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. 2024 Nov 22;82(1):221.
doi: 10.1186/s13690-024-01450-x.

Prognostic effectiveness of interactive vs. non-interactive mobile app interventions in type 2 diabetes: a systematic review and meta-analysis

Zheng Tang #  1 , Lijuan Zhao #  2 , Jixin Li #  3 , Yang Yang  1 , Fengzhao Liu  2 , Han Li  4 , Zhenyu Yang  5 , Shanyu Qin  1 , Xinqin Li  6   7
Affiliations

Prognostic effectiveness of interactive vs. non-interactive mobile app interventions in type 2 diabetes: a systematic review and meta-analysis

Zheng Tang et al. Arch Public Health. .

Abstract

Background: Mobile app interventions are emerging as significant tools in managing the prognosis of type 2 diabetes, demonstrating progressively greater impacts. The effectiveness of these interventions needs further evidence-based support.

Objective: This study conducted a systematic review and meta-analysis of randomized controlled trials to evaluate the effectiveness of mobile app interventions in improving prognosis for patients with type 2 diabetes.

Methods: We searched PubMed, Cochrane, Embase, and Web of Science for relevant studies published from inception to 18 April 2024, adhering to the Cochrane Handbook guidelines. The quality of the included studies was assessed using the Cochrane risk of bias tool. Primary outcomes measured were changes in glycated hemoglobin (HbA1c) and diabetes self-management (DSM). Secondary outcomes included changes in diastolic blood pressure (DBP), systolic blood pressure (SBP), triglycerides(TG), total cholesterol(TC), high-density lipoprotein (HDL), low-density lipoprotein (LDL), lipid profiles, fasting plasma glucose (FPG), body mass index (BMI), and Steps outcomes. Subgroup analyses were performed for the primary outcomes and for high-density lipoprotein (HDL), low-density lipoprotein (LDL), diastolic blood pressure (DBP), and systolic blood pressure (SBP). Interventions with or without interactions were also used as a basis for subgrouping.

Results: A total of 15 eligible articles involving 17 studies with 2,028 subjects (1,123 in the intervention group and 1,020 in the control group) were included in the synthesis. Interactive mobile app interventions significantly reduced HbA1c levels (SMD - 0.24; 95% CI, -0.33 to -0.15; P < 0.00001) and significantly improved diabetes self-care (SMD 0.71; 95% CI, 0.21 to 1.21; P = 0.005). Secondary outcomes, including FPG, LDL, DBP, and SBP, showed varying degrees of improvement. Subgroup analyses indicated that the intervention effect was more pronounced and less heterogeneous in the short-term (≤ 3 months) for younger Asian individuals (< 55 years) who used an interactive mobile app.

Conclusion: Interactive mobile app interventions effectively improve HbA1c levels and diabetes self-care competencies in patients with type 2 diabetes. These interventions offer supportive evidence for their clinical use in managing and prognosticating type 2 diabetes.

Systematic review registration: CRD42024550643.

Keywords: Diabets self-management; Meta-analysis; Mobile app; Systematic review; Type 2 diabetes mellitus.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: No approval was required. All the authors complied with the ethics and policy of the journal. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests

Figures

Fig. 1
Fig. 1
Flow diagram for articles included in interactive vs. non-interactive mobile app interventions in type 2 diabetes (searched up to april 18, 2024)
Fig. 2
Fig. 2
Risk of bias summary
Fig. 3
Fig. 3
Risk of bias graph
Fig. 4
Fig. 4
Forest plots of (a) hba1c, b fpg, c bmi for interactive vs. non-interactive mobile app interventions in type 2 diabetes
Fig. 5
Fig. 5
Funnel plots of (a) hba1c, b fpg, c bmi for interactive vs. non-interactive mobile app interventions in type 2 diabetes
Fig. 6
Fig. 6
Forest plots of (a) tg, b tc, c hdl, d ldl for interactive vs. non-interactive mobile app interventions in type 2 diabetes
Fig. 7
Fig. 7
Funnel plots of (a) tg, b tc, c hdl, d ldl for interactive vs. non-interactive mobile app interventions in type 2 diabetes
Fig. 8
Fig. 8
Sensitivity analysis plots for interactive vs. non-interactive mobile app interventions in type 2 diabetes: a hdl, b diabetes self-care, c steps
Fig. 9
Fig. 9
Forest plots of (a) sbp, b dbp, c diabetes self-care (d) steps for interactive vs. non-interactive mobile app interventions in type 2 diabetes
Fig. 10
Fig. 10
Funnel plots of (a) sbp, b dbp, c diabetes self-care, d steps for interactive vs. non-interactive mobile app interventions in type 2 diabetes
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