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Introduction:
Due to demographic change and lack of health care personnel new solutions like preventive home visits (PHV) are necessary. PHV reduces the risk of long-term care and therefore, enables older people to live in their home as long as possible.
Aim of the study:
The aim of this study is to analyse the acceptance of PHV and the effect of PHV on health status of the older people.
Methods:
In this mixed method study PHV as a nursing intervention will be offered to people older than 65 years, not yet eligible for benefits from the long-term care insurance and living in Emlichheim, a region in the northwestern part of Lower Saxony. A sample of 75 people is determined. The health status will be recorded with the Short Form 12 questionnaire. Fifteen semi-structured interviews will be performed to investigate acceptance of the PHV intervention. Quantitative data will be analysed using inferential statistics, qualitative data will be analysed using content analysis. Ethical approval has been obtained.
Results:
It is expected that the findings of this study complete current knowledge about the concept of PHV.
Practical relevance:
This study is of high practical relevance, because additional insights of acceptance might enable the adaption of the PHV concept. Furthermore, increased knowledge and motivation for preventive behaviour of the older people is anticipated in order to extend their autonomy. The results of this study could contribute to the implementation of PHV in Germany, especially in rural areas. It tends to allow a self-determined life in their familiar environment for the older people, as the biggest need of this group.
Companies and R&D institutions increasingly collaborate not only in isolated projects but also in knowledge-based networks. In those networks, participants combine expertise and applied problems to generate both ‘problem-solving knowledge’ and specialized knowledge: during the process of common problem-solving each partner acquires some of the specialized knowledge of the other partners as well as the newly generated problem-solving knowledge. This article examines the basic principles involved and provides a simple mathematical description of the step-by-step accumulation of knowledge through the solving of applied problems in a knowledge-based network. The rate of increase of the total amount of available knowledge in the network is derived and implications for the orientation of R&D institutes and companies are set out.