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Gamification for the Improvement of Diet, Nutritional Habits, and Body Composition in Children and Adolescents: A Systematic Review and Meta-Analysis.
Suleiman-Martos, N, García-Lara, RA, Martos-Cabrera, MB, Albendín-García, L, Romero-Béjar, JL, Cañadas-De la Fuente, GA, Gómez-Urquiza, JL
Nutrients. 2021;(7)
Abstract
Currently, one of the main public health problems among children and adolescents is poor adherence to healthy habits, leading to increasingly high rates of obesity and the comorbidities that accompany obesity. Early interventions are necessary, and among them, the use of gamification can be an effective method. The objective was to analyse the effect of game-based interventions (gamification) for improving nutritional habits, knowledge, and changes in body composition. A systematic review and meta-analysis were performed in CINAHL, EMBASE, LILACS, MEDLINE, SciELO, and Scopus databases, following the PRISMA recommendations. There was no restriction by year of publication or language. Only randomized controlled trials were included. Twenty-three articles were found. After the intervention, the consumption of fruit and vegetables increased, as well as the knowledge on healthy food groups. The means difference showed a higher nutritional knowledge score in the intervention group 95% CI 0.88 (0.05-1.75). No significant effect of gamification was found for body mass index z-score. Gamification could be an effective method to improve nutritional knowledge about healthier nutritional habits. Promoting the development of effective educational tools to support learning related to nutrition is necessary in order to avoid and prevent chronic diseases.
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Association between characteristics of behavioural weight loss programmes and weight change after programme end: systematic review and meta-analysis.
Hartmann-Boyce, J, Theodoulou, A, Oke, JL, Butler, AR, Scarborough, P, Bastounis, A, Dunnigan, A, Byadya, R, Hobbs, FDR, Sniehotta, FF, et al
BMJ (Clinical research ed.). 2021;:n1840
Abstract
OBJECTIVE To determine if the characteristics of behavioural weight loss programmes influence the rate of change in weight after the end of the programme. DESIGN Systematic review and meta-analysis. DATA SOURCES Trial registries, 11 electronic databases, and forward citation searching (from database inception; latest search December 2019). Randomised trials of behavioural weight loss programmes in adults with overweight or obesity, reporting outcomes at ≥12 months, including at the end of the programme and after the end of the programme. REVIEW METHODS Studies were screened by two independent reviewers with discrepancies resolved by discussion. 5% of the studies identified in the searches met the inclusion criteria. One reviewer extracted the data and a second reviewer checked the data. Risk of bias was assessed with Cochrane's risk of bias tool (version 1). The rate of change in weight was calculated (kg/month; converted to kg/year for interpretability) after the end of the programme in the intervention versus control groups by a mixed model with a random intercept. Associations between the rate of change in weight and prespecified variables were tested. RESULTS Data were analysed from 249 trials (n=59 081) with a mean length of follow-up of two years (longest 30 years). 56% of studies (n=140) had an unclear risk of bias, 21% (n=52) a low risk, and 23% (n=57) a high risk of bias. Regain in weight was faster in the intervention versus the no intervention control groups (0.12-0.32 kg/year) but the difference between groups was maintained for at least five years. Each kilogram of weight lost at the end of the programme was associated with faster regain in weight at a rate of 0.13-0.19 kg/year. Financial incentives for weight loss were associated with faster regain in weight at a rate of 1-1.5 kg/year. Compared with programmes with no meal replacements, interventions involving partial meal replacements were associated with faster regain in weight but not after adjustment for weight loss during the programme. Access to the programme outside of the study was associated with slower regain in weight. Programmes where the intensity of the interaction reduced gradually were also associated with slower regain in weight in the multivariable analysis, although the point estimate suggested that the association was small. Other characteristics did not explain the heterogeneity in regain in weight. CONCLUSION Faster regain in weight after weight loss was associated with greater initial weight loss, but greater initial weight loss was still associated with reduced weight for at least five years after the end of the programme, after which data were limited. Continued availability of the programme to participants outside of the study predicted a slower regain in weight, and provision of financial incentives predicted faster regain in weight; no other clear associations were found. STUDY REGISTRATION PROSPERO CRD42018105744.
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Behavioural interventions delivered through interactive social media for health behaviour change, health outcomes, and health equity in the adult population.
