ABSTRACT Objective: To examine the associations between individual chronic diseases and multidimensional frailty comprising physical, psychological, and social frailty. Methods: Dutch individuals (N = 47,768) age ≥ 65 years completed a general health questionnaire sent by the Public Health Services (response rate of 58.5 %), including data concerning self-reported chronic diseases, multidimensional frailty, and sociodemographic characteristics. Multidimensional frailty was assessed with the Tilburg Frailty Indicator (TFI). Total frailty and each frailty domain were regressed onto background characteristics and the six most prevalent chronic diseases: diabetes mellitus, cancer, hypertension, arthrosis, urinary incontinence, and severe back disorder. Multimorbidity was defined as the presence of combinations of these six diseases. Results: The six chronic diseases had medium and strong associations with total ((f2 = 0.122) and physical frailty (f2 = 0.170), respectively, and weak associations with psychological (f2 = 0.023) and social frailty (f2 = 0.008). The effects of the six diseases on the frailty variables differed strongly across diseases, with urinary incontinence and severe back disorder impairing frailty most. No synergetic effects were found; the effects of a disease on frailty did not get noteworthy stronger in the presence of another disease. Conclusions: Chronic diseases, in particular urinary incontinence and severe back disorder, were associated with frailty. We thus recommend assigning different weights to individual chronic diseases in a measure of multimorbidity that aims to examine effects of multimorbidity on multidimensional frailty. Because there were no synergetic effects of chronic diseases, the measure does not need to include interactions between diseases.
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In deze literatuurstudie werden vier databanken doorzocht met behulp van trefwoorden zoals chronic disease, e-health, factors en suggested interventions. Kwalitatieve, kwantitatieve en mixed methods-studies werden meegenomen. Uit de data van de 22 artikelen die werden geïncludeerd in de studie, blijken leeftijd, geslacht, inkomen, opleidingsniveau, etnische achtergrond en woonplaats (stad of platteland) in meer of mindere mate van invloed te zijn op het gebruik van e-health. Het artikel is een Nederlandstalige samenvatting van het artikel: Reiners, Sturm, Bouw & Wouters (2019) uit Int J Environ Res Public Health 2019;16(4)
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Alongside the growing number of older persons, the prevalence of chronic diseases is increasing, leading to higher pressure on health care services. eHealth is considered a solution for better and more efficient health care. However, not every patient is able to use eHealth, for several reasons. This study aims to provide an overview of: (1) sociodemographic factors that influence the use of eHealth; and (2) suggest directions for interventions that will improve the use of eHealth in patients with chronic disease. A structured literature review of PubMed, ScienceDirect, Association for Computing Machinery Digital Library (ACMDL), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) was conducted using four sets of keywords: “chronic disease”, “eHealth”, “factors”, and “suggested interventions”. Qualitative, quantitative, and mixed-method studies were included. Four researchers each assessed quality and extracted data. Twenty-two out of 1639 articles were included. Higher age and lower income, lower education, living alone, and living in rural areas were found to be associated with lower eHealth use. Ethnicity revealed mixed outcomes. Suggested solutions were personalized support, social support, use of different types of Internet devices to deliver eHealth, and involvement of patients in the development of eHealth interventions. It is concluded that eHealth is least used by persons who need it most. Tailored delivery of eHealth is recommended
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Chronic diseases represent a significant burden for the society and health systems; addressing this burden is a key goal of the European Union policy. Health and other professionals are expected to deliver behaviour change support to persons with chronic disease. A skill gap in behaviour change support has been identified, and there is room for improvement. Train4Health is a strategic partnership involving seven European Institutions in five countries, which seeks to improve behaviour change support competencies for the self-management of chronic disease. The project envisages a continuum in behaviour change support education, in which an interprofessional competency framework, relevant for those currently practising, guides the development of a learning outcomes-based curriculum and an educational package for future professionals (today’s undergraduate students).
