Effect of implementing a mobile game on improving dietary information in diabetic patients

Koohmareh, Zahra; Karandish, Majid; Hadianfard, Ali Mohammad

doi:10.47176/mjiri.35.68

Cited by 7 publications

(29 citation statements)

References 37 publications

(34 reference statements)

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“…Overall, there was a diverse population of patients diagnosed with prediabetes (glucose: 5.55-6.94 mmol/L or 100-125 mg/dL; HbA 1c : 39-46 mmol/mol or 5.7%-6.4%), type 1 DM, T2DM, and gestational DM (2-hour oral glucose tolerance test level of ≥9 mmol/L). The features of each app included food tracking [ 53 - 62 ], education, knowledge, or recommendations [ 54 - 56 , 59 - 65 ], physical activity tracking [ 54 - 56 , 59 - 62 ], weight monitoring [ 56 , 59 - 62 ], glucose monitoring [ 55 , 57 , 60 , 61 , 64 ], blood pressure monitoring [ 60 ], community support [ 54 , 59 , 60 ], feedback [ 54 - 56 , 59 , 61 , 62 , 64 ], health coaches [ 55 ], clinician portals [ 60 - 62 ], connectivity to digital health devices [ 56 , 57 ], scheduled reminders [ 56 , 58 , 59 , 62 ], gamification [ 59 , 63 ], and goal setting [ 59 ]. In addition, several targeted behavioral domains and outcomes were measured as a result of the mHealth app nutrition intervention.…”

Section: Resultsmentioning

confidence: 99%

Behavior Change Effectiveness Using Nutrition Apps in People With Chronic Diseases: Scoping Review

Salas-Groves¹,

Galyean²,

Alcorn³

et al. 2023

JMIR Mhealth Uhealth

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Background Cardiovascular disease, cancer, diabetes mellitus, and obesity are common chronic diseases, and their prevalence is reaching an epidemic level worldwide. As the impact of chronic diseases continues to increase, finding strategies to improve care, access to care, and patient empowerment becomes increasingly essential. Health care providers use mobile health (mHealth) to access clinical information, collaborate with care teams, communicate over long distances with patients, and facilitate real-time monitoring and interventions. However, these apps focus on improving general health care concerns, with limited apps focusing on specific chronic diseases and the nutrition involved in the disease state. Hence, available evidence on the effectiveness of mHealth apps toward behavior change to improve chronic disease outcomes is limited. Objective The objective of this scoping review was to provide an overview of behavior change effectiveness using mHealth nutrition interventions in people with chronic diseases (ie, cardiovascular disease, diabetes mellitus, cancer, and obesity). We further evaluated the behavior change techniques and theories or models used for behavior change, if any. Methods A scoping review was conducted through a systematic literature search in the MEDLINE, EBSCO, PubMed, ScienceDirect, and Scopus databases. Studies were excluded from the review if they did not involve an app or nutrition intervention, were written in a language other than English, were duplicates from other database searches, or were literature reviews. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines, the systematic review process included 4 steps: identification of records through the database search, screening of duplicate and excluded records, eligibility assessment of full-text records, and final analysis of included records. Results In total, 46 studies comprising 256,430 patients were included. There was diversity in the chronic disease state, study design, number of participants, in-app features, behavior change techniques, and behavior models used in the studies. In addition, our review found that less than half (19/46, 41%) of the studies based their nutrition apps on a behavioral theory or its constructs. Of the 46 studies, 11 (24%) measured maintenance of health behavior change, of which 7 (64%) sustained behavior change for approximately 6 to 12 months and 4 (36%) showed a decline in behavior change or discontinued app use. Conclusions The results suggest that mHealth apps involving nutrition can significantly improve health outcomes in people with chronic diseases. Tailoring nutrition apps to specific populations is recommended for effective behavior change and improvement of health outcomes. In addition, some studies (7/46, 15%) showed sustained health behavior change, and some (4/46, 9%) showed a decline in the use of nutrition apps. These results indicate a need for further investigation on the sustainability of the health behavior change effectiveness of disease-specific nutrition apps.

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Section: Resultsmentioning

confidence: 99%

Behavior Change Effectiveness Using Nutrition Apps in People With Chronic Diseases: Scoping Review

Salas-Groves¹,

Galyean²,

Alcorn³

et al. 2023

JMIR Mhealth Uhealth

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show abstract

“…23,24,30 A total of 35.5% to 100.0% participants took oral antihyperglycemic medication, 19,15,22,25,26,28,29,31 11.8% to 37.8% participants injected insulin, 22,25,29,31 and 23.5% to 30% had mixed oral medication and insulin. 25,26 A total of six studies reported the duration of diabetes, ranging from 2.6 to 13.7 y 15,19,23,27,29,31 Among 15 reviewed studies, a total of eight studies were two-arm RCT intervention, 15,20,22,23,25 -28 two studies were two-arm quasi-experimental studies, 18,24 and five studies were single-group intervention. 17,19,29 -31 A total of 12 studies lasted less than or equal to three months, 15,17 -20,23 -26,29 -31 and three lasted 12 months.…”

Section: Resultsmentioning

confidence: 99%

“…25,26 A total of six studies reported the duration of diabetes, ranging from 2.6 to 13.7 y 15,19,23,27,29,31 Among 15 reviewed studies, a total of eight studies were two-arm RCT intervention, 15,20,22,23,[25][26][27][28] two studies were two-arm quasi-experimental studies, 18,24 and five studies were single-group intervention. 17,19,[29][30][31] A total of 12 studies lasted less than or equal to three months, 15,[17][18][19][20][23][24][25][26][29][30][31] and three lasted 12 months. 22,27,28…”

