| 1. |
- van Wanrooij, Lennard L., et al.
(författare)
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Pooling individual participant data from randomized controlled trials : Exploring potential loss of information
- 2020
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 15:5
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Tidskriftsartikel (refereegranskat)abstract
- Background Pooling individual participant data to enable pooled analyses is often complicated by diversity in variables across available datasets. Therefore, recoding original variables is often necessary to build a pooled dataset. We aimed to quantify how much information is lost in this process and to what extent this jeopardizes validity of analyses results. Methods Data were derived from a platform that was developed to pool data from three randomized controlled trials on the effect of treatment of cardiovascular risk factors on cognitive decline or dementia. We quantified loss of information using the R-squared of linear regression models with pooled variables as a function of their original variable(s). In case the R-squared was below 0.8, we additionally explored the potential impact of loss of information for future analyses. We did this second step by comparing whether the Beta coefficient of the predictor differed more than 10% when adding original or recoded variables as a confounder in a linear regression model. In a simulation we randomly sampled numbers, recoded those < = 1000 to 0 and those > 1000 to 1 and varied the range of the continuous variable, the ratio of recoded zeroes to recoded ones, or both, and again extracted the R-squared from linear models to quantify information loss. Results The R-squared was below 0.8 for 8 out of 91 recoded variables. In 4 cases this had a substantial impact on the regression models, particularly when a continuous variable was recoded into a discrete variable. Our simulation showed that the least information is lost when the ratio of recoded zeroes to ones is 1:1. Conclusions Large, pooled datasets provide great opportunities, justifying the efforts for data harmonization. Still, caution is warranted when using recoded variables which variance is explained limitedly by their original variables as this may jeopardize the validity of study results.
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| 2. |
- Akenine, Ulrika, et al.
(författare)
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Attitudes of at-risk older adults about prevention of cardiovascular disease and dementia using eHealth : a qualitative study in a European context
- 2020
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Ingår i: BMJ Open. - 2044-6055. ; 10:8
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Tidskriftsartikel (refereegranskat)abstract
- Objectives Prevention of cardiovascular disease (CVD) and dementia is a key health priority among older adults. Understanding individuals’ attitudes to, the prevention of these conditions, particularly when delivered through novel eHealth tools, could help in designing effective prevention programmes. The aim of the study was to explore the attitudes of older adults at increased risk of CVD and dementia regarding engagement in eHealth self-management prevention programmes, and to describe the facilitators and barriers.Design A qualitative research approach was used. Data were collected through eight focus groups in Finland, France and the Netherlands. Data were analysed following the principles of grounded theory.Setting and participants Forty-four community-dwellers aged 65+ at risk of CVD were recruited from a previous trial cohort in Finland, and through general practices in France and the Netherlands.Results The study identified three categories: access to reliable information, trust in the healthcare providers and burden and stigma of dementia. A core category was also identified: the interactive process of the three categories influencing engagement in self-management prevention programme. The categories were interconnected through an interactive process and influenced by the local healthcare culture and context which shaped them differently, becoming either facilitators or barriers to engage in eHealth self-management prevention programmes.Conclusions The study emphasises the importance of considering the interactions between the identified categories in this study, grounded in the local healthcare culture and context in further developments of eHealth self-management interventions that aim to prevent CVD and dementia.
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| 3. |
- Beishuizen, Cathrien R. L., et al.
