Characteristics of the selected studies.
|Choi et al., 2015||United States of America||30 inactive pregnant women aged 33.7 ± 2.6 years, between 10 and 20 weeks of gestation. 56% belonged to ethnic minorities.||12-week intervention with a mobile phone application developed by a research team and Fitbit Ultra. Women were asked to increase their steps by 10% each week until they reached at least 8,500 steps/day, 5 days or more per week. A daily text message or short video script was sent, to support PA or to reinforce their prescheduled weekly goal.||The change between groups in weekly mean steps per day was not statistically significant. The intervention group reported lower perceived barrier to being active, lack of energy (p = .02). The rates of responding to daily messages and using the diary through the mobile app declined during the study period.||Fair||Findings may not be generalizable due to the small size of the sample and to non-English speakers or women who are not motivated to use those technologies. Self-perceived scales are not defined. No CONSORT criteria.|
|Duscha et al., 2018a||United States of America||25 cardiac rehabilitation adult patients. An mHealth group (n = 16) aged 59.9 ± 8.1 years, 81.2% of which were male. Usual care group (n = 9) aged 66.5 ± 7.2 years of which 66.7% were male.||12-week mHealth program was implemented using physical activity trackers and health coaching. Patients were randomized into mHealth or usual care after completing cardiac rehabilitation.||The combination of a 4.7 ± 13.8% increase in the mHealth and a 8.5 ± 11.5% decrease in the usual care group resulted in a difference between groups (p ≤ .05) for absolute peak VO2. The divergent changes between intervention and control group in moderate-high physical activity minutes/week were significant (21 ± 103 vs – 46 ± 36; p < .05).||Fair||Previous fitness levels, activity levels, socioeconomic status or comorbidities of this group are not defined. The results can’t be generalized. No internal load parameters included on the research. No CONSORT criteria.|
|Duscha et al., 2018b||United States of America||20 adult and elderly peripheral artery disease patients with peripheral artery disease with intermittent claudication, aged 69.4 ± 8.4 years. 84,2% were male.||12-week mHealth intervention consisting of patient education, smartphones, and physical activity trackers.||Intervention patients significantly increased peak VO2 from 15.2 ± 4.3 to 18.0 ± 4.8 ml/kg/min (20.3 ± 26.4%; p ≤ .05), while control ones did not change from 14.3 ± 5.4 to 14.5 ± 5.7 ml/kg/min (1.0 ± 6.9%; NS).||Fair||Sample size was little. Results can’t be generalized. Age and weight of the usual care group could affect the results. No internal load parameters included on the research. No CONSORT criteria.|
|Ellis et al., 2019||United States of America||51 adult and elderly mild-to-moderately severe (Hoehn and Yahr stages 1–3) idiopathic Parkinson Disease patients, aged 64.1 ± 9.5 years. 45.1% women, and 100% white.||1-year mHealth-mediated exercise strengthening, stretching and walking program, with a pedometer plus engagement in planned exercise supported by a mobile health application was compared with an active control condition (walking with a pedometer and exercise only).||Both groups increased daily steps, moderate-intensity minutes, and 6-Minute Walk Test, with non-statistically significant between-group differences. The less active subgroup changes in daily steps and moderate-intensity minutes were clinically meaningful. There was a statistical improvement in the Parkinson Disease Questionnaire 39 mobility score in intervention overall comparison.||Fair||Further study in a larger group of people with low activity baseline is needed. More measures would offer a longitudinal data of the program outcomes and patients’ behavior. Strength program data is not registered. No internal load parameters included on the research. No CONSORT criteria.|
|Gomez Quiñonez et al., 2016||Netherlands||373 Dutch adults, ≥1 year post cancer therapy, aged 38.69 ± 11.99 years. 69.2% women.||6-month intervention where all participants were asked to complete questionnaires at the 5 points in time baseline (after 1 week, after 2 weeks, after 3 weeks, and after 6 months). Participants in the eHealth and mHealth group received fully automated tailored feedback messages about their current level of PA. Followed CONSORT criteria||Participants receiving feedback messages were significantly more physically active after 6 months than participants in the control group (B = 8.48, df = 2, P = .03, Cohen d = 0.27)||Fair||All outcome measures were self-reported. The process analyses were not accompanied by qualitative measurements. No internal load parameters included on the research.|
|Hart et al., 2017||United States of America||15 inactive to moderate active rural college students||Intervention components lasted four weeks. The eHealth group received four week-long health education modules via a campus-based website. Each weekly module consisted of lecture slides and a short multiple-choice quiz. The mHealth group also received four week-long modules with similar content as eHealth but with use of instant messaging and Facebook.||Positive values indicate improvement with exception of BMI, PBF, perceived control over physical activity, and sitting time. mHealth made improvement on all physical fitness measures. Also, mHealth made more improvement on physical activity measures than either eHealth or control.||Fair||Small size of the sample. Gender not defined. The control group did not receive any education that could affect a behavioral effect. No CONSORT criteria|
|Klaussen et al., 2016||Denmark||158 adolescents (66 girls, 92 boys), aged 13–16 (intervention group 14.6 ± 1.3; control group 14.6 ± 1.2) years with no physical activity restrictions after repaired complex congenital heart disease.||A 52-week Internet, mobile application, and SMS-based program delivering individually tailored text messages to encourage physical activity. Patients were asked to wear the accelerometer from 6 AM to 10 PM for two weekends and four weekdays. |
The patients could monitor their results and goals on a personal website. Followed CONSORT criteria.Los pacientes podían supervisar sus resultados y objetivos en un sitio web personal. Se siguieron los criterios de CONSORT.
