Symptom recognition and perceived urgency of help-seeking for rheumatoid arthritis and other diseases in the general public: a mixed method approach

Objective: Clinical outcomes in Rheumatoid arthritis (RA) are improved if the disease is treated early. However, treatment is often significantly delayed as a result of delayed help seeking by patients who fail to recognise its symptoms or the need for rapid medical attention. We conducted two studies to investigate the role of symptom recognition in help-seeking for the symptoms of RA and compared this with angina and bowel cancer. Methods: We conducted a qualitative interview study with 31 individuals and a postal survey of 1088 members of the general public (all without RA). Both studies used vignettes describing the symptoms of RA, bowel cancer and angina. Participants made causal attributions and rated the perceived seriousness of the symptoms and the urgency with which they would seek medical help if confronted with these symptoms. Results: Only a small proportion of participants in both studies recognised the symptoms of RA, whereas the symptoms of bowel cancer and angina were readily recognised by many participants and considered to be more serious and to require more rapid medical attention (Z values of 14.7 to 34.2, p<.001). Conclusion: Accurate symptom attribution and the perception that symptoms are indicative of a serious underlying condition are both important drivers for rapid help seeking. In the case of angina and bowel cancer, recent campaigns have promoted not only recognition of symptoms and their seriousness, but also emphasised the consequences of not seeking timely help. Our results suggest that these consequences should also be addressed in any public health campaign for RA

High-throughput sequence analysis of variants of human cytomegalovirus strains Towne and AD169

The genomes of commonly used variants of human cytomegalovirus (HCMV) strains Towne and AD169 each contain a substantial mutation in which a region (UL/b′) at the right end of the long unique region has been replaced by an inverted duplication of a region from the left end of the genome. Using high-throughput technology, we have sequenced HCMV strain Towne (ATCC VR-977) and confirmed the presence of two variants, one exhibiting the replacement in UL/b′ and the other intact in this region. Both variants are mutated in genes RL13, UL1, UL40, UL130, US1 and US9. We have also sequenced a novel AD169 variant (varUC) that is intact in UL/b′ except for a small deletion that affects genes UL144, UL142, UL141 and UL140. Like other AD169 variants, varUC is mutated in genes RL5A, RL13, UL36 and UL131A. A subpopulation of varUC contains an additional deletion affecting genes IRS1, US1 and US2

Class, Youth and Dirty Jobs: The Working-Class and Post-War Britain in Pete Townshend's Quadrophenia

FOS

Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis

In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed