The Impact of Parental Electronic Health Literacy on Disease Management and Outcomes in Pediatric Type 1 Diabetes Mellitus: Cross-Sectional Clinical Study.

BACKGROUND: Despite the growing uptake of smart technologies in pediatric type 1 diabetes mellitus (T1DM) care, little is known about caregiving parents' skills to deal with electronic health information sources. OBJECTIVE: We aimed to assess the electronic health literacy of parents caring for children with T1DM and investigate its associations with disease management and children's outcomes. METHODS: A cross-sectional survey was performed involving 150 parent-child (8-14 years old with T1DM) dyads in a university pediatric diabetology center. Parents' electronic health literacy (eHealth Literacy Scale [eHEALS]), general health literacy (Chew questionnaire and Newest Vital Sign [NVS]), and attitudes toward T1DM care (Parental Self-Efficacy Scale for Diabetes Management [PSESDM] and Hypoglycemia Fear Survey [HFS]) were investigated. Children's treatment, HbA1c level, and quality of life (Pediatric Quality of Life Inventory Diabetes Module [PedsQL Diab] and EQ-5D-Y-3L) were assessed. Multiple linear regression analysis was performed to investigate the determining factors of 6-month average HbA1c. RESULTS: Of the 150 children, 38 (25.3%) used a pen, 55 (36.7%) used a pen plus a sensor, 6 (4.0%) used an insulin pump, and 51 (34.0%) used an insulin pump plus a sensor. Parents' average eHEALS score (mean 31.2, SD 4.9) differed significantly by educational level (P=.04) and the children's treatment (P=.005), being the highest in the pump + sensor subgroup. The eHEALS score showed significant Pearson correlations with the Chew score (r=-0.45; P<.001), NVS score (r=0.25; P=.002), and PSESDM score (r=0.35; P<.001) but not with the children's HbA1c (r=-0.143; P=.08), PedsQL Diab (r=-0.0002; P>.99), and EQ-5D-Y-3L outcomes (r=-0.13; P=.12). Regression analysis revealed significant associations of the child's HbA1c level with sex (ß=0.58; P=.008), treatment modality (pen + sensor: ß=-0.66; P=.03; pump + sensor: ß=-0.93; P=.007), and parents' self-efficacy (PSESDM; ß=-0.08; P=.001). CONCLUSIONS: Significantly higher parental electronic health literacy was found in T1DM children using a glucose sensor. The electronic health literacy level was associated with parents' diabetes management attitude but not with the child's glycemic control. Studies further investigating the role of parental electronic health literacy in T1DM children managed at different levels of care and the local context are encouraged.

Psychometric Properties of General Oral Health Assessment Index Across Ages: COSMIN Systematic Review.

OBJECTIVES: To systematically review the psychometric properties of the Geriatric Oral Health Assessment Index (GOHAI) across age groups using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) methodology. METHODS: Data: English peer-reviewed articles reporting studies of the development, translation, or validation of GOHAI. SOURCES: PubMed, Web of Science, and EMBASE from Jan 1990 until December 31, 2023. Methodological evaluation: based on COSMIN methodology. The results are presented overall and for 4 age groups (≥60 years, all ages, <60 years, ≤45 years). Structural validity was summarized qualitatively. Internal consistency and reliability were synthesized via random-effects meta-analysis of T-transformed Cronbach α values, and Fisher's Z transformed correlation coefficients. Construct validity and responsiveness were assessed using effect sizes. RESULTS: Four hundred ninety-seven records were identified, 72 underwent full-text assessment, resulting in 60 included reports. Structural validity was inconsistent across all age groups and overall. Internal consistency was sufficient with overall α = 0.81, and high evidence quality. Test-retest reliability was consistently sufficient across age groups with overall r = 0.84. For construct validity 361 hypotheses were assessed (37.4% for convergent-, 62.6% for known-groups validity). The percentage of confirmed hypotheses in ≥60-years, all ages, <60-years and ≤45-years were 75.5%, 66.7%, 78.9%, and 88.9%, respectively. Responsiveness was not assessed in the <60-years and ≤45-years age groups, leading to indeterminate overall rating with very low evidence quality. CONCLUSIONS: This review affirms that GOHAI has sufficient psychometric properties as an oral health-related quality of life instrument in various age groups, but its responsiveness is scarcely researched and its utility for individual-level follow-up is limited. The measurement properties of oral health-related quality of life tools must be scrutinized in the changing demands of personalized and value-based dental care. (PROSPERO registration: CRD42022384132).

Robot-assisted surgery and artificial intelligence-based tumour diagnostics: social preferences with a representative cross-sectional survey.

