Conceptualising social media support for tacit knowledge sharing: physicians’ perspectives and experiences

Purpose – This paper aims to explore the potential contributions of social media in supporting tacit knowledge sharing, according to the physicians’ perspectives and experiences. Design/methodology/approach – Adopting a qualitative survey design, 24 physicians were interviewed. Purposive and snowball sampling were used to select the participants. Thematic analysis approach was used for data analysis. Findings – The study revealed five major themes and over 20 sub-themes as potential contributions of social media to tacit knowledge flow among physicians. The themes included socialising, practising, networking, storytelling and encountering. In addition, with the help of the literature and the supporting data, the study proposed a conceptual model that explains the potential contribution of social media to tacit knowledge sharing. Research limitations/implications – The study had both theoretical (the difficulty of distinguishing tacit and explicit knowledge in practice) and practical limitations (small sample size). The study findings have implications for the healthcare industry whose clinical teams are not always physically co-located but must exchange their critical experiential and tacit knowledge. Originality/value – The study has opened up a new discussion of this area by demonstrating and conceptualising how social media tools may facilitate tacit knowledge sharing.

The profile of psychiatric symptoms exacerbated by methamphetamine use

Background Methamphetamine use can produce symptoms almost indistinguishable from schizophrenia. Distinguishing between the two conditions has been hampered by the lack of a validated symptom profile for methamphetamine-induced psychiatric symptoms. We use data from a longitudinal cohort study to examine the profile of psychiatric symptoms that are acutely exacerbated by methamphetamine use. Methods 164 methamphetamine users, who did not meet DSM-IV criteria for a lifetime primary psychotic disorder, were followed monthly for one year to assess the relationship between days of methamphetamine use and symptom severity on the 24-item Brief Psychiatric Rating Scale. Exacerbation of psychiatric symptoms with methamphetamine use was quantified using random coefficient models. The dimensions of symptom exacerbation were examined using principal axis factoring and a latent profile analysis. Results Symptoms exacerbated by methamphetamine loaded on three factors: positive psychotic symptoms (suspiciousness, unusual thought content, hallucinations, bizarre behavior); affective symptoms (depression, suicidality, guilt, hostility, somatic concern, self-neglect); and psychomotor symptoms (tension, excitement, distractibility, motor hyperactivity). Methamphetamine use did not significantly increase negative symptoms. Vulnerability to positive psychotic and affective symptom exacerbation was shared by 28% of participants, and this vulnerability aligned with a past year DSM-IV diagnosis of substance-induced psychosis (38% vs. 22%, _2 (df1) = 3.66, p = 0.056). Conclusion Methamphetamine use produced a symptom profile comprised of positive psychotic and affective symptoms, which aligned with a diagnosis of substance-induced psychosis, with no evidence of a negative syndrome.

Avian diversification patterns across the K-Pg boundary: Influence of calibrations, datasets, and model misspecification

Birds represent the most diverse extant tetrapod clade, with ca. 10,000 extant species, and the timing of the crown avian radiation remains hotly debated. The fossil record supports a primarily Cenozoic radiation of crown birds, whereas molecular divergence dating analyses generally imply that this radiation was well underway during the Cretaceous. Furthermore, substantial differences have been noted between published divergence estimates. These have been variously attributed to clock model, calibration regime, and gene type. One underappreciated phenomenon is that disparity between fossil ages and molecular dates tends to be proportionally greater for shallower nodes in the avian Tree of Life. Here, we explore potential drivers of disparity in avian divergence dates through a set of analyses applying various calibration strategies and coding methods to a mitochondrial genome dataset and an 18-gene nuclear dataset, both sampled across 72 taxa. Our analyses support the occurrence of two deep divergences (i.e., the Palaeognathae/Neognathae split and the Galloanserae/Neoaves split) well within the Cretaceous, followed by a rapid radiation of Neoaves near the K-Pg boundary. However, 95% highest posterior density intervals for most basal divergences in Neoaves cross the boundary, and we emphasize that, barring unreasonably strict prior distributions, distinguishing between a rapid Early Paleocene radiation and a Late Cretaceous radiation may be beyond the resolving power of currently favored divergence dating methods. In contrast to recent observations for placental mammals, constraining all divergences within Neoaves to occur in the Cenozoic does not result in unreasonably high inferred substitution rates. Comparisons of nuclear DNA (nDNA) versus mitochondrial DNA (mtDNA) datasets and NT- versus RY-coded mitochondrial data reveal patterns of disparity that are consistent with substitution model misspecifications that result in tree compression/tree extension artifacts, which may explain some discordance between previous divergence estimates based on different sequence types. Comparisons of fully calibrated and nominally calibrated trees support a correlation between body mass and apparent dating error. Overall, our results are consistent with (but do not require) a Paleogene radiation for most major clades of crown birds.

Towards a typology of hashtag publics: A large-scale comparative study of user engagement across trending topics

Twitter’s hashtag functionality is now used for a very wide variety of purposes, from covering crises and other breaking news events through gathering an instant community around shared media texts (such as sporting events and TV broadcasts) to signalling emotive states from amusement to despair. These divergent uses of the hashtag are increasingly recognised in the literature, with attention paid especially to the ability for hashtags to facilitate the creation of ad hoc or hashtag publics. A more comprehensive understanding of these different uses of hashtags has yet to be developed, however. Previous research has explored the potential for a systematic analysis of the quantitative metrics that could be generated from processing a series of hashtag datasets. Such research found, for example, that crisis-related hashtags exhibited a significantly larger incidence of retweets and tweets containing URLs than hashtags relating to televised events, and on this basis hypothesised that the information-seeking and -sharing behaviours of Twitter users in such different contexts were substantially divergent. This article updates such study and their methodology by examining the communicative metrics of a considerably larger and more diverse number of hashtag datasets, compiled over the past five years. This provides an opportunity both to confirm earlier findings, as well as to explore whether hashtag use practices may have shifted subsequently as Twitter’s userbase has developed further; it also enables the identification of further hashtag types beyond the “crisis” and “mainstream media event” types outlined to date. The article also explores the presence of such patterns beyond recognised hashtags, by incorporating an analysis of a number of keyword-based datasets. This large-scale, comparative approach contributes towards the establishment of a more comprehensive typology of hashtags and their publics, and the metrics it describes will also be able to be used to classify new hashtags emerging in the future. In turn, this may enable researchers to develop systems for automatically distinguishing newly trending topics into a number of event types, which may be useful for example for the automatic detection of acute crises and other breaking news events.