A total of 20 reviews reported findings on diet behaviors or a weight loss outcome that resulted from an intervention that only targeted diet. The breakdown of their characteristics is shown in Table S1.

The effectiveness of digital interventions in improving results related to diet was at best mixed, for both behavioral and health outcomes (Table 3); where improvements were reported, the effect sizes were typically small. This was the case across all modes of delivery.

Of the 6 reviews covering internet interventions, 2 meta-analyses found small, favorable effects of internet interventions on dietary behavior, Cohen d=0.223 [110] and Cohen d+=0.20 [113]. A total of 4 narrative syntheses found mixed results with heterogeneous target outcomes [63,99,100,108]. The most common dietary target across the studies was fruit intake, which increased by approximately 1 serving per day [99].

Across 6 reviews of mobile interventions, there was some evidence of positive effects on dietary behaviors, especially fruit and vegetable intake, but no statistically significant effects on weight loss [21,23,60,99,104,111]. One of these reviews [99] reported a previous systematic review (not covered in this paper) that found no significant change in calorie intake or the consumption of sugar-sweetened beverages in 4 trials evaluating diet.

A total of 3 social media reviews had mixed findings on dietary outcomes, such as fruit and vegetable intake and fat intake, but the 2 reviews with meta-analyses found no differences in weight [65,75].

The effects of interactive computer interventions were equivocal and not clinically significant [22,74].

There was little evidence about the effectiveness of digital interventions on diet compared with no intervention or minimal intervention controls, and the available evidence was mixed (Table 3). One meta-analysis found small effects on fruit and vegetable intake (g=0.16) and dietary fat reduction (g=0.22) [109], but another meta-analysis found no statistically significant effects on dietary behaviors [73].

The relative effectiveness of digital interventions on diet compared with active comparators was mixed, with approximately half of the studies or less in narrative syntheses, showing that digital interventions were effective compared with active controls (Table 3). This was true across all modes of delivery: internet [99], mobile [99,104], and combined interventions [99].

Reviews included studies that ranged from single-contact interventions to 5-year follow-ups (Table 3). Relatively few reviews reported on follow-ups; of those that did, about half reported follow-ups in the medium term (3-6 months) and half in the long term (≥12 months).

Where reported, digital interventions were generally found to be effective for over 3 to 6 months. Several reviews have found positive results at 6 months [20,21,74]. However, this finding is not universal [111].

Long-term findings were more mixed in the 5 reviews that investigated them. Two reviews suggested promising effects at 12 months [108] and 18 months [20]. However, 3 reviews found no significant effects at 12 months [22], 24 months [111], and 30 months [74].

We included the findings on physical activity–related outcomes from 45 systematic reviews. The breakdown of their characteristics is shown in Multimedia Appendix 6.

The effectiveness of digital interventions was mixed across all modes of delivery, apart from mobiles, for which the evidence was consistently positive (Table 4).

Evidence for the effectiveness of internet interventions on physical activity has been mixed. In total, 5 out of 10 reviews were positive [26,29,33,108,113], including 2 meta-analyses that found small but significant effects of internet interventions: Cohen d=0.14 [29] and Cohen d+=0.24 [113]. However, there was significant heterogeneity across studies [29]. In contrast, 5 studies were not positive [35,47,63,100,110], one of which was very unfavorable, with only 1 of 9 (11%) studies demonstrating an effect of the intervention [100]. Two meta-analyses found that the effect of internet interventions on physical activity was not significant [63,110].

A total of 4 reviews of social media interventions were mixed. In total, 2 meta-analyses of social media interventions found no significant difference in changes in physical activity [65,75], and a narrative synthesis reported mixed results [76]. However, one narrative synthesis found that 76% of studies using web-based social networks had positive results for physical activity [56].

The results of the mobile interventions to improve health were more positive. In total, 8 of 10 (80%) narrative syntheses reported a majority of positive results [25,27,31,39,41,42,60,99], with one reporting an increase of 800 to 1104 steps per day [25]. One review noted that effective interventions used SMS text messaging communication or self-monitoring [42]. A review that was specifically on SMS text messaging reported that effect sizes were all greater than 0.20, and the median was 0.50, a medium effect size [27]. In contrast, 2 narrative syntheses reported that most mobile trials did not show any benefits [61,111].

