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).

The PICOTS-ComTeC Framework for Defining Digital Health Interventions: An ISPOR Special Interest Group Report.

OBJECTIVES: Digital health definitions are abundant, but often lack clarity and precision. We aimed to develop a minimum information framework to define patient-facing digital health interventions (DHIs) for outcomes research. METHODS: Definitions of digital-health-related terms (DHTs) were systematically reviewed, followed by a content analysis using frameworks, including PICOTS (population, intervention, comparator, outcome, timing, and setting), Shannon-Weaver Model of Communication, Agency for Healthcare Research and Quality Measures, and the World Health Organization's Classification of Digital Health Interventions. Subsequently, we conducted an online Delphi study to establish a minimum information framework, which was pilot tested by 5 experts using hypothetical examples. RESULTS: After screening 2610 records and 545 full-text articles, we identified 101 unique definitions of 67 secondary DHTs in 76 articles, resulting in 95 different patterns of concepts among the definitions. World Health Organization system (84.5%), message (75.7%), intervention (58.3%), and technology (52.4%) were the most frequently covered concepts. For the Delphi survey, we invited 47 members of the ISPOR Digital Health Special Interest Group, 18 of whom became the Delphi panel. The first, second, and third survey rounds were completed by 18, 11, and 10 respondents, respectively. After consolidating results, the PICOTS-ComTeC acronym emerged, involving 9 domains (population, intervention, comparator, outcome, timing, setting, communication, technology, and context) and 32 optional subcategories. CONCLUSIONS: Patient-facing DHIs can be specified using PICOTS-ComTeC that facilitates identification of appropriate interventions and comparators for a given decision. PICOTS-ComTeC is a flexible and versatile tool, intended to assist authors in designing and reporting primary studies and evidence syntheses, yielding actionable results for clinicians and other decision makers.

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.

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.

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.

How Useful Are Digital Health Terms for Outcomes Research? An ISPOR Special Interest Group Report.

OBJECTIVES: This study aimed to review definitions of digital health and understand their relevance for health outcomes research. Four umbrella terms (digital health, electronic health, mobile health, and telehealth/telemedicine) were summarized in this article. METHODS: PubMed/MEDLINE, Embase, Cochrane Library, and EconLit were searched from January 2015 to May 2020 for systematic reviews containing key Medical Subject Headings terms for digital health (n = 38) and synonyms of "definition." Independent pairs of reviewers performed each stage of the review, with reconciliation by a third reviewer if required. A single reviewer consolidated each definition for consistency. We performed text analysis via word clouds and computed document frequency-and inverse corpus frequency scores. RESULTS: The search retrieved 2610 records with 545 articles (20.9%) taken forward for full-text review. Of these, 39.3% (214 of 545) were eligible for data extraction, of which 134 full-text articles were retained for this analysis containing 142 unique definitions of umbrella terms (digital health [n = 4], electronic health [n = 36], mobile health [n = 50], and telehealth/telemedicine [n = 52]). Seminal definitions exist but have increasingly been adapted over time and new definitions were created. Nevertheless, the most characteristic words extracted from the definitions via the text analyses still showed considerable overlap between the 4 umbrella terms. CONCLUSIONS: To focus evidence summaries for outcomes research purposes, umbrella terms should be accompanied by Medical Subject Headings terms reflecting population, intervention, comparator, outcome, timing, and setting. Ultimately a functional classification system is needed to create standardized terminology for digital health interventions denoting the domains of patient-level effects and outcomes.

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.

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.

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.

Validation of the Hungarian version of the CarerQol instrument in informal caregivers: results from a cross-sectional survey among the general population in Hungary.

PURPOSE: The CarerQol instrument has been designed and validated as an instrument able to measure both the positive and the negative impacts of caregiving on the quality of life of informal caregivers (CarerQol-7D), as well as their general happiness (CarerQol-VAS). The aim of this study was to assess the construct validity of the CarerQol in the Hungarian context. METHODS: The CarerQol was translated into Hungarian. Subsequently, in a cross-sectional online survey, representative for the general Hungarian population (N = 1000), informal caregivers were identified (N = 149, female 51.2%, mean age 53.2). Clinical, convergent and discriminant validity of the CarerQol were evaluated in relation to the caregivers' and care recipients' EQ-5D-5L health status, and caregiving situation characteristics. RESULTS: Average CarerQol-7D and CarerQol-VAS scores were 76.0 (SD 16.2) and 6.8 (SD 2.3), respectively. CarerQol-7D and CarerQol-VAS scores were significantly correlated with caregiving time (r = - 0.257; - 0.212), caregivers' EQ-5D-5L scores (r = 0.453; 0.326) and the CarerQol-7D also with care recipients' EQ-5D-5L scores (r = 0.247). CarerQol-7D scores differed significantly with relevant caregiving characteristics (e.g. nature and severity of care recipients' health status, sharing household) and both the CarerQol-7D and CarerQol-VAS with the overall care experience. CONCLUSION: Our findings confirmed the validity of the Hungarian language version of the CarerQol and support the cross-cultural validity of the instrument. CarerQol-7D scores performed better in distinguishing caregiving situation characteristics than the general happiness measure CarerQol-VAS. Care recipients' health status was only weakly associated with informal caregivers' care-related quality of life and happiness. Caregivers' own health and caregiving circumstances were more strongly associated with these scores.

