Effectiveness of Physical Activity Intervention on ADHD Symptoms: A Systematic Review and Meta-Analysis.
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ABSTRACT:
SUBMITTER: Xie Y
PROVIDER: S-EPMC8575983 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundWith the popularity of computers, the internet, and the global spread of COVID-19, more and more attention deficit hyperactivity disorder (ADHD) patients need timely interventions through the internet. At present, there are many online intervention schemes may help these patients. It is necessary to integrate data to analyze their effectiveness.ObjectivesOur purpose is to integrate the ADHD online interventions trials, study its treatment effect and analyze its feasibility, and provide reference information for doctors in other institutions to formulate better treatment plans.MethodsWe searched PubMed, EMBASE and Cochrane libraries. We didn't limit the start date and end date of search results. Our last search was on December 1, 2021. The keyword is ADHD online therapy. We used the Cochrane bias risk tool to assess the quality of included studies, used the standardized mean difference (SMD) as an effect scale indicator to measure data. Random effects model, subgroup analysis were used to analyze the data.ResultsSix randomized controlled trials (RCTs) were identified, including 261 patients with ADHD. These studies showed that online interventions was more effective than waiting list in improving attention deficit and social function of adults and children with ADHD. The attention deficit scores of subjects were calculated in six studies. The sample size of the test group was 123, the sample size of the control group was 133, and the combined SMD was -0.73 (95% confidence interval: -1.01, -0.44). The social function scores of subjects were calculated in six studies. The sample size of the experimental group was 123 and the control group was 133. The combined SMD was -0.59 (95% confidence interval: -0.85, -0.33).ConclusionsThe results show that online interventions of ADHD may be an effective intervention. In the future, we need more online intervention researches to improve the symptoms of different patients, especially for some patients who have difficulties in accepting face-to-face treatment.
| S-EPMC9274127 | biostudies-literature
Project description:The purpose of this systematic review and meta-analysis was to determine the effects of supervised resistance and/or aerobic training physical activity interventions on performance-based measures of physical functioning among community-dwelling older adults, and to identify factors impacting intervention effectiveness. Diverse search strategies were used to identify eligible studies. Standardized mean difference effect sizes (d, ES) were synthesized using a random effects model. Moderator analyses were conducted using subgroup analyses and meta-regression. Twenty-eight studies were included. Moderator analyses were limited by inconsistent reporting of sample and intervention characteristics. The overall mean ES was 0.45 (k = 38, p ? .01), representing a clinically meaningful reduction of 0.92 s in the Timed Up and Go for treatment versus control. More minutes per week (p < .01) and longer intervention session duration (p < .01) were associated with larger effects. Interventions were especially effective among frail participants (d = 1.09). Future research should clearly describe sample and intervention characteristics and incorporate frail populations.
| S-EPMC5291294 | biostudies-literature
Project description:Well-developed theories are necessary to guide the public in increasing physical activity (PA) and promoting physical health. The role of positive affective variables (PAVs) in exercise is gaining more attention, but none of the literature has provided a systematic review and quantitative analysis of its mediating role. Therefore, the purposes of this study are (1) to systematically review studies of PA interventions, that use PAVs as the mediating variables, in order to evaluate and provide narrative summaries of these studies; (2) to statistically synthesize evidence for the mechanism of the effects of PAVs on PA outcomes. To conduct an extensive search, a PRISMA-compliant protocol was completed, and five electronic databases had been searched by 1 April 2020. We used a two-stage structural equation modeling (TSSEM) analysis approach to test how interventions trigger the critical PA change process to influence outcomes. The search strategy generated 1,732 papers potentially relevant to this study; forty of these studies met the data extraction criteria for meta-analytic mediation analysis. The path coefficient from intervention to PAV a = 0.26 (95% CI = 0.08 to 0.44), the path coefficient from PAV to PA b = 0.21 (95% CI = 0.13 to 0.28), and the direct effect from intervention to PA is also significant (c = 0.19, 95% CI = 0.12 to 0.26). In addition, the indirect effect of intervention on PA via PAV was statistically significant (c' = 0.05, 95% CI = 0.02 to 0.10). This reveals that PAVs partially mediate the relationship between interventions and PA. Our study is the first to systematically summarize the effects of experimental studies to increase PA through PAVs. It is highly recommended to make future interventions more innovative and to target the PAVs as mediators with higher fidelity.
