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. 2020 Jan 24;26:100470. doi: 10.1016/j.ijcha.2020.100470

Table 1.

Studies with digital health interventions.

First and last author Study acronym Number of participants (total/intervention vs control) Primary endpoints Successful (yes/no) Type of DHI doi
Widmer&Lerman n/a 80/40 vs. 40 physical/biochemical metrics; behavorial characteristics yes online and smartphone https://doi.org/10.1016/j.ahj.2017.02.016
Anand&Beyene n/a 343/174 vs. 169 MI (myocardial infarction) risk score no emails and text messages https://doi.org/10.1001/jamacardio.2016.1035
Martin&Blaha mActive 48/16 vs. 32 change in steps/day yes text messages https://doi.org/10.1161/JAHA.115.002239
Glynn&Murphy SMART MOVE 90/41 vs. 37 change in steps/day yes smartphone app https://doi.org/10.3399/bjgp14X680461
Torbjørnsen&Ribu n/a 101/51 vs. 50 acceptability yes smartphone app https://doi.org/10.2196/mhealth.8824
Dallinga&Baart de la Faille-Deutekom n/a 3772/ 1976 vs. 1796 running physical activity yes smartphone app https://doi.org/10.1186/s12889-015–2165-8
Litman&Robinson n/a 726/464 vs. 262 physical activity (self-report) yes smartphone app https://doi.org/10.2196/jmir.4142
Turner-McGrievy&Tate n/a 85/48 vs. 37 activity levels; dietary intake; weight loss yes smartphone app https://doi.org/10.1136/amiajnl-2012–001510
Patel&Hilbert STEP UP 602/451 vs.151 change in steps/day yes wearable; gamification https://doi.org/10.1001/jamainternmed.2019.3505
Bennet&Miranda Track 351/176 vs. 175 weight change yes smartphone app; smart scale; telephone calls https://doi.org/10.1016/j.amepre.2018.07.005
Block&Block Alive-PD study 339/163 vs. 176 fasting glucose; HbA1c; body weight yes behavioural intervention via web app; internet; mobile phone; automated calls https://doi.org/10.2196/jmir.4897
Castro Sweet&Prewitt n/a 501 body weight; glucose/HbA1c; lipid profile; well being yes web/mobile information and tracking combined with human coaching https://doi.org/10.1177/0898264316688791
Alonso-Domínguez& Recio-Rodríguez EMID Study 204/102 vs. 102 adherence to Mediterranean diet yes smartphone app; workshop; exercise https://doi.org/10.3390/nu11010162
Frias&Osterberg n/a 109/80 vs. 29 change of systolic blood pressure yes Digital medicine offerings (digital medicine, wearable sensor patch and mobile device app) https://doi.org/10.2196/jmir.7833
Morawski&Choudhry MedISAFE-BP 411/209 vs. 202 medication adherence; change of systolic blood pressure yes Smartphone app (Medisafe app) https://doi.org/10.1001/jamainternmed.2018.0447
Johnston&Varenhorst SUPPORT study 174/91 vs. 83 medication adherence yes smartphone app https://doi.org/10.1016/j.ahj.2016.05.005
Zhang&Wang SBCHDP (smartphone-based coronary heart disease prevention) programme 80/40 vs. 40 perceived stress; behavioural risk factors no (but positive tendency) smartphone app (Care4Heart) https://doi.org/10.1186/s12955-017–0623-y
Polizzi&Tolsma Quit Smart 97 (no control group, compared with published data) smoking cessation no audiotape (accompanied by discount vouchers for nicotine replacement therapy, group sessions and a self-help manual) https://doi.org/10.7812/tpp/03–048
Brendryen&Kraft Happy ending 290/ 144 vs. 146 abstinence from smoking yes internet and cell phone https://doi.org/10.2196/jmir.1005
Webb Hooper & Robinson n/a 140/ 70 vs. 70 feasibility and process variables, including intervention evaluations, readiness to quit yes DVD https://doi.org/10.1093/ntr/ntu079
Burford & Hendrie n/a 160/ 80 vs. 80 quit attempts at 6-month follow-up (self-reported and biochemically validated through testing for carbon monoxide (CO)) yes face aging software https://doi.org/10.2196/jmir.2337
Zeng & Bricker n/a 98 descriptive analysis of user characteristics and utilization of a app for smoking cessation smartphone app https://doi.org/10.1089/tmj.2014.0232
Heffner & Bricker n/a 76 explorative analysis of most-used app features; prospective associations between feature usage and quitting smartphone app https://doi.org/10.3109/00952990.2014.977486
Buller & Zimmerman n/a 102/ 51 vs. 51 self-reported usability of REQ-Mobile and quitting behavior no smartphone app; text messaging https://doi.org/10.1089/tmj.2013.0169
BinDhim & Trevena SSC App 684/ 342 vs. 342 smoking abstinence yes interactive smoking cessation decision-aid application https://doi.org/10.1136/bmjopen-2017–017105
Westmaas & Abroms n/a 1070/ 535 vs. 535 abstinence from smoking yes email https://doi.org/10.1136/tobaccocontrol-2016–053056
Lewis & Lyons n/a 35/ 19 intervention vs. 16 on waitlist (secondary mixed-method analysis) descriptive analysis of social support patterns using a mobile app for PA Jawbone Up24 activity monitor and Apple iPad Mini; Social support features in the UP app included comments and likes https://doi.org/10.2196/12496
Tong & Laranjo n/a 55 (secondary mixed-methods feasibility study) descriptive analysis of users’ perspectives regarding mobile social networking interventions to promote physical activity physical activity tracker and a wireless scale integrated with a social networking mobile app https://doi.org/10.2196/11439
Vandelanotte & Alley n/a 243/ 122 vs. 121 increase in physical activity yes 8 modules of theory-based, personally tailored physical activity advice and action planning. Participants were randomized to receive the same intervention either with or without Fitbit tracker integration. https://doi.org/10.2196/11321
Devi & Singh n/a 94/ 48 vs. 46 change in steps/day yes step count via accelerometer https://doi.org/10.2196/jmir.3340
Harris & Cook PACE-UPPACE-Lift PACE-UP: 236 (postal) vs. 231 (nurse support) vs. 214 (control)
PACE-Lift: 108 vs. 117 (control)
change in steps/day yes step count via pedometer +/- nurse counselling +/- postal counselling https://doi.org/10.1371/journal.pmed.1002526