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Background If UK healthcare services are to respond effectively to pandemic influenza, levels of absenteeism amongst healthcare workers (HCWs) must be minimised. Current estimates of the likelihood that HCWs will continue to attend work during a pandemic are subject to scientific and predictive uncertainty, yet an informed evidence base is needed if contingency plans addressing the issues of HCW absenteeism are to be prepared. Methods This paper reports the findings of a self-completed survey of randomly selected HCWs across three purposively sampled healthcare trusts in the West Midlands. The survey aimed to identify the factors positively or negatively associated with willingness to work during an influenza pandemic, and to evaluate the acceptability of potential interventions or changes to working practice to promote the continued presence at work of those otherwise unwilling or unable to attend. 'Likelihood' and 'persuadability' scores were calculated for each respondent according to indications of whether or not they were likely to work under different circumstances. Binary logistic regression was used to compute bivariate and multivariate odds ratios to evaluate the association of demographic variables and other respondent characteristics with the self-described likelihood of reporting to work. Results The survey response rate was 34.4% (n = 1032). Results suggest absenteeism may be as high as 85% at any point during a pandemic, with potential absence particularly concentrated amongst nursing and ancillary workers (OR 0.3; 95% CI 0.1 to 0.7 and 0.5; 95% CI 0.2 to 0.9 respectively). Conclusion Levels of absenteeism amongst HCWs may be considerably higher than official estimates, with potential absence concentrated amongst certain groups of employees. Although interventions designed to minimise absenteeism should target HCWs with a low stated likelihood of working, members of these groups may also be the least receptive to such interventions. Changes to working conditions which reduce barriers to the ability to work may not address barriers linked to willingness to work, and may fail to overcome HCWs' reluctance to work in the face of what may still be deemed unacceptable risk to self and/or family.

Background Patient-reported outcomes (PROs), such as health-related quality of life (HRQL) are increasingly used to evaluate treatment effectiveness in clinical trials, are valued by patients, and may inform important decisions in the clinical setting. It is of concern, therefore, that preliminary evidence, gained from group discussions at UK-wide Medical Research Council (MRC) quality of life training days, suggests there are inconsistent standards of HRQL data collection in trials and appropriate training and education is often lacking. Our objective was to investigate these reports, to determine if they represented isolated experiences, or were indicative of a potentially wider problem. Methods And Findings We undertook a qualitative study, conducting 26 semi-structured interviews with research nurses, data managers, trial coordinators and research facilitators involved in the collection and entry of HRQL data in clinical trials, across one primary care NHS trust, two secondary care NHS trusts and two clinical trials units in the UK. We used conventional content analysis to analyze and interpret our data. Our study participants reported (1) inconsistent standards in HRQL measurement, both between, and within, trials, which appeared to risk the introduction of bias; (2), difficulties in dealing with HRQL data that raised concern for the well-being of the trial participant, which in some instances led to the delivery of non-protocol driven co-interventions, (3), a frequent lack of HRQL protocol content and appropriate training and education of trial staff, and (4) that HRQL data collection could be associated with emotional and/or ethical burden. Conclusions Our findings suggest there are inconsistencies in the standards of HRQL data collection in some trials resulting from a general lack of HRQL-specific protocol content, training and education. These inconsistencies could lead to biased HRQL trial results. Future research should aim to develop HRQL guidelines and training programmes aimed at supporting researchers to carry out high quality data collection.