Background We adapted the eHealth Literacy Scale (eHEALS) for Hungary and tested its psychometric properties on a large representative online sample of the general population. Methods The Hungarian version of eHEALS was developed using forward–backward translation. For the valuation study, 1000 respondents were recruited in early 2019 from a large online panel by a survey company. We tested internal consistency, test–retest reliability and construct and criterion validity using classical test theory, as well as item characteristics using an item-response theory (IRT) graded response model (GRM). Results 55% of respondents were female, and 22.1% were ≥ 65 years old. Mean eHEALS score was 29.2 (SD: 5.18). Internal consistency was good (Cronbach’s α = 0.90), and test–retest reliability was moderate (intraclass correlation r = 0.64). We identified a single-factor structure by exploratory factor analysis, explaining 85% of test variance. Essential criteria for GRM analysis were met. Items 3 and 4 (search of health resources) were the least difficult, followed by items 5 and 8 (utilisation of health information), and then items 1 and 2 (awareness of health resources). Items 6 and 7 (appraisal of health resources) were most difficult. The measurement properties of eHEALS were not affected by gender, age, education or income levels. Female gender, older age, intensity of health information seeking, formal health education and visit at the electronic health-record website were associated with higher eHEALS scores, as well as best and worst self-perceived health states, BMI < 25 and participation at health screenings over the past year. Conclusions The Hungarian eHEALS is a useful and valid tool for measuring subjective eHealth literacy. Electronic supplementary material The online version of this article (10.1007/s10198-019-01062-1) contains supplementary material, which is available to authorized users.

Background Subjective expectations regarding future health are rarely studied, yet may have implications for medical decision making, health behaviour and health economic analysis.

The PsAQoL, the HAQ, and the EQ-5D are able to distinguish well across levels of PsA severity.

Background We aimed to investigate individuals' subjective expectations regarding health and happiness alongside their provisions on life circumstances for older ages. Methods A cross-sectional online survey was performed involving a representative sample (N = 1000; mean age 50.9, SD = 15.4; female 54.5%) in Hungary. Subjective expectations on health status (EQ-5D-3L/-5L, GALI, WHO-5), happiness (0-10 VAS), employment status, care time, and forms of care for ages 60, 70, 80, and 90 were surveyed. Results Current mean EQ-5D-5L was 0.869 (SD = 0.164) and happiness was 6.7 (SD = 2.4). Subjective life expectancy was 80.9 (SD = 11.1), and median expected retirement age was 65. Mean expected EQ-5D-5L for ages 60/70/80/90 was 0.761/0.684/0.554/0.402, and no activity limitations (GALI) were expected by 64%/40%/18%/14%, respectively. Expected happiness score was 6.8/6.7/6.2/5.7, and a decrease in mental well-being (WHO-5) was provisioned. A substantial increase in drug expenses and care time was anticipated, but only 52% thought to have extra income besides pension. The great majority expected to be helped by the family (77%/72%/53%/40%) if needed. Educational level, GALI, and longevity expectations were significant predictors of EQ-5D-5L expectations using a standard 5% significance level of decision. Current happiness was major determinant of expected future happiness. Conclusions Individuals expect a significant deterioration of health with age but only a moderate decrease in happiness. Overestimation of future activity limitations suggests a gap between statistical and subjective healthy life expectancy. The majority expects to rely on informal care in the elderly. Raise in retirement age is underestimated. Our results can be used as inputs for economic modelling of labor force participation and ageing.

A felsőoktatási szféra mindennapjait elsősorban a jogok és a kötelezettségek rendje határozza meg. A felvételi követelményektől az államvizsga feltételeinek teljesítéséig transzparens szabályok sokaságát kell teljesítenie minden egyetemi, főiskolai polgárnak. A felsőoktatásban tanítók felelősségéről kevesebb szó esik, pedig az oktatók magatartása, viselkedéskultúrája komoly hatással bír a hallgatók további életszakaszaira. A szerzők az oktatói felelősség kérdéseit a XXI. század első negyedére fókuszálják, és a hazai közgazdasági felsőoktatás viszonyait elemzik több évtizedes tapasztalatuk alapján. A gazdaságpolitika, a statisztika, az ökonometria, és a számvitel területéről hozott példákkal illusztrálják a felsőoktatók felelősségét. Fő megállapításuk az, hogy a világban, és az emberek magánéletében lejátszódó folyamatok miatt a tanári felelősség fokozatosan nő. Az egyetemi, főiskolai oktatóknak a katedrán tartózkodniuk kell saját politikai véleményük sugalmazásától.

