Many promising technological innovations in health and social care are characterized by nonadoption or abandonment by individuals or by failed attempts to scale up locally, spread distantly, or sustain the innovation long term at the organization or system level.
Personal health records (PHRs) have emerged as an important tool with which patients can electronically communicate with their doctors and doctor’s offices. However, there is a lack of theoretical and empirical research on how patients perceive the PHR and the differences in perceptions between users and non-users of the PHR.
BACKGROUND: Although collaborative team models (CTM) improve care processes and health outcomes, their diffusion poses challenges related to difficulties in securing their adoption by primary care clinicians. The objectives of this study are to understand: (1) how the perceived characteristics of a CTM influenced clinicians' decision to adopt -or not- the model; and (2) the model’s diffusion process. METHODS: We conducted a longitudinal case study based on the Diffusion of Innovations Theory. First, diffusion curves were developed for all 175 primary care physicians (PCPs) and 59 nurses practicing in one borough of Paris. Second, semi-structured interviews were conducted with a representative sample of 40 PCPs and 15 nurses to better understand the implementation dynamics. RESULTS: Diffusion curves showed that 3.5 years after the start of the implementation, 100% of nurses and over 80% of PCPs had adopted the CTM. The dynamics of the CTM’s diffusion were different between the PCPs and the nurses. The slopes of the two curves are also distinctly different. Among the nurses, the critical mass of adopters was attained faster, since they adopted the CTM earlier and more quickly than the PCPs. Results of the semi-structured interviews showed that these differences in diffusion dynamics were mostly founded in differences between the PCPs' and the nurses' perceptions of the CTM’s compatibility with norms, values and practices and its relative advantage (impact on patient management and work practices). Opinion leaders played a key role in the diffusion of the CTM among PCPs. CONCLUSION: CTM diffusion is a social phenomenon that requires a major commitment by clinicians and a willingness to take risks; the role of opinion leaders is key. Paying attention to the notion of a critical mass of adopters is essential to developing implementation strategies that will accelerate the adoption process by clinicians. Key-words: primary care, primary care physician, nurses, chronic disease, collaboration, health service research, diffusion of innovation.
Because of its fundamental relevance to scientific innovation, artistic expression, and human ingenuity, creativity has long been the subject of systematic psychological investigation. Concomitantly, the far-reaching effects of stereotypes on various cognitive and social processes have been widely researched. Bridging these two literatures, we show in a series of two studies that stereotypes related to creativity can both enhance and diminish individuals' performance on a divergent thinking task. Specifically, Study 1 demonstrated that participants asked to take on a stereotypically uninhibited perspective performed significantly better on a divergent thinking task than those participants who took on a stereotypically inhibited perspective, and a control group. Relatedly, Study 2 showed that the same effect is found within-subjects, with divergent thinking significantly improving when participants invoke an uninhibited stereotype. Moreover, we demonstrate the efficacy of Latent Semantic Analysis as an objective measure of the originality of ideas, and discuss implications of our findings for the nature of creativity. Namely, that creativity may not be best described as a stable individual trait, but as a malleable product of context and perspective.
- Proceedings. Biological sciences / The Royal Society
- Published about 5 years ago
Tool use can be inherited, or acquired as an individual innovation or by social transmission. Having previously reported individual innovative tool use and manufacture by a Goffin cockatoo, we used the innovator (Figaro, a male) as a demonstrator to investigate social transmission. Twelve Goffins saw either demonstrations by Figaro, or ‘ghost’ controls where tools and/or food were manipulated using magnets. Subjects observing demonstrations showed greater tool-related performance than ghost controls, with all three males in this group (but not the three females) acquiring tool-using competence. Two of these three males further acquired tool-manufacturing competence. As the actions of successful observers differed from those of the demonstrator, result emulation rather than high-fidelity imitation is the most plausible transmission mechanism.
- Journal of the Royal Society, Interface / the Royal Society
- Published over 4 years ago
Invention has been commonly conceptualized as a search over a space of combinatorial possibilities. Despite the existence of a rich literature, spanning a variety of disciplines, elaborating on the recombinant nature of invention, we lack a formal and quantitative characterization of the combinatorial process underpinning inventive activity. Here, we use US patent records dating from 1790 to 2010 to formally characterize invention as a combinatorial process. To do this, we treat patented inventions as carriers of technologies and avail ourselves of the elaborate system of technology codes used by the United States Patent and Trademark Office to classify the technologies responsible for an invention’s novelty. We find that the combinatorial inventive process exhibits an invariant rate of ‘exploitation’ (refinements of existing combinations of technologies) and ‘exploration’ (the development of new technological combinations). This combinatorial dynamic contrasts sharply with the creation of new technological capabilities-the building blocks to be combined-that has significantly slowed down. We also find that, notwithstanding the very reduced rate at which new technologies are introduced, the generation of novel technological combinations engenders a practically infinite space of technological configurations.
The origin of the Middle Stone Age (MSA) denotes the transition from a highly persistent mode of stone toolmaking, the Acheulean, to a period of increasing technological innovation and cultural indicators associated with the evolution ofHomo sapiensHere we use40Ar/39Ar and U-series dating to calibrate the chronology of Acheulean- and early MSA-rich sedimentary deposits in the Olorgesailie Basin, South Kenya Rift. We establish the age of late Acheulean tool assemblages from 615 to 499 ka, after which a large technological and faunal transition occurred, with definitive MSA lacking Acheulean elements beginning most likely by ~320 ka, but at least by 305 ka. These results establish the currently oldest repository of MSA in eastern Africa.
The past decade has seen the emergence of new diagnostics and drugs for tuberculosis, a disease that kills over 1.8 million people each year. However, these new tools are yet to reach scale, and access remains a major challenge for patients in low and middle income countries. Urgent action is needed if we are committed to ending the TB epidemic. This means raising the level of ambition, embracing innovation, increasing financial investments, addressing implementation gaps, and ensuring that new technologies reach those who need them to survive. Otherwise, the promise of innovative technologies will never be realized.
Understanding how the brain works requires a delicate balance between the appreciation of the importance of a multitude of biological details and the ability to see beyond those details to general principles. As technological innovations vastly increase the amount of data we collect, the importance of intuition into how to analyze and treat these data may, paradoxically, become more important.
Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of “big data” for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.