Health Literacy as Communicative Action-A Qualitative Study among Persons at Risk in the Context of Predictive and Preventive Medicine.
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SUBMITTER: Harzheim L
PROVIDER: S-EPMC7084333 | biostudies-literature | 2020 Mar
REPOSITORIES: biostudies-literature
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Health Literacy as Communicative Action-A Qualitative Study among Persons at Risk in the Context of Predictive and Preventive Medicine.
Harzheim Laura L Lorke Mariya M Woopen Christiane C Jünger Saskia S
International journal of environmental research and public health 20200305 5
Predictive and preventive medicine play an increasingly important role in public debates on health, providing cutting-edge technologies with the potential to measure and predict individual risks of getting ill. This leads to an ever-expanding definitional space between being "healthy" and being "ill", challenging the individual's everyday life, attitudes and perceptions towards the self and the process of health-related decision-making. "How do the condition of 'being at risk' and individual hea ...[more]
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Project description:ObjectivesSuboptimal health status (SHS), a reversible borderline condition between optimal health status and disease, has been recognized as a main risk factor for non-communicable diseases (NCDs). From the standpoint of predictive, preventive, and personalized medicine (PPPM/3PM), the early detection of SHS provides a window of opportunity for targeted prevention and personalized treatment of NCDs. Considering that immunoglobulin G (IgG) N-glycosylation levels are associated with NCDs, it can be speculated that IgG N-glycomic alteration might occur at the SHS stage.MethodsA case-control study was performed and it consisted of 124 SHS individuals and 124 age-, gender-, and body mass index-matched healthy controls. The IgG N-glycan profiles of 248 plasma samples were analyzed by ultra-performance liquid chromatography instrument.ResultsAfter adjustment for potential confounders (i.e., age, levels of education, physical activity, family income, depression score, fasting plasma glucose, and low-density lipoprotein cholesterol), SHS was significantly associated with 16 IgG N-glycan traits at 5% false discovery rate, reflecting decreased galactosylation and fucosylation with bisecting GlcNAc, as well as increased agalactosylation and fucosylation without bisecting GlcNAc. Canonical correlation analysis showed that glycan peak (GP) 20, GP9, and GP12 tended to be significantly associated with the 5 domains (fatigue, the cardiovascular system, the digestive system, the immune system, and mental status) of SHS. The logistic regression model including IgG N-glycans was of moderate performance in tenfold cross-validation, achieving an average area under the receiver operating characteristic curves of 0.703 (95% confidence interval: 0.637-0.768).ConclusionsThe present findings indicated that SHS-related alteration of IgG N-glycans could be identified at the early onset of SHS, suggesting that IgG N-glycan profiles might be potential biomarker of SHS. The altered SHS-related IgG N-glycans are instrumental for SHS management, which could provide a window opportunity for PPPM in advanced treatment of NCDs and shed light on future studies investigating the pathogenesis of progression from SHS to NCDs.Supplementary informationThe online version contains supplementary material available at 10.1007/s13167-022-00278-1.
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Project description:ObjectivesConsidering health literacy needs is a key component of health services responsiveness to diabetes self-management among vulnerable individuals. The purpose of this qualitative study was to provide a detailed analysis of the health literacy of people with type 2 diabetes in relation to their daily self-care practices.DesignNested qualitative study in the ERMIES randomised controlled trial testing a 2-year structured care in type 2 diabetes. First round of semidirected interviews at the beginning of the trial with thematic analysis of content. Second round at the completion with directed interviews guided by the first round's themes together with Health Literacy Questionnaire.SettingsInterviews conducted at home.ParticipantsForty-four (31 females/13 males, 30-79 years, glycated haemoglobin (HbA1c)≥7.5%) consecutive participants out of 100 recruited in the ERMIES trial from 4 diabetology outpatient settings (Reunion Island). Forty-two respondents to the second round interviews.ResultsThree poles structured into eight themes characterised practices in context: health knowledge, disease management, expertise and social support. The relationships of participants in each of the eight themes were differentiated, ranging from functional to interactive and critical. Treatment and follow-up were essentially functional, while diet and exercise remained more interactive. Social support and relationship to health professionals were important determinants of disease management.ConclusionsTreatment management and disease monitoring remain primarily the job of health professionals, as opposed to diet, physical activity and social support being part of ordinary practice. Decision-making, as a shared social task, as well as resources for participation in health services, should be considered for relevant interventions in type 2 diabetes.Trial registration numberNCT01425866.
