprising that nursing researchers
have largely ignored Twitter, particularly those established in
their careers who have found sufficient translation of their
body of work through other, traditional platforms, and who
find limited utility for social media platforms in other facets of
their daily lives. As clearly outlined by MacVaugh and Schiav-
one (2010), the ‘[u]tility [of an innovation], regardless of its
nature or source, has never been a complete explanation for
the behaviour of humans’ (p. 204). Therefore, a more fruitful
area of exploration of Twitter within the profession would be
to explore postadoptive behaviours of the platform, and how
certain cross-sections of nurses utilize the platform, to what
intensity, and for what purpose.
2406 ©2014 John Wiley & Sons Ltd
One area of adoption that we have anecdotally observed
(not the least in our own neophyte careers) is the use of social
platforms by researchers who are early in their academic jour-
neys. Twitter adopters may find the technology to be a means
to increase their visibility and clout amongst fellow researchers
and other academic centres, community partners or traditional
media outlets. Given the contraction in research funding, it is
becoming increasingly difficult for new researchers to obtain
research grants to assist in the development of their academic
careers. Subsequently, Twitter may offer a competitive advan-
tage to these novice researchers as a mechanism that helps
build career momentum in asymmetric fashions, alongside tra-
ditional academic requirements like publications and grants. It
is now possible for a new researcher to leverage their existing
expertise through the amplifying nature of Twitter and its glo-
bal reach (e.g. tweeting recent publications, attendance at con-
ferences and other scholarship-related material on a regular
basis to followers). That said, the basic adoption of Twitter
does not yield even these sorts of returns immediately. As out-
lined by Archibald and Clark, time and effort is required to
build followers to establish oneself as a valuable Twitter con-
tributor who should be followed for their insights. Only nurses
who have this information/communication ‘push-pull’ desire
will use Twitter to its fullest capabilities, and likely already
possess insights of their presence online similar to the Kietz-
mann et al. (2011) ecology framework.
In this way, we agree with Archibald and Clark’s interpreta-
tion of the potential value of Twitter for nursing research.
Regardless, we offer the caveat that any individual proposing
the adoption of social technology to others should reflect upon,
and be cognizant of, the deeper socio-technical forces that are
at play. Twitter uptake and adoption, like all other social
media platforms, likely does not conform to traditional innova-
tion diffusion logic.
Disclaimer: RB originally discovered Archibald and Clark’s
article via a Twitter feed
Richard Booth PhD RN
Assistant Professor
Arthur Labatt Family School of Nursing, Western University,
London, Ontario, Canada
Abram Oudshoorn PhD RN
Assistant Professor
Arthur Labatt Family School of Nursing, Western University,
London, Ontario, Canada
Archibald M. & Clark A. (2014) Twitter and nursing research:
How diffusion of innovation theory can help uptake. Journal of
Advanced Nursing 70,e3e5.
Fox S. (2014) Facebook is an accidental health platform. Read the
patient-communities/ [Twitter]. 1 February 2014. Retrieved from on
1 February 2014.
Kietzmann J., Hermkens K., McCarthy I. & Silvestre B. (2011)
Social media? Get serious!Understanding the functional building
blocks of social media. Business Horizons 54, 241251.
MacVaugh J. & Schiavone F. (2010) Limits to the diffusion of
innovation: a literature review and integrative model. European
Journal of Innovation Management 13, 197221.
Rogers E. (2003) Diffusion of Innovations, 5th edn. Free Press,
New York.
©2014 John Wiley & Sons Ltd 2407
Full-text available
Aims: To ask: (i) is it feasible to include Twitter as an assessed element of the first-year nursing curriculum; (ii) how should it be introduced and assessed; and (iii) do students think it worthwhile and learn anything from its use? Background: Nursing students need to use social media professionally, avoiding pitfalls but using learning opportunities. Design: This case study (2014-2015) comprised: (i) pilot introduction of Digital Professionalism (including Twitter) with second- and third-year students; (ii) introduction and assessment with a first cohort of 450 first-year students. Based on feedback, methods were revised for; (iii) a second cohort of 97. Methods: Students received a face-to-face lecture, two webinars, used chat rooms and were asked to create course Twitter accounts and were assessed on their use. Results: Few second and third year students started optional Twitter use whereas nearly all first years used it. Most students (70·1% first, 88·0% second cohort) thought inclusion of Twitter was worthwhile. Changes from first to second cohort included better peer-peer support, more contextualization and more emphasis on nursing communities. More second cohort students learned from Twitter (44·4% vs. 70·8%) and used Twitter recently (43·3% vs. 81·6%). Students gained wider perspectives on nursing, better understanding of social media, 'being student nurses' and topics like health promotion. Students mostly followed not only online nursing communities but also patient organizations. Conclusion: Including Twitter as an assessed element for first-year nursing students was feasible, students think it worthwhile and other nursing schools should consider introducing it in the broader context of Digital Professionalism.
