In the future, an increasing number of elderly people will be asked to accept care delivered through the Internet. For example, health-care professionals can provide treatment or support via telecare. But do elderly people intend to use such so-called e-Health applications? The objective of this study is to gain insight into the intention of older people, i.e. the elderly of the future, to use e-Health applications. Using elements of the Unified Theory of Acceptance and Use of Technology (UTAUT), we hypothesized that their intention is related to the belief that e-Health will help (performance expectancy), the perceived ease of use (effort expectancy), the beliefs of important others (social influence), and the self-efficacy concerning Internet usage. A pre-structured questionnaire was completed by 1014 people aged between 57 and 77 (response 67%). The hypothesized relationships were tested using nested linear regression analyses. If offered an e-Health application in the future, 63.1% of the respondents would definitely or probably use it. In general, people with a lower level of education had less intention of using e-Health. The majority of respondents perceived e-Health as easy to use (60.8%) and easy to learn (68.4%), items that constitute the scale for effort expectancy. Items in the performance expectancy scale generally scored lower: 45.8% perceived e-Health as useful and 38.2% perceived it as a pleasant way to interact. The tested model showed that expected performance and effort were highly related to intention to use e-Health. In addition, self-efficacy was related to intention to use while social influence was not. Acceptance of e-Health can be increased by informing people about the potential benefits of e-Health and letting them practice with the application. Special attention should be paid to people with less education and people who have not used the Internet before.

Patients vary in their preferences towards involvement in medical decision-making. Previous research, however, gives no clear explanation for this observed variation in their involvement. One possible explanation might be health literacy. Health literacy refers to personal characteristics and social resources needed for people to access, understand and use information to make decisions about their health. This study aimed to examine the relationship between health literacy and self-reported patient involvement. With respect to health literacy, we focused on those competences relevant for medical decision-making. We hypothesized that people with higher health literacy report that they are more involved in medical decision-making. A structured questionnaire was sent to members of the Dutch Health Care Consumer Panel in May 2015 (response 46%, N = 974). Health literacy was measured using five scales of the Health Literacy Questionnaire. A regression model was used to estimate the relationship between health literacy and self-reported involvement. In general, our results did not show a relationship between health literacy and self-reported involvement. We did find a positive significant association between the health literacy scale appraisal of health information and self-reported involvement. Our hypothesis was partly confirmed. The results from this study suggest that higher order competences, that is to say critical health literacy, in particular, are important in reporting involvement in medical decision-making. Future research is recommended to unravel further the relationship between health literacy and patient involvement in order to gain insight into whether health literacy might be an asset to enhance patient participation in medical decision-making.

Clinical informatics, decision support for health professionals, electronic health records, and ehealth infrastructures.

Increasing antibiotic resistance is recognized as a major threat to global health and is related to antibiotic prescription rates in primary care. Shared decision-making (SDM), the process in which patients and doctors participate together in making decisions, is argued to possibly promote more appropriate use of antibiotics and reduce prescribing. However, it is unknown whether in practice fewer antibiotics are prescribed where more SDM takes place. To investigate whether more SDM is related to less antibiotic prescribing and whether this relationship differs between subgroups of patients (male/female and age groups). A questionnaire survey was conducted among 2670 members of the Dutch Health Care Consumer Panel to measure SDM (response rate 45%). Average practice-level SDM scores were calculated for 15 general practices. Data from routine electronic health records of 8192 adult patients of these general practices participating in the Nivel Primary Care Database were used to assess relevant illness episodes (acute cough, acute rhinosinusitis and urinary tract infection), the indication for antibiotics and antibiotic prescriptions. Logistic multilevel regression analyses were performed to investigate the relationship between practice-level SDM and patient-level antibiotic prescriptions. In practices where more SDM takes place, general practitioners prescribed fewer antibiotics for adult patients under the age of 40 years in preference-sensitive situations (i.e. situations in which antibiotics could be considered according to clinical guidelines). SDM can be a framework to reduce the prescribing of antibiotics and thus to control antibiotic resistance.

In the Netherlands, ethnic minority populations visit their general practitioner (GP) more often than the indigenous population. An explanation for this association is lacking. Recently, health literacy is suggested as a possible explaining mechanism. Internationally, associations between health literacy and health care use, and between ethnicity and health literacy have been studied separately, but, so far, have not been linked to each other. In the Netherlands, some expectations have been expressed with regard to supposed low health literacy of ethnic minority groups, however, no empirical study has been done so far. The objectives of this study are therefore to acquire insight into the level of health literacy of ethnic minorities in the Netherlands and to examine whether the relationship between ethnicity and health care use can be (partly) explained by health literacy. A questionnaire was sent to a sample of 2.116 members of the Dutch Health Care Consumer Panel (response rate 46%, 89 respondents of non-western origin). Health literacy was measured with the Health Literacy Questionnaire (HLQ) which covers nine different domains. The health literacy levels of ethnic minority groups were compared to the indigenous population. A negative binomial regression model was used to estimate the association between ethnicity and GP visits. To examine whether health literacy is an explaining factor in this association, health literacy and interaction terms of health literacy and ethnicity were added into the model. Differences in levels of health literacy were only found between the Turkish population and the indigenous Dutch population. This study also found an association between ethnicity and GP visits. Ethnic minorities visit their GP 33% more often than the indigenous population. Three domains of the HLQ (the ability to navigate the health care system, the ability to find information and to read and understand health information) partly explained the association between ethnicity and GP visits. In general, there are no differences in health literacy between most of the ethnic minority groups in the Netherlands and the indigenous Dutch population. Only the Turkish population scored significantly lower on several health literacy domains. Some domains of health literacy do explain the association between ethnicity and higher frequency of GP visits. Further research is recommended to understand the pathways through which health literacy impacts health care use.