Open Access

Background: Often preventive measures are not accessed by the people who were intended to be reached. Programs for older adults may target men and women, older adults, advanced old age groups and/or chronically ill patients with specific indications. The defined target groups rarely participate in the conception of programs or in the design of information materials, although this would increase accessibility and participation. In the German “Reaching the Elderly” study (2008–2011), an approach to motivating older adults to participate in a preventive home visit (PHV) program was modified with the participatory involvement of the target groups. The study examines how older men and women would prefer to be addressed for health and prevention programs. Methods: Four focus groups (N = 42 participants) and 12 personal interviews were conducted (women and men in 2 age groups: 65–75 years and ≥ 76 years). Participants from two districts of a major German city were selected from a stratified random sample (N = 200) based on routine data from a local health insurance fund. The study focused on the participants’ knowledge about health and disease prevention and how they preferred to be approached and addressed. Videos of the focus groups were recorded and analysed using mind mapping techniques. Interviews were digitally recorded, transcribed verbatim and subjected to qualitative content analysis. Results: A gender-specific approach profile was observed. Men were more likely to favor competitive and exerciseoriented activities, and they associated healthy aging with mobility and physical activity. Women, on the other hand, displayed a broader understanding of healthy aging, which included physical activity as only one aspect as well as a healthy diet, relaxation/wellness, memory training and independent living; they preferred holistic and socially oriented services that were not performance-oriented. The “older seniors” (76+) were ambivalent towards certain wordings referring to aging. Conclusions: Our results suggest that gender-specific needs must be considered in order to motivate older adults to participate in preventive services. Age-specific characteristics seem to be less relevant. It is more important to pay attention to factors that vary according to the individual state of health and life situation of the potential participants.

Semantic classification of words using distributional features is usually based on the semantic similarity of words. We show on two different datasets that a trained classifier using the distributional features directly gives better results. We use Support Vector Machines (SVM) and Multirelational Matrix Factorization (MRMF) to train classifiers. Both give similar results. However, MRMF, that was not used for semantic classification with distributional features before, can easily be extended with more matrices containing more information from different sources on the same problem. We demonstrate the effectiveness of the novel approach by including information from WordNet. Thus we show, that MRMF provides an interesting approach for building semantic classifiers that (1) gives better results than unsupervised approaches based on vector similarity, (2) gives similar results as other supervised methods and (3) can naturally be extended with other sources of information in order to improve the results.

In distributional semantics words are represented by aggregated context features. The similarity of words can be computed by comparing their feature vectors. Thus, we can predict whether two words are synonymous or similar with respect to some other semantic relation. We will show on six different datasets of pairs of similar and non-similar words that a supervised learning algorithm on feature vectors representing pairs of words outperforms cosine similarity between vectors representing single words. We compared different methods to construct a feature vector representing a pair of words. We show that simple methods like pairwise addition or multiplication give better results than a recently proposed method that combines different types of features. The semantic relation we consider is relatedness of terms in thesauri for intellectual document classification. Thus our findings can directly be applied for the maintenance and extension of such thesauri. To the best of our knowledge this relation was not considered before in the field of distributional semantics.

The purpose of this study is to investigate the market potential in the German outdoor apparel industry by focusing on sustainable production in terms of environmental and human health. A literature study of the Cradle to Cradle (C2C) design concept is provided, as it represents a solution for pollution, waste and environmental destruction caused by the current industrial design and waste management. The data for the subsequent market- and competitive analysis of the German outdoor apparel industry was collected through secondary research in order to identify several key market indicators for the assessment of the market potential. The outcome of this research is the identification of a positioning strategy for outdoor apparel according to the C2C design concept. The results show stagnant growth rates in recent years in the German outdoor apparel market and strong rivalry among the competitors. However, a significant market potential was calculated and beneficial trends for sustainable outdoor brands were recognised. These findings reveal the existence of a market potential for an outdoor apparel brand according to the C2C design concept. By following a positioning strategy of transparency and full commitment to a sustainable production, the company might be able to gain market shares from its competitors, as future predictions indicate slow growth rates in the market. The results of this analysis can be of great interest for entrepreneurs that plan to enter the German outdoor apparel industry.

Background: Physician-rating websites have become a popular tool to create more transparency about the quality of health care providers. So far, it remains unknown whether online-based rating websites have the potential to contribute to a better standard of care. Objective: Our goal was to examine which health care providers use online rating websites and for what purposes, and whether health care providers use online patient ratings to improve patient care. Methods: We conducted an online-based cross-sectional study by surveying 2360 physicians and other health care providers (September 2015). In addition to descriptive statistics, we performed multilevel logistic regression models to ascertain the effects of providers' demographics as well as report card-related variables on the likelihood that providers implement measures to improve patient care. Results: Overall, more than half of the responding providers surveyed (54.66%, 1290/2360) used online ratings to derive measures to improve patient care (implemented measures: mean 3.06, SD 2.29). Ophthalmologists (68%, 40/59) and gynecologists (65.4%, 123/188) were most likely to implement any measures. The most widely implemented quality measures were related to communication with patients (28.77%, 679/2360), the appointment scheduling process (23.60%, 557/2360), and office workflow (21.23%, 501/2360). Scaled-survey results had a greater impact on deriving measures than narrative comments. Multilevel logistic regression models revealed medical specialty, the frequency of report card use, and the appraisal of the trustworthiness of scaled-survey ratings to be significantly associated predictors for implementing measures to improve patient care because of online ratings. Conclusions: Our results suggest that online ratings displayed on physician-rating websites have an impact on patient care. Despite the limitations of our study and unintended consequences of physician-rating websites, they still may have the potential to improve patient care.