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Ethan Phillips
Ethan Phillips

Young Smoking 004 Mp4 REPACK


We conducted a systematic review to assess the effectiveness of smoking cessation, physical activity (PA), diet, and alcohol reduction interventions delivered by mobile technology to prevent non-communicable diseases (NCDs).




Young Smoking 004 mp4


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Citation: Palmer M, Sutherland J, Barnard S, Wynne A, Rezel E, Doel A, et al. (2018) The effectiveness of smoking cessation, physical activity/diet and alcohol reduction interventions delivered by mobile phones for the prevention of non-communicable diseases: A systematic review of randomised controlled trials. PLoS ONE 13(1): e0189801.


Physical inactivity, unhealthy diet, tobacco use and the harmful use of alcohol all increase the risk of developing and dying from NCDs. The Global Burden of Disease Study estimated that in 2010, 12.5 million deaths were attributable to dietary risk factors and physical inactivity, over 6 million deaths were attributable tobacco smoking (including second hand smoke), and over 2.5 million deaths were attributable to alcohol use [3]. Encouraging health care consumers to adopt healthy behaviours can prevent the onset or progression of NCDs and reduce mortality [4, 5].


For the purpose of this review, primary outcomes were defined as any objective measure of outcomes related to the specified NCD behavioural risk factors, including objective measures of the behaviour and the distal biometric or health effects of the behaviour. For example, objective measures of the behaviour would include salivary cotinine levels for smoking cessation, and step counts for physical activity; biometric measures of effect would include blood pressure, weight, and VO2 max (e.g. for fitness); and health effects would include incidence of diabetes or cardiovascular disease. Secondary outcomes were defined as self-reported measures relating to NCD-related health behaviours, health status, and cognitive outcomes. Studies reporting outcomes for any length of follow-up were included.


The combined search strategies identified 42,268 electronic records which were screened for eligibility (Fig 1). The full texts of 723 potentially eligible reports were obtained for further assessment. Out of the 723 potentially eligible reports, 72 met the study inclusion criteria and were trials delivered to health care consumers to improve health behaviours. Two papers report on the same trial involving an intervention targeting smoking cessation and an attention-matched control receiving messages promoting improved diet and physical activity. Ybarra (2013) reports on the smoking outcomes and Filion (2015) reports on the physical activity/diet outcomes. Therefore, in total, there were 71 unique trials. 18 interventions aimed to increase smoking cessation; 44 aimed to increase physical activity, improve diet, or a combination of both; 2 aimed to increase physical activity, improve diet, and increase smoking cessation; and 8 aimed to reduce harmful alcohol consumption.


There were 18 randomised controlled trials with parallel groups which aimed to increase smoking cessation (Table 1). The smoking cessation trials included a total of 17857 participants, with sample sizes ranging from 31 to 5800. Twelve of the smoking cessation trials were delivered by SMS, three were delivered by voice calls, one by interactive voice response, one by a combination of SMS and video messages, and one by a mobile application combined with voice calls.


There were 2 trials [82, 83] which targeted physical activity, diet, and smoking cessation as part broad lifestyle interventions (Table 5). One, conducted in Australia, included 710 respondents and trialled an intervention delivered by SMS [82], and the other, conducted in Iran, involved 180 participants and assessed the effectiveness of an app-based intervention [83].


According to our behaviour change technique coding of the studies (Table 7), smoking cessation studies included between 1 and 13 BCTs (median: 8), physical activity/diet studies included between 0 and 9 BCTs (median: 5), the two combined physical activity, diet and smoking trials included 1 and 11 BCTs, and alcohol studies included between 5 and 13 BCTs (median: 8).


The physical activity, diet and smoking trials reported up to ten outcomes. Primary outcomes included medical outcomes such as systolic blood pressure, diastolic blood pressure, resting heart rate, high density lipoprotein cholesterol, low density lipoprotein cholesterol, total cholesterol, and triglycerides and biochemically confirmed smoking status. Secondary outcomes were self-report measures of physical activity and dietary intake.


The assessment of risk of bias for the smoking cessation trials is reported in S1 Table and the risk of bias summary is presented in Fig 2. Two trials targeting smoking cessation were at low risk of bias for all quality criteria [25, 26].