BACKGROUND: The aim of this study was to assess social preferences for two different advanced digital health technologies and investigate the contextual dependency of the preferences. METHODS: A cross-sectional online survey was performed among the general population of Hungary aged 40 years and over. Participants were asked to imagine that they needed a total hip replacement surgery and to indicate whether they would prefer a traditional or a robot-assisted (RA) hip surgery. To better understand preferences for the chosen method, the willingness to pay (WTP) method was used. The same assessment was conducted for preferences between a radiologist's and AI-based image analysis in establishing the radiological diagnosis of a suspected tumour. Respondents' electronic health literacy was assessed with the eHEALS questionnaire. Descriptive methods were used to assess sample characteristics and differences between subgroups. Associations were investigated with correlation analysis and multiple linear regressions. RESULTS: Altogether, 1400 individuals (53.7% female) with a mean age of 58.3 (SD = 11.1) years filled in the survey. RA hip surgery was chosen by 762 (54.4%) respondents, but only 470 (33.6%) chose AI-based medical image evaluation. Those who opted for the digital technology had significantly higher educational levels and electronic health literacy (eHEALS). The majority of respondents were willing to pay to secure their preferred surgical (surgeon 67.2%, robot-assisted: 68.8%) and image assessment (radiologist: 70.9%; AI: 77.4%) methods, reporting similar average amounts in the first (p = 0.677), and a significantly higher average amount for radiologist vs. AI in the second task (p = 0.001). The regression showed a significant association between WTP and income, and in the hip surgery task, it also revealed an association with the type of intervention chosen. CONCLUSIONS: Individuals with higher education levels seem to accept the advanced digital medical technologies more. However, the greater openness for RA surgery than for AI image assessment highlights that social preferences may depend considerably on the medical situation and the type of advanced digital technology. WTP results suggest rather firm preferences in the great majority of the cases. Determinants of preferences and real-world choices of affected patients should be further investigated in future studies.

The Reporting Quality of Machine Learning Studies on Pediatric Diabetes Mellitus: Systematic Review.

BACKGROUND: Diabetes mellitus (DM) is a major health concern among children with the widespread adoption of advanced technologies. However, concerns are growing about the transparency, replicability, biasedness, and overall validity of artificial intelligence studies in medicine. OBJECTIVE: We aimed to systematically review the reporting quality of machine learning (ML) studies of pediatric DM using the Minimum Information About Clinical Artificial Intelligence Modelling (MI-CLAIM) checklist, a general reporting guideline for medical artificial intelligence studies. METHODS: We searched the PubMed and Web of Science databases from 2016 to 2020. Studies were included if the use of ML was reported in children with DM aged 2 to 18 years, including studies on complications, screening studies, and in silico samples. In studies following the ML workflow of training, validation, and testing of results, reporting quality was assessed via MI-CLAIM by consensus judgments of independent reviewer pairs. Positive answers to the 17 binary items regarding sufficient reporting were qualitatively summarized and counted as a proxy measure of reporting quality. The synthesis of results included testing the association of reporting quality with publication and data type, participants (human or in silico), research goals, level of code sharing, and the scientific field of publication (medical or engineering), as well as with expert judgments of clinical impact and reproducibility. RESULTS: After screening 1043 records, 28 studies were included. The sample size of the training cohort ranged from 5 to 561. Six studies featured only in silico patients. The reporting quality was low, with great variation among the 21 studies assessed using MI-CLAIM. The number of items with sufficient reporting ranged from 4 to 12 (mean 7.43, SD 2.62). The items on research questions and data characterization were reported adequately most often, whereas items on patient characteristics and model examination were reported adequately least often. The representativeness of the training and test cohorts to real-world settings and the adequacy of model performance evaluation were the most difficult to judge. Reporting quality improved over time (r=0.50; P=.02); it was higher than average in prognostic biomarker and risk factor studies (P=.04) and lower in noninvasive hypoglycemia detection studies (P=.006), higher in studies published in medical versus engineering journals (P=.004), and higher in studies sharing any code of the ML pipeline versus not sharing (P=.003). The association between expert judgments and MI-CLAIM ratings was not significant. CONCLUSIONS: The reporting quality of ML studies in the pediatric population with DM was generally low. Important details for clinicians, such as patient characteristics; comparison with the state-of-the-art solution; and model examination for valid, unbiased, and robust results, were often the weak points of reporting. To assess their clinical utility, the reporting standards of ML studies must evolve, and algorithms for this challenging population must become more transparent and replicable.

Epidemiology and patients' self-reported knowledge of implantable medical devices: Results of a cross-sectional survey in Hungary.

