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Unhealthy alcohol use (UAU) is one of the major causes of preventable morbidity, mortality, and associated behavioral risks worldwide. Although mobile health (mHealth) interventions can provide consumers with an effective means for self-control of UAU in a timely, ubiquitous, and cost-effective manner, to date, there is a lack of understanding about different health outcomes brought by such interventions. The core components of these interventions are also unclear.
This study aimed to systematically review and synthesize the research evidence about the efficacy of mHealth interventions on various health outcomes for consumer self-control of UAU and to identify the core components to achieve these outcomes.
We systematically searched 7 electronic interdisciplinary databases: Scopus, PubMed, PubMed Central, CINAHL Plus with full text, MEDLINE with full text, PsycINFO, and PsycARTICLES. Search terms and Medical Subject Headings “mHealth,” “text message,” “SMS,” “App,” “IVR,” “self-control,” “self-regulation,” “alcohol*,” and “intervention” were used individually or in combination to identify peer-reviewed publications in English from 2008 to 2017. We screened titles and abstracts and assessed full-text papers as per inclusion and exclusion criteria. Data were extracted from the included papers according to the Consolidated Standards of Reporting Trials-EHEALTH checklist (V 1.6.1) by 2 authors independently. Data quality was assessed by the Mixed Methods Appraisal Tool. Data synthesis and analyses were conducted following the procedures for qualitative content analysis. Statistical testing was also conducted to test differences among groups of studies.
In total, 19 studies were included in the review. Of these 19 studies, 12 (63%) mHealth interventions brought significant positive outcomes in improving participants’ health as measured by behavioral (n=11), physiological (n=1), and cognitive indicators (n=1). No significant health outcome was reported in 6 studies (6/19, 32%). Surprisingly, a significant negative outcome was reported for the male participants in the intervention arm in 1 study (1/19, 5%), but no change was found for the female participants. In total, 5 core components reported in the mHealth interventions for consumer self-control of UAU were context, theoretical base, delivery mode, content, and implementation procedure. However, sound evidence is yet to be generated about the role of each component for mHealth success. The health outcomes were similar regardless of types of UAU, deployment setting, with or without nonmobile cointervention, and with or without theory.
Most studies reported mHealth interventions for self-control of UAU appeared to be improving behavior, especially the ones delivered by short message service and interactive voice response systems. Further studies are needed to gather sound evidence about the effects of mHealth interventions on improving physiological and cognitive outcomes as well as the optimal design of these interventions, their implementation, and effects in supporting self-control of UAU.
Unhealthy alcohol use (UAU) is one of the major causes of preventable morbidity, mortality, and related behavioral risks around the world [
As an umbrella term, UAU covers various degrees of negative effects of alcohol use on people’s well-being [
Risky drinking is also known as problematic drinking, harmful alcohol use, risky single-occasion drinking (RSOD), or heavy episodic drinking. It refers to alcohol use that leads to the risk of negative health consequences [
The other major type of UAU is AUD. It is a chronically recurrent brain impairment in which compulsive and maladaptive alcohol use results in behavior dysregulation and negative mood once alcohol consumption is ceased [
Mobile health (mHealth), also known as ecological momentary intervention [
mHealth interventions are mainly delivered solely or in combination of 3 channels: short message services (SMS) text messaging, apps, and interactive voice response (IVR). SMS text messaging has been used to guide consumers to change alcohol use behavior, for example, to reduce alcohol intake to enable self-control of UAU [
Recent reviews on digital interventions for self-control of UAU focus on the benefit of such interventions on improving health care services. In total, 2 reviews investigated electronic or Web-based interventions and found that despite a small effect, these interventions might improve behavioral outcomes, particularly for the group less likely to access traditional alcohol interventions such as women, youth, and risky drinkers [
A mixed-methods systematic review was conducted. Literature search and screening followed the preferred reporting items for systematic reviews and meta-analyses [
The literature search was performed from December 2016 to March 2017 and further refined in August 2018 in 7 electronic interdisciplinary databases: Scopus, PubMed, PubMed Central, CINAHL Plus with full text, MEDLINE with full text, PsycINFO, and PsycARTICLES (see
The papers were included in which (1) the research focused on supporting consumer self-control of UAU; (2) health intervention was delivered through mobile phone technologies; and (3) the data were collected from empirical randomized controlled trials.
The papers were excluded that (1) reported clinical therapy such as injection and medication rather than consumer active participation in the daily self-control of UAU; (2) did not report any alcohol-related health outcome; (3) used the intervention not dealing with UAU or containing Web-based components delivered by desktop or Web-based computer applications; or (4) were review papers, study protocols, conceptual papers, editorials, government reports, or guidelines in the topic area.
