Dataset Information

Effectiveness of mHealth diet interventions in cancer survivors: A systematic review and meta-analysis of randomized controlled trials.

ABSTRACT:

Objective

To evaluate the effects of mobile health (mHealth) diet interventions on cancer survivors' diet intake, weight change, waist circumference, hip circumference, and quality of life (QoL).

Methods

The PubMed, Embase, Web of Science, Cochrane Library, Scopus, ProQuest, China National Knowledge Infrastructure, Wanfang, and SinoMed databases were searched from their inception to September 25, 2022. Randomized controlled trials (RCTs) on the effects of mHealth diet interventions in cancer survivors were identified. Two researchers independently selected the included studies and appraised their quality. The methodological quality of the included studies was assessed using the Revised Cochrane risk-of-bias tool for RCTs (RoB2).

Results

A total of 15 RCTs involving 2363 cancer survivors were included. MHealth diet interventions significantly improved fruit and vegetable intake (standardized mean difference [SMD] = 0.19, 95% confidence interval [CI] [0.05, 0.33], P < 0.01), and QoL (SMD = 0.13, 95% CI [0.01, 0.26], P = 0.04) and reduced fat intake (SMD = -0.22, 95% CI [-0.34, -0.11], P < 0.01), weight (SMD = -0.35, 95% CI [-0.48, -0.22], P < 0.01), waist circumference (MD = -1.43, 95% CI [-2.33, -0.53], P < 0.01), and hip circumference (MD = -3.54, 95% CI [-4.88, -2.19], P < 0.01) in cancer survivors. No significant differences were observed in energy intake (P = 0.46) or whole grain intake (P = 0.14).

Conclusions

MHealth diet interventions may be an effective strategy for cancer survivors. Large-scale RCTs with rigorous study designs are needed to examine the effect of diet intervention delivered via mHealth.

SUBMITTER: Gong Y

PROVIDER: S-EPMC10140457 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature

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Publications

Effectiveness of mHealth diet interventions in cancer survivors: A systematic review and meta-analysis of randomized controlled trials.

Gong Yabo Y Jiang Xiaohan X Chen Xijie X Chen Shi S Wen Yuee Y Yuan Xiuhong X Chen Jiamin J Peng Junsheng J

Asia-Pacific journal of oncology nursing 20230214 3

<h4>Objective</h4>To evaluate the effects of mobile health (mHealth) diet interventions on cancer survivors' diet intake, weight change, waist circumference, hip circumference, and quality of life (QoL).<h4>Methods</h4>The PubMed, Embase, Web of Science, Cochrane Library, Scopus, ProQuest, China National Knowledge Infrastructure, Wanfang, and SinoMed databases were searched from their inception to September 25, 2022. Randomized controlled trials (RCTs) on the effects of mHealth diet intervention ...[more]

PMID: 37124242

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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.

Project description:BackgroundPhysical activity (PA) is a vital factor in promoting health in the workforce. Mobile health (mHealth) interventions have recently emerged in workplace health promotion as an effective strategy for inducing changes in health behaviors among workers; however, the effectiveness of mHealth interventions in promoting PA and weight loss for workers is unclear.ObjectiveThis study aims to provide a comprehensive analysis of current evidence on the effectiveness of mHealth interventions in promoting PA and weight loss among workers.MethodsWe searched relevant databases, including PubMed, Embase, CINAHL Complete, and the Cochrane Library, for publications on mHealth interventions in the English or Korean language from inception to December 2020. Randomized controlled trials that evaluated the effectiveness of mHealth in improving PA and weight loss were retrieved. A meta-analysis with a random effects model and subgroup analyses was performed on PA types and mHealth intervention characteristics.ResultsA total of 8 studies were included in this analysis. More than half of the studies (5/8, 63%) were identified as having a high risk of bias. The mHealth intervention group showed a significant improvement in PA (standardized mean difference [SMD] 0.22, 95% CI 0.03-0.41; P<.001; I2=78%). No significant difference in weight loss was observed when comparing the intervention group with the control groups (SMD 0.02, 95% CI -0.07 to 0.10; P=.48; I2=0%). A subgroup analysis was also performed; walking activity (SMD 0.70, 95% CI 0.21-1.19; P<.001; I2=83.3%), a multicomponent program (SMD 0.19, 95% CI 0.05-0.33; P=.03; I2=57.4%), objective measurement (SMD 0.58, 95% CI 0.05-1.10; P<.001; I2=87.3%), and 2 or more delivery modes (SMD 0.44, 95% CI 0.01-0.87; P<.001; I2=85.1%) were significantly associated with an enhancement in PA.ConclusionsThis study suggests that mHealth interventions are effective for improving PA among workers. Future studies that assess long-term efficacy with a larger population are recommended.

Project description:BackgroundChildren and adolescents increasingly do not meet physical activity (PA) recommendations. Hence, insufficient PA (IPA) and sedentary behavior (SB) among children and adolescents are relevant behavior change domains for using individualized mobile health (mHealth) interventions.ObjectiveThis review and meta-analysis investigated the effectiveness of mHealth interventions on IPA and SB, with a special focus on the age and level of individualization.MethodsPubMed, Scopus, Web of Science, SPORTDiscus, and Cochrane Library were searched for randomized controlled trials published between January 2000 and March 2021. mHealth interventions for primary prevention in children and adolescents addressing behavior change related to IPA and SB were included. Included studies were compared for content characteristics and methodological quality and summarized narratively. In addition, a meta-analysis with a subsequent exploratory meta-regression examining the moderating effects of age and individualization on overall effectiveness was performed.ResultsOn the basis of the inclusion criteria, 1.3% (11/828) of the preliminary identified studies were included in the qualitative synthesis, and 1.2% (10/828) were included in the meta-analysis. Trials included a total of 1515 participants (mean age (11.69, SD 0.788 years; 65% male and 35% female) self-reported (3/11, 27%) or device-measured (8/11, 73%) health data on the duration of SB and IPA for an average of 9.3 (SD 5.6) weeks. Studies with high levels of individualization significantly decreased insufficient PA levels (Cohen d=0.33; 95% CI 0.08-0.58; Z=2.55; P=.01), whereas those with low levels of individualization (Cohen d=-0.06; 95% CI -0.32 to 0.20; Z=0.48; P=.63) or targeting SB (Cohen d=-0.11; 95% CI -0.01 to 0.23; Z=1.73; P=.08) indicated no overall significant effect. The heterogeneity of the studies was moderate to low, and significant subgroup differences were found between trials with high and low levels of individualization (χ21=4.0; P=.04; I2=75.2%). Age as a moderator variable showed a small effect; however, the results were not significant, which might have been because of being underpowered.ConclusionsEvidence suggests that mHealth interventions for children and adolescents can foster moderate reductions in IPA but not SB. Moreover, individualized mHealth interventions to reduce IPA seem to be more effective for adolescents than for children. Although, to date, only a few mHealth studies have addressed inactive and sedentary young people, and their quality of evidence is moderate, these findings indicate the relevance of individualization on the one hand and the difficulties in reducing SB using mHealth interventions on the other.Trial registrationPROSPERO CRD42020209417; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=209417.

Dataset Information

Effectiveness of mHealth diet interventions in cancer survivors: A systematic review and meta-analysis of randomized controlled trials.

Objective

Methods

Results

Conclusions

Publications

Effectiveness of mHealth diet interventions in cancer survivors: A systematic review and meta-analysis of randomized controlled trials.

Similar Datasets

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