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Project description:BackgroundConceptualizing health literacy as a relational concept, which involves how individuals interact with complex health and social systems, requires a greater understanding of the context of people's health experiences.ObjectivesTo describe individuals' experiences of accessing, understanding, appraising and applying health information; explore the barriers and facilitators to using these skills; and to describe the experience of information exchange in health consultations.DesignA longitudinal qualitative methodology with thematic analysis of interviews was used. Health literacy levels were assessed using the HLS-EU-47-Item Questionnaire. Findings are presented from the first round of data collection.Setting and participantsTwenty-six participants purposefully selected from a CVD risk reduction programme at three separate time points.ResultsFour key themes identified: using health literacy capacities for managing health; psychological and structural factors that impact on these capacities; and the relationship quality with the health-care provider (HCP). Although limited health literacy was prevalent across the sample (65%), all individuals were very proactive in attempting to utilize health literacy skills. Findings emphasize the importance of contextual factors such as the quality of communication with the health-care provider, perceptions of control, attitudes to family medical history, navigating structural barriers and being supported in managing treatment and medication side-effects.Discussion and conclusionFindings are relevant for health-care providers in order to enhance the patient-provider relationship and to ensure optimum health outcomes for all individuals regardless of health literacy levels.
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Project description:BackgroundRecognising the early signs of ischemic stroke (IS) in emergency settings has been challenging. Machine learning (ML), a robust tool for predictive, preventive and personalised medicine (PPPM/3PM), presents a possible solution for this issue and produces accurate predictions for real-time data processing.MethodsThis investigation evaluated 4999 IS patients among a total of 10,476 adults included in the initial dataset, and 1076 IS subjects among 3935 participants in the external validation dataset. Six ML-based models for the prediction of IS were trained on the initial dataset of 10,476 participants (split participants into a training set [80%] and an internal validation set [20%]). Selected clinical laboratory features routinely assessed at admission were used to inform the models. Model performance was mainly evaluated by the area under the receiver operating characteristic (AUC) curve. Additional techniques-permutation feature importance (PFI), local interpretable model-agnostic explanations (LIME), and SHapley Additive exPlanations (SHAP)-were applied for explaining the black-box ML models.ResultsFifteen routine haematological and biochemical features were selected to establish ML-based models for the prediction of IS. The XGBoost-based model achieved the highest predictive performance, reaching AUCs of 0.91 (0.90-0.92) and 0.92 (0.91-0.93) in the internal and external datasets respectively. PFI globally revealed that demographic feature age, routine haematological parameters, haemoglobin and neutrophil count, and biochemical analytes total protein and high-density lipoprotein cholesterol were more influential on the model's prediction. LIME and SHAP showed similar local feature attribution explanations.ConclusionIn the context of PPPM/3PM, we used the selected predictors obtained from the results of common blood tests to develop and validate ML-based models for the diagnosis of IS. The XGBoost-based model offers the most accurate prediction. By incorporating the individualised patient profile, this prediction tool is simple and quick to administer. This is promising to support subjective decision making in resource-limited settings or primary care, thereby shortening the time window for the treatment, and improving outcomes after IS.Supplementary informationThe online version contains supplementary material available at 10.1007/s13167-022-00283-4.
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Project description:BackgroundThe premise of disease-related phenotypes is the definition of the counterpart normality in medical sciences. Contrary to clinical practices that can be carefully planned according to clinical needs, heterogeneity and uncontrollability is the essence of humans in carrying out health studies. Full characterization of consistent phenotypes that define the general population is the basis to individual difference normalization in personalized medicine. Self-claimed normal status may not represent health because asymptomatic subjects may carry chronic diseases at their early stage, such as cancer, diabetes mellitus and atherosclerosis. Currently, treatments for non-communicable chronic diseases (NCD) are implemented after disease onset, which is a very much delayed approach from the perspective of predictive, preventive and personalized medicine (PPPM). A NCD pandemic will develop and be accompanied by increased global economic burden for healthcare systems throughout both developed and developing countries. This paper examples the characterization of the suboptimal health status (SHS) which represents a new PPPM challenge in a population with ambiguous health complaints such as general weakness, unexplained medical syndrome (UMS), chronic fatigue syndrome (CFS), myalgic encephalomyelitis (ME), post-viral fatigue syndrome (PVFS) and chronic fatigue immune dysfunction syndrome (CFIDS).MethodsWe applied clinical informatic approaches and developed a questionnaire-suboptimal health status questionnaire-25 (SHSQ-25) for measuring SHS. The validity and reliability of this approach were evaluated in a small pilot study and then in a cross-sectional study of 3,405 participants in China.ResultsWe found a correlation between SHS and systolic blood pressure, diastolic blood pressure, plasma glucose, total cholesterol and high-density lipoprotein (HDL) cholesterol among men, and a correlation between SHS and systolic blood pressure, diastolic blood pressure, total cholesterol, triglycerides and HDL cholesterol among women.ConclusionsThe SHSQ-25 is a self-rated questionnaire of perceived health complaints, which can be used as a new instrument for PPPM. An ongoing longitudinal SHS cohort survey (China Sub-optimal Health Cohort Study, COACS) consisting of 50,000 participants will provide a powerful health trial to use SHSQ-25 for its application to PPPM through patient stratification and therapy monitoring using innovative technologies of predictive diagnostics and prognosis: an effort of paradigm shift from reactive to predictive medicine.
