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Background: Regular blood donors are the cornerstone of blood safety. Understanding the donors' behavior to donate blood improves blood donor retention programs. The purpose of this study is to evaluate the return rate of first-time blood donors following different interventions to identify effective ways to retain first-time donors.Study Design and Methods: The study was conducted on 1356 first-time blood donors at four main blood centers in Iran. The donors were randomly assigned based on different interventions (phone calls, educational letter, emotional letter, incentive, motivational meeting, and no intervention) to six groups. The return rate of donors was defined as a second attempt to donate within 6 months after the first donation. Return rate and 95% confidence intervals (CIs) were calculated and compared among different groups.Results: A total of 394 (29%) donors returned within 6 months for a second donation (95% CI, 0.26-0.31). The return rate in the emotional letter group, educational letter, phone reminder, incentives, motivational meeting, and control groups was 36% (95% CI, 0.31-0.42), 33.2% (95% CI, 0.27-0.38), 31.5% (95% CI, 0.25-0.37), 30% (95% CI, 0.22-0.38), 22% (95% CI, 0.17-0.27) and 22.1% (95% CI, 0.17-0.27), respectively.Conclusions: This study provides evidence supporting the fact that more first-time blood donors can be motivated to donate again by implementing targeted interventions. It demonstrates that emotional letters, educational letters, and phone reminders were effective in improving the return rate of first-time donors. [ABSTRACT FROM AUTHOR]

Abstract: Aims: To assess the cost‐effectiveness of alternative smoking cessation scenarios from the perspective of the Spanish National Health Service (NHS). Design: We used the European study on Quantifying Utility of Investment in Protection from Tobacco model (EQUIPTMOD), a Markov‐based state transition economic model, to estimate the return on investment (ROI) of: (a) the current provision of smoking cessation services (brief physician advice and printed self‐helped material + smoking ban and tobacco duty at current levels); and (b) four alternative scenarios to complement the current provision: coverage of proactive telephone calls; nicotine replacement therapy (mono and combo) [prescription nicotine replacement therapy (Rx NRT)]; varenicline (standard duration); or bupropion. A rate of 3% was used to discount life‐time costs and benefits. Setting: Spain. Participants: Adult smoking population (16+ years). Measurements: Health‐care costs associated with treatment of smoking attributable diseases (lung cancer, coronary heart disease, chronic obstructive pulmonary infection and stroke); intervention costs; quality‐adjusted life years (QALYs). Costs and outcomes were summarized using various ROI estimates. Findings: The cost of implementing the current provision of smoking cessation services is approximately €61 million in the current year. This translates to 18 quitters per 1000 smokers and a life‐time benefit–cost ratio of 5, compared with no such provision. All alternative scenarios were dominant (cost‐saving: less expensive to run and generated more QALYs) from the life‐time perspective, compared with the current provision. The life‐time benefit–cost ratios were: 1.87 (proactive telephone calls); 1.17 (Rx NRT); 2.40 (varenicline‐standard duration); and bupropion (2.18). The results remained robust in the sensitivity analysis. Conclusions: According to the EQUIPTMOD modelling tool it would be cost‐effective for the Spanish authorities to expand the reach of existing GP brief interventions for smoking cessation, provide pro‐active telephone support, and reimburse smoking cessation medication to smokers trying to stop. Such policies would more than pay for themselves in the long run. [ABSTRACT FROM AUTHOR]

Abstract: Aims: To evaluate costs, effects and cost‐effectiveness of increased reach of specific smoking cessation interventions in Germany. Design: A Markov‐based state transition return on investment model (EQUIPTMOD) was used to evaluate current smoking cessation interventions as well as two prospective investment scenarios. A health‐care perspective (extended to include out‐of‐pocket payments) with life‐time horizon was considered. A probabilistic analysis was used to assess uncertainty concerning predicted estimates. Setting: Germany. Participants: Cohort of current smoking population (18+ years) in Germany. Interventions: Interventions included group‐based behavioural support, financial incentive programmes and varenicline. For prospective scenario 1 the reach of group‐based behavioral support, financial incentive programme and varenicline was increased by 1% of yearly quit attempts (= 57 915 quit attempts), while prospective scenario 2 represented a higher reach, mirroring the levels observed in England. Measurements: EQUIPTMOD considered reach, intervention cost, number of quitters, quality‐of‐life years (QALYs) gained, cost‐effectiveness and return on investment. Findings: The highest returns through reduction in smoking‐related health‐care costs were seen for the financial incentive programme (€2.71 per €1 invested), followed by that of group‐based behavioural support (€1.63 per €1 invested), compared with no interventions. Varenicline had lower returns (€1.02 per €1 invested) than the other two interventions. At the population level, prospective scenario 1 led to 15 034 QALYs gained and €27 million cost‐savings, compared with current investment. Intervention effects and reach contributed most to the uncertainty around the return‐on‐investment estimates. At a hypothetical willingness‐to‐pay threshold of only €5000, the probability of being cost‐effective is approximately 75% for prospective scenario 1. Conclusions: Increasing the reach of group‐based behavioural support, financial incentives and varenicline for smoking cessation by just 1% of current annual quit attempts provides a strategy to German policymakers that improves the population's health outcomes and that may be considered cost‐effective. [ABSTRACT FROM AUTHOR]

Long-horizon predictive regressions in finance pose formidable econometric problems when estimated using avail-able sample sizes. Hodrick in 1992 proposed a remedy that is based on running a reverse regression of short-horizon returns on the long-run mean of the predictor. Unfortunately, this only allows the null of no predictability to be tested, and assumes stationary regressors. In this paper, we revisit long-horizon forecasting from reverse regressions, and argue that reverse regression methods avoid serious size distortions in long-horizon predictive regressions, even when there is some predictability and/or near unit roots. Meanwhile, the reverse regression meth-odology has the practical advantage of being easily applicable when there are many predictors. We apply these methods to forecasting excess bond returns using the term structure of forward rates, and find that there is indeed some return forecastability. However, confidence intervals for the coefficients of the predictive regressions are about twice as wide as those obtained with the conventional approach to inference. We also include an application to forecasting excess stock returns. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]