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Meta-Analysis
. 2017 Sep 25;9(9):CD011479.
doi: 10.1002/14651858.CD011479.pub2.

Personalised digital interventions for reducing hazardous and harmful alcohol consumption in community-dwelling populations

Affiliations
Meta-Analysis

Personalised digital interventions for reducing hazardous and harmful alcohol consumption in community-dwelling populations

Eileen Fs Kaner et al. Cochrane Database Syst Rev. .

Abstract

Background: Excessive alcohol use contributes significantly to physical and psychological illness, injury and death, and a wide array of social harm in all age groups. A proven strategy for reducing excessive alcohol consumption levels is to offer a brief conversation-based intervention in primary care settings, but more recent technological innovations have enabled people to interact directly via computer, mobile device or smartphone with digital interventions designed to address problem alcohol consumption.

Objectives: To assess the effectiveness and cost-effectiveness of digital interventions for reducing hazardous and harmful alcohol consumption, alcohol-related problems, or both, in people living in the community, specifically: (i) Are digital interventions more effective and cost-effective than no intervention (or minimal input) controls? (ii) Are digital interventions at least equally effective as face-to-face brief alcohol interventions? (iii) What are the effective component behaviour change techniques (BCTs) of such interventions and their mechanisms of action? (iv) What theories or models have been used in the development and/or evaluation of the intervention? Secondary objectives were (i) to assess whether outcomes differ between trials where the digital intervention targets participants attending health, social care, education or other community-based settings and those where it is offered remotely via the internet or mobile phone platforms; (ii) to specify interventions according to their mode of delivery (e.g. functionality features) and assess the impact of mode of delivery on outcomes.

Search methods: We searched CENTRAL, MEDLINE, PsycINFO, CINAHL, ERIC, HTA and Web of Knowledge databases; ClinicalTrials.com and WHO ICTRP trials registers and relevant websites to April 2017. We also checked the reference lists of included trials and relevant systematic reviews.

Selection criteria: We included randomised controlled trials (RCTs) that evaluated the effectiveness of digital interventions compared with no intervention or with face-to-face interventions for reducing hazardous or harmful alcohol consumption in people living in the community and reported a measure of alcohol consumption.

Data collection and analysis: We used standard methodological procedures expected by The Cochrane Collaboration.

Main results: We included 57 studies which randomised a total of 34,390 participants. The main sources of bias were from attrition and participant blinding (36% and 21% of studies respectively, high risk of bias). Forty one studies (42 comparisons, 19,241 participants) provided data for the primary meta-analysis, which demonstrated that participants using a digital intervention drank approximately 23 g alcohol weekly (95% CI 15 to 30) (about 3 UK units) less than participants who received no or minimal interventions at end of follow up (moderate-quality evidence).Fifteen studies (16 comparisons, 10,862 participants) demonstrated that participants who engaged with digital interventions had less than one drinking day per month fewer than no intervention controls (moderate-quality evidence), 15 studies (3587 participants) showed about one binge drinking session less per month in the intervention group compared to no intervention controls (moderate-quality evidence), and in 15 studies (9791 participants) intervention participants drank one unit per occasion less than no intervention control participants (moderate-quality evidence).Only five small studies (390 participants) compared digital and face-to-face interventions. There was no difference in alcohol consumption at end of follow up (MD 0.52 g/week, 95% CI -24.59 to 25.63; low-quality evidence). Thus, digital alcohol interventions produced broadly similar outcomes in these studies. No studies reported whether any adverse effects resulted from the interventions.A median of nine BCTs were used in experimental arms (range = 1 to 22). 'B' is an estimate of effect (MD in quantity of drinking, expressed in g/week) per unit increase in the BCT, and is a way to report whether individual BCTs are linked to the effect of the intervention. The BCTs of goal setting (B -43.94, 95% CI -78.59 to -9.30), problem solving (B -48.03, 95% CI -77.79 to -18.27), information about antecedents (B -74.20, 95% CI -117.72 to -30.68), behaviour substitution (B -123.71, 95% CI -184.63 to -62.80) and credible source (B -39.89, 95% CI -72.66 to -7.11) were significantly associated with reduced alcohol consumption in unadjusted models. In a multivariable model that included BCTs with B > 23 in the unadjusted model, the BCTs of behaviour substitution (B -95.12, 95% CI -162.90 to -27.34), problem solving (B -45.92, 95% CI -90.97 to -0.87), and credible source (B -32.09, 95% CI -60.64 to -3.55) were associated with reduced alcohol consumption.The most frequently mentioned theories or models in the included studies were Motivational Interviewing Theory (7/20), Transtheoretical Model (6/20) and Social Norms Theory (6/20). Over half of the interventions (n = 21, 51%) made no mention of theory. Only two studies used theory to select participants or tailor the intervention. There was no evidence of an association between reporting theory use and intervention effectiveness.