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Project description:BackgroundAlthough substantial progress has been made in reducing total mortality resulting from foodborne diseases, diarrheal illness are still the second most common illnesses among children. In Ghana, foodborne diseases have consistently been among the top 20 causes of outpatient illness over the last couple of decades. This study, therefore, examines health literacy on foodborne diseases and the relative effects of health literacy on self-rated health.MethodsFoodborne diseases are major causes of morbidity and mortality globally. A mixed-method approach was used for this study. A survey questionnaire and an in-depth interview guideline were administered to samples of 401 and 30 individuals, respectively. We undertook reliability and validity analyses. ANOVA and chi-square tests were undertaken to assess bivariate association between health literacy and demographic variables as well as health status. Ordinal logistic regression models were used to examine the relative effects of health literacy on self-rated health status controlling for individual characteristics.ResultsThe instrument was internally consistent (Cronbach alpha = 0.744) and valid. On health literacy, 40% of the respondents reported not to require help when they are given information on foodborne diseases to read by a doctor, nurse, or pharmacist. Approximately 60% of respondents need help with completing or filling out hospital documents. Educational level was found to be positively related to functional health literacy. Ordinal logit regression models showed that health literacy is a predictor of self-rated health after controlling for demographic variables.ConclusionFunctional literacy is relatively low in the community. There is a positive association between educational level and functional health literacy. The study has also demonstrated the direct positive relationship between health literacy and health status controlling for covariates. Subsequent studies will need to examine multiple level dimensions of health literacy with direct link between specific foodborne diseases and health literacy.
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Project description:Background:Previous health literacy research has often focused on individual functional health literacy, ignoring the cultural contexts through which many people experience health care. Objective:We aimed to explore the nature of maternal health literacy among ethnic minority women in a low-resource setting in Vietnam. Methods:Using a qualitative approach, we conducted focus groups with 42 pregnant women, mothers, and grandmothers of children younger than age 5 years from the Thai and Hmong ethnic groups. Semi-structured interviews were conducted with key informants and thematic analysis was performed. Key Results:The findings of our thematic analysis aligned well with the concept of distributed health literacy. We found that ethnic minority women drew upon family and social networks of health literacy mediators to share knowledge and understanding, assess and evaluate information, communicate with health professionals, and support decision-making. Family members were also involved in making health decisions that had the potential to negatively affect women and children's health. Conclusions:Family members are an important source of information for ethnic minority women, and they influence decision-making. Relatives and husbands of pregnant women could be included in maternal health education programs to potentially strengthen the health literacy of the whole community. The distributed health literacy concept can be used to strengthen health promotion messages and to reduce the risk of negative health outcomes. [HLRP: Health Literacy Research and Practice. 2019;3(1):e31-e42.]. Plain Language Summary:Distributed health literacy refers to how health literacy skills and practices are distributed through social networks. This concept applies well to the maternal health context in Vietnam. Older women are trusted sources of information, and family influences decision-making during pregnancy. Women's limited autonomy increases the importance of family involvement. Distributed health literacy could be used to strengthen health promotion messages.
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Project description:Tuberculosis is a major global health issue, with approximately 10 million people falling ill and 1.4 million dying yearly. One of the most significant challenges to public health is the emergence of drug-resistant tuberculosis. For the last half-century, treating tuberculosis has adhered to a uniform management strategy in most patients. However, treatment ineffectiveness in some individuals with pulmonary tuberculosis presents a major challenge to the global tuberculosis control initiative. Unfavorable outcomes of tuberculosis treatment (including mortality, treatment failure, loss of follow-up, and unevaluated cases) may result in increased transmission of tuberculosis and the emergence of drug-resistant strains. Treatment failure may occur due to drug-resistant strains, non-adherence to medication, inadequate absorption of drugs, or low-quality healthcare. Identifying the underlying cause and adjusting the treatment accordingly to address treatment failure is important. This is where approaches such as artificial intelligence, genetic screening, and whole genome sequencing can play a critical role. In this review, we suggest a set of particular clinical applications of these approaches, which might have the potential to influence decisions regarding the clinical management of tuberculosis patients.