Data were extracted using a combination of an Endnote X8 and an Excel spreadsheet by 2 authors independently. These included name(s) of the author(s), year of publication, country of origin, population type, study setting, type of UAU, study type, eligibility, sample size, study arms and grouping, nonmobile cointervention, mHealth intervention theory, delivery mode, mHealth intervention content, implementation procedure, measurement, and outcomes.
All studies were assessed using the 4 criteria in section 2 of the MMAT, in terms of (1) randomization or sequence generation, checking if there is a clear description about randomization; (2) allocation concealment, verifying if there is a clear description about blinding; (3) outcome data, confirming if more than 80% outcomes were reported; and (4) attrition, assessing if less than 20% of the participants dropped out. Responses to each criterion were “yes,” “no,” or “can’t tell.”
Data were synthesized and analyzed using an inductive method. We reviewed all data that collected and identified similar notions and tagged them with the same code. Thereafter, we grouped the codes with similar meaning into an overarching concept. Concepts with similar meaning were grouped into a category that addresses our research question. The coding and data management were iteratively developed through constant comparison of the similarities and differences among codes.
To explore the initial outcomes about which components really make the intervention works, chi-square testing was conducted to test the relationship between health outcomes with the following 4 parameters: (1) types of UAU, being risky drinking or AUD; (2) with or without nonmobile cointervention; (3) theory-based or not; (4) deployment setting, being clinical, educational, or community based.
The primary search yielded 1345 publications. After removing duplicates, 517 papers remained. Their titles and/or abstracts were manually screened against the inclusion and exclusion criteria. This led to 41 candidate papers. Of these, 20 were excluded after further scrutinizing the full paper (see
Although we searched studies published since 2008, all 19 eligible studies were conducted in 2012 and beyond and were from 7 developed countries (see
Literature search and screening process.
Of these, 9 studies (9/19, 47%) were conducted in the United States [
Study arms ranged from 2 to 6. In total, 12 studies (12/19, 63%) were 2-arm trials with an intervention arm and a control arm [
We identified 5 core components of mHealth interventions for UAU: context, theoretical base, content, delivery mode, and implementation procedure and 3 types of potential health outcomes: behavioral, physiological, and cognitive outcome (see
There are 3 types of contexts: participant characteristics, deployment setting, and nonmobile cointervention, which were conducted simultaneously to support the mHealth intervention.
In total, 5 core components of mobile health interventions for self-control of unhealthy alcohol use and 3 types of potential health outcomes.
The participants can be categorized into 2 cohorts according to their age: youth group aged below 35 years [
In total, 2 types of theories were reported to guide the design and implementation of the mHealth interventions, including behavioral change theories and psychological theories of motivation.
Behavioral change theories included theory of planned behavior [
A total of 3 delivery modes were identified: SMS text messaging (12/19, 63%) [
In total, 3 types of content were designed to support the participants’ self-control of UAU. They were information [
Informational content included general and personalized information. The general information facilitated the participants in (1) enriching their knowledge about risks and negative consequences of UAU [
The personalized information helped the participants in (1) providing the tailored feedback according to their responses [
Motivational content included (1) encouragement messages for reducing alcohol use [
Reminding content facilitated participants in (1) reminding them to remember and fulfill their promises [
The duration of the interventions varied, ranging from 4 days [
With regard to the frequency, SMS text messages were sent once [
In 3 studies in which the interventions were delivered by mobile apps, the frequency of data collection was once daily in Aharonovich et al’s study [
Andersson divided his intervention arm into 2 subgroups, both receiving the same content but through different delivery modes, either delivering single IVR every day for 1 week or delivering repeated IVR for 4 weeks [
In terms of timing of delivery, 10 studies reported the fixed time or time slots to deliver the intervention, the rest were flexibly available on demand. The popular days of intervention delivery were Thursday [
All studies conducted the baseline assessments. In total, 6 studies conducted an assessment during the intervention period to explore the initial outcome [
Behavioral outcome was measured in 18 studies [
No significant behavioral change was found in 6 studies [
Physiological outcome was measured in only 1 study via BrAC [
Cognitive outcome was measured in 3 studies [
Over half of the SMS- and IVR-enabled interventions were effective in reducing alcohol use or increasing readiness to change UAU in 8 out of 12 studies (67%) [
Chi-square test did not find any significant differences in health outcomes among groups of studies with different conditions. It suggested that the health outcomes were similar regardless of the types of UAU studied, whether there was nonmobile cointervention, whether the study was theoretical-based, or which setting it was deployed.