Risk stratification in endoscopic type I. tympanoplasty.

PURPOSE: Several risk factors were studied in endoscopic type I. tympanoplasty, however, an easy-to-use risk stratification model is still missing. METHODS: Retrospective chart review, focusing on individual risk factors and middle ear risk index (MERI). Patients who underwent endoscopic type I. tympanoplasty were included. RESULTS: Closed tympanic cavity was succesfully created in 88.1% of the 42 cases, the overall 21,5 dB air-bone gap (ABG) was reduced by 9,8 dB. The average MERI score of the patients was 2.1 ± 1.5. 78.6% of the patients were categorised into the mild, while 21.4% into the moderate risk group. The perforation was considered small in 81.0% of the cases, while large in 19.0%. The size of the perforation and the preoperative ABG, but not the MERI status were the only single predictors of success. Using a risk stratification model that is based on the size of the perforation, the preoperative ABG and MERI status, patients could be referred into two distinct groups of risk: the majority expecting excellent outcomes with maximum one risk factor present, and patients with deteriorated rate of success when having two or three risk factors. CONCLUSIONS: Endoscopic type I. tympanoplasty with underlay perichondrium graft can be performed with good chance of success. However, if more than one risk factors are present, the chance of residual perforation becomes great. In addition to the established risk factors, our results point out that despite its strong correlation with perforation size, ABG may have a predictive role.

Acceptable health and ageing: results of a cross-sectional study from Hungary.

BACKGROUND: We aimed to investigate the acceptability of imperfect health states in relation to age in Hungary and analyse its determinants. Results are contrasted to age-matched actual population health scores and to findings from a previous study in The Netherlands. METHODS: A cross-sectional online survey was performed. The same survey questions were applied as in a previous study in The Netherlands in order to enable inter-country comparisons. The descriptive system of the EQ-5D-3L health status questionnaire was used to assess the acceptability of moderate and severe health problems at ages from 30 to 80 by 10-year age-groups. Descriptive statistics were performed and linear regression analysis was used to investigate the determinants of acceptability. RESULTS: Altogether 9281 (female 32.8%) were involved with mean age 36.0 years and EQ-5D-3L index score of 0.852 (SD 0.177). Acceptability of health problems increased with age, differed per health domain and with severity of the problems. Except for 'Self-care', moderate health problems were acceptable by the majority from age 70 and acceptability scores were lower than EQ-5D-3L population norms from that age. The lowest average acceptability age was found in the 'Anxiety/depression' and dimension the highest in the 'Self-care' dimension. Respondents' age, current health, and lifestyle were significant determinants (R2: 0.041-0.130). With a few minor exceptions in some health dimensions, acceptability levels and patterns were strikingly similar to the Dutch findings. CONCLUSION: In Hungary, acceptability of health problems increases with age and the majority found severe problems never acceptable. Views on acceptability of health problems seem to be fairly generalizable across European countries with different health and economic indicators.

Capability of well-being: validation of the Hungarian version of the ICECAP-A and ICECAP-O questionnaires and population normative data.

