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Grady A, Pearson N, Lamont H, Leigh L, Wolfenden L, Barnes C, Wyse R, Finch M, Mclaughlin M, Delaney T, Sutherland R, Hodder R, Yoong SL. The Effectiveness of Strategies to Improve User Engagement With Digital Health Interventions Targeting Nutrition, Physical Activity, and Overweight and Obesity: Systematic Review and Meta-Analysis. J Med Internet Res 2023; 25:e47987. [PMID: 38113062 PMCID: PMC10762625 DOI: 10.2196/47987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Revised: 09/07/2023] [Accepted: 09/07/2023] [Indexed: 12/21/2023] Open
Abstract
BACKGROUND Digital health interventions (DHIs) are effective in improving poor nutrition, physical inactivity, overweight and obesity. There is evidence suggesting that the impact of DHIs may be enhanced by improving user engagement. However, little is known about the overall effectiveness of strategies on engagement with DHIs. OBJECTIVE This study aims to assess the overall effectiveness of strategies to improve engagement with DHIs targeting nutrition, physical activity, and overweight or obesity and explore associations between strategies and engagement outcomes. The secondary aim was to explore the impact of these strategies on health risk outcomes. METHODS The MEDLINE, Embase, PsycINFO, CINAHL, CENTRAL, Scopus, and Academic Source Complete databases were searched up to July 24, 2023. Eligible studies were randomized controlled trials that evaluated strategies to improve engagement with DHIs and reported on outcomes related to DHI engagement (use or user experience). Strategies were classified according to behavior change techniques (BCTs) and design features (eg, supplementary emails). Multiple-variable meta-analyses of the primary outcomes (usage and user experience) were undertaken to assess the overall effectiveness of strategies. Meta-regressions were conducted to assess associations between strategies and use and user experience outcomes. Synthesis of secondary outcomes followed the "Synthesis Without Meta-Analysis" guidelines. The methodological quality and evidence was assessed using the Cochrane risk-of-bias tool, and the Grading of Recommendations Assessment, Development, and Evaluation tool respectively. RESULTS Overall, 54 studies (across 62 publications) were included. Pooled analysis found very low-certainty evidence of a small-to-moderate positive effect of the use of strategies to improve DHI use (standardized mean difference=0.33, 95% CI 0.20-0.46; P<.001) and very low-certainty evidence of a small-to-moderate positive effect on user experience (standardized mean difference=0.29, 95% CI 0.07-0.52; P=.01). A significant positive association was found between the BCTs social support (effect size [ES]=0.40, 95% CI 0.14-0.66; P<.001) and shaping knowledge (ES=0.39, 95% CI 0.03-0.74; P=.03) and DHI use. A significant positive association was found among the BCTs social support (ES=0.70, 95% CI 0.18-1.22; P=.01), repetition and substitution (ES=0.29, 95% CI 0.05-0.53; P=.03), and natural consequences (ES=0.29, 95% CI 0.05-0.53; P=.02); the design features email (ES=0.29, 95% CI 0.05-0.53; P=.02) and SMS text messages (ES=0.34, 95% CI 0.11-0.57; P=.01); and DHI user experience. For secondary outcomes, 47% (7/15) of nutrition-related, 73% (24/33) of physical activity-related, and 41% (14/34) of overweight- and obesity-related outcomes reported an improvement in health outcomes. CONCLUSIONS Although findings suggest that the use of strategies may improve engagement with DHIs targeting such health outcomes, the true effect is unknown because of the low quality of evidence. Future research exploring whether specific forms of social support, repetition and substitution, natural consequences, emails, and SMS text messages have a greater impact on DHI engagement is warranted. TRIAL REGISTRATION PROSPERO CRD42018077333; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=77333.
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Affiliation(s)
- Alice Grady
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Nicole Pearson
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Hannah Lamont
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Lucy Leigh
- Data Sciences, Hunter Medical Research Institute, New Lambton, Australia
| | - Luke Wolfenden
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Courtney Barnes
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Rebecca Wyse
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
- Equity in Health and Wellbeing Program, Hunter Medical Research Institute, New Lambton, Australia
| | - Meghan Finch
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Matthew Mclaughlin
- Telethon Kids Institute, University of Western Australia, Perth, Australia
| | - Tessa Delaney
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Rachel Sutherland
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Rebecca Hodder
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
| | - Sze Lin Yoong
- School of Medicine and Public Health, University of Newcastle, Callaghan, Australia
- Hunter New England Population Health, Hunter New England Local Health District, Wallsend, Australia
- Population Health Research Program, Hunter Medical Research Institute, New Lambton, Australia
- National Centre of Implementation Science, University of Newcastle, Callaghan, Australia
- College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, Australia
- Global Obesity Centre, Institute for Health Transformation, School of Health and Social Development, Deakin University, Melbourne, Australia
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Irvin L, Madden LA, Marshall P, Vince RV. Digital Health Solutions for Weight Loss and Obesity: A Narrative Review. Nutrients 2023; 15:nu15081858. [PMID: 37111077 PMCID: PMC10145832 DOI: 10.3390/nu15081858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 03/29/2023] [Accepted: 04/07/2023] [Indexed: 04/29/2023] Open
Abstract
Personal exercise programmes have long been used and prescribed for weight loss and the improvement of quality of life in obese patients. While individualised programmes are usually the preferred option, they can be more costly and challenging to deliver in person. A move to digital programmes with a wider reach has commenced, and demand has increased due to the SARS-CoV-2 pandemic. In this review, we evaluate the current status of digital exercise programme delivery and its evolution over the past decade, with a focus on personalisation. We used specific keywords to search for articles that met our predetermined inclusion and exclusion criteria in order to provide valuable evidence and insights for future research. We identified 55 studies in total in four key areas of focus, from the more recent development of apps and personal digital assistants to web-based programmes and text or phone call interventions. In summary, we observed that apps may be useful for a low-intensity approach and can improve adherence to programmes through self-monitoring, but they are not always developed in an evidence-based manner. Engagement and adherence are important determinants of weight loss and subsequent weight maintenance. Generally, professional support is required to achieve weight loss goals.