Background Digital health, which encompasses the use of information and communications technology in support of health, is a key driving force behind the cultural transformation of medicine toward people-centeredness. Thus, eHealth literacy, assisted by innovative digital health solutions, may support better experiences of care. Objective The purpose of this study is to explore the relationship between eHealth literacy and patient-reported experience measures (PREMs) among users of outpatient care in Hungary. Methods In early 2019, we conducted a cross-sectional survey on a large representative online sample recruited from the Hungarian general population. eHealth literacy was measured with the eHealth Literacy Scale (eHEALS). PREMs with outpatient care were measured with a set of questions recommended by the Organisation for Economic Co-operation and Development (OECD) for respondents who attended outpatient visit within 12 months preceding the survey. Bivariate relationships were explored via polychoric correlation, the Kruskal–Wallis test, and chi-square test. To capture nonlinear associations, after controlling covariates, we analyzed the relationship between eHEALS quartiles and PREMs using multivariate probit, ordinary least squares, ordered logit, and logistic regression models. Results From 1000 survey respondents, 666 individuals (364 females, 54.7%) were included in the study with mean age of 48.9 (SD 17.6) years and mean eHEALS score of 29.3 (SD 4.9). Respondents with higher eHEALS scores were more likely to understand the health care professionals’ (HCPs’) explanations (χ29=24.2, P=.002) and to be involved in decision making about care and treatment (χ29=18.2, P=.03). In multivariate regression, respondents with lowest (first quartile) and moderately high (third quartile) eHEALS scores differed significantly, where the latter were more likely to have an overall positive experience (P=.02) and experience fewer problems (P=.02). In addition, those respondents had better experiences in terms of how easy it was to understand the HCPs’ explanations (P<.001) and being able to ask questions during their last consultation (P=.04). Patient-reported experiences of individuals with highest (fourth quartile) and lowest (first quartile) eHEALS levels did not differ significantly in any items of the PREM instrument, and neither did composite PREM scores generated from the PREM items (P>.05 in all models). Conclusions We demonstrated the association between eHealth literacy and PREMs. The potential patient-, physician-, and system-related factors explaining the negative experiences among people with highest levels of eHealth literacy warrant further investigation, which may contribute to the development of efficient eHealth literacy interventions. Further research is needed to establish causal relationship between eHealth literacy and patient-reported experiences.

Cost-utility analyses use the quality-adjusted life-year (QALY) as a measure of health benefit. Normally, they treat every QALY gain equally, that is, attach the same weight (or value) to each QALY gained. However, it appears that this practice does not reflect the distributional preferences of the general public nor of health care professionals. Maximizing the QALY gain from a given budget is not the only aim in priority setting. This article presents a study into such distributional preferences of general practitioners (GPs) for prioritization at the patient level in Hungary. Given the special position GPs have in many health care systems, including the Hungarian, more knowledge of their preferences is important. The authors used a discrete choice experiment to study these preferences, focusing on factors related to the characteristics of the patients, the disease, and treatment effects. Results show that the most important factors influencing the GPs’ decision were the age of the patient, the mortality of the disease, the impact of the disease on patients’ quality of life, and the potential for the full restoration of the previous health status. The treatment of patients without comorbidities was preferred to that of patients with comorbidities. Importantly, these preferences in GPs may steer the actual distribution of health care.

BACKGROUND Digital health, which encompasses the use of information and communications technology in support of health, is a key driving force behind the cultural transformation of medicine towards people-centredness. Thus, eHealth literacy may support better experiences of care supported by innovative digital health solutions. OBJECTIVE To explore the relationship between eHealth literacy and patient-reported experience measures (PREMs) among users of outpatient care in Hungary. METHODS In early 2019, we conducted a cross-sectional survey on a large representative online sample recruited from the Hungarian general population. eHealth literacy was measured with the eHealth Literacy Scale (eHEALS) and PREMs with outpatient care with a set of questions recommended by the Organisation for Economic Co-operation and Development (OECD). Bivariate relationships were explored via polychoric correlation, the Kruskal-Wallis test and chi-square test. To capture non-linear associations, after controlling covariates, we analysed the relationship between eHEALS quartiles and PREMs using multivariate probit, OLS, ordered logit and logistic regression models. RESULTS 653 respondents (356 females, 54.5%) were included in the study with mean age of 49.2 (SD 17.5) and eHEALS score of 29.4 (SD 4.9). Respondents with higher eHEALS score were more likely to understand the healthcare professionals’ explanations (Chi-square(9)=25.6, P=.002) and to be involved in decision-making about care and treatment (Chi-square(9)=18.0, P=.03). In multivariate regression, respondents with lowest (1st quartile) and moderately high (3rd quartile) eHEALS scores differed significantly, where the latter were more likely to have an overall positive experience (P=.03) and experience fewer problems (P=.03). Also, those respondents had better experiences in terms of how easy it was to understand the healthcare professionals’ explanations (P=.002) and being able to ask questions during their last consultation (P=.03). Patient reported experiences of individuals with highest (4th quartile) and lowest (1st quartile) eHEALS levels did not differ significantly. Also, the relationship between eHealth literacy and self-reported unmet medical needs, and waiting times, was not significant. CONCLUSIONS We demonstrated the association between eHealth literacy and PREMs. Individuals with the lowest self-reported eHealth literacy levels have a greater chance of a negative experiences with outpatient care, while those with moderately high eHealth literacy are more likely to have positive experiences. Actions should be taken to identify and support people with low eHealth literacy as they are at higher risk of experiencing problems in outpatient care, and hence, having difficulties to cope with medical treatments. The potential patient-, physician- and system-related factors explaining the negative experiences among people with highest levels of eHealth literacy warrant further investigation.