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Project description:BackgroundAtherosclerosis is a major contributor to morbidity and mortality worldwide. Although several molecular markers associated with atherosclerosis have been developed in recent years, the lack of robust evidence hinders their clinical applications. For these reasons, identification of novel and robust biomarkers will directly contribute to atherosclerosis management in the context of predictive, preventive, and personalized medicine (PPPM). This integrative analysis aimed to identify critical genetic markers of atherosclerosis and further explore the underlying molecular immune mechanism attributing to the altered biomarkers.MethodsGene Expression Omnibus (GEO) series datasets were downloaded from GEO. Firstly, differential expression analysis and functional analysis were conducted. Multiple machine-learning strategies were then employed to screen and determine key genetic markers, and receiver operating characteristic (ROC) analysis was used to assess diagnostic value. Subsequently, cell-type identification by estimating relative subsets of RNA transcript (CIBERSORT) and a single-cell RNA sequencing (scRNA-seq) data were performed to explore relationships between signatures and immune cells. Lastly, we validated the biomarkers' expression in human and mice experiments.ResultsA total of 611 overlapping differentially expressed genes (DEGs) included 361 upregulated and 250 downregulated genes. Based on the enrichment analysis, DEGs were mapped in terms related to immune cell involvements, immune activating process, and inflaming signals. After using multiple machine-learning strategies, dehydrogenase/reductase 9 (DHRS9) and protein tyrosine phosphatase receptor type J (PTPRJ) were identified as critical biomarkers and presented their high diagnostic accuracy for atherosclerosis. From CIBERSORT analysis, both DHRS9 and PTPRJ were significantly related to diverse immune cells, such as macrophages and mast cells. Further scRNA-seq analysis indicated DHRS9 was specifically upregulated in macrophages of atherosclerotic lesions, which was confirmed in atherosclerotic patients and mice.ConclusionsOur findings are the first to report the involvement of DHRS9 in the atherogenesis, and the proatherogenic effect of DHRS9 is mediated by immune mechanism. In addition, we confirm that DHRS9 is localized in macrophages within atherosclerotic plaques. Therefore, upregulated DHRS9 could be a novel potential target for the future predictive diagnostics, targeted prevention, patient stratification, and personalization of medical services in atherosclerosis.Supplementary informationThe online version contains supplementary material available at 10.1007/s13167-022-00289-y.
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Project description:BackgroundArterial stiffness is a major risk factor and effective predictor of cardiovascular diseases and a common pathway of pathological vascular impairments. Homocysteine (Hcy) and uric acid (UA) own the shared metabolic pathways to affect vascular function. Serum uric acid (UA) has a great impact on arterial stiffness and cardiovascular risk, while the mutual effect with Hcy remains unknown yet. This study aimed to evaluate the mutual effect of serum Hcy and UA on arterial stiffness and 10-year cardiovascular risk in the general population. From the perspective of predictive, preventive, and personalized medicine (PPPM/3PM), we assumed that combined assessment of Hcy and UA provides a better tool for targeted prevention and personalized intervention of cardiovascular diseases via suppressing arterial stiffness.MethodsThis study consisted of 17,697 participants from Beijing Health Management Cohort, who underwent health examination between January 2012 and December 2019. Brachial-ankle pulse wave velocity (baPWV) was used as an index of arterial stiffness.ResultsIndividuals with both high Hcy and UA had the highest baPWV, compared with those with low Hcy and low UA (β: 30.76, 95% CI: 18.36-43.16 in males; β: 53.53, 95% CI: 38.46-68.60 in females). In addition, these individuals owned the highest 10-year cardiovascular risk (OR: 1.49, 95% CI: 1.26-1.76 in males; OR: 7.61, 95% CI: 4.63-12.68 in females). Of note, males with high homocysteine and low uric acid were significantly associated with increased cardiovascular risk (OR: 1.30, 95% CI: 1.15-1.47), but not the high uric acid and low homocysteine group (OR: 1.02, 95% CI: 0.90-1.16).ConclusionsThis study found the significantly mutual effect of Hcy and UA on arterial stiffness and cardiovascular risk using a large population and suggested the clinical importance of combined evaluation and control of Hcy and UA for promoting cardiovascular health. The adverse effect of homocysteine on arteriosclerosis should be addressed beyond uric acid, especially for males. Monitoring of the level of both Hcy and UA provides a window opportunity for PPPM/3PM in the progression of arterial stiffness and prevention of CVD. Hcy provides a novel predictor beyond UA of cardiovascular health to identify individuals at high risk of arterial stiffness for the primary prevention and early treatment of CVD. In the progressive stage of arterial stiffness, active control of Hcy and UA levels from the aspects of dietary behavior and medication treatment is conducive to alleviating the level of arterial stiffness and reducing the risk of CVD. Further studies are needed to evaluate the clinical effect of Hcy and UA targeted intervention on arterial stiffness and cardiovascular health.Supplementary informationThe online version contains supplementary material available at 10.1007/s13167-022-00298-x.
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