There was mixed evidence of active gaming across 3 reviews. One review found that gamification has a positive impact on physical activity and found evidence that gamification can increase motivation to exercise [37]. However, another review found a positive effect on attendance but not on physical activity or BMI [46]. A third review found that active gaming did not support increases in either physical activity or attendance [43].

Computer-delivered interventions in physical activity behaviors did not have consistent results in either weight loss or weight maintenance trials [74].

In total, 4 of the 5 reviews assessing a variety of interventions found favorable results [40,45,53,99]. One of the narrative syntheses reported a wide range of values for improvement, from 1.5 to 153 extra minutes of physical activity a week and 1000 to 2600 steps per day [99]. A meta-analysis found that computer, mobile, and wearable technology led to a mean change of −41.28 minutes per day of sitting time (a reduction in sitting time) [45]. However, one meta-analysis found no difference between the experimental and control groups [34].

Compared with minimal controls, evidence for the effectiveness of digital interventions has been mixed.

For internet interventions, one review found favorable evidence [39], another found unfavorable evidence [24], and a third found mixed evidence [36].

The 3 reviews of mobile interventions have also provided mixed evidence. One narrative synthesis found that interventions were effective, with 4 studies (3 pre-post and 1 comparative) reporting increases of 800 to 1104 steps per day [25]. However, another study found that mobile interventions were not effective in increasing physical activity of moderate-to-vigorous intensity or in decreasing sedentary behavior [30]. Wearables were also not very effective, with only 1 of 3 (33%) studies comparing a pedometer with a minimal control showing increased physical activity [32].

Social media–based interventions increased the daily number of steps taken by 1530 steps per day [49]. However, they were not associated with energy expenditure, total physical activity, or moderate-to-vigorous physical activity.

There were small effect sizes for both computer-delivered interventions (g=0.16) [109] and interactive voice response–based interventions (g=0.254) [73].

There were mixed results compared with active controls.

A meta-analysis of internet interventions found an increase in physical activity with an SMD of 0.25 compared with active controls [102].

In total, 3 reviews of mobile phones had active controls, and there were mixed results. A meta-analysis found that the use of a mobile phone app was associated with significant changes in body weight (−1.04 kg) and BMI (−0.43 kg/m²); however, there was no significant difference in physical activity between the 2 groups [38]. A narrative synthesis app was also not favorable for assessing changes in physical activity, with less than half of the studies showing a significant increase in physical activity in the intervention group [104]. However, another narrative synthesis of general mobile interventions found that most studies had interventions that led to changes in body weight, increases in step count, and increases in frequency of physical activity [44].

There were also promising results from a review on wearables: when an activity tracker is combined with a comprehensive weight loss program, it may provide superior short-term (≤6 months) results than a standard weight loss program in middle-aged or older adults (>30 years) [28].

There was little evidence on sustainability, as many physical activity studies did not have follow-up assessment postintervention or only had follow-ups relatively soon after the intervention end point.

There is some evidence that digital interventions can have sustained effects. A meta-analysis assessing combinations of digital technologies found that the pooled effects showed mean changes (reductions) at short (≤3 months), medium (3 to 6 months), and long-term follow-up (>6 months) of −42.42 minutes per day, −37.23 minutes per day, and −1.65 minutes per day, respectively [45]. A meta-analysis of internet interventions also found a small but significant effect on physical activity for follow-ups at least six months postintervention (Cohen d=0.11) [29]. The sustainability of internet interventions was also supported by a narrative synthesis that found that only 12 of 35 (34%) studies had follow-up assessments, which ranged from 7 weeks to 15 months postprogram; 10 out of 12 (83%) studies demonstrated successful maintenance of physical activity and/or secondary measures indicative of positive changes in physical activity; however, follow-up durations were primarily shorter: in 9 studies, follow-up was conducted at less than 12 months [26]. However, for mobile interventions, 2 reviews found evidence that effects tended to decrease in the long term [31], with effects disappearing after as little as 12 weeks [44].