PURPOSE: We aimed to develop and assess the psychometric characteristics of the Hungarian language version of two well-being capability measures, the ICEpop CAPability measure for Adults/Older people (ICECAP-A/-O), and to establish population norms. METHODS: A cross-sectional survey was performed involving a representative sample of the Hungarian population. Socio-demographic characteristics, the use and provision of informal care were recorded. The Minimum European Health Module (MEHM), EQ-5D-5L, WHO-5 well-being index, happiness and life satisfaction visual analogue scale (VAS), Satisfaction with Life Scale (SWLS) measures were applied alongside the ICECAP-A (age-group 18-64) and ICECAP-O (age-group 65+). RESULTS: Altogether 1568 and 453 individuals completed the ICECAP-A/-O questionnaires, respectively. Cronbach's alpha was 0.86 for both measures (internal consistency). Subgroup analyses showed positive associations between ICECAP-A/-O scores and marital status, employment, income, health status (MEHM) and informal care use (construct validity). Pearson correlations were strong (r > 0.5; p < 0.01) between ICECAP-A/-O indexes and EQ-5D-5L, WHO-5, happiness and satisfaction VAS and SWLS scores (convergent validity). The age, education, and marital status were no longer significant in the multiple regression analysis. Test-retest average (SD) scores were 0.88 (0.11) and 0.89 (0.10) for the ICECAP-A, and equally 0.86 (0.09) for the ICECAP-O (reliability). CONCLUSION: This is the first study to provide ICECAP-A/-O population norms. Also, it is the first to explore associations with WHO-5 well-being index which, alongside the MEHM measures, enable estimates from routinely collected international health statistics. The Hungarian ICECAP-A/-O proved to be valid and reliable measurement tools. Socio-demographic characteristics had minor or no impact on ICECAP-A/-O. Other influencing factors deserve further investigation in future 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.

Thrombocytosis and Effects of IL-6 Knock-Out in a Colitis-Associated Cancer Model.

There is an increasing number of studies showing that thrombocytosis-accompanying a variety of solid tumors including colorectal cancer (CRC)-is associated with shorter survival and earlier development of metastases. The mechanisms of cancer-associated thrombocytosis are not completely understood yet. The aim of our study was to evaluate the role of IL-6 in tumor development and thrombocytosis in mice with inflammation-induced CRC, using a CRISPR/cas9 IL-6 knockout (KO) strain. Adult male FB/Ant mice (n = 39) were divided into four groups: (1) IL-6 KO controls (n = 5); (2) IL-6 KO CRC model group (n = 18); (3) Wild-type (WT) controls (n = 6); and (4) WT CRC model group (n = 10). CRC model animals in (2) and (4) received azoxymethane (AOM)/dextran sodium sulfate (DSS) treatment to induce inflammation-related CRC. Plasma and liver tissues were obtained to determine platelet counts, IL-6 and thrombopoietin-1 (TPO) levels. In 1 WT and 2 IL-6 KO mice in vivo confocal endomicroscopy and 18F-fluorodeoxyglucose (FDG) PET/MRI examinations were performed to evaluate the inflammatory burden and neoplastic transformation. At the end of the study, tumorous foci could be observed macroscopically in both CRC model groups. Platelet counts were significantly elevated in the WT CRC group compared to the IL-6 KO CRC group. TPO levels moved parallelly with platelet counts. In vivo fluorescent microscopy showed signs of disordered and multi-nuclear crypt morphology with increased mucus production in a WT animal, while regular mucosal structure was prominent in the IL-6 KO animals. The WT animal presented more intense and larger colonic FDG uptake than IL-6 KO animals. Our study confirmed thrombocytosis accompanying inflammation-related CRC and the crucial role of IL-6 in this process. Significantly higher platelet counts were found in the WT CRC group compared to both the control group and the IL-6 KO group. Concomitantly, the tumor burden of WT mice was also greater than that of IL-6 KO mice. Our findings are in line with earlier paraneoplastic IL-6 effect suggestions.

EQ-5D studies in musculoskeletal and connective tissue diseases in eight Central and Eastern European countries: a systematic literature review and meta-analysis.

EQ-5D is becoming the preferred instrument to measure health-state utilities involved in health technology assessment. The objective of this study is to assess the state of EQ-5D research in musculoskeletal disorders in 8 Central and Eastern European countries and to provide a meta-analysis of EQ-5D index scores. Original research articles published in any language between Jan 2000 and Sept 2016 were included, if they reported any EQ-5D outcome from at least two musculoskeletal patients from Austria, Bulgaria, the Czech Republic, Hungary, Poland, Romania, Slovakia, or Slovenia. Risk of bias was assessed with the Cochrane Collaboration's tool. Twenty-nine articles (5992 patients) were included on rheumatoid arthritis (n = 7), osteoporosis (n = 5), chronic pain (n = 5), osteoarthritis (n = 4), ankylosing spondylitis (n = 2), psoriatic arthritis (n = 2), total hip replacement (n = 2), and scleroderma (n = 2). Low back pain was under-represented, while studies in neck pain, systemic lupus erythematosus, gout, and childhood disorders were lacking. EQ-5D index scores were reported in 24 studies, while the version of the instrument and the value-set was not specified in 41% and 46% of the articles, respectively. Meta-analysis was performed on 24 disease states involving 6876 observation points. Intervention effect was reported in 22 subgroups, out of which risk of bias was low in 41%. This review provides recommendations to improve reporting standards of EQ-5D results and highlights potential areas for future research. Coordinated research in conditions with greatest public health impact as well as a development of a regional value-set could provide locally relevant health-state utilities that are transferable among countries within the region.

