In total, 21 peer-review articles and one thesis —stemmed from 14 studies— were finally retained. The list of excluded publications and reasons for exclusion is provided in Appendix (Supplementary file 3).
The characteristics of the 14 included studies are presented in Table 1. Five studies were conducted in the USA (24, 42–44, 53), one in Japan (51) and the remaining eight in Europe (41, 45–50). Among European studies, three were conducted in the Netherlands (47, 48, 50), two in the UK (46, 52), and one in three countries (Greece, Spain and Sweden) (41). Furthermore, three studies presented different parts of their results in distinct publications: (i) Wijsman et al. (50, 54, 55); (ii) van het Reve et al. (49, 56, 57); and (iii) Peels et al. (47, 58–62).
Table 1
Characteristics of included studies
Study ID, Country Related publications | Study design, Duration of the intervention | Population and setting Number of participants (n) Age (years) Female/male | Description of the intervention Intervention group (IG)/control group (CG) | Outcome measures (Primary outcome; Secondary outcome) | Key findings |
Myhre 2013, USA | RCT, 3 arms 8 weeks | 2 cohorts from retirement communities in Arizona; n = 41 mean age: 79.4 Female/male: IG1: 9/5 IG2: 9/4 CG: 11/3 | Micro-blogging shared with others or kept private IG1: Facebook IG2: online diary CG: Waitlist | Knowledge Letter memory Keep Track | IG1: Knowledge, Memory task improved at Time 2 vs. baseline (p < 0.01); Keep Track slightly improved (p < 0.10) |
Mouton 2015, Belgium | RCT, 4-arms | One municipality in Belgium; n = 204 mean age: 65 Female/male: IG1: 20/13 IG2: 27/13 IG3: 25/13 CG: 23/15 | Web-based, center-based or combined physical activity (PA) intervention IG1: web-based intervention IG2: center-based intervention IG3: mixed (center- and web-based) intervention CG: no intervention | Physical activity (PA) level Readiness for PA Awareness of PA (general) Awareness of PA (opportunities in municipality) | IG3 improved in: PA level (p: 0.041); Readiness for PA (p: 0.001). IG3 improved on awareness of PA (p: 0.003) and awareness of PA opportunities in municipality (p: 0.001) |
Kurti 2013 USA | Quasi experimental (controlled trial), 2 months | Community members over 50 years in Florida; n = 12 mean age: 65,5 Female/male: IG: 5/1 CG: 5/1 | Internet-based intervention (successive 5-day blocks) to increase physical activity in sedentary adults IG: Monetary consequences CG: No monetary consequences | Physical activity | IG and CG reached the 10,000-step goal. IG vs CG increased steps (182% vs 108%) and met steps goals (87% vs 52%) |
Peels 2013a Netherlands Related publications: Golsteijn 2014, Peels 2012, Peels 2013b. Peels 2014a, 2014b | cluster-RCT, 5-arms 1 year | Community members n = 1729 mean age: 62 Female/male: IG1: 127/51 IG2: 144/112 IG3: 111/113 IG4:93/100 CG: 158/152 | Printed or web-based tailored physical activity intervention IG1: printed basic IG2: print-delivered with environmental information IG3: web-based basic IG4: web-based with environmental information CG: No advice | Process outcomes (appreciation, understanding of information) | IG1-IG2: Printed intervention vs web-based intervention was significantly higher 92.7–98.2% read, 70.1–76.5% kept and 39.9–56.8% discussed, and better appreciated: (6.06–6.91 versus 5.05–6.11 on a scale of 1–10) |
van het Reve 2014 Switzerland Related publications Silveira, 2013 | Preclinical Exploratory Trial, 12-week | 2 institutions for older people and 1 organization providing home nursing care for seniors n = 44 mean age (yrs): 75 (SD: 6) Female/male: IG1: 8/5 IG2: 10/4 CG: 10/7 | A tablet with ActiveLifestyle IG1: social group with tablet IG2: individual group with tablet GC: brochure group | Gait performance (dual task walking) Physical performance Short Physical Performance Battery (SPPB) Fall efficacy Fall efficacy scale International (FES-I) | IG1 and IG2 improved significantly in single and dual task walking. IG1, IG2, GC showed SPPB improvement (p: 0.02) between pre- and post-test Group difference for FES-I between GC and IG1et IG2 (p: 0.04). |
Cook 2015, USA | RCT, 3 months | Workers aged 50 years and older n = 278 age range: 50 to 68 Female/male: IG: 40/98 CG: 50/89 | Web-based multimedia program (information and guidance) IG: Web-based multimedia program CG: Waitlist | Diet change Mild exercise Self-efficacy Eating practices Exercise planning Beliefs about ageing | IG performed better on diet change (p: 0.048), planning healthy eating (p: 0.03), and mild exercise (p: 0.01). IG vs CG showed effects on: eating practices (p: 0.03), exercise self-efficacy (p: 0.03), exercise planning (p: 0.03), and aging beliefs (p: 0.01). |
Irvine 2013, USA | RCT, 12 weeks | Sedentary men and women 55 years and over, community n = 368 mean age: 60.3 (SD: 4.9) Female/male: IG: 127/51 CG: 129/61 | Web-based intervention to promote physical activity IG: web-based intervention CG: No access to website | Physical activity Body mass index Quality of life SF-12 Health Survey | IG improved on 13 of 14 outcomes measures at both t1 vs t2 and t1 vs t3. IG maintained large gains on all 14 outcomes measures at 6 months. |
Kim 2013 USA | RCT, 6 weeks | African-American community, n = 46 mean age: GI: 69.3 (SD: 7.3) GC: 70.5 (SD: 7.5) Female/male: IG: 21/5 CG: 8/2 | Text Messaging to Motivate Walking IG: pedometer, walking instructional manual and text messaging CG: without text messaging | Physical activity Step count Perceived activity levels Leisure Time Exercise Questionnaire (LTEQ). | IG improved steps vs CG (679 vs. 398; p < 0.05), as well as LTEQ (p < 0.05). IG increased step (p < 0.05) text messaging 3 times/week Both groups increased their LTEQ score at 6-weeks (p < 0.001) |
Nyman 2009 UK | RCT, No duration specified | Community in Southampton n = 302 mean age: 70.41 (SD: 7.07) Female/male: 187/115 | Website with tailored advice to undertake strength and balance training (SBT). IG: website with tailored advice CG: generic website | Attitudes to Falls-Related Interventions Scale (AFRIS) | No significant differences in attitudes toward SBT. IG participants indicated that advice was relevant (p: 0.017) and activities good (p: 0.047). |
Slegers 2008 Netherland | Feasibility RCT, 4-arms 12 months | Community in Maastricht, n = 236 range age: 64–75 Female/male: ? | Computer Training and Internet Usage IG 1: training and intervention IG 2: training, no intervention CG1: No training, no intervention CG2: Not interested (passive control) | Physical and psychological well-being (SF-36) Social well-being and social network | Most outcomes were not significant IG participants spent more time on learning new things |
Ballesteros 2014 Spain, Sweden and Greece | RCT, 12 months | Communities in Spain, Sweden and Greece, n = 41 age range: 65–85 GI: mean age: 74 GC mean age: 75 Female/male: IG: 16/9 CG: 11/5 | ICT-mediated social network: AGNES IG: AGNES CG: Chat and coffee with the research team | Wellbeing (SPF-IL scale) | IG improved Affective dimension (p < 0.05) at post-test. IG improved Affective dimension 8.92 (SD: 1.93) and 10.20 (SD: 1.44), at pre- and post-test, respectively. |
Lara 2016 UK | RCT, 8 weeks | Workplaces in Northeast England n = 75 mean age: 61 (SD: 4) Female/male: IG: 38/12 CG: 19/6 | Web-based intervention (LEAP) IG: LEAP CG: use NHS choices website, UK Department of Health | Physical activity Mediterranean diet (MD adherence) | Both IG and CG improved outcomes and no significant differences were detected. |
Wijsman 2013 Netherlands Related publications: Vroege, 2014, Broekhuizen, 2016 | RCT, 3 months | Community in Leiden n = 235 age range: 60–70 Mean age GI: 64.7 (SD: 3.0) CG: 64.9 (SD:2.8) Female/male IG:47/72 CG: 49/67 | Internet-Based Physical Activity Intervention: Philips DirectLife IG: Philips DirectLife CG: No intervention | Physical activity Moderate-to-vigorous physical activity (MVPA) Metabolic parameters Quality of life (RAND-36) | IG improved PA, weight, waist circumference, Insulin and HbA1c) (p < 0.001), and MVPA (p < 0.001). IG improved emotional and mental health (p < 0.03) and health change (p < 0.01) |