(författare)
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Web-Based Interventions Targeting Cardiovascular Risk Factors in Middle-Aged and Older People : A Systematic Review and Meta-Analysis
- 2016
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Ingår i: Journal of Medical Internet Research. - : JMIR Publications Inc.. - 1438-8871. ; 18:3
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Forskningsöversikt (refereegranskat)abstract
- Background: Web-based interventions can improve single cardiovascular risk factors in adult populations. In view of global aging and the associated increasing burden of cardiovascular disease, older people form an important target population as well.Objective: In this systematic review and meta-analysis, we evaluated whether Web-based interventions for cardiovascular risk factor management reduce the risk of cardiovascular disease in older people.Methods: Embase, Medline, Cochrane and CINAHL were systematically searched from January 1995 to November 2014. Search terms included cardiovascular risk factors and diseases (specified), Web-based interventions (and synonyms) and randomized controlled trial. Two authors independently performed study selection, data-extraction and risk of bias assessment. In a meta-analysis, outcomes regarding treatment effects on cardiovascular risk factors (blood pressure, glycated hemoglobin A1c (HbA1C), low-density lipoprotein (LDL) cholesterol, smoking status, weight and physical inactivity) and incident cardiovascular disease were pooled with random effects models.Results: A total of 57 studies (N=19,862) fulfilled eligibility criteria and 47 studies contributed to the meta-analysis. A significant reduction in systolic blood pressure (mean difference -2.66 mmHg, 95% CI -3.81 to -1.52), diastolic blood pressure (mean difference -1.26 mmHg, 95% CI -1.92 to -0.60), HbA1c level (mean difference -0.13%, 95% CI -0.22 to -0.05), LDL cholesterol level (mean difference -2.18 mg/dL, 95% CI -3.96 to -0.41), weight (mean difference -1.34 kg, 95% CI -1.91 to -0.77), and an increase of physical activity (standardized mean difference 0.25, 95% CI 0.10-0.39) in the Web-based intervention group was found. The observed effects were more pronounced in studies with short (<12 months) follow-up and studies that combined the Internet application with human support (blended care). No difference in incident cardiovascular disease was found between groups (6 studies).Conclusions: Web-based interventions have the potential to improve the cardiovascular risk profile of older people, but the effects are modest and decline with time. Currently, there is insufficient evidence for an effect on incident cardiovascular disease. A focus on long-term effects, clinical endpoints, and strategies to increase sustainability of treatment effects is recommended for future studies.
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| 4. |
- Hoevenaar-Blom, Marieke P., et al.
(författare)
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Improving data sharing in research with context-free encoded missing data
- 2017
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 12:9
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Tidskriftsartikel (refereegranskat)abstract
- Lack of attention to missing data in research may result in biased results, loss of power and reduced generalizability. Registering reasons for missing values at the time of data collection, or-in the case of sharing existing data-before making data available to other teams, can save time and efforts, improve scientific value and help to prevent erroneous assumptions and biased results. To ensure that encoding of missing data is sufficient to understand the reason why data are missing, it should ideally be context-free. Therefore, 11 context-free codes of missing data were carefully designed based on three completed randomized controlled clinical trials and tested in a new randomized controlled clinical trial by an international team consisting of clinical researchers and epidemiologists with extended experience in designing and conducting trials and an Information System expert. These codes can be divided into missing due to participant and/or participation characteristics (n = 6), missing by design (n = 4), and due to a procedural error (n = 1). Broad implementation of context-free missing data encoding may enhance the possibilities of data sharing and pooling, thus allowing more powerful analyses using existing data.
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| 5. |
- Richard, Edo, et al.
(författare)
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Healthy Ageing Through Internet Counselling in the Elderly : the HATICE randomised controlled trial for the prevention of cardiovascular disease and cognitive impairment
- 2016
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Ingår i: BMJ Open. - : BMJ. - 2044-6055. ; 6:6
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Tidskriftsartikel (refereegranskat)abstract
- Introduction Cardiovascular disease and dementia share a number of risk factors including hypertension, hypercholesterolaemia, smoking, obesity, diabetes and physical inactivity. The rise of eHealth has led to increasing opportunities for large-scale delivery of prevention programmes encouraging self-management. The aim of this study is to investigate whether a multidomain intervention to optimise self-management of cardiovascular risk factors in older individuals, delivered through an coach-supported interactive internet platform, can improve the cardiovascular risk profile and reduce the risk of cardiovascular disease and cognitive decline. Methods and analysis HATICE is a multinational, multicentre, prospective, randomised, open-label blinded end point (PROBE) trial with 18months intervention. Recruitment of 2600 older people (65years) at increased risk of cardiovascular disease will take place in the Netherlands, Finland and France. Participants randomised to the intervention condition will have access to an interactive internet platform, stimulating self-management of vascular risk factors, with remote support by a coach. Participants in the control group will have access to a static internet platform with basic health information. The primary outcome is a composite score based on the average z-score of the difference between baseline and 18months follow-up values of systolic blood pressure, low-density-lipoprotein and body mass index. Main secondary outcomes include the effect on the individual components of the primary outcome, the effect on lifestyle-related risk factors, incident cardiovascular disease, mortality, cognitive functioning, mood and cost-effectiveness.
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