Information Technology and Lifestyle: A Systematic Evaluation of Internet and Mobile Interventions for Improving Diet, Physical Activity, Obesity, Tobacco, and Alcohol Use
Background Novel interventions are needed to improve lifestyle and prevent noncommunicable diseases, the leading cause of death and disability globally. This study aimed to systematically review, synthesize, and grade scientific evidence on effectiveness of novel information and communication technology to reduce noncommunicable disease risk.
Methods and Results We systematically searched PubMed for studies evaluating the effect of Internet, mobile phone, personal sensors, or stand‐alone computer software on diet, physical activity, adiposity, tobacco, or alcohol use. We included all interventional and prospective observational studies conducted among generally healthy adults published between January 1990 and November 2013. American Heart Association criteria were used to evaluate and grade the strength of evidence. From 8654 abstracts, 224 relevant reports were identified. Internet and mobile interventions were most common. Internet interventions improved diet (N=20 studies) (Class IIa A), physical activity (N=33), adiposity (N=35), tobacco (N=22), and excess alcohol (N=47) (Class I A each). Mobile interventions improved physical activity (N=6) and adiposity (N=3) (Class I A each). Evidence limitations included relatively brief durations (generally <6 months, nearly always <1 year), heterogeneity in intervention content and intensity, and limited representation from middle/low‐income countries.
Conclusions Internet and mobile interventions improve important lifestyle behaviors up to 1 year. This systematic review supports the need for long‐term interventions to evaluate sustainability.
Noncommunicable diseases (NCDs) are the leading cause of mortality and morbidity globally, accounting for 65% of deaths and 54% of disability‐adjusted life‐years in 2010.1, 2 Suboptimal lifestyle is the major cause of NCDs, including poor diet, physical inactivity, tobacco, adiposity, and excess alcohol.2 Clearly, novel interventions to improve lifestyle and prevent NCDs are urgently required. In recent years, the evidence for effectiveness of conventional clinic‐based education3 and policy4 approaches to improve lifestyle has been systematically evaluated. In comparison, the effectiveness of more novel information and communication technologies, such as Internet and mobile applications, to improve lifestyle is not well established. Such technologies are particularly promising because of potential for scalability, low cost, use in multiple settings including middle‐ and low‐income nations, and opportunities for real‐time modifications and improvements. Numerous small trials have been reported, but their findings have not been systematically reviewed.
To understand and compare the effectiveness of novel technologies for behavior change across diverse lifestyle targets, we systematically investigated, summarized, and graded the evidence for effectiveness of such interventions to improve diet, adiposity, tobacco, physical inactivity, and excess alcohol.
Search Strategy and Study Selection
Following Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines, we systematically searched PubMed for all interventional trials (randomized, quasi‐experimental) and prospective observational cohorts evaluating the effect of novel information and communication technologies on diet habits, adiposity, physical inactivity, tobacco (ie, smoking cessation), and excess alcohol among adults. Eligible technologies included those based on Internet, mobile (text messages, cellphone calls, smartphone apps), personal digital assistant, and social media applications, as well personal sensors (eg, pedometers, accelerometers). The full search strategy including search terms is provided in Datas S1 through S4.
Studies were excluded if cross‐sectional, ecological, or lab experiments (hypothetical situations); conducted among people with underlying prevalent disease related to the study outcome (eg, cardiovascular disease, except diabetes); only evaluating intervention feasibility or acceptability; or only evaluating changes in knowledge, awareness, or attitude. We also excluded studies with fewer than 50 subjects, or duration <1 week. Additionally, we excluded studies published prior to 1990 (because of our focus on novel technologies) or conducted only among children (because of our focus on NCDs). For diet and adiposity, our searches identified several prior systematic reviews on information and communication technologies; for these targets, we included prior identified investigations and searched for additional original articles published after the time period of search of these reports (after January 2011). Titles and abstracts of all identified articles were screened by 1 investigator; and full texts were reviewed by 1 investigator after 10% of the articles were reviewed independently and in duplicate by 2 investigators until 100% concordance was achieved.
Using a standardized electronic format, data were extracted by 1 investigator on first author name, publication year, study location, design, population characteristics (sample size, age, race, sex, education), intervention characteristics (description, components, duration), study outcomes (description, assessment method), and intervention effectiveness (effect measure, uncertainty estimates). To ensure accuracy and quality of data extraction, data from 10% of studies were extracted by 2 investigators in independently and in duplicate.
Assessment of Effectiveness
In some studies, the technology intervention was compared to usual care or minimal intervention (eg, printed leaflets); and in other studies, to intensive, non‐technology‐based, behavioral interventions (eg, standard‐of care clinical counseling). Thus, the various “control groups” received mixed interventions with varying degrees of intensity. For studies including a usual care or minimal intervention control group, intervention effectiveness was evaluated by comparing the change in lifestyle target between the 2 groups. These studies provide direct evidence for effectiveness of the intervention, compared to usual care.
For studies having a control group receiving more intensive behavioral interventions (and for quasi‐experimental studies with no control), we evaluated intervention effectiveness based on change in the target lifestyle from pre‐ to postintervention within the intervention group. This provides better comparability of findings to studies with minimal intervention controls. However, because such results could be confounded by participation (Hawthorne effect), we also reviewed and summarized the findings from the comparison groups whenever relevant.
We generally separately evaluated each lifestyle target. Because many studies jointly evaluated diet and adiposity, these 2 lifestyle targets were considered and reviewed together.
Two investigators reviewed and graded the evidence independently and in duplicate, based on the American Heart Association criteria for evidence grading (Table 1).5 Briefly, Class of recommendation (I, IIa, IIb, III) was determined based on the consistency of evidence for benefits and effectiveness of the intervention; and Level of evidence (A, B, C) was determined based on the number and types of studies (eg, clinical trials, nonrandomized studies) used to assess the intervention.
This study did not meet the definition of human subjects research because no identifiable private information was obtained for this research.
Diet and Adiposity
Of 3602 abstracts screened, 65 original articles met inclusion criteria (Figure 1). These included 47 randomized controlled trials (RCTs) and 18 quasi‐experimental studies. Thirty‐seven studies were conducted in the United States; 26 in other high‐income countries (Australia, United Kingdom, New Zealand, Belgium, The Netherlands, Austria, Korea, Japan, Germany); and 2 in middle‐income countries (Iran, Brazil).6 Settings included community, worksite, university/college, hospital/clinic, church, health club, and online populations. Study durations ranged from 1 week (examining effects of an Internet intervention on fruit intake7) to 37 months (examining effects of an Internet intervention on weight loss).8 Most studies had durations between 6 weeks and 6 months; only 10 studies had durations >1 year. Details on the intervention strategies and dietary and adiposity outcomes are provided in Table 2.
We also identified 5 prior systematic reviews evaluating relevant studies published prior to January 2011, each including from 7 to 36 studies.9, 10, 11, 12, 13 Table 3 summarizes the characteristics and findings of these reviews.
Of 35 studies (22 RCTs, 13 quasi‐experimental) assessing Internet interventions and adiposity, 24 (69%) reported significant improvements following the intervention (Table 2). Findings were similar, limited only to RCTs, with reduced adiposity in 13 of 22 (59%) trials. In studies reporting significant weight reduction, the magnitude of weight change ranged from 1 to 6 kg after 6 months of follow‐up. Of 9 studies comparing Internet interventions with higher intensity conventional interventions (rather than usual care/minimal intervention), 4 reported significantly higher weight reduction in the Internet intervention group, 4 showed both interventions were equally effective in reducing adiposity, and 1 showed no significant effect in either of the intervention groups. In a meta‐analysis of 23 RCTs evaluating the effect of the Internet component of weight loss programs, using the Internet resulted in 0.68 kg (95% CI: 0.08, 1.29 kg) additional weight reduction over a period of 3 to 30 months.9 However, stratified analysis suggested that such interventions were effective when used in combination with in‐person counseling (−1.93 kg; 95% CI: −2.71, −1.15 kg), rather than as a substitute for that (−0.19 kg, 95% CI: −0.87, 0.49 kg).
Twenty studies (15 RCTs, 5 quasi‐experimental studies) evaluated Internet interventions and diet. Fourteen (10 RCTs and 4 quasi‐experimental; 70%) found significant dietary improvements following the intervention. Effect sizes varied due to heterogeneity in dietary targets. As an example, the intake of fruit, the most common dietary target across studies, increased by ≈1 serving/day. Five of these 20 studies compared Internet intervention with higher‐intensity conventional interventions: 2 showed significantly greater dietary effects in the Internet group, 2 showed both interventions were equally effective, and 1 showed no significant effect in either intervention arm.