The assessment of risk of bias of the physical activity, diet and smoking trials is reported in S1 Table and the risk of bias summary is presented in Fig 6. Of the two trials, one was assessed as being at low risk of bias across all quality criteria [82].


One trial of an SMS-based intervention promoting smoking cessation showed a statistically significant improvement in biochemically verified smoking cessation at 6 months (time frame of smoking abstinence not defined) [82] (Table 8).


For trials targeting alcohol consumption, one trial delivering supportive SMS observed a statistically significant increase in the number of days to first drink after inpatient discharge but no statistically significant effect on drinking frequency or cognitive outcomes [84]. A trial of an SMS-based drinking assessment intervention found a statistically significant reduction in the number of binge drinking days and number of drinks per drinking day among the intervention group receiving real time feedback, but no such effect in the intervention group who did not receive feedback [86]. A second trial delivering a smartphone intervention observed a small but statistically significant effect on the number of risky drinking days but no effect on continuous abstinence [87]. Another trial observed no effect of SMS-based drinking assessments and brief interventions on drinking frequency in young adults discharged from the Emergency Department [90]. One trial found a small but statistically significant beneficial effect of an intervention delivered by interactive voice response on a multi-item scale measuring alcohol consumption, alcohol dependence and alcohol-related harm [85]. A study among Swedish students assessing the effect of an application-based intervention found that those in the intervention group had slightly increased alcohol consumption [86] (S2 Table).


According to the GRADE [19] criteria (Table 12), there was high quality evidence of benefit for smoking cessation support delivered by text message and no evidence of harms. For SMS based physical activity interventions, there was low quality evidence of changes in physical activity which was not statistically significant. For SMS based diet and physical activity interventions there was low quality evidence suggesting benefit in reducing the incidence of diabetes in those with pre diabetes and modest or small benefits in change in weight (KG or %), BMI and triglycerides. The evidence of benefit for end point weight, waist circumference, total cholesterol, and blood pressure was very low, with one trial at low risk of bias conducted in those with coronary heart disease reporting statistically significant improvements. The evidence of benefit on HDL cholesterol was very low with one trial reporting statistically significant improvements. The effect of diet and physical activity interventions delivered by app was in the direction of a small benefit, but not statistically significant.


We identified 71 trials of interventions delivered by mobile phone targeting prevention of NCD focussed on smoking cessation, physical activity, diet, and alcohol reduction. No trials reported effects on morbidity or mortality.


There is high quality evidence that smoking cessation support delivered by text message for smokers making a quit attempt increases smoking cessation in trials conducted in high income countries and no evidence for adverse effects of these interventions. In single trials there was no suggestion that text messages to prompt a quit attempt and link people with existing smoking cessation services are more effective than a leaflet with the same content [24]. There was low quality evidence that phone counseling by mobile phone increased smoking cessation at 3 months [35].


There are also a number of limitations to our review. It was not possible to contact authors for data in this review, due to time and funding constraints. It was beyond the scope of our review to include interventions delivered by PDA or hand held computer or to review all internet or video based interventions, which in principal can be viewed on many modern mobile phones. Our review aimed to examine the effects of interventions delivered by mobile technologies alone. We excluded interventions combining mobile technologies with additional interventions such as face-to-face counselling, which could be subject to a separate systematic review. We only pooled the results of trial where the trial aim, outcomes and mobile phone media used were the same (e.g. SMS, application software). Nonetheless some of the results of pooled analyses were heterogeneous. This is likely to be due to the wide range of factors which could influence the effectiveness of particular mobile technology interventions including: trial quality [95], participant factors, the setting (low/middle or high income country), intervention design, intervention components (e.g. the behaviour change techniques employed), intensity or intervention duration. We only pooled objectively measured outcomes in meta-analyses due to prior evidence that self-reported outcomes in behaviour change trials can be prone to overstated benefits. Some evidence in our review supports this, for example, a smoking cessation trial showed a null result for a biochemically-confirmed measure, but a benefit in the equivalent self-report outcome [21]. Our review provides no insight into the mechanism of action of interventions. The examination of funnel plots in exploring publication bias was limited as few trials contributed to some pooled analyses. 041b061a72


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