| S-EPMC7674307 | biostudies-literature
Project description:BackgroundThe effectiveness of digital health interventions is commonly assumed to be related to the level of user engagement with the digital health intervention, including measures of both digital health intervention use and users' subjective experience. However, little is known about the relationships between the measures of digital health intervention engagement and physical activity or sedentary behavior.ObjectiveThis study aims to describe the direction and strength of the association between engagement with digital health interventions and physical activity or sedentary behavior in adults and explore whether the direction of association of digital health intervention engagement with physical activity or sedentary behavior varies with the type of engagement with the digital health intervention (ie, subjective experience, activities completed, time, and logins).MethodsFour databases were searched from inception to December 2019. Grey literature and reference lists of key systematic reviews and journals were also searched. Studies were eligible for inclusion if they examined a quantitative association between a measure of engagement with a digital health intervention targeting physical activity and a measure of physical activity or sedentary behavior in adults (aged ≥18 years). Studies that purposely sampled or recruited individuals on the basis of pre-existing health-related conditions were excluded. In addition, studies were excluded if the individual engaging with the digital health intervention was not the target of the physical activity intervention, the study had a non-digital health intervention component, or the digital health interventions targeted multiple health behaviors. A random effects meta-analysis and direction of association vote counting (for studies not included in meta-analysis) were used to address objective 1. Objective 2 used vote counting on the direction of the association.ResultsOverall, 10,653 unique citations were identified and 375 full texts were reviewed. Of these, 19 studies (26 associations) were included in the review, with no studies reporting a measure of sedentary behavior. A meta-analysis of 11 studies indicated a small statistically significant positive association between digital health engagement (based on all usage measures) and physical activity (0.08, 95% CI 0.01-0.14, SD 0.11). Heterogeneity was high, with 77% of the variation in the point estimates explained by the between-study heterogeneity. Vote counting indicated that the relationship between physical activity and digital health intervention engagement was consistently positive for three measures: subjective experience measures (2 of 3 associations), activities completed (5 of 8 associations), and logins (6 of 10 associations). However, the direction of associations between physical activity and time-based measures of usage (time spent using the intervention) were mixed (2 of 5 associations supported the hypothesis, 2 were inconclusive, and 1 rejected the hypothesis).ConclusionsThe findings indicate a weak but consistent positive association between engagement with a physical activity digital health intervention and physical activity outcomes. No studies have targeted sedentary behavior outcomes. The findings were consistent across most constructs of engagement; however, the associations were weak.
| S-EPMC8011420 | biostudies-literature
Project description:BackgroundMobile health (mHealth) interventions can increase physical activity (PA); however, their long-term impact is not well understood.ObjectiveThe primary aim of this study is to understand the immediate and long-term effects of mHealth interventions on PA. The secondary aim is to explore potential effect moderators.MethodsWe performed this study according to the Cochrane and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched PubMed, the Cochrane Library, SCOPUS, and PsycINFO in July 2020. Eligible studies included randomized controlled trials of mHealth interventions targeting PA as a primary outcome in adults. Eligible outcome measures were walking, moderate-to-vigorous physical activity (MVPA), total physical activity (TPA), and energy expenditure. Where reported, we extracted data for 3 time points (ie, end of intervention, follow-up ≤6 months, and follow-up >6 months). To explore effect moderators, we performed subgroup analyses by population, intervention design, and control group type. Results were summarized using random effects meta-analysis. Risk of bias was assessed using the Cochrane Collaboration tool.ResultsOf the 2828 identified studies, 117 were included. These studies reported on 21,118 participants with a mean age of 52.03 (SD 14.14) years, of whom 58.99% (n=12,459) were female. mHealth interventions significantly increased PA across all the 4 outcome measures at the end of intervention (walking standardized mean difference [SMD] 0.46, 95% CI 0.36-0.55; P<.001; MVPA SMD 0.28, 95% CI 0.21-0.35; P<.001; TPA SMD 0.34, 95% CI 0.20-0.47; P<.001; energy expenditure SMD 0.44, 95% CI 0.13-0.75; P=.01). Only 33 studies reported short-term follow-up measurements, and 8 studies reported long-term follow-up measurements in addition to end-of-intervention results. In the short term, effects were sustained for walking (SMD 0.26, 95% CI 0.09-0.42; P=.002), MVPA (SMD 0.20, 95% CI 0.05-0.35; P=.008), and TPA (SMD 0.53, 95% CI 0.13-0.93; P=.009). In the long term, effects were also sustained for walking (SMD 0.25, 95% CI 0.10-0.39; P=.001) and MVPA (SMD 0.19, 95% CI 0.11-0.27; P<.001). We found the study population to be an effect moderator, with higher effect scores in sick and at-risk populations. PA was increased both in scalable and nonscalable mHealth intervention designs and regardless of the control group type. The risk of bias was rated high in 80.3% (94/117) of the studies. Heterogeneity was significant, resulting in low to very low quality of evidence.ConclusionsmHealth interventions can foster small to moderate increases in PA. The effects are maintained long term; however, the effect size decreases over time. The results encourage using mHealth interventions in at-risk and sick populations and support the use of scalable mHealth intervention designs to affordably reach large populations. However, given the low evidence quality, further methodologically rigorous studies are warranted to evaluate the long-term effects.