|The difference between the intervention group and the control group in mean VO2 peak at 1 year was −0.65 ml/kg−1·min−1 (95% CI −2.66 to 1.36). Between group differences at 1 year in physical activity, generic health-related quality of life, and disease-specific quality of life were not statistically significant.||Fair||Just 75% of the sample (119 subjects) finished the intervention. The intervention did not allow for interaction between patients due to concerns regarding safeguarding minors on the Internet.|
|Martin et al., 2015||United States of America||48 mActive adults and elderly outpatients (46% women, 21% nonwhite) aged 58 ± 8 years||After establishing baseline activity during a blinded run-in (week 1), in phase I (weeks w2 to 3), we randomized 2:1 to unblinded versus blinded tracking. Unblinding allowed continuous access to activity data through a smartphone interface. Followed CONSORT criteria.||Participants receiving texts increased their daily steps over those not receiving texts by 2,534 (95% CI, 1,318 to 3750; P < .001) and over blinded controls by 3,376 (95% CI, 1,951 to 4,801; P < .001)||Fair||The mActive trial lends support to the notion of new mHealth devices as facilitators, not drivers, of behavior change, because sequential randomization suggested that unblinding to device data did not significantly modify behavior, whereas coupling it with smart texts did. Not internal load parameters included on the research.|
|Mendoza et al., 2017||United States of America||59 adolescents and young adults, ≥1 year post cancer therapy, aged 16.6 ± 1.5 years. 59.3% women, and 71.2%, non-Hispanic white.||The 10-week intervention consisted of a wearable physical activity-tracking device (Fitbit Flex) and a peer-based virtual support group (Facebook group). Research staff helped set step goals and awarded badges weekly.||Some modest differences were found for select subscales of quality of life and motivation for physical activity.||Fair||Social network not active for this group age. Few external parameters. Not internal load parameters included on the research. No CONSORT criteria.|
|Shcherbina et al., 2019||United States of America||2,783 adults, mean age of users was 44.4 years (SD 7.5), 73.5% men, and of those who reported ethnicity, 86.6% self-identified as white.||7-day intervention consisted of daily prompts to complete 10,000 steps and to stand following 1 h of sitting. Instructions to read the guidelines from the American Heart Association website, or e-coaching based upon the individual’s personal activity patterns from the baseline week of data collection.||All interventions significantly increased mean daily step count from baseline.||Fair||Despite the large size of the sample, it is too heterogeneous and conditioned by the app download self-intention. No CONSORT criteria. |
|Uhm et al., 2016||Korea||365 breast cancer patients, aged 50.3 ± 9.5 years, whose treatment had been terminated when enrolled.||12 week aerobic and resistance exercise intervention. The mHealth group received a pedometer and a newly smartphone app to provide information and monitor prescribed exercises.||Physical function, physical activity and quality of life were significantly improved regardless of the intervention method, and changes were not significantly different between the two groups.||Good||Workload values are not reported during the intervention. NO CONSORT criteria.|
|Vasankari et al., 2019||Finland||540 patients scheduled for elective coronary artery bypass grafting, aortic valve replacement or mitral valve repair.||Postsurgical rehabilitation personalised physical guidance during 90 days after discharge, receiving personalized daily goals, via application. Feedback of accomplishing their activity goals will be given and customized by the physiotherapy team.||Change was observed in mean daily step count between the baseline and 3 and 12 months after hospital discharge.||Low||Detailed data from the sample not provided. Baseline values may differ from patients’ normal habitual activity profiles. Many patients have comorbidities during their postoperative rehabilitation. No internal load parameters included on the research. No CONSORT criteria.|
|Vorrink et al., 2016||Netherlands||157 adults and elderly subjects (79 women, 78 men), aged 62 ± 9 years for the intervention group and 63 ± 8 for the control group, diagnosed with chronic obstructive lung disease.||Multicenter intervention of 6 months duration, consisted of a smartphone application for the patients and a monitoring website for the physiotherapists. Physical activity, functional exercise capacity, lung function, health-related quality of life and body mass index were assessed. Subjects were persuaded to achieve their personalized physical activity goal by automated persuasive messages and an emoticon. Followed CONSORT criteria.||There were no significant positive effects of the intervention on physical activity. There was a significant decrease over time in physical activity (p < .001), lung function (p < .001) and mastery (p = .017), but not in functional exercise capacity (p = .585).||Low||Drop-out in the intervention group was 39%. Worries about the smartphone were reasons for patients to drop out of the study. Patients might have received insufficient support to adhere to the personalized PA goals. The sample was designed with different population groups and did not measure baseline values at the start of the program.|