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Purpose: The aim of this study was to investigate the occupational well-being among employees with chronic diseases, and the buffering effect of four job resources, possibly offering targets to enhance occupational well-being.Method: This cross-sectional study (N = 1951) was carried out among employees in educational and (semi-)governmental organizations in the Netherlands. The dimensions of the survey were chronic diseases (i.e., physical, mental, or both physical and mental), occupational well-being (i.e., work ability, burnout complaints, and work engagement), and job resources (i.e., autonomy, social support by colleagues, supportive leadership style, and open and communicative culture). First, it was analyzed if chronic diseases were associated with occupational well-being. Second, it was analyzed if each of the four job resources would predict better occupational well-being. Third, possible moderation effects between the chronic disease groups and each job resource on occupational well-being were examined. Regression analyses were used, controlling for age.Results: Each chronic disease group was associated with a lower work ability. However, higher burnout complaints and a lower work engagement were only predicted by the group with mental chronic diseases and by the group with both physical and mental chronic disease(s). Furthermore, all four job resources predicted lower burnout complaints and higher work engagement, while higher work ability was only predicted by autonomy and a supportive leadership style. Some moderation effects were observed. Autonomy buffered the negative relationship between the chronic disease groups with mental conditions (with or without physical conditions) and work ability, and the positive relationship between the group with both physical and mental chronic disease(s) and burnout complaints. Furthermore, a supportive leadership style is of less benefit for occupational well-being among the employees with mental chronic diseases (with or without physical chronic diseases) compared to the group employees without chronic diseases. No buffering was demonstrated for social support of colleagues and an open and communicative organizational culture.Conclusion: Autonomy offers opportunities to reinforce occupational well-being among employees with mental chronic diseases. A supportive leadership style needs more investigation to clarify why this job resource is less beneficial for employees with mental chronic diseases than for the employees without chronic diseases.
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BackgroundTo describe the prevalence of multimorbidity and to study the association between acute and chronic diseases in acutely hospitalized older patientsMethodsProspective cohort study conducted between 2006 and 2008 in three teaching hospitals in the Netherlands. 639 patients aged 65 years and older, hospitalized for > 48 h were included. Two physicians scored diseases, using ICD-9 codes. Chronic multimorbidity was defined as the presence of ≥ 2 chronic diseases, and acute multimorbidity as ≥ 1 acute diseases upon pre-existent chronic diseases. Logistic regression analyses were conducted to analyse cluster associations between a chronic index disease and the concurrent chronic or acute disease, corrected for age and sex.ResultsThe mean age of patients was 78 years, over 50% had ADL impairments. Prevalence of chronic multimorbidity was 69%, and acute multimorbidity was present in 88%. Hypertension (OR 1.16; 95% CI 1.08–1.24), diabetes (type I or type 2) (OR 1.12; 95% CI 1.04–1.21), heart failure (OR 1.25; 95% CI 1.14–1.38) and COPD (OR 1.19; 95% CI 1.05–1.34) were associated with acute renal failure. Hypertension (OR 1.10; 95% CI 1.04–1.17) and atrial fibrillation (OR 1.17; 95% CI 1.08–1.27) were associated with an adverse drug event. Gastro-intestinal bleeding was clustered with atrial fibrillation (OR 1.11; 95% CI 1.04–1.19) and gastric ulcer (OR 1.16; 95% CI 1.07–1.25).ConclusionBoth acute and chronic multimorbidity was frequently present in hospitalized older patients. We identified specific associations between acute and chronic diseases. There is a need for strategies addressing multimorbidity during the exacerbation of chronic diseases.
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This open access book is a valuable resource for students in health and other professions and practicing professionals interested in supporting effective change in self-management behaviors in chronic disease, such as medication taking, physical activity and healthy eating. Developed under the auspices of the Train4Health project, funded by the Erasmus+ program of the European Union, the book contains six chapters written by international contributors from different disciplines. This chapter sets the stage for the remaining book, by introducing the Train4Health project and by explaining how the learning outcomes presented in subsequent chapters have been derived and linked with content of the book. Firstly, the Train4Health interprofessional competency framework to support behaviour change in persons self-managing chronic disease is briefly presented. This European competency framework was the starting point for developing the learning outcomes-based curriculum, which is succinctly addressed in the subsequent section. Finally, practical considerations about the Train4Health curriculum are discussed, including opportunities and challenges for interprofessional education.
