Unconscious bias may interfere with the interpretation of research from some settings, particularly from lower-income countries. Most studies of this phenomenon have relied on indirect outcomes such as article citation counts and publication rates; few have addressed or proven the effect of unconscious bias in evidence interpretation. In this randomized, blinded crossover experiment in a sample of 347 English clinicians, we demonstrate that changing the source of a research abstract from a low- to a high-income country significantly improves how it is viewed, all else being equal. Using fixed-effects models, we measured differences in ratings for strength of evidence, relevance, and likelihood of referral to a peer. Having a high-income-country source had a significant overall impact on respondents' ratings of relevance and recommendation to a peer. Unconscious bias can have far-reaching implications for the diffusion of knowledge and innovations from low-income countries.

Background:The rising financial burden of cancer on health-care systems worldwide has led to the increased demand for evidence-based research on which to base reimbursement decisions. Economic evaluations are an integral component of this necessary research. Ascertainment of reliable health-care cost and quality-of-life estimates to inform such studies has historically been challenging, but recent advances in informatics in the United Kingdom provide new opportunities.Methods:The costs of hospital care for breast, colorectal and prostate cancer disease-free survivors were calculated over 15 months from initial diagnosis of cancer using routinely collected data within a UK National Health Service (NHS) Hospital Trust. Costs were linked at patient level to patient-reported outcomes and registry-derived sociodemographic factors. Predictors of cost and the relationship between costs and patient-reported utility were examined.Results:The study population included 223 breast cancer patients, 145 colorectal and 104 prostate cancer patients. The mean 15-month cumulative health-care costs were £12 595 (95% CI £11 517–£13 722), £12 643 (£11 282–£14 102) and £3722 (£3263–£4208), per-patient respectively. The majority of costs occurred within the first 6 months from diagnosis. Clinical stage was the most important predictor of costs for all cancer types. EQ-5D score was predictive of costs in colorectal cancer but not in breast or prostate cancer.Conclusion:It is now possible to evaluate health-care cost using routine NHS data sets. Such methods can be utilised in future retrospective and prospective studies to efficiently collect economic data.

This study investigates heterogeneous response to state cigarette tax increases using unconditional quantile regression (UQR). We make two contributions to the empirical policy analysis literature. First, we argue that UQR provides more policy‐relevant information than conventional quantile regression in most empirical state policy analyses. Second, we document cigarette tax elasticity across a sample of adult smokers in the Current Population Survey Tobacco Use Supplements between 1992 and 2011. Our ordinary least squares regression show an imprecise negative relationship between taxes and cigarettes smoked in the past 30 days, while UQR reveals a U‐shaped relationship: Only moderate smokers reduce their smoking following a cigarette tax increase, and the magnitude of the effect is small. A $1.00 (135 percent) increase in the cigarette tax leads to a 3.5 percent reduction in the number of cigarettes smoked in the past 30 days among the most responsive smokers (implied tax elasticity = −0.03).

Objective Studies have found that illness perceptions explain significant variance in health outcomes in numerous diseases. However, most of the research is cross‐sectional and non‐oncological. We examined, for the first time in breast, colorectal and prostate cancer patients, if cognitive and emotional illness perceptions near diagnosis predict future multidimensional health‐related quality of life (HRQoL). Methods UK‐based patients (N = 334) completed the illness perception questionnaire‐revised within 6 months post‐diagnosis and the quality of life in adult cancer survivors scale 15 months post‐diagnosis. Sociodemographic and clinical data were obtained from medical records. Hierarchical multiple regression analyses were conducted. Results The sociodemographic and clinical factors collectively significantly predicted 8/12 HRQoL domains, although for 5/8 accounted for <10% of the variance. For all 12 HRQoL domains, illness perceptions collectively explained significant substantial additional variance (∆R2 range: 5.6–27.9%), and a single illness perception questionnaire‐revised dimension was the best individual predictor of 9/12 HRQoL domains. The consequences dimension independently predicted 7/12 HRQoL domains; patients who believed their cancer would have a more serious negative impact on their life reported poorer future HRQoL. The emotional representations and identity dimensions also predicted multiple HRQoL domains. Conclusions Future research should focus on realising the potential of illness perceptions as a modifiable target for and mediating mechanism of interventions to improve patients' HRQoL. Copyright © 2015 John Wiley & Sons, Ltd.

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