Mobile phone text-messaging interventions aimed to prevent cardiovascular diseases (Text2PreventCVD): systematic review and individual patient data meta-analysis

Background A variety of small mobile phone text-messaging interventions have indicated improvement in risk factors for cardiovascular disease (CVD). Yet the extent of this improvement and whether it impacts multiple risk factors together is uncertain. We aimed to conduct a systematic review and individual patient data (IPD) meta-analysis to investigate the effects of text-messaging interventions for CVD prevention. Methods Electronic databases were searched to identify trials investigating a text-messaging intervention focusing on CVD prevention with the potential to modify at least two CVD risk factors in adults. The main outcome was blood pressure (BP). We conducted standard and IPD meta-analysis on pooled data. We accounted for clustering of patients within studies and the primary analysis used random-effects models. Sensitivity and subgroup analyses were performed. Results Nine trials were included in the systematic review involving 3779 participants and 5 (n=2612) contributed data to the IPD meta-analysis. Standard meta-analysis showed that the weighted mean differences are as follows: systolic blood pressure (SBP), -4.13 mm Hg (95% CI -11.07 to 2.81, p<0.0001); diastolic blood pressure (DBP), -1.11 mm Hg (-1.91 to -0.31, p=0.002); and body mass index (BMI), -0.32 (-0.49 to -0.16, p=0.000). In the IPD meta-analysis, the mean difference are as follows: SBP, -1.3 mm Hg (-5.4 to 2.7, p=0.5236); DBP, -0.8 mm Hg (-2.5 to 1.0, p=0.3912); and BMI, -0.2 (-0.8 to 0.4, p=0.5200) in the random-effects model. The impact on other risk factors is described, but there were insufficient data to conduct meta-analyses. Conclusion Mobile phone text-messaging interventions have modest impacts on BP and BMI. Simultaneous but small impacts on multiple risk factors are likely to be clinically relevant and improve outcome, but there are currently insufficient data in pooled analyses to examine the extent to which simultaneous reduction in multiple risk factors occurs.