A total of 35 reviews reported on both diet and physical activity. The breakdown of their characteristics is shown in Multimedia Appendix 6.

Overall, digital interventions were generally found to be effective, with mobile phone interventions in particular having consistently positive results (Table 5).

Internet interventions were found to be somewhat effective. A total of 5 narrative syntheses found them to be effective in approximately half of the studies [47,62,99,100,108]. In total, 3 meta-analyses quantified weight loss and other health effects. A total of 3 reviews found a significant reduction in weight: mean difference –1.34 kg [102], SMD 2.13 kg [70], and a 0.68-kg additional weight reduction over a period of 3 to 30 months [99]. A fourth review found that internet interventions significantly reduced waist circumference (mean change −2.99 cm) [69]. However, stratified analysis suggested that internet interventions were effective when used in combination with in-person counseling (−1.93 kg), rather than as a substitute [98]. This finding was supported by a narrative synthesis, which reported that internet interventions were more effective when they were enhanced to offer more than just educational resources (several studies found medium effect sizes) [62].

There were mixed results regarding the effectiveness of social media interventions. A total of 2 reviews were favorable [49,56], including a meta-analysis that found that social media–based interventions reduced body weight by 1.01 kg, BMI by 0.92 kg/m², and waist circumference by 2.65 cm but did not find significant changes in body fat or body fat percentage [49]. A total of 2 narrative syntheses found effects that were small and not meaningful [61,76]. Two meta-analyses found no significant effects on the diverse primary outcomes of the studies or on body weight [65,75].

Most reviews of mobile phone interventions found that they were effective in achieving weight loss via diet and physical activity. One meta-analysis found a statistically significant medium effect size (Cohen d=0.430) in favor of mobile phone interventions [60]. Two others quantified the change in terms of body weight: mobile phone interventions were associated with significant changes in body weight of −1.44 kg and in BMI of −0.24 kg/m² compared with controls [59]; the weighted mean body weight change in intervention participants was −2.56 kg compared with −0.37 kg in controls [71]. These results were supported by 3 narrative syntheses, which found evidence that mobile interventions led to weight loss [50,68,99]. However, one review of apps to promote healthy lifestyles found that most trials did not show significant differences [104], and one of the reviews that looked at the use of apps for diet, physical activity, and sedentary behavior, which concluded that apps led to weight loss, also concluded that the apps were more successful when used alongside other intervention components than when used alone [68].

In total, 4 of 5 narrative syntheses that ranged over a variety of digital interventions found that around half of the interventions were effective compared with controls [48,51,53,54], with only one finding that a large majority (81%) reported a significant reduction in adiposity [99]. One of these studies found that most trials reported within-group weight loss, even when there was no difference between digital interventions and controls [54]. Another study compared the success of different modes of delivery, finding the highest proportion of successful trials involving SMS text messaging or email (67%), followed by online chat rooms (50%), web-based (48%), and self-monitoring with technology (43%) [48].

A total of 6 reviews that reported results for digital interventions for diet and physical activity to no intervention or minimal intervention controls all agreed that digital interventions were more effective [66,67,69,70,72,74]. Table 5 provides a summary of the results.

Internet interventions were more effective than nonactive controls according to 3 meta-analyses and 1 narrative synthesis [67,69,70,72]. Internet interventions led to a greater reduction in waist circumference (mean change –2.99 cm, 95% CI −3.68 to −2.30, I2=93.3% vs 2.38 cm, 95% CI 1.61 to 3.25, I2=97.2%) [69]; internet-delivered personal feedback led to greater weight loss (mean difference 2.14 kg) [70]; and self-directed internet interventions led to significantly more weight loss (mean difference −1.56 kg) and showed a significantly greater reduction in BMI (mean difference −0.41 kg/m²) [72].

Similar effects were observed for computer-based interventions, which led to greater weight loss at 6 months (mean difference −1.5 kg) and were superior to limiting weight regain (mean difference −0.7 kg) [74].

A narrative review of tailored internet interventions found that effect sizes ranged from very small to moderate [67]. This was supported by a meta-analysis that covered various digital interventions, which found small effect sizes favoring digital interventions for weight (g=0.34) and behavioral outcomes (g=0.17) [66].