Petkovic, J, Duench, S, Trawin, J, Dewidar, O, Pardo Pardo, J, Simeon, R, DesMeules, M, Gagnon, D, Hatcher Roberts, J, Hossain, A, et al
The Cochrane database of systematic reviews. 2021;(5):CD012932
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Abstract
BACKGROUND Social networking platforms offer a wide reach for public health interventions allowing communication with broad audiences using tools that are generally free and straightforward to use and may be combined with other components, such as public health policies. We define interactive social media as activities, practices, or behaviours among communities of people who have gathered online to interactively share information, knowledge, and opinions. OBJECTIVES We aimed to assess the effectiveness of interactive social media interventions, in which adults are able to communicate directly with each other, on changing health behaviours, body functions, psychological health, well-being, and adverse effects. Our secondary objective was to assess the effects of these interventions on the health of populations who experience health inequity as defined by PROGRESS-Plus. We assessed whether there is evidence about PROGRESS-Plus populations being included in studies and whether results are analysed across any of these characteristics. SEARCH METHODS We searched CENTRAL, CINAHL, Embase, MEDLINE (including trial registries) and PsycINFO. We used Google, Web of Science, and relevant web sites to identify additional studies and searched reference lists of included studies. We searched for published and unpublished studies from 2001 until June 1, 2020. We did not limit results by language. SELECTION CRITERIA We included randomised controlled trials (RCTs), controlled before-and-after (CBAs) and interrupted time series studies (ITSs). We included studies in which the intervention website, app, or social media platform described a goal of changing a health behaviour, or included a behaviour change technique. The social media intervention had to be delivered to adults via a commonly-used social media platform or one that mimicked a commonly-used platform. We included studies comparing an interactive social media intervention alone or as a component of a multi-component intervention with either a non-interactive social media control or an active but less-interactive social media comparator (e.g. a moderated versus an unmoderated discussion group). Our main outcomes were health behaviours (e.g. physical activity), body function outcomes (e.g. blood glucose), psychological health outcomes (e.g. depression), well-being, and adverse events. Our secondary outcomes were process outcomes important for behaviour change and included knowledge, attitudes, intention and motivation, perceived susceptibility, self-efficacy, and social support. DATA COLLECTION AND ANALYSIS We used a pre-tested data extraction form and collected data independently, in duplicate. Because we aimed to assess broad outcomes, we extracted only one outcome per main and secondary outcome categories prioritised by those that were the primary outcome as reported by the study authors, used in a sample size calculation, and patient-important. MAIN RESULTS We included 88 studies (871,378 participants), of which 84 were RCTs, three were CBAs and one was an ITS. The majority of the studies were conducted in the USA (54%). In total, 86% were conducted in high-income countries and the remaining 14% in upper middle-income countries. The most commonly used social media platform was Facebook (39%) with few studies utilising other platforms such as WeChat, Twitter, WhatsApp, and Google Hangouts. Many studies (48%) used web-based communities or apps that mimic functions of these well-known social media platforms. We compared studies assessing interactive social media interventions with non-interactive social media interventions, which included paper-based or in-person interventions or no intervention. We only reported the RCT results in our 'Summary of findings' table. We found a range of effects on health behaviours, such as breastfeeding, condom use, diet quality, medication adherence, medical screening and testing, physical activity, tobacco use, and vaccination. For example, these interventions may increase physical activity and medical screening tests but there was little to no effect for other health behaviours, such as improved diet or reduced tobacco use (20,139 participants in 54 RCTs). For body function outcomes, interactive social media interventions may result in small but important positive effects, such as a small but important positive effect on weight loss and a small but important reduction in resting heart rate (4521 participants in 30 RCTs). Interactive social media may improve overall well-being (standardised mean difference (SMD) 0.46, 95% confidence interval (CI) 0.14 to 0.79, moderate effect, low-certainty evidence) demonstrated by an increase of 3.77 points on a general well-being scale (from 1.15 to 6.48 points higher) where scores range from 14 to 70 (3792 participants in 16 studies). We found no difference in effect on psychological outcomes (depression and distress) representing a difference of 0.1 points on a standard scale in which scores range from 0 to 63 points (SMD -0.01, 95% CI -0.14 to 0.12, low-certainty evidence, 2070 participants in 12 RCTs). We also compared studies assessing interactive social media interventions with those with an active but less interactive social media control (11 studies). Four RCTs (1523 participants) that reported on physical activity found an improvement demonstrated by an increase of 28 minutes of moderate-to-vigorous physical activity per week (from 10 to 47 minutes more, SMD 0.35, 95% CI 0.12 to 0.59, small effect, very low-certainty evidence). Two studies found little to no difference in well-being for those in the intervention and control groups (SMD 0.02, 95% CI -0.08 to 0.13, small effect, low-certainty evidence), demonstrated by a mean change of 0.4 points on a scale with a range of 0 to 100. Adverse events related to the social media component of the interventions, such as privacy issues, were not reported in any of our included studies. We were unable to conduct planned subgroup analyses related to health equity as only four studies reported relevant data. AUTHORS' CONCLUSIONS This review combined data for a variety of outcomes and found that social media interventions that aim to increase physical activity may be effective and social media interventions may improve well-being. While we assessed many other outcomes, there were too few studies to compare or, where there were studies, the evidence was uncertain. None of our included studies reported adverse effects related to the social media component of the intervention. Future studies should assess adverse events related to the interactive social media component and should report on population characteristics to increase our understanding of the potential effect of these interventions on reducing health inequities.