Authors' conclusions: There is moderate-quality evidence that digital interventions may lower alcohol consumption, with an average reduction of up to three (UK) standard drinks per week compared to control participants. Substantial heterogeneity and risk of performance and publication bias may mean the reduction was lower. Low-quality evidence from fewer studies suggested there may be little or no difference in impact on alcohol consumption between digital and face-to-face interventions.The BCTs of behaviour substitution, problem solving and credible source were associated with the effectiveness of digital interventions to reduce alcohol consumption and warrant further investigation in an experimental context.Reporting of theory use was very limited and often unclear when present. Over half of the interventions made no reference to any theories. Limited reporting of theory use was unrelated to heterogeneity in intervention effectiveness.

PubMed Disclaimer

Conflict of interest statement

Eileen Kaner, Fiona Beyer and Colin Muirhead are authors on a related Cochrane Review (Kaner 2007).

Eileen Kaner is an investigator on the ongoing SIPS Junior trial (NIHR programme grant number NIHR RP‐PG‐0609‐10162), which will have an app component in one arm of the trial.

Jamie Brown, David Crane, Claire Garnett and Susan Michie are currently working on the development and evaluation of an app to reduce excessive alcohol consumption (ISRCTN40104069).

Matthew Hickman, Frank de Vocht, and James Redmore, Amy O'Donnell, James Newham, Heather Brown and Gregory Maniatopoulos have no interests to declare.

Figures

1
1
Study flow diagram
2
2
Risk of bias summary: review authors' judgements about each risk of bias item for each included study
3
3
Funnel plot of comparison 1: Digital intervention vs. control, outcome 1.1: Quantity of drinking (g/week), based on longest follow‐up
4
4
Funnel plot of comparison 1: Digital intervention vs. control, outcome 1.6: Quantity of drinking (g/week), based on longest follow‐up and categorised on whether restricted to adolescents or young adults
1.1
1.1. Analysis
Comparison 1 Digital intervention versus no or minimal intervention, Outcome 1 Quantity of drinking (g/week), based on longest follow‐up.
1.2
1.2. Analysis
Comparison 1 Digital intervention versus no or minimal intervention, Outcome 2 Quantity of drinking (g/week), categorised by length of follow‐up.
1.3
1.3. Analysis
Comparison 1 Digital intervention versus no or minimal intervention, Outcome 3 Quantity of drinking (g/week), based on longest follow‐up and categorised on whether restricted to adolescents or young adults.
1.4
1.4. Analysis
Comparison 1 Digital intervention versus no or minimal intervention, Outcome 4 Quantity of drinking (g/week), categorised by length of follow‐up and restricted to trials of adolescents/young adults.
1.5
1.5. Analysis
Comparison 1 Digital intervention versus no or minimal intervention, Outcome 5 Quantity of drinking (g/week), based on longest follow‐up and categorised by gender.
1.6
1.6. Analysis
Comparison 1 Digital intervention versus no or minimal intervention, Outcome 6 Quantity of drinking (g/week), based on longest follow‐up and omitting trials at high risk of bias owing to incomplete data.
1.7
1.7. Analysis
Comparison 1 Digital intervention versus no or minimal intervention, Outcome 7 Quantity of drinking (g/week), based on longest follow‐up and omitting trials at high risk of performance bias.
1.8
1.8. Analysis
Comparison 1 Digital intervention versus no or minimal intervention, Outcome 8 Quantity of drinking (g/week), based on longest follow‐up, with imputation of missing standard deviations or number of participants per arm.
1.9
1.9. Analysis
Comparison 1 Digital intervention versus no or minimal intervention, Outcome 9 Quantity of drinking (g/week), categorised by length of follow‐up, with imputation of missing standard deviations or number of participants per arm.
1.10
1.10. Analysis
Comparison 1 Digital intervention versus no or minimal intervention, Outcome 10 Frequency of drinking (no. of days drinking/week), based on longest follow‐up.
1.11
1.11. Analysis
Comparison 1 Digital intervention versus no or minimal intervention, Outcome 11 Frequency of binge drinking (no. of binges/week), based on longest follow‐up.
1.12
1.12. Analysis
Comparison 1 Digital intervention versus no or minimal intervention, Outcome 12 Intensity of drinking (g/drinking day), based on longest follow‐up.
1.13
1.13. Analysis
Comparison 1 Digital intervention versus no or minimal intervention, Outcome 13 Binge drinkers, based on longest period of follow‐up.
2.1
2.1. Analysis
Comparison 2 Digital intervention versus face‐to‐face intervention, Outcome 1 Quantity of drinking (g/week), based on longest follow‐up.
2.2
2.2. Analysis
Comparison 2 Digital intervention versus face‐to‐face intervention, Outcome 2 Quantity of drinking (g/week), categorised by length of follow‐up.
2.3
2.3. Analysis
Comparison 2 Digital intervention versus face‐to‐face intervention, Outcome 3 Frequency of drinking (no. of days drinking/week), based on longest follow‐up.
2.4
2.4. Analysis
Comparison 2 Digital intervention versus face‐to‐face intervention, Outcome 4 Frequency of binge drinking (no. of binges/week), based on longest follow‐up.