Of 3 studies (2 RCTs, 1 quasi‐experimental) evaluating mobile interventions and adiposity, 2 found significant reductions in adiposity.14, 15 Two RCTs assessed mobile‐based interventions and fruit/vegetable intake; each found significant improvement (by 2 and 4 servings/day)14, 16 One of these compared a mobile intervention to an established conventional intervention, finding a greater effect in the mobile intervention group.14 In a prior systematic review of 14 mobile trials (2007–2010) focused on text messages and lasting from 2 weeks to 12 months (Table 3), 11 studies reported significant improvements in weight loss–related outcomes, whereas no significant change was reported in calorie intake or consumption of sugar‐sweetened beverages in 4 trials evaluating diet.10
Fourteen RCTs and 2 quasi‐experimental studies evaluated combined Internet/mobile interventions and adiposity. Most (13 of 16, 81%) reported significant reduction in adiposity. Of 6 studies that compared combined interventions with conventional interventions, 4 reported significantly higher effect on adiposity in the combined intervention group. Of 5 RCTs evaluating combined interventions and diet, 3 found significant improvement in dietary intake.17, 18, 19, 20 Of 2 studies assessing combined interventions and conventional interventions, 1 reported significantly higher effect on diet in the combined intervention group and 1 reported no effect in either intervention group.
Of 2855 abstracts screened, 55 RCTs and 16 quasi‐experimental studies were identified (Figure 2). Thirty‐three studies were from the United States, 35 from other high‐income countries (Australia, Austria, Belgium, Canada, Denmark, Finland, Germany, New Zealand, Norway, Scotland, Switzerland, The Netherlands, United Kingdom), and 3 from middle‐income countries (Brazil, Taiwan). Studies were conducted in different settings including worksites, colleges, hospitals, churches, and in online communities. Study durations ranged from 1 week to 5 years, with most lasting between 6 weeks and 6 months (Table 4).
Of the 33 Internet interventions (29 RCTs and 4 quasi‐experimental), 29 (88%) reported significant improvement in physical activity (Table 4). Among RCTs, 25 of 29 (86%) found improved physical activity after the intervention. Of 2 RCTs comparing Internet interventions with conventional interventions, 1 reported significantly higher physical activity among participants receiving the Internet intervention, and 1 reported no significant improvement in either of the intervention groups.
The measure and magnitude of effect sizes varied across the studies reporting statistically significant effects. For example, in studies evaluating total duration of physical activity, the effect size ranged from 1.5 to 153 minutes/week. The difference of 153 minutes was reported in a 6‐month study in which participants received immediate individually tailored computer‐generated motivational messages after completing a monthly online questionnaire.21 In studies evaluating frequency of physical activity, the effect sizes ranged from 1 to 1.2 days per week. In studies that used the odds ratio (OR) of meeting a physical activity recommendation as the effect measure, the effect sizes were between 1.3 and 1.5.
Nineteen studies (13 RCTs and 6 quasi‐experimental studies) evaluated personal sensor (pedometer) interventions alone or along with educational materials, classes, or behavioral change techniques including goal setting. Of these, 15 (79%) reported significant positive effects. In these studies, the increase in step count from baseline was between 900 and 4500 steps/day. Examples of other types of effect sizes reported include the following: 97 minutes/week increase in leisure‐time physical activity22; 32% reduction in percentage of sedentary participants23; 95 minutes/day reduction in sitting time24; and 2‐day per week increase in walking days.24 In general, studies that included behavioral change techniques were more effective. Of 5 RCTs that compared sensor interventions with conventional interventions, 2 reported significantly higher step counts and leisure walking with sensor interventions, 2 only found significant within‐group improvements (from baseline) in physical activity, and 1 reported no significant within‐ or between‐group difference in step count.
Six studies (5 RCTs and 1 quasi‐experimental) assessed mobile interventions: 3 text message interventions, 2 smartphone applications, and 1 automated voice response. Of these, 2 of 3 utilizing text messages and all interventions involving smartphone applications and automated voice response were effective.