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Effect of Behavioral Weight Management Interventions Using Lifestyle mHealth Self-Monitoring on Weight Loss: A Systematic Review and Meta-Analysis.
Cavero-Redondo, I, Martinez-Vizcaino, V, Fernandez-Rodriguez, R, Saz-Lara, A, Pascual-Morena, C, Álvarez-Bueno, C
Nutrients. 2020;(7)
Abstract
Alongside an increase in obesity, society is experiencing the development of substantial technological advances. Interventions that are easily scalable, such as lifestyle (including diet and physical activity) mobile health (mHealth) self-monitoring, may be highly valuable in the prevention and treatment of excess weight. Thus, the aims of this systematic review and meta-analysis were to estimate the following: (i) the effect of behavioral weight management interventions using lifestyle mHealth self-monitoring on weight loss and (ii) the adherence to behavioral weight management interventions using lifestyle mHealth self-monitoring. MEDLINE via PubMed, EMBASE, the Cochrane Central Register of Controlled Trials and the Web of Science databases were systematically searched. The DerSimonian and Laird method was used to estimate the effect of and adherence to behavioral weight management interventions using lifestyle mHealth self-monitoring on weight loss. Twenty studies were included in the systematic review and meta-analysis, yielding a moderate decrease in weight and higher adherence to intervention of behavioral weight management interventions using lifestyle mHealth self-monitoring, which was greater than other interventions. Subgroup analyses showed that smartphones were the most effective mHealth approach to achieve weight management and the effect of behavioral weight management interventions using lifestyle mHealth self-monitoring was more pronounced when compared to usual care and in the short-term (less than six months). Furthermore, behavioral weight management interventions using lifestyle mHealth self-monitoring showed a higher adherence than: (i) recording on paper at any time and (ii) any other intervention at six and twelve months.
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What makes implementation intention interventions effective for promoting healthy eating behaviours? A meta-regression.
Carrero, I, Vilà, I, Redondo, R
Appetite. 2019;:239-247
Abstract
This study examines the efficacy of implementation intentions (II), a widely used self-regulatory strategy to help people achieve their goals. Although previous research has shown that the effect of II interventions is significantly higher in promoting healthy eating behaviours than in diminishing unhealthy eating behaviours, the factors that can moderate the effectiveness of these interventions remain unclear. In a meta-analysis of 70 interventions (N = 9689), we confirmed that II interventions for healthy eating behaviours yielded a medium significant effect size (d = 0.33) and a low significant effect size for unhealthy eating behaviors (d = 0.18). We show that the moderator variables of II interventions for healthy and unhealthy eating goals are very different. Regarding healthy eating, since moderator variables explain 53% of the variance in the heterogeneity of the effect sizes, the present study helps in gaining an understanding of the previous inconsistent results and offers suggestions for designing more efficient interventions. Effect size was negatively predicted by age, indicating that for younger people the effect size is higher, and II check, showing that if the instructor checks the plan it decreases its efficacy. Moreover, the effect of II interventions on students is significantly smaller than in non-student samples. In contrast, the effect size was positively predicted by initial training, off-line delivered interventions and, specific if-then and action plans versus complex plans. For unhealthy eating behaviours, our results show that there is less room to improve the intervention; there is only one moderator variable (plan formulation), and the heterogeneity found in the studies is lower for unhealthy eating behaviours (I2 = 46.70%) than for healthy eating behaviours (I2 = 73.25%), indicating that the intervention has low efficacy regardless of the design of the intervention.
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A systematic review and meta-analysis of interventions incorporating behaviour change techniques to promote breastfeeding among postpartum women.