Homma 2016 Japan | Pilot RCT, 3 months | Two districts of Kurihara city n = 68 Mean age: IG: 65.1 GC: 67.2 Female/male: IG: 22/13 CG: 22/11 | IG: Videophone group (interactive interviews) CG: Document group (printed communication) Telemonitoring of health conducted in both groups | Physical activity Behavioral change self-assessment (PA and Diet), Clinical parameters (body weight, BMI, blood pressure, albumin). Perceived health condition and improved lifestyle | Both CG and IG improved average step per day: CG: 5046 vs. 5992 (p < 0.01): IG: 5829 vs. 7324 (p < 0.01); between group (p = 0.16). IG improved behavioral change for: PA (p: 0.004), diet (p: 0.002), and change in lifestyles (p: 0.005). IG improved significantly in most clinical parameters such as blood pressure, HbA1c, albumin, BMI. IG perceived higher improvement in health condition and lifestyle (72.7% vs. 97.1% (p < 0.01) |
Legend: CG control group, IG1 intervention group 1, IG2 intervention group 2, IG3 intervention group 3, IG4 intervention group 4. |
When appraising the quality of the retained studies, we first noted that great variation existed with regard to sample size with a minimum of 14 and a maximum of 1729 participants. Seven studies had small samples (n < 100) ― for a total number of 3645 participants aged between 50 and 88 years old. Also, in the majority of studies, the samples comprised more women than men. Second, as shown in Fig. 2, the risk of bias was moderate to high across the studies, but the source of bias was varying. The blinding (participants, personnel or outcomes assessor) bias was present at a high risk or unclear in most studies. Sequence generation and allocation concealment were variable among the studies, which means that the potential selection biases were foreseeable in half of the studies. Finally, potential risk of bias related to incomplete outcome data and selective outcome was low in a large majority of studies, meaning that there was a low risk of reporting bias. We also noted the use of a wide range of validated questionnaires (such as: Quality of life: RAND 36, Physical and Psychological well-being: SF-36; Wellbeing: SPF-IL scale) and non-validated rating scales (such as: behavioral change self-assessment, IT literacy, engagement in activity) to assess the impact of the interventions.
Focus area of the technology
All the included study interventions were primarily internet-based. These interventions were often compared with either paper-based interventions, interventions with a videophone component, mixed intervention; tailored or not. The technology devices that were part of the interventions consisted mainly of computers, tablets or mobile phones. In reference to the Center for Technology and Aging classification (37), three areas are represented in this systematic review: remote patient monitoring, remote training and supervision, and social networking. One study consisted of an educational program with telemonitoring of step count, blood pressure and body weight (51). Most studies aimed to detect, train and supervise patient remotely. One intervention was personalized with participants’ information provided during the use of the web-based intervention (52), other interventions included information provision to increase daily physical activity (49, 50), or through a Web site with a tailored advice to undertake strength and balance training (46). Finally, two studies evaluated social networking: one focused on Facebook with the use of an online diary (53), the second on an ICT-mediated social network (41).
As for the remaining studies, Cook et al. (24) focused more widely on health promotion goals (diet, physical activity, stress, tobacco use), whereas Slegers et al. (48) and van het Reve et al. (49) focused on computer training and internet usage. Lastly, Homma et al. (51) focused on information technology literacy.
With respect to the outcomes, the majority of included studies (11/14) focused on physical activity (PA) (24, 42-47, 49-52) with some focusing on the effect of physical activity on metabolic health and quality of life (50, 51) and another covering increasing healthy behavior (24). The three other e-Health interventions targeted multiple dimensions including cognitive function, wellbeing, social engagement or connections, quality of life or lifestyle modification (41, 48, 53).