BACKGROUND: Implantable medical devices (IMDs) are medical instruments embedded inside the body. Well-informed and empowered patients living with IMDs are key players of improving IMD-related patient safety and health outcomes. However, little is known about IMD patients' epidemiology, characteristics, and current awareness levels. Our primary aim was to investigate the point and lifetime prevalence of patients living with IMDs. Patients' IMD-related knowledge and determinants of IMDs' impact on their life were also explored. METHODS: An online cross-sectional survey was conducted. Respondents' IMD history, whether they received instructions for use and IMD's overall impact on life were recorded by self-reports. Patients' knowledge about living with IMDs was assessed on visual analogue scales (VAS, 0-10). Shared decision-making was analyzed by the 9-item Shared Decision Making Questionnaire (SDM-Q-9). Descriptive statistics and subgroup comparisons between IMD wearers were performed for statistical differences. Significant determinants of IMD's overall impact on life were examined in linear regression analysis. RESULTS: In the total sample (N = 1400, mean age 58.1 ±11.1; female 53.7%), nearly one third of respondents were living with IMD (30.9%; 433/1400). Among them, the most frequent IMDs were tooth implants (30.9%) and intraocular lens (26.8%). Mean knowledge VAS scores were similar (range: 5.5 ±3.8-6.5 ±3.2) but differences by IMD types were observed. Patients who received instructions for use or reported better impact on life indicated higher self-reported knowledge. Regression confirmed that patients' knowledge was significant predictor of IMD's impact on life, but this effect was overwritten by the SDM-Q-9. CONCLUSIONS: This first comprehensive epidemiological study on IMDs provides basic data for public health strategy planning alongside the implementation of MDR. Improved self-perceived outcomes were associated with higher knowledge hence education of patients receiving IMD deserves consideration. We suggest to investigate further the role of shared decision-making on IMD's overall impact on patients' life in future prospective studies.

[Personalized medicine and healthcare: where are we now, where should we go?] / Személyre szabott orvoslás és egészségügy: hol tartunk, merre menjünk?

The authors of this manuscript are representatives of different subdisciplines of medicine, all of them are experienced researchers. As of their origin, they are practicing doctors from the primary care and from the clinical/hospital setting, diagnostics experts, researchers from healthcare management, health economics, representatives of patients' rights and patient organizations. They are all devoted to the implementation of personalized medicine and personalized healthcare in Hungary. The current manuscript - also meant to be a keynote message provoking further discussion in the medical community - is devoted to correcting for two false ideas. One is that personalized medicine is not yet ready for practical applications, it is merely a research area of futurologists. The other false idea is that only (or mainly) the lack of financial resources hinders the introduction of personalized healthcare in Hungary. Orv Hetil. 2023; 164(6): 202-209.

Digital Biomarker-Based Interventions: Systematic Review of Systematic Reviews.

BACKGROUND: The introduction of new medical technologies such as sensors has accelerated the process of collecting patient data for relevant clinical decisions, which has led to the introduction of a new technology known as digital biomarkers. OBJECTIVE: This study aims to assess the methodological quality and quality of evidence from meta-analyses of digital biomarker-based interventions. METHODS: This study follows the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guideline for reporting systematic reviews, including original English publications of systematic reviews reporting meta-analyses of clinical outcomes (efficacy and safety endpoints) of digital biomarker-based interventions compared with alternative interventions without digital biomarkers. Imaging or other technologies that do not measure objective physiological or behavioral data were excluded from this study. A literature search of PubMed and the Cochrane Library was conducted, limited to 2019-2020. The quality of the methodology and evidence synthesis of the meta-analyses were assessed using AMSTAR-2 (A Measurement Tool to Assess Systematic Reviews 2) and GRADE (Grading of Recommendations, Assessment, Development, and Evaluations), respectively. This study was funded by the National Research, Development and Innovation Fund of Hungary. RESULTS: A total of 25 studies with 91 reported outcomes were included in the final analysis; 1 (4%), 1 (4%), and 23 (92%) studies had high, low, and critically low methodologic quality, respectively. As many as 6 clinical outcomes (7%) had high-quality evidence and 80 outcomes (88%) had moderate-quality evidence; 5 outcomes (5%) were rated with a low level of certainty, mainly due to risk of bias (85/91, 93%), inconsistency (27/91, 30%), and imprecision (27/91, 30%). There is high-quality evidence of improvements in mortality, transplant risk, cardiac arrhythmia detection, and stroke incidence with cardiac devices, albeit with low reporting quality. High-quality reviews of pedometers reported moderate-quality evidence, including effects on physical activity and BMI. No reports with high-quality evidence and high methodological quality were found. CONCLUSIONS: Researchers in this field should consider the AMSTAR-2 criteria and GRADE to produce high-quality studies in the future. In addition, patients, clinicians, and policymakers are advised to consider the results of this study before making clinical decisions regarding digital biomarkers to be informed of the degree of certainty of the various interventions investigated in this study. The results of this study should be considered with its limitations, such as the narrow time frame. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/28204.

Digital Biomarker-Based Studies: Scoping Review of Systematic Reviews.