Section: Description Of Included Studiesmentioning

confidence: 99%

“…27,28 Of the two-arm RCT pilot studies that lasted less than or equal to three months, 15,20,23,25,26 three studies resulted in a significant reduction in HbA1c, 15,23,25 one resulted in reduction in carbohydrate food consumption, 23 improvement in dietary information scores, 26 attention to high carbohydrate food, high calorie food, 26 and diet behavior, 20 and significant improvement in diabetes distress 20,23 and depression. 23 However, others did not result in HbA1c reduction, 20 fasting blood glucose changes, 20,26 did not resulted in improving diet self-management skills. 15,25 Of the two two-arm quasi-experimental studies, 18,24 one resulted in a significant reduction in HbA1c, 24 and the other achieved a BMI reduction and improved dietary behavior and dietary attitude.…”

Section: Intervention Effects On Physiological Dietary Behavioral And...mentioning

confidence: 99%

“…Among 15 reviewed studies, four were conducted in the United States, 19,23,24,30 seven were in Asia, 15,18,[25][26][27][28][29] two were in Australia, 17,20 and two were in Europe. 22,31 The sample sizes ranged from 10 to 800.…”

Section: Description Of Included Studiesmentioning

confidence: 99%

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Dietary Self-Management Using Mobile Health Technology for Adults With Type 2 Diabetes: A Scoping Review

Zheng¹,

Rice²,

Melkus³

et al. 2023

J Diabetes Sci Technol

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Objective: Dietary self-management is one key component to achieve optimal glycemic control. Advances in mobile health (mHealth) technology have reduced the burden of diabetes self-management; however, limited evidence has been known regarding the status of the current body of research using mHealth technology for dietary management for adults with type 2 diabetes. Methods: Literature searches were conducted electronically using PubMed, CINAHL (EBSCO), Web of Science Core Collection, PsycINFO (Ovid), EMBASE (Ovid), and Scopus. Keywords and subject headings covered dietary management, type 2 diabetes, and mHealth. Inclusion criteria included studies that applied mHealth for dietary self-management for adults with type 2 diabetes and were published in English as full articles. Results: This review (N = 15 studies) revealed heterogeneity of the mHealth-based dietary self-management or interventions and reported results related to physiological, dietary behavioral, and psychosocial outcomes. Twelve studies applied smartphone apps with varied functions for dietary management or intervention, while three studies applied continuous glucose monitoring (CGM) to guide dietary changes. Among 15 reviewed studies, only three of them were two-arm randomized clinical trial (RCT) with larger sample and 12-month study duration and 12 of them were pilot testing. Nine of 12 pilot studies showed improved HbA1c; most of them resulted in varied dietary changes; and few of them showed improved diabetes distress and depression. Conclusion: Our review provided evidence that the application of mHealth technology for dietary intervention for adults with type 2 diabetes is still in pilot testing. The preliminary effects are inconclusive on physiological, dietary behavioral, and psychosocial outcomes.

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Electronic Interactive Games for Glycemic Control in Individuals With Diabetes: Systematic Review and Meta-Analysis

Yao,

Han,

Yang

et al. 2024

JMIR Serious Games

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Background Several electronic interventions have been used to improve glycemic control in patients with diabetes. Electronic interactive games specific to physical activity are available, but it is unclear if these are effective at improving glycemic control in patients with diabetes. Objective This study aimed to determine the effects of electronic game–based interventions on glycemic control in patients with diabetes. Methods Relevant studies that were published before April 1, 2023, were searched from 5 databases: PubMed, Embase, Web of Science, Scopus, and Cochrane Library. Eligibility criteria included prospective studies examining the relationship between electronic games with physical activities or diet education and glycemic control as the outcome. The risk of bias was assessed using the Cochrane risk-of-bias tool. All analyses were conducted using RevMan5.4.1. Depending on the heterogeneity across studies, the pooled effects were calculated using fixed-effects or random-effects models. Results Participants from 9 studies were included and assessed. Glycated hemoglobin (HbA1c) and fasting blood glucose improved in the intervention group, although the analysis revealed no significant reduction in HbA1c (−0.09%, 95% CI −0.29% to 0.10%) or fasting blood glucose (−0.94 mg/dL, 95% CI −9.34 to 7.46 mg/dL). However, the physical activity of individuals in the intervention group was significantly higher than that of those in the control group (standardized mean difference=0.84, 95% CI 0.30 to 1.38; P=.002). Other outcomes, such as weight and blood lipids, exhibited no significant improvement (all P>.05). Conclusions Electronic games had a good impact on participants’ physical activity and offered an advantage in glycemic control without reaching statistical significance. Electronic games are convenient for reminders and education. Low-intensity exercise games may not be considered a better adjuvant intervention to improve diabetes self-management care.

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Effect of implementing a mobile game on improving dietary information in diabetic patients

Cited by 7 publications

References 37 publications

Behavior Change Effectiveness Using Nutrition Apps in People With Chronic Diseases: Scoping Review

Behavior Change Effectiveness Using Nutrition Apps in People With Chronic Diseases: Scoping Review

Dietary Self-Management Using Mobile Health Technology for Adults With Type 2 Diabetes: A Scoping Review

Electronic Interactive Games for Glycemic Control in Individuals With Diabetes: Systematic Review and Meta-Analysis

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