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Affiliation(s)
- Liam Irvin
- School of Sport, Exercise and Rehabilitation Sciences, University of Hull, Hull HU6 7RX, UK
| | - Leigh A Madden
- Centre for Biomedicine, Hull York Medical School, University of Hull, Hull HU6 7RX, UK
| | - Phil Marshall
- School of Sport, Exercise and Rehabilitation Sciences, University of Hull, Hull HU6 7RX, UK
| | - Rebecca V Vince
- School of Sport, Exercise and Rehabilitation Sciences, University of Hull, Hull HU6 7RX, UK
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Loh YL, Yaw QP, Lau Y. Social media-based interventions for adults with obesity and overweight: a meta-analysis and meta-regression. Int J Obes (Lond) 2023:10.1038/s41366-023-01304-6. [PMID: 37012428 PMCID: PMC10069737 DOI: 10.1038/s41366-023-01304-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 03/20/2023] [Accepted: 03/22/2023] [Indexed: 04/05/2023]
Abstract
Social isolation and loneliness are growing public health concerns in adults with obesity and overweight. Social media-based interventions may be a promising approach. This systematic review aims to (1) evaluate the effectiveness of social media-based interventions on weight, body mass index, waist circumference, fat, energy intake and physical activity among adults with obesity and overweight and (2) explore potential covariates on treatment effect. Eight databases, namely, PubMed, Cochrane Library, Embase, CINAHL, Web of Science, Scopus PsycINFO and ProQuest, were searched from inception until December 31, 2021. The Cochrane Collaboration Risk of Bias Tool and Grading of Recommendations, Assessment, Development and Evaluation criteria evaluated the evidence quality. Twenty-eight randomised controlled trials were identified. Meta-analyses found that social media-based interventions had small-to-medium significant effects on weight, BMI, waist circumference, body fat mass and daily steps. Subgroup analysis found greater effect in interventions without published protocol or not registered in trial registries than their counterparts. Meta-regression analysis showed that duration of intervention was a significant covariate. The certainty of evidence quality of all outcomes was very low or low. Social media-based interventions can be considered an adjunct intervention for weight management. Future trials with large sample sizes and follow-up assessment are needed.
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Affiliation(s)
- Yue Lun Loh
- Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Qin Ping Yaw
- Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ying Lau
- Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
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Antoun J, Itani H, Alarab N, Elsehmawy A. The Effectiveness of Combining Nonmobile Interventions With the Use of Smartphone Apps With Various Features for Weight Loss: Systematic Review and Meta-analysis. JMIR Mhealth Uhealth 2022; 10:e35479. [PMID: 35394443 PMCID: PMC9034427 DOI: 10.2196/35479] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 02/09/2022] [Accepted: 03/11/2022] [Indexed: 12/11/2022] Open
Abstract
Background The effectiveness of smartphone apps for weight loss is limited by the diversity of interventions that accompany such apps. This research extends the scope of previous systematic reviews by including 2 subgroup analyses based on nonmobile interventions that accompanied smartphone use and human-based versus passive behavioral interventions. Objective The primary objective of this study is to systematically review and perform a meta-analysis of studies that evaluated the effectiveness of smartphone apps on weight loss in the context of other interventions combined with app use. The secondary objective is to measure the impact of different mobile app features on weight loss and mobile app adherence. Methods We conducted a systematic review and meta-analysis of relevant studies after an extensive search of the PubMed, MEDLINE, and EBSCO databases from inception to January 31, 2022. Gray literature, such as abstracts and conference proceedings, was included. Working independently, 2 investigators extracted the data from the articles, resolving disagreements by consensus. All randomized controlled trials that used smartphone apps in at least 1 arm for weight loss were included. The weight loss outcome was the change in weight from baseline to the 3- and 6-month periods for each arm. Net change estimates were pooled across the studies using random-effects models to compare the intervention group with the control group. The risk of bias was assessed independently by 2 authors using the Cochrane Collaboration tool for assessing the risk of bias in randomized trials. Results Overall, 34 studies were included that evaluated the use of a smartphone app in at least 1 arm. Compared with controls, the use of a smartphone app–based intervention showed a significant weight loss of –1.99 kg (95% CI –2.19 to –1.79 kg; I2=81%) at 3 months and –2.80 kg (95% CI –3.03 to –2.56 kg; I2=91%) at 6 months. In the subgroup analysis, based on the various intervention components that were added to the mobile app, the combination of the mobile app, tracker, and behavioral interventions showed a statistically significant weight loss of –2.09 kg (95% CI –2.32 to –1.86 kg; I2=91%) and –3.77 kg (95% CI –4.05 to –3.49 kg; I2=90%) at 3 and 6 months, respectively. When a behavioral intervention was present, only the combination of the mobile app with intensive behavior coaching or feedback by a human coach showed a statistically significant weight loss of –2.03 kg (95% CI –2.80 to –1.26 kg; I2=83%) and –2.63 kg (95% CI –2.97 to –2.29 kg; I2=91%) at 3 and 6 months, respectively. Neither the type nor the number of mobile app features was associated with weight loss. Conclusions Smartphone apps have a role in weight loss management. Nevertheless, the human-based behavioral component remained key to higher weight loss results.
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Affiliation(s)
| | - Hala Itani
- American University of Beirut, Beirut, Lebanon
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