Abstract: Combined lifestyle interventions (CLI) are focused on guiding clients with weight-related health risks into a healthy lifestyle. CLIs are most often delivered through face-to-face sessions with limited use of eHealth technologies. To integrate eHealth into existing CLIs, it is important to identify how behavior change techniques are being used by health professionals in the online and offline treatment of overweight clients. Therefore, we conducted online semi-structured interviews with providers of online and offline lifestyle interventions. Data were analyzed using an inductive thematic approach. Thirty-eight professionals with (n = 23) and without (n = 15) eHealth experience were interviewed. Professionals indicate that goal setting and action planning, providing feedback and monitoring, facilitating social support, and shaping knowledge are of high value to improve physical activity and eating behaviors. These findings suggest that it may be beneficial to use monitoring devices combined with video consultations to provide just-in-time feedback based on the client’s actual performance. In addition, it can be useful to incorporate specific social support functions allowing CLI clients to interact with each other. Lastly, our results indicate that online modules can be used to enhance knowledge about health consequences of unhealthy behavior in clients with weight-related health risks.
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Abstract Background: Lifestyle interventions for severe mental illness (SMI) are known to have small to modest efect on physical health outcomes. Little attention has been given to patient-reported outcomes (PROs). Aim: To systematically review the use of PROs and their measures, and quantify the efects of lifestyle interventions in patients with SMI on these PROs. Methods: Five electronic databases were searched (PubMed/Medline, Embase, PsycINFO, CINAHL, and Web of Science) from inception until 12 November 2020 (PROSPERO: CRD42020212135). Randomised controlled trials (RCTs) evaluating the efcacy of lifestyle interventions focusing on healthy diet, physical activity, or both for patients with SMI were included. Outcomes of interest were PROs. Results: A total of 11.267 unique records were identifed from the database search, 66 full-text articles were assessed, and 36 RCTs were included, of which 21 were suitable for meta-analyses. In total, 5.907 participants were included across studies. Lifestyle interventions had no signifcant efect on quality of life (g=0.13; 95% CI=−0.02 to 0.27), with high heterogeneity (I2 =68.7%). We found a small efect on depression severity (g=0.30, 95% CI=0.00 to 0.58, I2 =65.2%) and a moderate efect on anxiety severity (g=0.56, 95% CI=0.16 to 0.95, I2 =0%). Discussion: This meta-analysis quantifes the efects of lifestyle interventions on PROs. Lifestyle interventions have no signifcant efect on quality of life, yet they could improve mental health outcomes such as depression and anxiety symptoms. Further use of patient-reported outcome measures in lifestyle research is recommended to fully capture the impact of lifestyle interventions.
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The combination of self-tracking and persuasive eCoaching in healthy lifestyle interventions is a promising approach. The objective of this study is to map the key components of existing healthy lifestyle interventions combining self-tracking and persuasive eCoaching using the scoping review methodology in accordance with the York methodological framework by Arksey and O’Malley. Seven studies were included in this preliminary scoping review. Components related to persuasive eCoaching applied only in effective interventions were reduction of complex behavior into small steps, providing positive motivational feedback by praise and providing reliable information to show expertise. Concerning self-tracking, it did not seem to matter if more action was required by the participant to obtain personal data. The first results of this study indicate the necessity to identify the needs and problems of the specific target group of the interventions, due to differences found between various groups of users. In addition to objective data on lifestyle and health behavior, other factors need to be taken into account, such as the context of use, daily experiences, and feelings of the users.
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(1) Background: Recent research showed that subtypes of patients with type 2 diabetes may differ in response to lifestyle interventions based on their organ-specific insulin resistance (IR). (2) Methods: 123 Subjects with type 2 diabetes were randomized into 13-week lifestyle intervention, receiving either an enriched protein drink (protein+) or an isocaloric control drink (control). Before and after the intervention, anthropometrical and physiological data was collected. An oral glucose tolerance test was used to calculate indices representing organ insulin resistance (muscle, liver, and adipose tissue) and β-cell functioning. In 82 study-compliant subjects (per-protocol), we retrospectively examined the intervention effect in patients with muscle IR (MIR, n = 42) and without MIR (no-MIR, n = 40). (3) Results: Only in patients from the MIR subgroup that received protein+ drink, fasting plasma glucose and insulin, whole body, liver and adipose IR, and appendicular skeletal muscle mass improved versus control. Lifestyle intervention improved body weight and fat mass in both subgroups. Furthermore, for the MIR subgroup decreased systolic blood pressure and increased VO2peak and for the no-MIR subgroup, a decreased 2-h glucose concentration was found. (4) Conclusions: Enriched protein drink during combined lifestyle intervention seems to be especially effective on increasing muscle mass and improving insulin resistance in obese older, type 2 diabetes patients with muscle IR.