Full-text available
Purpose The purpose of this article is to integrate existing theoretical explanations for innovation diffusion across the disciplines of marketing, innovation and sociology research. Design/methodology/approach Literature reviews and historical case analysis were used to support an integrative model. Findings Innovation diffusion is affected by technological, social and learning “conditions” while operating in the contextual “domain” of the individual, community or market/industry. Research limitations/implications The model is drawn from new product development and marketing theory. Both fields are dominated by the assumption that users adopt new technology to maximise their utility. Also, the model does not integrate the overlapping effects of the different contexts and domains. Practical implications The article provides a sound model for orienting new product development strategy, since it may reduce the risk of low and slow user adoption of radical innovations due, for instance, to their technological, social, and cognitive differences with former products. A second critical managerial implication is that technological, social and learning conditions clearly have an effect on marketing actions and competitive strategies. Originality/value The article provides a literature review of resistance to technology adoption through a multidisciplinary lens.
Full-text available
Traditionally, consumers used the Internet to simply expend content: they read it, they watched it, and they used it to buy products and services. Increasingly, however, consumers are utilizing platforms--such as content sharing sites, blogs, social networking, and wikis--to create, modify, share, and discuss Internet content. This represents the social media phenomenon, which can now significantly impact a firm's reputation, sales, and even survival. Yet, many executives eschew or ignore this form of media because they don't understand what it is, the various forms it can take, and how to engage with it and learn. In response, we present a framework that defines social media by using seven functional building blocks: identity, conversations, sharing, presence, relationships, reputation, and groups. As different social media activities are defined by the extent to which they focus on some or all of these blocks, we explain the implications that each block can have for how firms should engage with social media. To conclude, we present a number of recommendations regarding how firms should develop strategies for monitoring, understanding, and responding to different social media activities.
Getting an innovation adopted is difficult; a common problem is increasing the rate of its diffusion. Diffusion is the communication of an innovation through certain channels over time among members of a social system. It is a communication whose messages are concerned with new ideas; it is a process where participants create and share information to achieve a mutual understanding. Initial chapters of the book discuss the history of diffusion research, some major criticisms of diffusion research, and the meta-research procedures used in the book. This text is the third edition of this well-respected work. The first edition was published in 1962, and the fifth edition in 2003. The book's theoretical framework relies on the concepts of information and uncertainty. Uncertainty is the degree to which alternatives are perceived with respect to an event and the relative probabilities of these alternatives; uncertainty implies a lack of predictability and motivates an individual to seek information. A technological innovation embodies information, thus reducing uncertainty. Information affects uncertainty in a situation where a choice exists among alternatives; information about a technological innovation can be software information or innovation-evaluation information. An innovation is an idea, practice, or object that is perceived as new by an individual or an other unit of adoption; innovation presents an individual or organization with a new alternative(s) or new means of solving problems. Whether new alternatives are superior is not precisely known by problem solvers. Thus people seek new information. Information about new ideas is exchanged through a process of convergence involving interpersonal networks. Thus, diffusion of innovations is a social process that communicates perceived information about a new idea; it produces an alteration in the structure and function of a social system, producing social consequences. Diffusion has four elements: (1) an innovation that is perceived as new, (2) communication channels, (3) time, and (4) a social system (members jointly solving to accomplish a common goal). Diffusion systems can be centralized or decentralized. The innovation-development process has five steps passing from recognition of a need, through R&D, commercialization, diffusions and adoption, to consequences. Time enters the diffusion process in three ways: (1) innovation-decision process, (2) innovativeness, and (3) rate of the innovation's adoption. The innovation-decision process is an information-seeking and information-processing activity that motivates an individual to reduce uncertainty about the (dis)advantages of the innovation. There are five steps in the process: (1) knowledge for an adoption/rejection/implementation decision; (2) persuasion to form an attitude, (3) decision, (4) implementation, and (5) confirmation (reinforcement or rejection). Innovations can also be re-invented (changed or modified) by the user. The innovation-decision period is the time required to pass through the innovation-decision process. Rates of adoption of an innovation depend on (and can be predicted by) how its characteristics are perceived in terms of relative advantage, compatibility, complexity, trialability, and observability. The diffusion effect is the increasing, cumulative pressure from interpersonal networks to adopt (or reject) an innovation. Overadoption is an innovation's adoption when experts suggest its rejection. Diffusion networks convey innovation-evaluation information to decrease uncertainty about an idea's use. The heart of the diffusion process is the modeling and imitation by potential adopters of their network partners who have adopted already. Change agents influence innovation decisions in a direction deemed desirable. Opinion leadership is the degree individuals influence others' attitudes
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