BACKGROUND: Sensors and digital devices have revolutionized the measurement, collection, and storage of behavioral and physiological data, leading to the new term digital biomarkers. OBJECTIVE: This study aimed to investigate the scope of clinical evidence covered by systematic reviews (SRs) of randomized controlled trials involving digital biomarkers. METHODS: This scoping review was organized using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. With the search limited to English publications, full-text SRs of digital biomarkers included randomized controlled trials that involved a human population and reported changes in participants' health status. PubMed and the Cochrane Library were searched with time frames limited to 2019 and 2020. The World Health Organization's classification systems for diseases (International Classification of Diseases, Eleventh Revision), health interventions (International Classification of Health Interventions), and bodily functions (International Classification of Functioning, Disability, and Health [ICF]) were used to classify populations, interventions, and outcomes, respectively. RESULTS: A total of 31 SRs met the inclusion criteria. The majority of SRs studied patients with circulatory system diseases (19/31, 61%) and respiratory system diseases (9/31, 29%). Most of the prevalent interventions focused on physical activity behavior (16/31, 52%) and conversion of cardiac rhythm (4/31, 13%). Looking after one's health (physical activity; 15/31, 48%), walking (12/31, 39%), heart rhythm functions (8/31, 26%), and mortality (7/31, 23%) were the most commonly reported outcomes. In total, 16 physiological and behavioral data groups were identified using the ICF tool, such as looking after one's health (physical activity; 14/31, 45%), walking (11/31, 36%), heart rhythm (7/31, 23%), and weight maintenance functions (7/31, 23%). Various digital devices were also studied to collect these data in the included reviews, such as smart glasses, smartwatches, smart bracelets, smart shoes, and smart socks for measuring heart functions, gait pattern functions, and temperature. A substantial number (24/31, 77%) of digital biomarkers were used as interventions. Moreover, wearables (22/31, 71%) were the most common types of digital devices. Position sensors (21/31, 68%) and heart rate sensors and pulse rate sensors (12/31, 39%) were the most prevalent types of sensors used to acquire behavioral and physiological data in the SRs. CONCLUSIONS: In recent years, the clinical evidence concerning digital biomarkers has been systematically reviewed in a wide range of study populations, interventions, digital devices, and sensor technologies, with the dominance of physical activity and cardiac monitors. We used the World Health Organization's ICF tool for classifying behavioral and physiological data, which seemed to be an applicable tool to categorize the broad scope of digital biomarkers identified in this review. To understand the clinical value of digital biomarkers, the strength and quality of the evidence on their health consequences need to be systematically evaluated.

Validation of the Musculoskeletal Health Questionnaire in a general population sample: a cross-sectional online survey in Hungary.

BACKGROUND: The Versus Arthritis Musculoskeletal Health Questionnaire (MSK-HQ) measures symptom severity and health-related quality of life (HRQoL) of people with musculoskeletal (MSK) conditions. We aimed to test the psychometric properties of the MSK-HQ among the general adult population and identify the determinants of MSK-HQ states. In addition, we aimed to explore the relationship between MSK-HQ and standard well-being measurement tools. METHODS: The translation proccess of the MSK-HQ into Hungarian followed the standard methods provided by the developer. A cross-sectional online survey was performed in Hungary involving a population normative sample (N = 2004, women: 53.1%; mean age: 48.3, SD = 16.6 years). Socio-demographic characteristics and self-reported MSK disorders were recorded. Alongside the MSK-HQ, standard measures of HRQoL (EQ-5D-5L), physical functioning (HAQ-DI) and well-being (ICECAP-A/O, WHO-5, Happiness VAS) were applied. Clinical and convergent validity were assessed by subgroup comparisons (Mann-Whitney-U and Kruskal-Wallis tests) and Spearman's rank correlations. Internal consistency was assessed by Cronbach's alpha. Test-retest reliability (N = 50) was evaluated by intraclass correlation coefficient (ICC). Predictors of MSK-HQ were analysed by ordinary least square multiple regressions. RESULTS: The mean MSK-HQ index score was 44.1 (SD = 9.9). MSK-HQ scores were significantly lower in subgroups with self-reported MSK disorders. Correlations were strong between MSK-HQ and EQ-5D-5L (0.788), EQ VAS (0.644) and HAQ-DI (-0.698) and moderate with the well-being measures (p < 0.05). Cronbach's alpha was 0.924 and ICC was 0.936 (p < 0.05). Being a man, living in the capital, having higher income and education were positively associated with MSK-HQ scores. CONCLUSIONS: This is the first study to prove the validity and reliability of the MSK-HQ among the general public. The impact of socio-demographic characteristics on MSK-HQ scores deserves consideration in clinical studies.

Disease-Related Costs Published in The Middle East and North Africa Region: Systematic Review and Analysis of Transferability.

BACKGROUND: In the Middle East and North Africa (MENA) the scarcity of local cost data is a key barrier to conducting health economic evaluations. We systematically reviewed reports of disease-related costs from MENA and analysed their transferability within the region. METHODS: We searched PubMed and included full text English papers that reported disease-related costs from the local populations of Algeria, Bahrain, Egypt, Iraq, Jordan, Saudi Arabia, Kuwait, Lebanon, Libya, Morocco, Oman, Palestine, Qatar, Syria, Tunisia, United Arab Emirates and Yemen between 1995 and 2019. Screening, study selection and data extraction were done in duplicate. Study-related variables, costing methods, all costs and their characteristics were extracted and analysed via descriptive methods. From multi-country studies of MENA employing homogenous costing methods, we estimated the ratio (cost transfer coefficient) between the relative differences in direct medical costs and macroeconomic indicators via robust regression. We predicted each cost via the estimated cost transfer formula and evaluated prediction error between true and predicted (transferred) costs. RESULTS: The search yielded 1646 records, 206 full text papers and 3525 costs from 84 diagnoses. Transferability was analysed involving 144 direct medical costs from eight multi-country studies. Adjusting the average of available foreign costs by 0.28 times the relative difference in GDP per capita provided the most accurate estimates. The correlation between true and predicted costs was 0.96; 68% of predicted costs fell in the true ± 50% range. Predictions were more accurate for costs from studies that involved the largest number of countries, for countries outside the Gulf region and for drug costs versus unit or disease costs. CONCLUSION: The estimated cost transfer formula allows the prediction of missing costs in MENA if only GDP per capita is available for adjustment to the local setting. Input costs for the formula should be collected from multiple sources and match the decision situation.