The effects of digital interventions on diet and physical activity (with regard to weight loss) compared with active controls were mixed. A total of 2 meta-analyses found no differences between web-based interventions and active offline interventions for weight loss outcomes [52,69]. One meta-analysis of a range of interventions found that standard active treatment was more effective for weight loss (g=0.31) [66]. However, one meta-analysis found that using the internet had a modest but significant additional weight loss effect compared with offline control groups (−0.68 kg; P=.03), with a subgroup analysis showing that the internet was effective compared with controls for achieving weight loss (weight change=−1.01 kg) but not weight maintenance [58]. The same meta-analysis also found that it was effective to use the internet as an adjunct to face-to-face care (−1 kg; P<.001) but that adverse effects on weight loss were found when it was used as a substitute (+1.27 kg; P=.01) [58].

Computer-based interventions led to less weight loss than in-person treatment (mean difference 2.1 kg) and were not superior to infrequent in-person treatment in limiting weight regain at 6 months [74].

Although technology-related health interventions may be effective, the maintenance of behavior is challenging [64], and there is insufficient evidence to determine the effectiveness of digital interventions on weight maintenance [54]. One review of internet interventions reported that, in studies finding significant weight reduction, the magnitude of weight change ranged from 1 to 6 kg after 6 months of follow-up [99].

Many studies included in the reviews had short follow-ups. Where longer follow-ups were reported, effectiveness typically diminished over time. Examples of the diminishing effects are clear in the 2 reviews. One meta-analysis of internet-delivered personal feedback found a greater reduction in BMI (mean difference 0.54 kg/m²) and waist circumference (2.81 cm) at 0 to 4 months follow-up than at later times compared with undefined control groups [72]. A narrative synthesis supports these findings, concluding from multiple high-quality randomized controlled trials (RCTs) that weight loss occurs for a short term through mobile interventions, with moderate evidence for the medium term [50]. Two other meta-analyses reported significantly greater weight loss in favor of digital interventions in the medium term only (<6 months): 2.13 kg [52] and 1.55 kg [58]. One meta-analysis assessed differences between trials of different lengths, reporting no differences between shorter and longer trials (<6 or ≥6 months) [59].

There were 28 reviews on smoking (see Multimedia Appendix 6 for summary characteristics).

Digital interventions were generally effective across different modes of delivery (Table 6).

Internet interventions were generally found to be effective (Table 6). A total of 3 relevant meta-analyses found small or small-to-medium effects [85,89,91]: pooled RR 1.39 [85]; RR 1.40 [92], and RR 1.43 [88] and a short-term (≤6 months) OR 1.29 (95% CI 1.12 to 1.50; P=.001) [91]; the latter showed that internet interventions were also successful for the individual outcomes of prolonged abstinence, that is, not smoking since a quit date (OR 1.43) and 30-day point prevalence abstinence, that is, not smoking one or more days before the follow-up (OR 1.75) [91]. However, one narrative synthesis noted that although the 3 studies that measured smoking cessation all showed significant intervention effects, they were all assessed to be of low quality [100].

The 3 reviews of mobile interventions that focused on SMS text messaging found it to be effective, again with small effects: Cohen d=0.14 [94]; OR 1.36 [96]; and OR 1.36 [98]. A fourth meta-analysis differentiated between specific outcomes and found a medium effect (RR 2.19) on biochemically verified continuous abstinence, and a small-to-medium effect (RR 1.51) on verified 7-day point prevalence of smoking cessation was pooled [111]. However, 2 reviews (including 1 meta-analysis) with information on mobile interventions in general did not find that they were effective [89,99].

A meta-analysis of computer-delivered interventions also found a small but significant effect size associated with studies addressing tobacco use (Cohen d=0.14) [112].

There is mixed evidence from reviews that cover a variety of digital technologies. One narrative synthesis [99] and one meta-analysis found that they were effective, with interventions increasing the odds of smoking cessation at 1 month (OR 1.70) [83]. However, another narrative synthesis that included both phone and internet interventions found that there were mixed results [86].