Effects of e-Health on physical outcomes
Peels et al., comparing paper-based and web-based intervention on physical activity (PA), concluded that the former was effective in increasing weekly days of sufficient PA (p=0.005) at baseline and 6 months later (p=0.042) (47). Conversely, on the process outcomes the printed group significantly performed better in reading (92.7–98.2%), keeping (70.1–76.5%), and discussing (39.9–56.8%) the advices received. Furthermore, the printed intervention was better appreciated than the web-based intervention (scores 6.06–6.91 versus 5.05–6.11, respectively on a scale of 1–10) (47). In similar vein, Irvine et al. showed that a web-based intervention to promote PA improved 13 of the 14 outcome measures and the intervention group maintained large gains on all 14 outcomes measured at 6 months (42). In the Mouton 2015 study, a mixed intervention (center- and web-based intervention) led to improvement in PA level (p=0.041), readiness for PA (p=0.001), and improved the awareness of PA (p=0.003) (45).
Using a tablet intervention, van het Reve et al. (49) showed improvement in physical performance for all groups (p: 0.02) compared to the brochure group in the single and dual task walking (p=0.03), as well as the falls efficacy (p=0.04) (van Het Reve et al., 2014a). In a trial using text messaging, Kim & Glanz contended that motivational text messaging (3 times/week) increases step count (679 vs. 398, p < 0.05) as well as perceived activity level (p < 0.05) (43).
In a trial testing the addition of a monetary incentive to an Internet intervention, Kurti & Dallery concluded to a higher percentage of goals achieved (87%) in the group that received the monetary motivation (44). Likewise, an internet-based moderate-to-vigorous PA intervention of Wijsman et al. (50) led to a significant improvement of weight and waist circumference (p=0.001). Finally, Homma et al. (51) reported an improvement in steps per day for both videophone intervention (interactive communication) and document groups (p < 0.01), although only the former group significantly improved in clinical parameters, such as body mass index (BMI) (51).
In addition, the study of Wijsman et al. comparing Internet-based PA intervention versus no intervention, concluded to a significant improvement in clinical parameters, including insulin and HbA1c (p < 0.001), this for moderate-to-vigorous PA (p = 0.001) (50). Likewise, Homma et al. found significant improvements for blood pressure, HbA1c, and albumin when comparing videophone intervention group to document group (51).
Nevertheless, some studies were unable to find any significant difference in the physical outcomes targeted. For instance, Lara et al.’s pilot study showed weak and non-significant differences between both groups for physical outcomes (52). However, we should not conclude in the absence of effect for this intervention, as the study was not sufficiently powered.
Effects of e-Health on psychological outcomes
Regarding the psychological outcomes, in the Nyman et al. study (46), receiving a web-based tailored advice led to higher ratings of the advice relevance (p = 0.017) and goodness of fit of activities (p = 0.047). Besides, Wijsman et al. (50) demonstrated that the Internet-based PA intervention improved the emotional and mental health (p: 0.03) and health change (p < 0.01) in their measure of quality of life. In the Slegers et al. study, however, using computers and the internet did not influence everyday functioning, well-being and mood, nor the social network of healthy older individuals (48).
For their part, Ballesteros et al. found that an ICT-mediated social network improved the affective dimension of wellbeing in their quality of life scale at post-test (p < 0.05) (41). Similarly, Myhre et al.’s Facebook intervention has improved Knowledge (p < 0.01), Letter Memory task (p < 0.01) as well as Keep Track (p < 0.10) (53).
Effects of e-Health on behavioral outcomes
Cook et al. (24) showed that their web-based multimedia program (information and guidance) had a significant effect on diet behavioral change self-efficacy (p = 0.05), planning healthy eating (p = 0.03), eating practices (p = 0.03), exercise self-efficacy (p = 0.03), exercise planning (p = 0.03), and aging beliefs (p = 0.01). Moreover, Homma et al. (51) showed a significant positive change in self-assessment of PA (p = 0.004), diet (p = 0.002), and lifestyles (p = 0.005). Participant satisfaction using IT-related devices was significantly higher in the intervention (videophone) group than in the control group (printed documents) (40% vs 15%).