Five RCTs and 5 quasi‐experimental studies evaluated combined interventions (eg, Internet and sensors). Of these, 7 (70%) demonstrated significant improvements: 5 reported increased step count (1000–2600 steps/day); 1, increased 7‐day walking (90 minutes/week)25; 1, increased odds of meeting physical activity recommendations (OR: 1.7).26
Of 1182 screened articles, 41 met inclusion criteria (Figure 3): 17 from the United States, 22 from other high‐income countries (United Kingdom, Australia, Germany, Norway, New Zealand, The Netherlands, Switzerland), and 2 from middle‐income nations (Turkey, Thailand). Study settings included worksites, academic institutions, communities, general clinical practice, and online populations. Primary outcomes were generally the prevalence of abstinence (eg, 7‐ or 30‐day abstinence) at different time‐points (eg, 1, 3, 6 months). Abstinence assessment methods ranged from self‐report (N=29 studies) to breath carbon monoxide (N=6) and salivary cotinine (N=3). Duration of interventions ranged from 4 weeks to 2 years, with only 4 studies lasting longer than 1 year (Table 5).
Of 22 studies (21 RCTs, 1 prospective cohort) assessing Internet interventions, 17 reported significant increase in abstinence (Table 5). In studies reporting benefits, the OR for 7‐day abstinence at 6 months ranged from 1.6 (95% CI: 1.1, 2.4) in an Internet worksite smoking cessation program in the United States to 2.7 (95% CI: 1.8, 4.0) utilizing email counseling in Switzerland. The OR did not consistently vary with longer durations of follow‐up, either within or between studies. Of 6 studies comparing Internet interventions with conventional interventions, 4 reported significantly greater effect in an Internet group and 2 reported significant within‐group changes with no significant difference between intervention arms.
Seven studies (6 RCTs, 1 quasi‐experimental) evaluated mobile phone text‐messaging smoking cessation programs. Of these, only 2 (29%) reported benefits with OR of 7‐day abstinence ranging from 1.3 (95% CI: 1.2, 1.5) in a UK‐based study to 2.2 (95% CI: 1.8, 2.7) in a study conducted in New Zealand. We did not identify any study comparing mobile interventions with conventional interventions.
Of 8 RCTs‐assessed computer‐based software, 4 (50%) reported significant improvements in abstinence, with ORs ranging from 1.1 to 1.6. The intervention generally included a questionnaire to assess smoking behavior, which was then used as a basis to provide tailored smoking cessation advice.
Excessive Alcohol Use
Of 1015 abstracts screened, 41 RCTs and 6 quasi‐experimental studies met inclusion criteria (Figure 4). All studies were conducted in high‐income Western countries including the United States (N=21), The Netherlands (n=7), United Kingdom (n=5), Canada (n=3), New Zealand (n=3), Sweden (n=2), Germany (n=2), Australia, Switzerland, Finland, and Denmark. More than half (n=27) were carried out in universities, colleges, or schools; and the remaining in primary care, workplace, or other community settings. The study population mostly included adults with unhealthy patterns of drinking. Most studies evaluated the effect of a single session intervention consisting of assessment and personalized feedback over a follow‐up period of 1 week to 2 years (Table 6).
Of 47 studies (41 RCTs, 6 quasi‐experimental) evaluating Internet interventions, 39 (34%) reported significant decrease in alcohol use (Table 6). Of 41 RCTs, 34 (83%) reported statistically significant benefits. The only trial that compared Internet versus conventional intervention reported significant within‐group improvement in heavy drinking days at 3 and 6 months, but no significant between‐group differences.
The type and magnitude of effect sizes varied across the studies reporting reductions in alcohol use. Examples included reductions of 63% in weekly alcohol use after a 3‐month intervention27; 50% in heavy drinking days at 6‐month follow‐up among veterans screening positive for alcohol misuse28; 7 drinks in mean weekly drinking at 3‐month follow‐up among risky drinkers29; 16% in heavy episodic drinking at 1‐month follow‐up relative to controls30; and 10 units (100 mL ethanol) in weekly alcohol use at 7‐week follow‐up.31 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.
We systematically investigated, synthesized, and graded scientific evidence for effectiveness of information and communication technology to improve lifestyle. Our results support the effectiveness of Internet interventions to improve diet, physical activity, adiposity, tobacco, and excess alcohol. Mobile interventions were also found to be effective for improving physical activity and adiposity. Our comprehensive review also identified several important research gaps and potential directions for future research.