A total of 2 reviews of social media interventions with narrative syntheses both found favorable effects of the interventions on outcomes related to smoking cessation [56,93].

As seen above, separate reviews of internet, mobile, and computer-delivered interventions found small effects for each. One meta-analysis looked for differences in effect sizes between different modes of intervention and found no statistically significant evidence of any differences in effect sizes of internet interventions, intensive advice, telephone support, individual counseling, or group behavior therapy [89].

There were small effects of digital interventions compared with nonactive controls for all modes of delivery (Table 6). Meta-analyses found small effects for pooled modes of digital interventions compared with controls: 1 month OR 1.70 (k=13) [83]; pooled estimate for prolonged abstinence, RR 1.32 (k=60) [84], and pooled estimate for point prevalence abstinence, RR 1.14 [84]. Internet interventions were more effective than nonactive controls [88-90,92,97], with 3 meta-analyses finding small effects compared with nonactive controls: RR 1.15 [97], RR 1.46 [89], and RR 1.60 [88]. Computer-tailored interventions had effects sizes of g=0.16 for point prevalence outcomes and g=0.24 for prolonged abstinence [109]. Mobile phone–based interventions appeared to have similar effectiveness to minimal controls (RR 1.18) and were more effective than no intervention (typically either waiting list control or no further contact until follow-up) [89].

Most reviews concluded that internet interventions were not more effective than active controls, with 3 reviews (including 2 meta-analyses) not finding differences [88,90,97]. This included a meta-analysis that found no significant effects of internet interventions compared with face-to-face counseling or telephone counseling [88]. However, one narrative synthesis was more positive about the greater effect of internet interventions compared with conventional ones [99].

There was no information on mobile interventions compared with active controls, but one meta-analysis with mixed controls noted that the summary effect sizes favored the treatment groups even when 18 of the 20 (90%) controlled trials used an active control and 12 (66%) of these active controls included some smoking-related content, including smoke-free websites, self-help guidebooks, and smartphone apps [94].

There was agreement that the effects of internet interventions were sustained for up to 6 months [83,87,91,95]. This was quantified as interventions increasing the 6-month abstinence by 17% [95], increasing the odds of cessation at the 6-month follow-up (OR 1.29) [83], and increasing the likelihood of prolonged abstinence (ie, not smoking since a quit date; OR 1.19) [91]. However, there was disagreement about whether there were significant effects at 12-month follow-ups, with 2 reviews in favor [87,89], one quantifying the quit rate at 12 months as 8% [89] but another reporting that the positive results of internet interventions were not generally maintained at 1-year follow-up assessments [103].

There is mixed evidence on the sustainability of the effects of mobile interventions. A total of 2 meta-analyses found that mobile interventions were effective in the medium term, with a quit rate of 13% [89] and effects on biochemical measures of quitting at 6 months (RR 1.83) [98]. However, a study of SMS text messages suggested that any effect was not sustained [96].

Regarding computer-delivered interventions, one meta-analysis found that computer programs increased the odds of cessation at the 3-month (OR 2.04), 12-month (OR 1.68), and 18-month follow-up (OR 1.83) [83]. A meta-analysis of computer-delivered interventions did not find evidence of differential effects depending on the length of follow-up or number of sessions [112].

A total of 2 reviews that considered a range of different technologies found evidence of sustained effects. A narrative synthesis of internet and mobile interventions found that the OR for 7-day abstinence at 6 months ranged from 1.6 to 2.7 [99]. A meta-analysis found that digital interventions increased the odds of smoking cessation at 3 months (OR 1.30), 6 months (OR 1.29), and 18 months (OR 1.83) postintervention [83].

In a pooled analysis of web-based and computer-based interventions, the smoking cessation rate was 14.8% in the intervention group and 14.3% in the control group at the short-term 3-month follow-up (P=.42), 11.7% and 7.0% at the midterm 6- to 10-month follow-up ( P<.001), and 9.9% and 5.7% at the long-term 12-month follow-up (P<.001), respectively [92].