[Measurement and health economic evaluation of informal care]. / Az informális ellátás mérése és egészség-gazdaságtani értékelése.

Informal care is non-financed care outside the realm of formal healthcare, which represents an increasing challenge for aging societies. Informal care has frequently been neglected in health economic analyses, while in recent years its coverage has increased considerably in the international scientific literature. This review summarizes the methodology of the health-economic assessment of informal care, including the objective and subjective metrics of caregiver burden, its financial and non-financial valuation and practical applications, with special emphasis on the introduction of care-related quality of life instruments (e.g. Care Related Quality of Life - CarerQoL instrument). Care-related quality of life is a different entity from health-related quality of life, the two cannot be combined, so their joint evaluation requires multi-criteria decision analysis methods. Therefore, it is important to determine the societal preferences of care-related quality of life versus health-related quality of life, and map the relationship of care-related quality of life with time. The local validation of tools measuring care-related quality of life, its more widespread practical application and the analysis of its effect on decision making are also important part of the future research agenda. Orv Hetil. 2017; 158(35): 1363-1372.

Automation of systematic reviews of biomedical literature: a scoping review of studies indexed in PubMed.

BACKGROUND: The demand for high-quality systematic literature reviews (SRs) for evidence-based medical decision-making is growing. SRs are costly and require the scarce resource of highly skilled reviewers. Automation technology has been proposed to save workload and expedite the SR workflow. We aimed to provide a comprehensive overview of SR automation studies indexed in PubMed, focusing on the applicability of these technologies in real world practice. METHODS: In November 2022, we extracted, combined, and ran an integrated PubMed search for SRs on SR automation. Full-text English peer-reviewed articles were included if they reported studies on SR automation methods (SSAM), or automated SRs (ASR). Bibliographic analyses and knowledge-discovery studies were excluded. Record screening was performed by single reviewers, and the selection of full text papers was performed in duplicate. We summarized the publication details, automated review stages, automation goals, applied tools, data sources, methods, results, and Google Scholar citations of SR automation studies. RESULTS: From 5321 records screened by title and abstract, we included 123 full text articles, of which 108 were SSAM and 15 ASR. Automation was applied for search (19/123, 15.4%), record screening (89/123, 72.4%), full-text selection (6/123, 4.9%), data extraction (13/123, 10.6%), risk of bias assessment (9/123, 7.3%), evidence synthesis (2/123, 1.6%), assessment of evidence quality (2/123, 1.6%), and reporting (2/123, 1.6%). Multiple SR stages were automated by 11 (8.9%) studies. The performance of automated record screening varied largely across SR topics. In published ASR, we found examples of automated search, record screening, full-text selection, and data extraction. In some ASRs, automation fully complemented manual reviews to increase sensitivity rather than to save workload. Reporting of automation details was often incomplete in ASRs. CONCLUSIONS: Automation techniques are being developed for all SR stages, but with limited real-world adoption. Most SR automation tools target single SR stages, with modest time savings for the entire SR process and varying sensitivity and specificity across studies. Therefore, the real-world benefits of SR automation remain uncertain. Standardizing the terminology, reporting, and metrics of study reports could enhance the adoption of SR automation techniques in real-world practice.

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.

Augmented or Mixed Reality Enhanced Head-Mounted Display Navigation for In Vivo Spine Surgery: A Systematic Review of Clinical Outcomes.

BACKGROUND: This research paper provides a systematic literature review (SLR) on the current status of augmented-reality head-mounted devices (AR-HMDs) that guide and navigate spine surgeries and pedicle screw placement. METHODS: Embase, Scopus, PubMed, Cochrane Library and IEEE Xplore databases were screened for the systematic literature search to collect and statistically analyze live patient clinical, procedural and user experience data. Multi-level Poisson and binominal models were used for analysis. RESULTS: In vivo patient data, only the clinically widely used Gertzbein-Robbins Scale, were published as an outcome in the recent heterogeneous literature. The statistical analysis supports the hypothesis that using AR-HMDs has the same clinical outcomes as using more expensive robot-assisted surgical (RAS) systems. CONCLUSIONS: AR-HMD-guided pedicle screw insertion is reaching its technology readiness, providing similar benefits to RAS. Further meta-analysis is expected in the future from higher case-numbered and standardized randomized clinical trials.