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Aim: To explore 1) GPs´ motivation to refer to lifestyle interventions and to investigate the association between GPs’ own lifestyle-behaviors and their referral behavior, and 2) patient indicators in the decision-making process of the GPs’ referral to lifestyle interventions. Method: A cross-sectional study was conducted among 99 Dutch primary care GPs. Their motivation to refer was assessed by beliefs regarding lifestyle interventions. GPs’ referral behaviors were assessed - considering referral and self-reported actual referral - and their own lifestyle behaviors - physical activity, dieting, being overweight). Decision-making regarding referring patients to lifestyle interventions was assessed by imposed patient indicators, spontaneously suggested decisive patient indicators, and by case-based referring (vignettes).Results: A substantial group of GPs was not motivated for referral to lifestyle interventions. GPs’ refer behavior was significantly associated with their perceived subjective norm, behavioral control, and their own physical activity and diet. Most important patient indicators in referral to lifestyle interventions were somatic indicators, and patients’ motivation for lifestyle interventions.Conclusions: GPs motivation and referral behavior might be improved by providing them with tailored resources about evidence based lifestyle interventions, with support from allied health professionals, and with official guidelines for a more objective and systematic screening of patients.
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Background: Insufficient amounts of physical activity is a risk factor for (recurrent) stroke. People with a stroke or transient ischemic attack (TIA) have a high risk of recurrent stroke and have lower levels of physical activity than their healthy peers. Though several reviews have looked at the effects of lifestyle interventions on a number of risk factors of recurrent stroke, the effectiveness of these interventions to increase the amounts of physical activity performed by people with stroke or TIA are still unclear. Therefore, the research question of this study was: what is the effect of lifestyle interventions on the level of physical activity performed by people with stroke or TIA? Method: A systematic review was conducted following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) statement. Pubmed, Embase and Cumulative Index for Nursing and Allied Health Literature (CINAHL), were searched up to August 2018. Randomised controlled trials that compared lifestyle interventions, aimed to increase the amount of physical activity completed by participants with a stroke or TIA, with controls were included. The Physiotherapy Evidence Database (PEDro) score was used to assess the quality of the articles, and the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) method for the best evidence synthesis. Results: Eleven trials (n = 2403) met the inclusion criteria. The quality of the trials was mostly high, with 8 (73%) of trials scoring ≥6 on the PEDro scale. The overall best evidence syntheses showed moderate quality evidence that lifestyle interventions do not lead to significant improvements in the physical activity level of people with stroke or TIA. There is low quality evidence that lifestyle interventions that specifically target physical activity are effective at improving the levels of physical activity of people with stroke or TIA. Conclusion: Based on the results of this review, general lifestyle interventions on their own seem insufficient in improving physical activity levels after stroke or TIA. Lifestyle interventions that specifically encourage increasing physical activity may be more effective. Further properly powered trials using objective physical activity measures are needed to determine the effectiveness of such interventions.
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To analyze the intervention components, levels of influence, explicit use of theory, and conditions for sustainability of currently used lifestyle interventions within lifestyle approaches aiming at physical activity and nutrition in healthcare organizations supporting people with Intellectual Disabilities (ID).