| S-EPMC8122296 | biostudies-literature
Project description:Mobile applications reach a high number of individuals at low costs. This systematic review investigated the effectiveness of mobile application-based interventions to increase physical activity (PA) and self-efficacy and to decrease sedentarism. Randomized controlled trials (RCTs) and quasi-RCTs investigating the effect of PA interventions using an app compared to no intervention or traditional interventions were included. Pooled effects using the standardized mean difference (SMD) or the weighted mean difference (WMD) were calculated and the overall quality of the evidence was rated using the GRADE. Eleven studies were included. In the short term, pooled estimates showed a small and positive effect in the number of steps favoring interventions using a mobile app when compared with no interventions (WMD = 1579.04, 95%CI 454.04 to 2703.38) and with traditional interventions (WMD = 665.96, 95%CI 167.92 to 1164.00). For self-efficacy and at follow-up, results favoured traditional interventions (WMD = -8.20, 95%CI -14.25 to -2.15). Non-significant results were found for the remaining comparisons. The quality of the evidence ranged from very low to low. There is very low to low quality evidence that interventions using mobile apps running on smartphones, when combined with traditional interventions, are superior to traditional interventions in the short term. Further high-quality studies are required.
| S-EPMC7177448 | biostudies-literature
Project description:BackgroundGamification refers to the use of game elements in nongame contexts. The use of gamification to change behaviors and promote physical activity (PA) is a promising avenue for tackling the global physical inactivity pandemic and the current prevalence of chronic diseases. However, there is no evidence of the effectiveness of gamified interventions with the existence of mixed results in the literature.ObjectiveThe aim of this systematic review and meta-analysis is to evaluate the effectiveness of gamified interventions and their health care potential by testing the generalizability and sustainability of their influence on PA and sedentary behavior.MethodsA total of 5 electronic databases (PubMed, Embase, Scopus, Web of Science, and the Cochrane Central Register of Controlled Trials) were searched for randomized controlled trials published in English from 2010 to 2020. Eligibility criteria were based on the components of the participants, interventions, comparators, and outcomes framework. Studies were included when they used gamified interventions in daily life with an active or inactive control group and when they assessed a PA or sedentary behavior outcome. We conducted meta-analyses using a random-effects model approach. Sensitivity analyses, influence analyses, and publication bias analyses were performed to examine the robustness of our results.ResultsThe main meta-analysis performed on 16 studies and 2407 participants revealed a small to medium summary effect of gamified interventions on PA behavior (Hedges g=0.42, 95% CI 0.14-0.69). No statistical difference among different subgroups (adults vs adolescents and healthy participants vs adults with chronic diseases) and no interaction effects with moderators such as age, gender, or BMI were found, suggesting good generalizability of gamified interventions to different user populations. The effect was statistically significant when gamified interventions were compared with inactive control groups, such as waiting lists (Hedges g=0.58, 95% CI 0.08-1.07), and active control groups that included a nongamified PA intervention (Hedges g=0.23, 95% CI 0.05-0.41). This suggests that gamified interventions are not only efficient in changing behavior but also more effective compared with other behavioral interventions. The long-term effect (measured with follow-up averaging 14 weeks after the end of the intervention) was weaker, with a very small to small effect (Hedges g=0.15, 95% CI 0.07-0.23).ConclusionsThis meta-analysis confirms that gamified interventions are promising for promoting PA in various populations. Additional analyses revealed that this effect persists after the follow-up period, suggesting that it is not just a novelty effect caused by the playful nature of gamification, and that gamified products appear effective compared with equivalent nongamified PA interventions. Future rigorous trials are required to confirm these findings.
| S-EPMC8767479 | biostudies-literature
Project description:IntroductionThis review aims to give an overview of available published evidence concerning the association between physical activity and asthma in children, adolescents and adults.MethodsWe included all original articles in which both physical activity and asthma were assessed in case-control, cross-sectional or longitudinal (cohort) studies. Excluded were studies concerning physical fitness, studies in athletes, therapeutic or rehabilitation intervention studies such as physical training or exercise in asthma patients. Methodological quality of the included articles was assessed according to the Newcastle-Ottawa Scale (NOS).ResultsA literature search was performed until June 2011 and resulted in 6,951 publications derived from PubMed and 1,978 publications from EMBASE. In total, 39 studies met the inclusion criteria: 5 longitudinal studies (total number of subjects n = 85,117) with physical activity at baseline as exposure, and asthma incidence as outcome. Thirty-four cross-sectional studies (n = 661,222) were included. Pooling of the longitudinal studies showed that subjects with higher physical activity levels had lower incidence of asthma (odds ratio 0.88 (95% CI: 0.77-1.01)). When restricting pooling to the 4 prospective studies with moderate to good study quality (defined as NOS≥5) the pooled odds ratio only changed slightly (0.87 (95% CI: 0.77-0.99)). In the cross-sectional studies, due to large clinical variability and heterogeneity, further statistical analysis was not possible.ConclusionsThe available evidence indicates that physical activity is a possible protective factor against asthma development. The heterogeneity suggests that possible relevant effects remain hidden in critical age periods, sex differences, or extremes of levels of physical activity (e.g. sedentary). Future longitudinal studies should address these issues.