In the Middle East and North Africa (MENA) scarce local cost data hinder health economic evaluations. This systematic review summarized disease-related costs from 17 countries (Algeria, Bahrain, Egypt, Iraq, Jordan, Saudi Arabia, Kuwait, Lebanon, Libya, Morocco, Oman, Palestine, Qatar, Syria, Tunisia, United Arab Emirates and Yemen). Eight studies applied the same costing method across multiple countries. We used these data to estimate a formula for transferring costs between countries. We assumed that costs vary proportionally with gross domestic product per capita (GDP). Most accurate cost predictions were provided when relative cost differences were set to 0.28-times the relative differences in GDP per capita. The correlation between transferred and true costs was very high. Still, only 68% of transferred costs fell in the true ± 50% range. Cost estimates were more accurate if costs were transferred from multiple countries. Also, estimates were more accurate for countries outside the Gulf region and for drug costs when compared to unit- or disease costs.

Predicting Patient-Level 3-Level Version of EQ-5D Index Scores From a Large International Database Using Machine Learning and Regression Methods.

OBJECTIVES: This study aimed to evaluate the performance of machine learning and regression methods in the prediction of 3-level version of EQ-5D (EQ-5D-3L) index scores from a large diverse data set. METHODS: A total of 30 studies from 3 countries were combined. Predictions were performed via eXtreme Gradient Boosting classification (XGBC), eXtreme Gradient Boosting regression (XGBR) and ordinary least squares (OLS) regression using 10-fold cross-validation and 80%/20% partition for training and testing. We evaluated 6 prediction scenarios using 3 samples (general population, patients, total) and 2 predictor sets: demographic and disease-related variables with/without patient-reported outcomes. Model performance was evaluated by mean absolute error and percent of predictions within clinically irrelevant error range and within correct health severity group (EQ-5D-3L index <0.45, 0.45-0.926, >0.926). RESULTS: The data set involved 26 318 individuals (clinical settings n = 6214, general population n = 20 104) and 26 predictor variables plus diagnoses. Using all predictors and the total sample, mean absolute error values were 0.153, 0.126, and 0.131, percent of predictions within clinically irrelevant error range were 47.6%, 39.5%, and 37.4%, and within the correct health severity group were 56.3%, 64.9%, and 63.3% by XGBC, XGBR, and OLS, respectively. The performance of models depended on the applied evaluation criteria, the target population, the included predictors, and the EQ-5D-3L index score range. CONCLUSIONS: Regression models (XGBR and OLS) outperformed XGBC, yet prediction errors were outside the clinically irrelevant error range for most respondents. Our results highlight the importance of systematic patient-reported outcome (EQ-5D) data collection. Dialogs between artificial intelligence and outcomes research experts are encouraged to enhance the value of accumulating data in health systems.

Comparing actuarial and subjective healthy life expectancy estimates: A cross-sectional survey among the general population in Hungary.

BACKGROUND: Healthy life expectancy (HLE) is becoming an important indicator of population health. While actuarial estimates of HLE are frequently studied, there is scarcity of research on the subjective expectations of people about their HLE. The objective of this study is to compare actuarial and subjective HLE (sHLE) estimates in the ≥50-year-old Hungarian general population. Furthermore, we assessed subjective life expectancy (sLE) and explored determinants of the individual variance of sHLE and sLE. METHODS: We conducted a cross-sectional online survey in 2019. Subjective health expectations were measured at 60, 70, 80 and 90 years of age via the Global Activity Limitation Indicator (GALI). Point-estimates of sLE and background variables were also recorded. sHLE was estimated from GALI and sLE responses. Actuarial estimates of life expectancy (LE) and HLE for 2019 were provided by the Central Statistical Office of Hungary. RESULTS: Five hundred and four respondents (female 51.6%) were included. Mean (±SD) age was 63 (±7.5) years. Median LE (81.5 years, 95%CI 81.1-81.7) and sLE (82 years, 95%CI 80-85) were similar (p = 0.142), while median sHLE (66.8 years, 95%CI 65.5-68.3) was lower than HLE (72.7 years, 95%CI 82.4-82.9) by 5.9 years (p<0.001). Despite the greater median actuarial LE of women compared to men (p<0.001), we found no gender differences between the median sLE (p = 0.930), HLE (p = 0.417) and sHLE (p = 0.403) values. With less apparent gender differences among the predictors when compared to sLE, sHLE was mainly determined by self-perceived health, age and place of residence, while self-perceived health, close relatives' longevity, social conditions, happiness and perceived lifestyle influenced sLE. CONCLUSIONS: Along subjective life expectancy, subjective healthy life expectancy may be a feasible indicator and provide insights to individuals' subjective expectations underlying the demographic estimates of the healthy life expectancy of the population.