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Background: Effective telemonitoring is possible through repetitive collection of electronic patient-reported outcome measures (ePROMs) in patients with chronic diseases. Low adherence to telemonitoring may have a negative impact on the effectiveness, but it is unknown which factors are associated with adherence to telemonitoring by ePROMs. The objective was to identify factors associated with adherence to telemonitoring by ePROMs in patients with chronic diseases. Methods: A systematic literature search was conducted in PubMed, Embase, PsycINFO and the Cochrane Library up to 8 June 2021. Eligibility criteria were: (1) interventional and cohort studies, (2) patients with a chronic disease, (3) repetitive ePROMs being used for telemonitoring, and (4) the study quantitatively investigating factors associated with adherence to telemonitoring by ePROMs. The Cochrane risk of bias tool and the risk of bias in nonrandomized studies of interventions were used to assess the risk of bias. An evidence synthesis was performed assigning to the results a strong, moderate, weak, inconclusive or an inconsistent level of evidence. Results: Five studies were included, one randomized controlled trial, two prospective uncontrolled studies and two retrospective cohort studies. A total of 15 factors potentially associated with adherence to telemonitoring by ePROMs were identified in the predominate studies of low quality. We found moderate-level evidence that sex is not associated with adherence. Some studies showed associations of the remaining factors with adherence, but the overall results were inconsistent or inconclusive. Conclusions: None of the 15 studied factors had conclusive evidence to be associated with adherence. Sex was, with moderate strength, not associated with adherence. The results were conflicting or indecisive, mainly due to the low number and low quality of studies. To optimize adherence to telemonitoring with ePROMs, mixed-method studies are needed.
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PURPOSE: To assess the association of clinical variables and the development of specified chronic conditions in ICU survivors.MATERIALS AND METHODS: A retrospective cohort study, combining a national health insurance claims database and a national quality registry for ICUs. Claims data from 2012 to 2014 were combined with clinical data of patients admitted to an ICU during 2013. To assess the association of clinical variables (ICU length of stay, mechanical ventilation, acute physiology score, reason for ICU admission, mean arterial pressure score and glucose score) and the development of chronic conditions (i.e. heart diseases, COPD or asthma, Diabetes mellitus type II, depression and kidney diseases), logistic regression was used.RESULTS: 49,004 ICU patients were included. ICU length of stay was associated with the development of heart diseases, asthma or COPD and depression. The reason for ICU admission was an important risk factor for the development of all chronic conditions with adjusted ORs ranging from 2.05 (CI 1.56; 2.69) for kidney diseases to 5.14 (CI 3.99; 6.62) for depression.CONCLUSIONS: Clinical variables, especially the reason for ICU admission, are associated with the development of chronic conditions after ICU discharge. Therefore, these clinical variables should be considered when organizing follow-up care for ICU survivors.
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Objective: The aim of this cross-sectional study was to determine the associations between frailty and multimorbidity on the one hand and quality of life on the other in community-dwelling older people. Methods: A questionnaire was sent to all people aged 70 years and older belonging to a general practice in the Netherlands; 241 persons completed the questionnaire (response rate 47.5%). For determining multimorbidity, nine chronic diseases were examined by self-report. Frailty was assessed by the Tilburg Frailty Indicator, and quality of life was assessed by the World Health Organization Quality of Life Instrument—Older Adults Module. Results: Multimorbidity, physical, psychological, as well as social frailty components were negatively associated with quality of life. Multimorbidity and all 15 frailty components together explained 11.6% and 36.5% of the variance of the score on quality of life, respectively. Conclusion: Health care professionals should focus their interventions on the physical, psychological, and social domains of human functioning. Interprofessional cooperation between health care professionals and welfare professionals seems necessary to be able to meet the needs of frail older people.
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