Kassianos, AP, Ward, E, Rojas-Garcia, A, Kurti, A, Mitchell, FC, Nostikasari, D, Payton, J, Pascal-Saadi, J, Spears, CA, Notley, C
Health psychology review. 2019;(3):344-372
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Abstract
The benefits of exclusive breastfeeding are well documented, yet few women adhere to recommendations. We report the Behaviour Change Techniques (BCTs) within interventions trialled internationally after pregnancy to promote exclusive and mixed breastfeeding as well as evidence of effectiveness. PsycINFO, EMBASE and MEDLINE databases were screened. Twenty-three (n = 23) studies met inclusion criteria. Three authors independently extracted data, coded interventions using the BCT v.1 taxonomy, and assessed study quality. There was a moderate significant effect of the interventions promoting exclusive breastfeeding up to four weeks postpartum (OR 1.77, [95% CI: 1.47-2.13]) but this effect slightly declined beyond thirteen weeks (OR 1.63, [95% CI: 1.07-2.47]). Twenty-nine BCTs were identified within interventions. 'Credible source' and 'instruction on how to perform the behaviour' were the most prevalent and 'social support (unspecified)' contributed to the effectiveness of exclusive breastfeeding interventions five to eight weeks postpartum. Using BCTs with cognitive and behavioural aspects may help women develop coping mechanisms promoting exclusive breastfeeding. Further trials are needed in countries with low breastfeeding rates such as the UK. The use of programme theory during intervention development and clear description of intervention components is recommended. This meta-analysis provides guidance for trials evaluating postpartum breastfeeding interventions.
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The Effects of Structured Exercise or Lifestyle Behavior Interventions on Long-Term Physical Activity Level and Health Outcomes in Individuals With Type 2 Diabetes: A Systematic Review, Meta-Analysis, and Meta-Regression.
Mosalman Haghighi, M, Mavros, Y, Fiatarone Singh, MA
Journal of physical activity & health. 2018;(9):697-707
Abstract
BACKGROUND Systematically evaluate the effects of structured exercise and behavioral intervention (physical activity [PA] alone/PA + diet) on long-term PA in type 2 diabetes. METHODS Systematic search of 11 databases (inception to March, 2017). Randomized controlled trials investigating structured exercise/behavioral interventions in type 2 diabetes reporting PA outcomes ≥6 months were selected. RESULTS Among 107,797 citations retrieved, 23 randomized controlled trials (including 18 behavioral programs and 5 structured exercise) met inclusion criteria (n = 9640, 43.6% men, age = 60.0 (4.0) y). All structured exercise trials demonstrated increased objective PA outcomes relative to control (pooling was inappropriate; I2 = 92%). Of 18 behavioral interventions, 10 increased PA significantly, with effect sizes ranging from 0.2 to 6.6 (pooling was inappropriate; I2 = 96%). After removing 1 outlier, the remaining 17 studies significantly improved PA (pooled effect size = 0.34), although smaller compared with structured exercise. After removing the outlier, meta-regression also revealed significant direct relationships between total contacts (r = .50, P < .01) and more face-to-face counseling (r = .75, P < .001) and increased PA. However, long-term changes in PA and HbA1c were not related. CONCLUSION Both structured exercise and behavioral interventions increased PA in type 2 diabetes, although effect sizes were larger for supervised exercise. The effectiveness of behavioral programs was improved when delivery included more extensive and face-to-face contact.
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Non-Pharmacological Interventions to Reduce Unhealthy Eating and Risky Drinking in Young Adults Aged 18⁻25 Years: A Systematic Review and Meta-Analysis.
Scott, S, Beyer, F, Parkinson, K, Muir, C, Graye, A, Kaner, E, Stead, M, Power, C, Fitzgerald, N, Bradley, J, et al
Nutrients. 2018;(10)
Abstract
Alcohol use peaks in early adulthood and can contribute both directly and indirectly to unhealthy weight gain. This review aimed to systematically evaluate the effectiveness of preventative targeted interventions focused on reducing unhealthy eating behavior and linked alcohol use in 18⁻25-year-olds. Twelve electronic databases were searched from inception to June 2018 for trials or experimental studies, of any duration or follow-up. Eight studies (seven with student populations) met the inclusion criteria. Pooled estimates demonstrated inconclusive evidence that receiving an intervention resulted in changes to self-reported fruit and vegetable consumption (mean change/daily servings: 0.33; 95% CI -0.22 to 0.87) and alcohol consumption (mean reduction of 0.6 units/week; CI -1.35 to 0.19). There was also little difference in the number of binge drinking episodes per week between intervention and control groups (-0.01 sessions; CI -0.07 to 0.04). This review identified only a small number of relevant studies. Importantly, included studies did not assess whether (and how) unhealthy eating behaviors and alcohol use link together. Further exploratory work is needed to inform the development of appropriate interventions, with outcome measures that have the capacity to link food and alcohol consumption, in order to establish behavior change in this population group.