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.

Measuring the acceptability of EQ-5D-3L health states for different ages: a new adaptive survey methodology.

BACKGROUND: Acceptable health and sufficientarianism are emerging concepts in health resource allocation. We defined acceptability as the proportion of the general population who consider a health state acceptable for a given age. Previous studies surveyed the acceptability of health problems separately per EQ-5D-3L domain, while the acceptability of health states with co-occurring problems was barely explored. OBJECTIVE: To quantify the acceptability of 243 EQ-5D-3L health states for six ages from 30 to 80 years: 1458 health state-age combinations (HAcs), denoted as the acceptability set of EQ-5D-3L. METHODS: In 2019, an online representative survey was conducted in the Hungarian general population. We developed a novel adaptive survey algorithm and a matching statistical measurement model. The acceptability of problems was evaluated separately per EQ-5D-3L domain, followed by joint evaluation of up to 15 HAcs. The selection of HAcs depended on respondents' previous responses. We used an empirical Bayes measurement model to estimate the full acceptability set. RESULTS: 1375 respondents (female: 50.7%) were included with mean (SD) age of 46.7 (14.6) years. We demonstrated that single problems that were acceptable separately for a given age were less acceptable when co-occurring jointly (p < 0.001). For 30 years of age, EQ-5D-3L health states of '11112' (11.9%) and '33333' (1%), while for 80 years of age '21111' (93.3%) and '33333' (7.4%) had highest and lowest acceptability (% of population), respectively. CONCLUSION: The acceptability set of EQ-5D-3L quantifies societal preferences concerning age and disease severity. Its measurement profiles and potential role in health resource allocation needs further exploration.

Resource utilization, work productivity and costs in patients with hidradenitis suppurativa: a cost-of-illness study.

BACKGROUND: Hidradenitis suppurativa (HS) is a, chronic skin disease affecting up to 1% of the population in Europe. This study aims to assess the cost-of-illness of HS from a societal perspective in Hungary and to analyze the predictors of costs. METHODS: A multicentre, cross-sectional cost-of-illness study was performed among 200 adult HS patients. We evaluated direct medical (physician consultations, inpatient admissions, medical, and surgeries), direct non-medical (transportation and caregiving), and indirect costs (productivity loss). RESULTS: The mean annual cost-of-illness of HS was €6,791 per patient. The main cost components were productivity loss (53.3%), biological treatment (21.5%), and informal care (9.2%). Patients missed, on average, 26 and 63 days from work annually due to absenteeism and presenteeism, respectively. Male sex, more severe disease, gluteal involvement, and coexisting inflammatory bowel disease were associated with higher direct medical costs, while lower education level and worse quality-of-life outcomes predicted higher indirect costs. CONCLUSION: This is the first study to assess both direct and indirect costs in HS patients. HS imposes a substantial burden on patients and society, predominantly arising from productivity loss and biological therapy. Resource utilization data and cost-of-illness estimates provide valuable inputs into cost-effectiveness analyses of health interventions in HS.

Development of Population Tariffs for the ICECAP-A Instrument for Hungary and their Comparison With the UK Tariffs.

OBJECTIVES: The ICEpop CAPability measure for Adults (ICECAP-A) was developed to assess the capability well-being of adults for use in economic evaluations. Currently, ICECAP-A tariffs are available only for the UK population. The objectives of this study were to develop a Hungarian tariff set for the ICECAP-A instrument and to explore intercountry differences between the Hungarian and the UK value sets. METHODS: A survey was conducted by computer-assisted personal interviews on a sample representative of the Hungarian adult population (N = 1000) to elicit their preferences regarding ICECAP-A attributes with the use of a best-worst scaling choice task. A latent class multinomial logit model with continuous variance scale was used to estimate the weights for each of the 4 capability levels of all 5 ICECAP-A attributes, namely, attachment, stability, achievement, enjoyment, and autonomy. RESULTS: The model identified 2 preference classes with approximately equal share. The first class had a stronger relative preference for autonomy and achievement, whereas the second class had a strong preference for attachment. Multivariate analysis of the classes revealed that women, pensioners, people who are married or living in a partnership, and people with poorer health status are characteristics associated with the latter class membership (preference for attachment). Population tariffs were estimated from the model. Overall, attachment was found to be the most important attribute, followed by stability, enjoyment, achievement, and autonomy. CONCLUSIONS: Hungarian tariffs are largely consistent with those found for the United Kingdom; nevertheless, autonomy seems to be less important in Hungary compared with the United Kingdom.