One meta-analysis that covered multiple intervention types found that SMS text messaging had the highest OR (2.81) at the 1-month follow-up, followed by the use of computer programs at the 3-month follow-up (OR 2.04), 12-month follow-up (OR 1.68), and 18-month follow-up (OR 1.83) and websites at 6 months (OR 1.37), while a DVD intervention and integrated videotelephony did not increase the odds of cessation compared with no intervention [83].

In total, 7 of 8 (88%) reviews with mixed controls reported favorable evidence that digital interventions were effective in decreasing alcohol consumption (Table 7), although one review noted that the controls were just as effective [103]. A total of 2 meta-analyses reported small effect sizes (Cohen d=0.26 [112] and Cohen d=0.14 [113]). A narrative synthesis of interventions using novel technologies found that, in studies finding benefits and reporting compliance with drinking recommendation as an outcome, the OR for drinking within the recommended limit ranged from 1.7 to 3.7 (small/medium to medium/large effects) [99]. In contrast, the sixth review, which surveyed mobile phone interventions, reported that the results were inconclusive for alcohol reduction, and the authors declined to perform a meta-analysis because the results were self-reported and therefore at risk of overstating the benefits [111].

In total, 4 of 6 (67%) reviews with nonactive controls found an effect of the intervention (Table 7). Of the 4 meta-analyses, 2 found a medium effect on alcohol consumption (g=0.44 [80] and g=0.44 [79]). A third found a small-to-medium effect on total alcohol consumption (Cohen d+=0.31), small effects on 2 other consumption measures, and a measure of frequency of heavy drinking episodes (Cohen d+=0.16-0.19) and no effect on drinking frequency [82]. The fourth review found no effect [73].

Two studies quantified the effect on alcohol consumption, finding a reduction in weekly consumption of 22 g of alcohol [80] and 23 g of alcohol [77], approximately 3 UK units. However, when studies with a high risk of bias were excluded, this number decreased to 11 g of alcohol (or 1.5 UK units) per week [77]. With regard to frequency of consumption, participants who were given digital interventions had less than one drinking day per month, which is fewer compared with no-intervention controls (moderate-quality evidence); had approximately 1 binge-drinking session less per month in the intervention group compared with no-intervention controls (moderate-quality evidence); and drank 1 unit per occasion, which is less than the no-intervention control participants (moderate-quality evidence) [77]. Participants in internet interventions were significantly more likely to adhere to low-risk drinking guidelines at the immediate posttreatment follow-up, compared with the no-intervention controls [80].

Only one review was negative. A narrative synthesis of mobile apps reported that there was a single RCT on alcohol reduction where, contrary to expectation, the frequency of drinking occasions was higher in the intervention group [104].

In total, 2 reviews that separated active controls found that there were no significant differences between the intervention and control groups [77,99], one of which was specifically compared with face-to-face controls (Table 7) [77].

The effectiveness of the interventions seemed to decrease over time (Table 7). One meta-analysis, which reported small-to-medium effects in the short term (Cohen d+=0.16-0.19), found that in the medium to long term, there were small (Cohen d+=0.07-0.12), significant effects on all outcomes [82]. A total of 2 reviews reported that, for internet-based intervention studies where there were 3-, 6-, or 12-month follow-up data, no significant differences in effect remained in later follow-up [80,103]. In contrast, one review of computer- or mobile-delivered interventions found that positive differences in measures of drinking were seen at 1, 6, and 12 months [77], and one review of internet interventions found a medium effect size (g=0.39), lasting up to 6 or 9 months posttreatment, as compared with no intervention; the effects of the interventions beyond 9 months could not be assessed, but 2 studies in the review suggested that they had faded out by 12 months [79].

A total of 11 reviews covered a number of areas of behavior [101-107,109,110,112,113]. The breakdown of their characteristics is shown in Multimedia Appendix 5.

All 5 reviews of internet interventions concluded that they were effective in changing behavior (Table 8). A total of 3 meta-analyses found small effects: Cohen d=0.19 [105], Cohen d=0.139 [110], and Cohen d=0.16 [113]. However, one study reported that the effect sizes were heterogeneous [113]. The fourth meta-analysis quantified the effects on health outcomes, finding statistically significant reductions in systolic blood pressure (mean difference –2.66 mm Hg), diastolic blood pressure (mean difference –1.26 mm Hg), glycated hemoglobin level (mean difference –0.13%), and low-density lipoprotein cholesterol level (mean difference –2.18 mg/dL) [102].