This study aimed to synthesize and understand the research evidence about efficacy of mHealth interventions on different health outcomes for consumer self-control of UAU and to identify their core components to achieve these outcomes. In total, 19 studies were systematically reviewed and 3 types of health outcomes such as behavioral, physiological, and cognitive outcome and 5 components of these interventions such as context, theoretical base, delivery mode, contents, and implementation procedure were found.
As approximately two-thirds (11/18) of the studies that measured the behavioral outcomes identified a significant positive change [
Despite the significant 100% positive physiological outcome measured by BrAC, only 5% of the included studies assessed the physiological measurement [
For the same reason, as the cognitive outcomes are inconvenient to measure in comparison with behavioral ones, only 16% of the studies [
Complementing the traditional interventions such as face-to-face counseling, in which unhealthy alcohol users’ access to treatment was provided in a passive manner within a confined time and location, mHealth interventions open new opportunities for engaging consumers in positive self-control with increased flexibility. The effect of control was improved by continuous tracking and monitoring, interactive communication, or personalized feedback from health care providers anytime, anywhere [
Participants in most reviewed studies were risky drinkers without documented pathological conditions [
The gender difference in intervention outcome found in 2 studies [
Although not having any significant impact on health outcomes, cointervention, such as induction or training to enable a participant to confidently use the apps or IVR, is an integral, vital component for a successful mHealth intervention [
Behavior change theory provides the foundation for the formation of strategies to incrementally change a consumer’s behavior of UAU [
Almost all SMS- or IVR-enabled interventions were effective in reducing alcohol use or increasing readiness to change except the mobile apps [
Informational content facilitated the participants to develop essential knowledge and skill to build their capacity to change their belief and UAU behavior. It also provided necessary feedback to enable self-awareness of UAU status, which could help execute self-regulation of UAU. Motivational content provided continuous encouragement and peer support through experience sharing to raise the participants’ morale in changing UAU behavior. Reminding content provided constant recall to ensure the participants to stay on track in self-control of UAU. Delivery of these 3 types of content is in line with the model of human practical reasoning developed by Michael Bratman [
As the length of the reviewed studies was not long enough, ranging from 4 days to 8 months, it is no surprise that there was no obvious improvement in tangible health outcomes in many studies. Longer duration, that is, 6 months or more [
With the same content and implementation procedure, Andersson et al found differences in health outcomes measured by peak eBAC and AUDIT scores with different delivery modes in which the efficacy was better delivered by IVR than the Web [
Although the first generation of iPhone was released in June 2007, marking the debut of smartphone technology [
The first limitation of this study was that the coverage of the studies might not be exhaustive, because of which our search was confined to the 7 databases. However, the comprehensiveness of these databases can ensure the representativeness of the trend suggested by this study. The heterogeneity of participant characteristics, intervention, and health outcome measures makes it difficult to compare rigorously the findings among the studies. A lack of homogenous, quantitative measures in the original studies also deemed it impossible to conduct more rigorous meta-analysis. As only peer-refereed journal papers were included to ensure the rigor of this study, there could be a potential risk of reporting bias toward positive findings.
This systematic review summarized the extant research evidence about the health outcomes of mHealth interventions for consumer self-control of UAU. A total of 3 health outcomes, that is, physiological, behavioral, and cognitive outcomes and 5 core components of these interventions, that is, context, theoretical base, delivery mode, content, and implementation procedure, were synthesized and analyzed. In comparison with the traditional interventions, the evidence to support effectiveness of mHealth interventions for consumer self-control of UAU is modest at best. A majority of studies showed that mHealth interventions brought positive health outcomes in helping unhealthy alcohol users to proactively engage in self-control of their UAU behavior, especially for the ones delivered by SMS text messaging and IVR systems. Sound evidence is yet to be sought about the effects of these interventions in improving the physiological and cognitive outcomes. Further research is needed to gather evidence about the optimal design of mHealth interventions, their implementation, and effects in supporting consumer self-control of UAU.
Search and screen records.
Excluded papers with reasons.
List of included studies.
Quality appraisal of the included studies.
Characteristics of the included studies.
Five components and three types of health outcomes.
Alcohol-Comprehensive Health Enhancement Support System
alcohol use disorder
alcohol use disorders identification test
alcohol use disorders identification test for consumption
Brief Alcohol and Smoking Intervention for College Students via Mobile
breath alcohol concentration
estimated blood alcohol concentration
fast alcohol screening test
interactive voice response
mobile health
Mixed Methods Appraisal Tool
risky single-occasion drinking
standard drink
short message services
unhealthy alcohol use
The authors would like to acknowledge and thank Diane Walton for proofreading the paper.
None declared.