We found that evidence on effectiveness of information and communication technologies mainly came from short‐term (<6 months) experimental studies, with far less data on long‐term effectiveness or sustainability. Additionally, most studies were in high‐income countries and largely included volunteers who were generally more motivated and more educated than the general public. This could limit generalizability of findings, highlighting the need for more evidence from studies with longer duration of follow‐up (>1 year), from population subgroups (eg, less educated, elderly) and from developing countries.
Our review also highlights operational challenges in evaluating the effectiveness of Internet and mobile interventions. Low adherence rate was a major challenge in most of the studies, in particular in studies with longer durations of follow‐up (>3 months). While, due to heterogeneity in definition of adherence, the direct comparison of adherence rates across studies was not possible, the majority of studies consistently showed a significant decline in adherence over time. Similarly, heterogeneity in the content, intensity, behavioral targets, and duration of interventions made it difficult to directly compare results across studies, perform quantitative meta‐analysis, or identify specific promising features of individual interventions. Additionally, few studies assessed their intervention's outreach or coverage.
We found that using evidence‐based behavioral change strategies could increase the effectiveness of Internet and mobile interventions. For example, in studies of the diet and adiposity, interventions were more effective if adopting multiple modes of communication, using tailored messages, and integrating goal‐setting and self‐monitoring. Similarly, in studies of physical activity, developing the content of Internet interventions based on psychological theories of behavioral change increased the effect of the intervention and retention of participants. We also found that interaction with providers could increase the success rate of the intervention. For example, in studies of smoking cessation, the interventions tended to be more effective if they included a direct interaction between smoker and healthcare provider. These findings could inform development of novel Internet and mobile interventions that are more effective and have a greater adherence rate. Many existing policies aiming to improve population lifestyle behaviors have focused on conventional strategies such as mass media campaigns, environment changes, and school‐based programs.4 In comparison, use of novel information and communication technologies that provide individually tailored data has grown more organically (for example, from private industry and consumer demand, with little systematic use or evaluation). There is growing recognition of the potentials of such interventions. For example, the US National Physical Activity Plan includes media strategies that encourage stakeholders to incorporate such emerging technologies into programs.32 The US Community Preventive Services Task Force recently recommended use of a computer‐based Electronic Screening and Brief Intervention (e‐SBI) for addressing excess alcohol.33 Yet, considering the strength of the evidence, our findings suggest that the application and testing of novel information and communication technologies should be greatly expanded.
Potential limitations should be considered. Application of Internet and mobile for health promotion and NCD prevention is rapidly growing, and this review might not have captured all the studies that have been published in this field. Although our findings suggest that Internet and mobile interventions are promising for lifestyle modification, the effect sizes of these interventions depend on multiple factors (eg, the content and components of the intervention) and could be widely varied across studies and over time. The present study only evaluated the efficacy of Internet and mobile interventions for primary prevention of NCDs and did not assess their effect in patients with chronic disease, highlighting the need for similar evaluation of evidence in this population.
In conclusion, our systematic review supports the effectiveness of Internet and mobile interventions to improve lifestyle and reduce NCD risk factors. Our findings also highlight the need for greater evaluation of long‐term effectiveness, sustainability, and assessment of utility in more diverse population subgroups.
Sources of Funding
Funding for this study was provided by The Sackler Institute for Nutrition Science, a program of the New York Academy of Sciences, through a grant from the Robert Wood Johnson Foundation, and its findings supported the Vitality Institute Commission on Health Promotion and the Prevention of Chronic Disease in Working‐Age Americans. Afshin reports research grants from the Gates Foundation and the Sackler Institute of Nutrition. Mozaffarian reports ad hoc travel reimbursement or honoraria from Bunge, Pollock Institute, Quaker Oats, and Life Sciences Research Organization; ad hoc consulting fees from McKinsey Health Systems Institute, Foodminds, Nutrition Impact, Amarin, Omthera, and Winston and Strawn LLP; membership, Unilever North America Scientific Advisory Board; royalties from UpToDate; and research grants from GlaxoSmithKline, Sigma Tau, Pronova, the Gates Foundation, the Sackler Institute of Nutrition, and the National Institutes of Health. The study sponsors had no role in study design; collection, analysis, and interpretation of data; writing the report; and the decision to submit the report for publication.
Data S1. PubMed search query for diet and adiposity.
Data S2. PubMed search query for physical activity.
Data S3. PubMed search query for tobacco.
Data S4. PubMed search query for alcohol use.
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