Validation of the PAM-13 instrument in the Hungarian general population 40 years old and above.

BACKGROUND: Patient activation comprises the skills, knowledge and motivation necessary for patients' effective contribution to their care. We adapted and validated the 13-item Patient Activation Measure (PAM-13) in the ≥ 40 years old Hungarian general population. METHODS: A cross-sectional web survey was conducted among 900 respondents selected from an online panel via quota sampling. After 10 days, the survey was repeated on 100 respondents. The distribution, internal consistency, test-retest reliability, factor structure, convergent, discriminant and known-groups validity of PAM-13 were assessed according to the COSMIN guidelines. RESULTS: The sample comprised 779 respondents. Mean (± SD) age was 60.4 ± 10.6 years, 54% were female and 67% had chronic illness. Mean (± SD) PAM-13 score was 60.6 ± 10.0. We found good internal consistency (Cronbach alpha: 0.77), moderate test-retest reliability (ICC: 0.62; n = 75), a single-factor structure and good content validity: PAM-13 showed moderate correlation with the eHealth Literacy Scale (r = 0.40), and no correlation with age (r = 0.02), education (r = 0.04) or income (ρ = 0.04). Higher PAM-13 scores were associated with fewer lifestyle risks (p < 0.001), more frequent health information seeking (p < 0.001), participation in patient education (p = 0.018) and various online health-related behaviours. When controlling for health literacy, sociodemographic factors and health status, the association of higher PAM-13 scores with overall fewer lifestyle risks, normal body mass index, physical activity and adequate diet remained significant. Similar properties were observed in the subgroup of participants with chronic morbidity, but not in the age group 65+. CONCLUSION: PAM-13 demonstrated good validity in the general population. Its properties in clinical populations and the elderly as well as responsiveness to interventions warrant further research.

Exploring eHealth Literacy and Patient-Reported Experiences With Outpatient Care in the Hungarian General Adult Population: Cross-Sectional Study.

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.

Psychometric properties of the Hungarian version of the eHealth Literacy Scale.

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.

Subjective expectations regarding ageing: a cross-sectional online population survey in Hungary.

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.

Subjective expectations regarding length and health-related quality of life in Hungary: results from an empirical investigation.

BACKGROUND: Subjective expectations regarding future health are rarely studied, yet may have implications for medical decision making, health behaviour and health economic analysis. OBJECTIVE: To study people's subjective expectations regarding length and future quality of life in Hungary and compare these with previous findings from the Netherlands. METHODS: A cross-sectional survey was performed, using a questionnaire that was put on a highly frequented web journal during 1 day. Main socio-demographic variables and health status of the voluntary participants were registered using the EQ-5D questionnaire. People were asked about the age they expected to live and the health status they expected to have at ages 60, 70, 80 and 90, using the EQ-5D descriptive system. Responses were matched and compared to age- and gender-specific life expectancy data from the Hungarian National Statistics and to age- and gender-specific EQ-5D scores from a prior nationally representative survey in Hungary. RESULTS: In total, 9407 people were included in the analysis with mean age of 36.1 (SD 10.6) years, mainly qualified (degree 74.0%), employed (86.0%) men (67.1%). People overestimated their life expectancy (women, 1.6; men, 8.2 years) and expected a sharp deterioration in health at the age 70. Age, current health status, perception of a healthy lifestyle and kins' age at death were important explanatory factors for subjective expectations. Subjective life expectancy correlates strongly with expected future health status. CONCLUSIONS: The striking similarities between two surveys from distinct nations suggest that people's (mis)expectations regarding length and future quality of life are probably rather generalizable between jurisdictions within Europe.