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Abstract Background: Multidimensional frailty, including physical, psychological, and social components, is associated to disability, lower quality of life, increased healthcare utilization, and mortality. In order to prevent or delay frailty, more knowledge of its determinants is necessary; one of these determinants is lifestyle. The aim of this study is to determine the association between lifestyle factors smoking, alcohol use, nutrition, physical activity, and multidimensional frailty. Methods: This cross-sectional study was conducted in two samples comprising in total 45,336 Dutch communitydwelling individuals aged 65 years or older. These samples completed a questionnaire including questions about smoking, alcohol use, physical activity, sociodemographic factors (both samples), and nutrition (one sample). Multidimensional frailty was assessed with the Tilburg Frailty Indicator (TFI). Results: Higher alcohol consumption, physical activity, healthy nutrition, and less smoking were associated with less total, physical, psychological and social frailty after controlling for effects of other lifestyle factors and sociodemographic characteristics of the participants (age, gender, marital status, education, income). Effects of physical activity on total and physical frailty were up to considerable, whereas the effects of other lifestyle factors on frailty were small. Conclusions: The four lifestyle factors were not only associated with physical frailty but also with psychological and social frailty. The different associations of frailty domains with lifestyle factors emphasize the importance of assessing frailty broadly and thus to pay attention to the multidimensional nature of this concept. The findings offer healthcare professionals starting points for interventions with the purpose to prevent or delay the onset of frailty, so communitydwelling older people have the possibility to aging in place accompanied by a good quality of life.
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Rationale: While combined lifestyle interventions have multiple health benefits, their impact on the oral microbiome is not known. We explored the effects of a lifestyle intervention including protein drink on the oral microbiome in older adults with obesity and type 2 diabetes (T2D).Methods: In a post-hoc analysis of the PROBE study, 87 subjects (66.5±6.1 years, 33% female) with tongue dorsum samples at baseline and week 13 were included. All subjects participated in a 13-week lifestyle intervention with exercise (3x/week) and hypocaloric diet (-600 kcal/day), and had been randomized to receive a test product (21g whey protein enriched with leucine and vitamin D) or isocaloric control (0g protein) 10x/week. T2D was subtyped as muscle insulin resistance (MIR, n=34) or no-MIR (n=36) based on available muscle insulin sensitivity index. Microbiome was analysed by V4 16s rDNA sequencing. Diversity, measured as species richness and Shannon diversity index, was statistically analysed with paired (within group) and independent (between groups) samples t-test.Results: displayed below. Conclusion: Consuming a whey protein drink enriched with leucine and vitamin D during a combined lifestyle intervention increased species richness of the oral microbiome in obese T2D subjects with muscle insulin resistance.
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Background: The combination of self-tracking and persuasive eCoaching in automated interventions is a new and promising approach for healthy lifestyle management. Objective: The aim of this study was to identify key components of self-tracking and persuasive eCoaching in automated healthy lifestyle interventions that contribute to their effectiveness on health outcomes, usability, and adherence. A secondary aim was to identify the way in which these key components should be designed to contribute to improved health outcomes, usability, and adherence. Methods: The scoping review methodology proposed by Arskey and O'Malley was applied. Scopus, EMBASE, PsycINFO, and PubMed were searched for publications dated from January 1, 2013 to January 31, 2016 that included (1) self-tracking, (2) persuasive eCoaching, and (3) healthy lifestyle intervention. Results: The search resulted in 32 publications, 17 of which provided results regarding the effect on health outcomes, 27 of which provided results regarding usability, and 13 of which provided results regarding adherence. Among the 32 publications, 27 described an intervention. The most commonly applied persuasive eCoaching components in the described interventions were personalization (n=24), suggestion (n=19), goal-setting (n=17), simulation (n=17), and reminders (n=15). As for self-tracking components, most interventions utilized an accelerometer to measure steps (n=11). Furthermore, the medium through which the user could access the intervention was usually a mobile phone (n=10). The following key components and their specific design seem to influence both health outcomes and usability in a positive way: reduction by setting short-term goals to eventually reach long-term goals, personalization of goals, praise messages, reminders to input self-tracking data into the technology, use of validity-tested devices, integration of self-tracking and persuasive eCoaching, and provision of face-to-face instructions during implementation. In addition, health outcomes or usability were not negatively affected when more effort was requested from participants to input data into the technology. The data extracted from the included publications provided limited ability to identify key components for adherence. However, one key component was identified for both usability and adherence, namely the provision of personalized content. Conclusions: This scoping review provides a first overview of the key components in automated healthy lifestyle interventions combining self-tracking and persuasive eCoaching that can be utilized during the development of such interventions. Future studies should focus on the identification of key components for effects on adherence, as adherence is a prerequisite for an intervention to be effective.
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