Of the 3 reviews of mobile interventions, a review of SMS text messaging concluded that they were effective, but the narrative synthesis of apps was the only review in the other combinations category that did not find a preponderance of positive results [104]. The effect sizes for the SMS text messaging interventions were small (Cohen d=0.24 [101] and Cohen d=0.329 [107]), and the effect sizes in the meta-analysis were heterogeneous [107].

Other modes of intervention continued in the pattern of positive, albeit small, effects. Computer-delivered interventions had a small effect (Cohen d=0.20) [112]. Prompts delivered by SMS text messaging or email were effective in changing diet, physical activity, and smoking behaviors [106].

A total of 3 meta-analyses that compared interventions targeting single versus multiple areas of behaviors found that both types of interventions were effective but they differed in whether they found interventions with single or multiple targets to be more effective. A total of 2 meta-analyses of internet-based interventions found that the effect size of interventions targeting a single area of health behavior was not significantly different to the effect size of those targeting multiple areas of health behaviors, but the numerical difference was in favor of single-area studies (Cohen d=0.146 vs Cohen d=0.121 for multiple-behavior studies [110]; Cohen d+=0.17 vs Cohen d+=0.12 [113]). However, the computer feedback–based meta-analysis found a trend for increased effect sizes across studies that intervened in 1 (g=0.15), 2 (g=0.21), and 3 (g=0.24) areas of behavior, but this trend did not continue with the one study that intervened in 4 areas (g=0.12) [109]. The review covered diet, physical activity, smoking cessation, and mammography.

The review of SMS text messaging interventions found that interventions targeting smoking cessation and physical activity were more successful than interventions targeting other areas of health behavior, including alcohol and weight loss [107]. In contrast, a review of computer-delivered interventions found that interventions targeting smoking had statistically significantly lower effect sizes than those targeting alcohol (Cohen d=0.26 and 0.12, respectively) [112].

Digital interventions had their largest effect sizes when compared with nonactive controls; however, the effect sizes were generally small. Internet interventions had the largest effect size when compared with waitlists and placebos, but the effect sizes were small: Cohen d=0.28 [105] and Cohen d=0.22 [107]. Tailored websites had extremely small effect sizes when compared with no-treatment control conditions (Cohen d=0.07), and the effects were not statistically significant compared with nontailored print materials [110]. There were medium effect sizes for SMS text messaging interventions that employed no-treatment control groups (Cohen d=0.369) [107].

The effects of digital interventions compared with active controls were very small or nonexistent.

A total of 2 meta-analyses found that there was an extremely small effect size (Cohen d=0.08) [110] or no significant difference [105] when internet-based interventions were compared with sophisticated print interventions. There were larger effects in internet-based interventions that combined internet application with human support (blended care) [102]. Computer-delivered interventions had very small effect sizes when the comparison condition was an active comparison (Cohen d=0.10); studies employing active treatments as the comparison condition mainly produced effect sizes close to zero [112]. SMS text messaging interventions had small effect sizes compared with active comparisons (Cohen d=0.226), which was statistically significantly smaller than their effect size compared with the no-treatment control groups [107].

Although digital feedback was effective, it seems that it was no more effective than feedback delivered by nondigital means, and 2 reviews that examined feedback interventions found that the medium did not affect behavior change (SMS text messaging, print, email, telephone, newspaper articles [106] and print, computer, telephone, etc [109]).

There was mixed evidence on the sustainability of interventions. A meta-analysis of internet-based interventions found the largest effect size at 1 month to 4 months [105], but a meta-analysis of computer-tailored interventions found that effects peaked from 4 months to 12 months postbaseline [109]. A total of 3 meta-analyses found that the correlation between effect size and follow-up was not significant for internet-based [110], SMS text messaging [107], or computer-delivered interventions [112].

The effects did seem to decline in the long run, and the 2 meta-analyses that explicitly examined effectiveness 1 year postintervention (for internet-based and computer-delivered interventions) found that the effect size declined, although it remained statistically significant [102,109].