Prevalence and incidence of iron deficiency in European community-dwelling older adults : An observational analysis of the DO-HEALTH trial

Background and aim Iron deficiency is associated with increased morbidity and mortality in older adults. However, data on its prevalence and incidence among older adults is limited. The aim of this study was to investigate the prevalence and incidence of iron deficiency in European community-dwelling older adults aged ≥ 70 years. Methods Secondary analysis of the DO-HEALTH trial, a 3-year clinical trial including 2157 community-dwelling adults aged ≥ 70 years from Austria, France, Germany, Portugal and Switzerland. Iron deficiency was defined as soluble transferrin receptor (sTfR) > 28.1 nmol/L. Prevalence and incidence rate (IR) of iron deficiency per 100 person-years were examined overall and stratified by sex, age group, and country. Sensitivity analysis for three commonly used definitions of iron deficiency (ferritin  1.5) were also performed. Results Out of 2157 participants, 2141 had sTfR measured at baseline (mean age 74.9 years; 61.5% women). The prevalence of iron deficiency at baseline was 26.8%, and did not differ by sex, but by age (35.6% in age group ≥ 80, 29.3% in age group 75–79, 23.2% in age group 70–74); P  1.5. Occurrences of iron deficiency were observed with IR per 100 person-years of 9.2 (95% CI 8.3–10.1) and did not significantly differ by sex or age group. The highest IR per 100 person-years was observed in Austria (20.8, 95% CI 16.1–26.9), the lowest in Germany (6.1, 95% CI 4.7–8.0). Regarding the other definitions of iron deficiency, the IR per 100 person-years was 4.5 (95% CI 4.0–4.9) for ferritin  1.5. Conclusions Iron deficiency is frequent among relatively healthy European older adults, with people aged ≥ 80 years and residence in Austria and Portugal associated with the highest risk

Empirical Evaluation of Interactive Multimodal Error Correction

Recently, the first commercial dictation systems for continuous speech have become available. Although they generally received positive reviews, error correction is still limited to choosing from list of alternatives, speaking again or typing. We developed a set of multimodal interactive correction methods which allow the user to switch modality between continuous speech, spelling, handwriting and pen gestures. We integrated these correction methods with our large vocabulary speech recognition system to build a prototypical multimodal listening typewriter. We designed an experiment to empirically evaluate the efficiency of different error correction methods. The experiment compares multimodal correction with methods available in current speech recognition applications. We confirm the hypothesis that switching modality can significantly expedite corrections. However in applications where a keyboard is acceptable, typing correction remains the fastest method to correct errors for users..

Interactive Systems Laboratories

Our research addresses two issues that will be crucial in the successful development of emerging multimodal user interfaces: how the problem of interpretation errors can be addressed, and how to evaluate such applications. We present results from a user study that compares multimodal correction methods with conventional correction methods (with and without keyboard input). The study confirms the hypothesis that multimodal correction expedites keyboard-less correction in speech user interfaces. Choice between modalities for experienced users is driven by correction accuracy; however there is initially a strong bias towards using speech. We also present a performance model of multimodal human-computer interaction that predicts input speeds including the time necessary for correction of recognition errors. We apply the model to important issues in speech user interfaces, such as what recognition accuracy is necessary to make multimodal input faster than typing, and we extrapolate results from the user study. To evaluate multimodal applications more effectively, a combination of user studies and modelbased predictions is proposed