#Deathbedlive:the end-of-life trajectory, reflected in a cancer patient's tweets

Abstract Background Understanding physical and psycho-social illness trajectories towards the end of life can help in the planning of palliative and supportive care. With terminal patients increasingly seeking and sharing health information and support via social media, it is timely to examine whether these trajectories are reflected in their digital narratives. In this exploratory study, we analysed the Twitter feed of prominent cancer sufferer and physician, Kate Granger, over the final 6 months of her life. Methods With the consent of Kate’s widower, Chris Pointon, 1628 Twitter posts from @GrangerKate were manually screened. The 550 tweets judged relevant to her disease were qualitatively content analysed with reference to the six modifiable dimensions of the patient experience in Emanuel and Emanuel’s ‘framework for a good death’. The frequency of each tweet category was charted over time and textual content was examined and cross-referenced with key events, to obtain a deeper understanding of its nature and significance. Results Tweets were associated with physical symptoms (N = 270), psychological and cognitive symptoms (N = 213), social relationships and support (N = 85), economic demands and care giving needs (N = 85), hopes and expectations (N = 51) and spiritual beliefs (N = 7). While medical treatments and procedures were discussed in detail, medical information-seeking was largely absent, likely reflecting Kate clinical expertise. Spirituality was expressed more as hope in treatments or “someone out there listening”, than in religious terms. The high value of Kate’s palliative care team was a dominant theme in the support category, alongside the support she received from her online community of fellow sufferers, friends, family and colleagues. Significant events, such as medical procedures and hospital stays generated the densest Twitter engagement. Transitions between trajectory phases were marked by changes in the relative frequency of tweet-types. Conclusions In Kate’s words, “the power of patient narrative cannot be underestimated”. While this analysis spanned only 6 months, it yielded rich insights. The results reflect theorised end-of-life dimensions and reveal the potential of social media data and digital bio-ethnography to shine a light on terminal patients’ lived experiences, coping strategies and support needs, suggesting new opportunities for enhancing personalised palliative care and avenues for further research

Re-imaging Bernstein's restricted codes

While accepting that the concept of restricted code has a troubled history that resulted in Bernstein being associated with deficit models of working-class life, it is argued that the concept should be re-imagined rather than abandoned. Bernstein’s early work refers to restricted code as a form of condensed, shorthand established through familiarity that was not tied to class per se. In Volume 2 of Class, Codes and Control social class was an independent variable in the research designs and coding only that which could be explicitly spoken, produced working class groups as inferior in comparison to middle class groups: Bernstein’s disquiet can be sensed in many places across his work where he explicitly renounced a deficit model. Methodological and theoretical work on embodied knowledge is used here to explicate the more-than, codeable features of restricted codes. An illustration from studies in ex-coalmining, working-class communities is used to explore what is missed in conventional approaches to data coding. Other studies in ex-mining communities reveal the intergenerational transmission of rich resources that were vital for community survival. Re-imagining restricted codes as relational assemblages recognises the value of the dynamic, creative and intergenerational features of localised, embodied knowledge