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Impact of lifestyle modification on some components of metabolic syndrome in persons with severe mental disorders: A meta-analysis.
Singh, VK, Karmani, S, Malo, PK, Virupaksha, HG, Muralidhar, D, Venkatasubramanian, G, Muralidharan, K
Schizophrenia research. 2018;:17-25
Abstract
BACKGROUND Metabolic syndrome (MS) is reportedly associated with high mortality from mostly cardiovascular causes in patients with severe mental disorders (SMD). Lifestyle interventions augment effective management of MS in patients with SMD. The present meta-analysis aims at updating the recent evidence on the effectiveness of lifestyle intervention for MS in patients with SMD. METHOD A literature search for English Language publications of randomized controlled trials (RCTs) from 2001 to 2016 comparing lifestyle modification (LM) with treatment as usual (TAU) in the management of MS were identified. Using PRISMA guidelines, 19 RCTs reporting data on 1688 SMD and MS patients and providing data on change in Body Weight, Body Mass Index (BMI) and waist circumference (WC) were included. Using random effects model, standardized mean difference between LM and TAU for the mean baseline-to-endpoint change in body weight, BMI and WC was calculated with a 95% confidence limit, on RevMan 5.3. The study was registered with PROSPERO (CRD42016046847). RESULTS LM had significantly superior efficacy in the reducing weight (-0.64, 95% CI -0.89, -0.39, Z = 5.03, overall effect p < 0.00001), BMI (-0.68, 95% CI -1.01, -0.35, Z = 4.05, overall effect p < 0.0001), and WC (-0.60, 95% CI -1.17, -0.03, Z = 2.06; overall effect p = 0.04), compared to TAU. LM was significantly more effective than TAU even in short duration (p = 0.0001) and irrespective of the treatment setting. CONCLUSION Interventions targeting LM in persons with SMD and MS are effective in reducing body weight, BMI and WC. It must be routinely recommended to all patients with SMD, ideally during commencement stage of second generation antipsychotic treatment.
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Effective behaviour change techniques for physical activity and healthy eating in overweight and obese adults; systematic review and meta-regression analyses.
Samdal, GB, Eide, GE, Barth, T, Williams, G, Meland, E
The international journal of behavioral nutrition and physical activity. 2017;(1):42
Abstract
PURPOSE This systematic review aims to explain the heterogeneity in results of interventions to promote physical activity and healthy eating for overweight and obese adults, by exploring the differential effects of behaviour change techniques (BCTs) and other intervention characteristics. METHODS The inclusion criteria specified RCTs with ≥ 12 weeks' duration, from January 2007 to October 2014, for adults (mean age ≥ 40 years, mean BMI ≥ 30). Primary outcomes were measures of healthy diet or physical activity. Two reviewers rated study quality, coded the BCTs, and collected outcome results at short (≤6 months) and long term (≥12 months). Meta-analyses and meta-regressions were used to estimate effect sizes (ES), heterogeneity indices (I2) and regression coefficients. RESULTS We included 48 studies containing a total of 82 outcome reports. The 32 long term reports had an overall ES = 0.24 with 95% confidence interval (CI): 0.15 to 0.33 and I2 = 59.4%. The 50 short term reports had an ES = 0.37 with 95% CI: 0.26 to 0.48, and I2 = 71.3%. The number of BCTs unique to the intervention group, and the BCTs goal setting and self-monitoring of behaviour predicted the effect at short and long term. The total number of BCTs in both intervention arms and using the BCTs goal setting of outcome, feedback on outcome of behaviour, implementing graded tasks, and adding objects to the environment, e.g. using a step counter, significantly predicted the effect at long term. Setting a goal for change; and the presence of reporting bias independently explained 58.8% of inter-study variation at short term. Autonomy supportive and person-centred methods as in Motivational Interviewing, the BCTs goal setting of behaviour, and receiving feedback on the outcome of behaviour, explained all of the between study variations in effects at long term. CONCLUSION There are similarities, but also differences in effective BCTs promoting change in healthy eating and physical activity and BCTs supporting maintenance of change. The results support the use of goal setting and self-monitoring of behaviour when counselling overweight and obese adults. Several other BCTs as well as the use of a person-centred and autonomy supportive counselling approach seem important in order to maintain behaviour over time. TRIAL REGISTRATION PROSPERO CRD42015020624.