Outcomes of Digital Biomarker-Based Interventions: Protocol for a Systematic Review of Systematic Reviews.

BACKGROUND: Digital biomarkers are defined as objective, quantifiable, physiological, and behavioral data that are collected and measured using digital devices such as portables, wearables, implantables, or digestibles. For their widespread adoption in publicly financed health care systems, it is important to understand how their benefits translate into improved patient outcomes, which is essential for demonstrating their value. OBJECTIVE: The paper presents the protocol for a systematic review that aims to assess the quality and strength of the evidence reported in systematic reviews regarding the impact of digital biomarkers on clinical outcomes compared to interventions without digital biomarkers. METHODS: A comprehensive search for reviews from 2019 to 2020 will be conducted in PubMed and the Cochrane Library using keywords related to digital biomarkers and a filter for systematic reviews. Original full-text English publications of systematic reviews comparing clinical outcomes of interventions with and without digital biomarkers via meta-analysis will be included. The AMSTAR-2 tool will be used to assess the methodological quality of these reviews. To assess the quality of evidence, we will evaluate the systematic reviews using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) tool. To detect the possible presence of reporting bias, we will determine whether a protocol was published prior to the start of the studies. A qualitative summary of the results by digital biomarker technology and outcomes will be provided. RESULTS: This protocol was submitted before data collection. Search, screening, and data extraction will commence in December 2021 in accordance with the published protocol. CONCLUSIONS: Our study will provide a comprehensive summary of the highest level of evidence available on digital biomarker interventions, providing practical guidance for health care providers. Our results will help identify clinical areas in which the use of digital biomarkers has led to favorable clinical outcomes. In addition, our findings will highlight areas of evidence gaps where the clinical benefits of digital biomarkers have not yet been demonstrated. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/28204.

Musculoskeletal health and capability wellbeing: Associations between the HAQ-DI, ICECAP-A and ICECAP-O measures in a population survey.

BACKGROUND: The capability approach has received increasing attention in wellbeing measurement in the past years, but it has still remained an underexplored area in musculoskeletal (MSK) health. OBJECTIVE: We aimed to explore the capability wellbeing in relation to MSK health, by measuring the associations between the Health Assessment Questionnaire Disability Index (HAQ-DI) physical functioning and the ICECAP-A and ICECAP-O capability wellbeing measures. DESIGN: A cross-sectional survey was performed in 2019 on a representative sample of the Hungarian general adult population. METHOD: Capability wellbeing was measured by the ICECAP-A (age-group 18-64) and ICECAP-O (age group 65+) questionnaires. MSK health was defined by the HAQ-DI, the mobility domain of the EQ-5D-3L/-5L health status measures, self-reported walking problems and MSK diagnosis (neck/back/low back defects, hip/knee arthrosis, osteoporosis). RESULTS: Altogether 2021 individuals (female: 50.1%) participated in the survey with mean (SD) age of 48.7 (17.9) years and HAQ-DI of 0.138 (0.390). ICECAP-A (N = 1568, 77.6%) and ICECAP-O (N = 453, 22.4%) scores were on average (SD) 0.894 (0.126) and 0.828 (0.150), respectively. Spearman correlations between the HAQ-DI and ICECAP-A/-O index scores were moderate (r = -0.303 and -0.496; p < 0.05). Both the ICECAP-A/-O index scores differed significantly (ANOVA test, p < 0.05) across all MSK subgroups. In the ordinary least square regressions, marginal effects of ICECAP-A/-O scores on HAQ-DI were significant (-0.149 and -0.123) when controlling for socio-demographic characteristics. CONCLUSIONS: MSK health problems are associated with lower capability wellbeing. ICECAP-A/-O might capture effects of MSK conditions not measured by the HAQ-DI or the EQ-5D-5L. Further studies should test these associations in disease-specific samples.

Subjective expectations concerning life expectancy and age-related health burden / Az élettartammal és az idoskori betegségteherrel kapcsolatos szubjektív várakozások.

