Table 1.
Basic characteristics and outcomes of included studies
| Study | Country/region | Sample size (Trial/Control) | TM interventiona | Mean age (year) | College education (%) | Gestational age at enrolment (week) | Outcomeb |
|---|---|---|---|---|---|---|---|
| Carral 2015 [29] | Spain | 77 (30/47) | Web-based system | 33.8 | 22.1 | 21.1 | ① |
| Dalfra 2009 [30] | Italy | 203 (88/115) | Health device | 34.0 | – | 28.0 | ①④⑦ |
| Given 2015 [31] | North Ireland and Ireland | 50 (24/26) | Health device | 31.7 | – | 28.0 | ④⑦⑧⑨⑩⑫ |
| Guo 2019 [6] | China | 124 (64/60) | Health app | 30.9 | 55.6 | 24.9 | ①②③④⑦⑪ |
| Homko 2007 [32] | USA | 57 (32/25) | Web-based system | 29.5 | 43.9 | 27.6 | ②④⑤⑥⑧⑨⑩⑪⑫ |
| Homko 2012 [33] | USA | 80 (40/40) | Web-based system | 30.2 | 60.0 | 28.5 | ②④⑤⑥⑧⑨⑩⑪⑫ |
| Mackillop 2018 [7] | UK | 203 (101/102) | Health app | 33.5 | 48.5 | 31.0 | ②④⑤⑦⑧⑨⑪⑫ |
| Miremberg 2018 [4] | Israel | 120 (60/60) | Health app | 31.9 | 32.5 | – | ④⑤⑧⑩⑪⑭ |
| Perez-Ferre 2010 [34] | Spain | 97 (49/48) | Health app | 33.8 | 15.5 | – | ④⑤⑪⑫ |
| Rasekaba 2018 [35] | Australia | 95 (61/34) | Web-based system | 32.0 | – | 28.0 | ②③④⑦⑧ |
| Yang 2018 [36] | China | 107 (57/50) | 31.9 | – | – | ②③④⑤⑥⑦⑧⑨⑪⑫ | |
| Carolan-Olah 2019 [37] | Australia | 110 (52/58) | Web-based system | 31.7 | 47.3 | 28–30 | ⑦ |
| Kim 2019 [3] | Korea | 44 (22/22) | Web-based system | 35.8 | 97.7 | 27.4 | ①② |
| Gao 2017 [18] | China | 58 (28/30) | Health app | 27.8 | 31.0 | – | ①②③ |
| Hua 2018 [19] | China | 120 (60/60) | 27.6 | 25.8 | 24.0 | ①②③④⑦⑪⑫ | |
| Zhang 2018 [38] | China | 80 (40/40) | Health app | 29.5 | – | 26.9 | ②③ |
| Zhao 2018 [39] | China | 60 (30/30) | Health app | – | – | – | ②③ |
| Zeng 2017 [40] | China | 86 (43/43) | – | 74.4 | – | ④⑪ | |
| Fang 2017 [41] | China | 60 (30/30) | 30.8 | – | 23.0 | ①②③④⑥⑦⑨⑪⑫⑬ | |
| Ge 2017 [23] | China | 586 (308/278) | 30.5 | 45.1 | 26.0 | ④⑦ | |
| Huang 2016 [42] | China | 80 (40/40) | 39.0 | 28.8 | 36.7 | ①②③④ | |
| Jiang 2017 [43] | China | 150 (78/72) | 28.0 | – | 29.5 | ①②③④⑤⑦⑩⑪⑭ | |
| Jiang 2019 [44] | China | 200 (100/100) | 28.7 | – | – | ④⑤⑦⑫⑬⑭ | |
| Jiang 2016 [20] | China | 120 (60/60) | 25.3 | – | 22.8 | ⑤⑦⑫⑭ | |
| Liu 2018 [45] | China | 98 (49/49) | Health device | 27.8 | – | 30.3 | ①②③ |
| Lu 201 [21] | China | 280 (140/140) | 26.1 | 47.9 | – | ①②③⑤⑦⑫⑬⑭ | |
| Luo 2017 [46] | China | 107 (57/50) | 31.9 | – | – | ②④⑥ | |
| Shao 2018 [47] | China | 410 (205/205) | 30.5 | 52.9 | – | ②③⑦ | |
| Su 2018 [22] | China | 820 (420/400) | Web-based system | 28.2 | 27.0 | – | ②③⑤⑥⑦⑫⑬⑭ |
| Weng 2018 [48] | China | 120 (60/60) | 39.5 | 53.3 | 36.6 | ①②③④ | |
| Xiao 2016 [24] | China | 206 (103/103) | 29.7 | – | 26.4 | ⑦⑪ | |
| Yang 2015 [49] | China | 100 (50/50) | 30.0 | 80.0 | – | ⑤⑥⑦⑫⑬⑭ |
aTM intervention: Detailed descriptions are listed in Additional file 3. bOutcome: ①change of HbA1c; ②change in FBG; ③change in 2hBG; ④caesarean section; ⑤pregnancy induced hypertension or preeclampsia; ⑥premature rupture of membranes; ⑦macrosomia; ⑧admission to the NICU; ⑨neonatal jaundice or hyperbilirubinemia; ⑩NARDS; ⑪neonatal hypoglycaemia; ⑫preterm birth; ⑬neonatal asphyxia; ⑭polyhydramnios