| S-EPMC3527462 | biostudies-literature
Project description:BackgroundThe holistic concept of physical literacy assumes that individuals require adequate cognitive (knowledge and understanding), affective (motivation and confidence), and physical (physical competence) qualities to engage in lifelong physical activity behavior. In recent years, the research field has undergone rapid development and has also yielded an increasing number of interventions that aim to translate the theoretical-philosophical ideas into practical endeavors.ObjectiveThe goal of the present pre-registered systematic review was to (a) provide a general overview of evaluation studies on physical literacy interventions and (b) to quantitatively examine the effectiveness of physical literacy interventions.MethodsDrawing on the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched a total of 18 databases for physical literacy interventions. Inclusion criteria were English language, publication by November 2021, and interventions using physical literacy as a theoretical underpinning or evaluation outcome. Articles that met these criteria were analyzed with respect to their basic delivery characteristics, study quality, evaluation approach, and main findings. We additionally ran meta-analyses with all non-randomized and randomized controlled trials to examine and compare the effect of these interventions on five outcome categories: (i) physical competence, (ii) motivation and confidence, (iii) knowledge and understanding, (iv) physical activity behavior, and (v) total physical literacy. Standardized mean differences (SMDs) with 95% confidence intervals (CIs) were calculated to assess the effects on the different categories.ResultsThe screening process with two independent raters yielded 48 eligible interventions reported in 51 eligible articles. Quantitative evaluations most frequently addressed physical competence (72.2%), followed by motivation and confidence (47.2%), physical activity behavior (41.7%), and knowledge and understanding (33.3%). The controlled intervention studies (n = 24) exerted significant effects on all five physical literacy categories. Despite meaningful heterogeneity across the subgroups, the strongest effects were found for physical competence (SMD 0.90; 95% CI 0.55-1.25), followed by physical literacy aggregate scores (SMD 0.61; 95% CI 0.20-1.01), knowledge and understanding (SMD 0.54; 95% CI 0.30-0.79), physical activity behavior (SMD 0.39; 95% CI 0.23-0.55), and motivation and confidence (SMD 0.30; 95% CI 0.17-0.44).ConclusionsThe present study empirically demonstrated the effectiveness of physical literacy interventions on several outcomes relevant for promoting physical activity and health. To better inform current practices, future studies are advised to identify those program characteristics that significantly influence the effectiveness of physical literacy interventions.Clinical trial registrationPROSPERO CRD42020188926.
| S-EPMC9691485 | biostudies-literature
Project description:To develop more efficient programmes for promoting dietary and/or physical activity change (in order to prevent type 2 diabetes) it is critical to ensure that the intervention components and characteristics most strongly associated with effectiveness are included. The aim of this systematic review of reviews was to identify intervention components that are associated with increased change in diet and/or physical activity in individuals at risk of type 2 diabetes.MEDLINE, EMBASE, CINAHL, PsycInfo, and the Cochrane Library were searched for systematic reviews of interventions targeting diet and/or physical activity in adults at risk of developing type 2 diabetes from 1998 to 2008. Two reviewers independently selected reviews and rated methodological quality. Individual analyses from reviews relating effectiveness to intervention components were extracted, graded for evidence quality and summarised.Of 3856 identified articles, 30 met the inclusion criteria and 129 analyses related intervention components to effectiveness. These included causal analyses (based on randomisation of participants to different intervention conditions) and associative analyses (e.g. meta-regression). Overall, interventions produced clinically meaningful weight loss (3-5 kg at 12 months; 2-3 kg at 36 months) and increased physical activity (30-60 mins/week of moderate activity at 12-18 months). Based on causal analyses, intervention effectiveness was increased by engaging social support, targeting both diet and physical activity, and using well-defined/established behaviour change techniques. Increased effectiveness was also associated with increased contact frequency and using a specific cluster of "self-regulatory" behaviour change techniques (e.g. goal-setting, self-monitoring). No clear relationships were found between effectiveness and intervention setting, delivery mode, study population or delivery provider. Evidence on long-term effectiveness suggested the need for greater consideration of behaviour maintenance strategies.This comprehensive review of reviews identifies specific components which are associated with increased effectiveness in interventions to promote change in diet and/or physical activity. To maximise the efficiency of programmes for diabetes prevention, practitioners and commissioning organisations should consider including these components.
| S-EPMC3048531 | biostudies-other