Összefoglaló. Bevezetés: A lakosság idosödésével növekvo betegségteher egyéni és társadalmi szinten is fokozódó nyomást jelent. Célkituzés: Felmérni a hazai általános felnott lakosságnak a korlátozottsággal, a gondozási igényekkel és a munkavégzéssel kapcsolatos idoskori szubjektív várakozásait. Módszer: Online keresztmetszeti felmérést végeztünk. A korlátozottsággal kapcsolatos várakozásokat a hivatalos szakstatisztikákban alkalmazott globális tevékenységkorlátozottsági mutató (Global Activity Limitation Indicator, GALI) segítségével elsoként vizsgáltuk. A jelen és szubjektíve várt munkavégzést, gondozási igényt, gondozói tevékenységet, valamint a jelen egészségi állapotot és szociodemográfiai helyzetet vizsgáló kérdéseket is feltettünk. Statisztikai analízis: A mintában mért adatokat lokális polinom segítségével simítottuk, és a 60/70/80/90 éves korra adott szubjektív várakozásokkal hasonlítottuk össze. A szubjektív várakozásokat meghatározó tényezoket intervallumregresszióval becsültük. Eredmények: 1000 kitöltotol 914 érvényes választ kaptunk. Az átlagéletkor (± szórás) 51,2 (± 15,2) év, a minta 55,8%-a no volt. A férfiak között a fizetett munkát végzok (p<0,001), a nok között az informális gondozók aránya volt magasabb (p = 0,010). Az átlagos (± szórás) szubjektíve várható élettartam (81,0 ± 11,1 év) a minta statisztikailag várható élettartamánál (79,6 ± 3,7 év) 1,3 évvel volt hosszabb (p<0,001), azonban az átlagos, szubjektíve várható egészséges élettartam (64,6 ± 15,2 év) 5,3 évvel volt rövidebb a statisztikailag várható értéknél (70,0 ± 4,2 év; p<0,001). A szubjektíve várható egészséges élettartamot és gondozási igényt elsosorban a válaszadók jelenlegi egészségi állapota befolyásolta. Az életmód és a szubjektíve várható egészséges élettartam között noknél nem találtunk összefüggés, míg a túlzott gyakorisággal alkoholt fogyasztó vagy elhízott férfiak hosszabb egészséges élettartamra számítottak. A szubjektív várakozások meghatározó tényezoi jelentos nemi különbségeket mutattak. Következtetés: Az egészséggel, munkával és gondozással kapcsolatos szubjektív várakozások eltéroek a populációban mért valós adatoktól, és különböznek a nemek között. Orv Hetil. 2021; 162(23): 911-923. INTRODUCTION: The growing disease burden due to ageing populations poses a challenge on both individuals and societies. OBJECTIVE: To explore the general population's subjective expectations concerning disability, care needs and employment at older ages. METHOD: We conducted an online cross-sectional survey. We were the first to measure subjective health expectations using the Global Activity Limitation Indicator (GALI) of official health statistics. Respondents' actual status and subjective expectations concerning employment, care needs and informal caregiver status, self-perceived health and sociodemographic factors were queried. STATISTICAL ANALYSIS: We estimated sample characteristics by local polynomial smoothing and compared with subjective expectations at ages of 60/70/80/90 years. Determinants of subjective expectations were analyzed via interval regression. RESULTS: From 1000 subjects, 914 provided valid responses. Mean (± SD) age was 51.2 (± 15.2) years, and 55.8% of respondents were women. Paid employment was more frequent among men (p<0.001), while informal caregiver status among women (p = 0.010). Mean (± SD) subjective life expectancy (81.0 ± 11.1 years) was 1.3 years longer (p<0.001) than actuarial life-expectancy (79.6 ± 3.7 years), while mean subjective healthy life expectancy (sHLE) (64.6 ± 15.2 years) was 5.3 years shorter than actuarial healthy life expectancy (70.0 ± 4.2 years; p<0.001). sHLE and care needs were mainly determined by respondents' self-perceived health. Lifestyle risks were not associated with sHLE in women, while pervasive drinker or obese men expected longer healthy life span. Determinants of sHLE showed considerable gender differences. CONCLUSION: Subjective expectations concerning health, employment and care needs differ from actual values of the general population, with considerable gender differences. Orv Hetil. 2021; 162(23): 911-923.

Comparing the measurement properties of the ICECAP-A and ICECAP-O instruments in ages 50-70: a cross-sectional study on a representative sample of the Hungarian general population.

OBJECTIVE: The ICECAP-A and ICECAP-O were validated as capability wellbeing measures of adults aged 18 + and 65 + years, respectively. We aimed to compare their measurement properties in age group 50-70. METHODS: Data were derived from a cross-sectional survey among a sample representative for the adult Hungarian population. Respondents aged between 50 and 70 filled in both the ICECAP-A and ICECAP-O questionnaires. We assessed and compared feasibility, agreement, discriminatory power, convergent and content validity of the two instruments and explored the determinants of the differences between the two measures. RESULTS: 707 respondents (99.4%) provided full answers to both questionnaires (46.3% women, average age 60.1 years). The instruments showed similar construct and convergent validity and discriminatory power. Pearson-correlations between instrument items were strong (r > 0.5). ICECAP-A and ICECAP-O scores could be calculated from each other with a good confidence (R2 = 0.69 and 0.71). ICECAP-O scores (mean 0.87, SD = 0.12) were systematically higher than ICECAP-A scores (0.85, SD = 0.15) in most subgroups. The difference increased with the deterioration of capability and health, and with age. Regression results showed that employment and health status had larger marginal effect on the ICECAP-A than on the ICECAP-O scores, and these effects were larger than the effect of age on both measures. CONCLUSION: Validity of both instruments was confirmed in the age groups 50-70. Given that employment and health status are important determinants of the differences between the two instruments besides age, the possibility of linking the choice between ICECAP-A and ICECAP-O to these factors should be investigated by further research.