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.
Background: Improved preferred gait speed in older adults is associated with increased survival rates. There are inconsistent findings in clinical trials regarding effects of exercise on preferred gait speed, and heterogeneity in interventions in the current reviews and meta-analyses. Objective: to determine the meta-effects of different types or combinations of exercise interventions from randomized controlled trials on improvement in preferred gait speed. Methods: Data sources: A literature search was performed; the following databases were searched for studies from 1990 up to 9 December 2013: PubMed, EMBASE, EBSCO (AMED, CINAHL, ERIC, Medline, PsycInfo, and SocINDEX), and the Cochrane Library. Study eligibility criteria: Randomized controlled trials of exercise interventions for older adults ≥ 65 years, that provided quantitative data (mean/SD) on preferred gait speed at baseline and post-intervention, as a primary or secondary outcome measure in the published article were included. Studies were excluded when the PEDro score was ≤4, or if participants were selected for a specific neurological or neurodegenerative disease, Chronic Obstructive Pulmonary Disease, cardiovascular disease, recent lower limb fractures, lower limb joint replacements, or severe cognitive impairments. The meta-effect is presented in Forest plots with 95 % confidence Study appraisal and synthesis methods: intervals and random weights assigned to each trial. Homogeneity and risk of publication bias were assessed. Results: Twenty-five studies were analysed in this meta-analysis. Data from six types or combinations of exercise interventions were pooled into sub-analyses. First, there is a significant positive meta-effect of resistance training progressed to 70-80 % of 1RM on preferred gait speed of 0.13 [CI 95 % 0.09-0.16] m/s. The difference between intervention- and control groups shows a substantial meaningful change (>0.1 m/s). Secondly, a significant positive meta-effect of interventions with a rhythmic component on preferred gait speed of 0.07 [CI 95 % 0.03-0.10] m/s was found. Thirdly, there is a small significant positive meta-effect of progressive resistance training, combined with balance-, and endurance training of 0.05 [CI 95 % 0.00-0.09] m/s. The other sub-analyses show non-significant small positive meta-affects. Conclusions: Progressive resistance training with high intensities, is the most effective exercise modality for improving preferred gait speed. Sufficient muscle strength seems an important condition for improving preferred gait speed. The addition of balance-, and/or endurance training does not contribute to the significant positive effects of progressive resistance training. A promising component is exercise with a rhythmic component. Keeping time to music or rhythm possibly trains higher cognitive functions that are important for gait. Limitations: The focus of the present meta-analysis was at avoiding as much heterogeneity in exercise interventions. However heterogeneity in the research populations could not be completely avoided, there are probably differences in health status within different studies.
Study selection: Randomized controlled trials published after 2007 with (former) healthcare patients ≥ 21 years of age were included if physical activity was measured objectively using a wearable monitor for both feedback and outcome assessment. The main goal of included studies was promoting physical activity. Any concurrent strategies were related only to promoting physical activity. Data extraction: Effect sizes were calculated using a fixed-effects model with standardized mean difference. Information on study characteristics and interventions strategies were extracted from study descriptions. Data synthesis: Fourteen studies met the inclusion criteria (total n = 1,902), and 2 studies were excluded from meta-analysis. The overall effect size was in favour of the intervention groups (0.34, 95% CI 0.23–0.44, p < 0.01). Study characteristics and intervention strategies varied widely. Conclusion: Healthcare interventions using feedback on objectively monitored physical activity have a moderately positive effect on levels of physical activity. Further research is needed to determine which strategies are most effective to promote physical activity in healthcare programmes. Lay Abstract Wearable technology is progressively applied in health care and rehabilitation to provide objective insight into physical activity levels. In addition, feedback on physical activity levels delivered by wearable monitors might be beneficial for optimizing their physical activity. A systematic review and meta-analysis was conducted to evaluate the effectiveness of interventions using feedback on objectively measured physical activity in patient populations. Fourteen studies including 1902 patients were analyzed. Overall, the physical activity levels of the intervention groups receiving objective feedback on physical activity improved, compared to the control groups receiving no objective feedback. Mostly, a variety of other strategies were applied in the interventions next to wearable technology. Together with wearable technology, behavioral change strategies, such as goal-setting and action planning seem to be an important ingredient to promote physical activity in health care and rehabilitation. LinkedIn: https://www.linkedin.com/in/hanneke-braakhuis-b9277947/ https://www.linkedin.com/in/moniqueberger/
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