Update of

  • doi: 10.1002/14651858.CD011479

References

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References to studies excluded from this review

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Kay‐Lambkin 2009 {published data only}
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Keurhorst 2013 {published data only}
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Kypri 2004 {published data only}
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    1. LaBrie JW, Hummer JF, Neighbors C, Pedersen ER. Live interactive group‐specific normative feedback reduces misperceptions and drinking in college students: a randomized cluster trial. Psychology of Addictive Behaviors 2008;22(1):141‐8. - PMC - PubMed
Lana 2014 {published data only}
    1. Lana A, Faya‐Ornia G, López ML. Impact of a web‐based intervention supplemented with text messages to improve cancer prevention behaviors among adolescents: results from a randomized controlled trial. Preventive Medicine 2014;59:54‐9. - PubMed
Lane 2012 {published data only}
    1. Lane DJ, Lindemann DF, Schmidt JA. A comparison of computer‐assisted and self‐management programs for reducing alcohol use among students in first year experience courses. Journal of Drug Education 2012;42(2):119‐35. - PubMed
Lovecchio 2010 {published data only}
    1. Lovecchio CP, Wyatt TM, DeJong W. Reductions in drinking and alcohol‐related harms reported by first‐year college students taking an online alcohol education course: a randomized trial. Journal of Health Communication 2010;15(7):805‐19. - PubMed
Maio 2005 {published data only}
    1. Maio RF, Shope JT, Blow FC, Gregor MA, Zakrajsek JS, Weber JE, et al. A randomized controlled trial of an emergency department‐based interactive computer program to prevent alcohol misuse among injured adolescents. Annals of Emergency Medicine 2005;45(4):420‐9. - PubMed
Martens 2010 {published data only}
    1. Martens MP, Kilmer JR, Beck NC, Zamboanga BL. The efficacy of a targeted personalized drinking feedback intervention among intercollegiate athletes: a randomized controlled trial. Psychology of Addictive Behaviors 2010;24(4):660‐9. - PubMed
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    1. Matano RA, Koopman C, Wanat SF, Winzelberg AJ, Whitsell SD, Westrup D, et al. A pilot study of an interactive web site in the workplace for reducing alcohol consumption. Journal of Substance Abuse Treatment 2007;32(1):71‐80. - PubMed
McCambridge 2013 {published data only}
    1. McCambridge J, Bendtsen M, Karlsson N, White IR, Nilsen P, Bendtsen P. Alcohol assessment and feedback by email for university students: main findings from a randomised controlled trial. British Journal of Psychiatry 2013;203(5):334‐40. - PMC - PubMed
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    1. Palfai TP, Winter M, Lu J, Rosenbloom D, Saitz R. Personalized feedback as a universal prevention approach for college drinking: a randomized trial of an e‐mail linked universal web‐based alcohol intervention. Journal of Primary Prevention 2014;35(2):75‐84. - PMC - PubMed
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    1. Paschall MJ, Antin T, Ringwalt CL, Saltz RF. Evaluation of an internet‐based alcohol misuse prevention course for college freshmen: findings of a randomized multi‐campus trial. American Journal of Preventive Medicine 2011;41(3):300‐8. - PMC - PubMed
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    1. Reis J, Riley W. Assessment of a computer‐supported alcohol education intervention program. Health Education 2002;102(3):124‐32.
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    1. Rhodes KV, Lauderdale DS, Stocking CB, Howes DS, Roizen MF, Levinson W. Better health while you wait: a controlled trial of a computer‐based intervention for screening and health promotion in the emergency department. Annals of Emergency Medicine 2001;37(3):284‐91. - PubMed
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References to studies awaiting assessment

Acosta 2017 {published data only}
    1. Acosta MC, Possemato K, Maisto SA, Marsch LA, Barrie K, Lantinga L. Web‐delivered CBT reduces heavy drinking in OEF‐OIF veterans in primary care with symptomatic substance use and PTSD. Behavior Therapy 2017;48(2):262‐76. - PMC - PubMed
Balestrieri 2016 {published data only}
    1. Balestrieri SG, Miller MB, DiBello AM, Merrill JE, Benz MB, Lowery AD, et al. Evaluating the efficacy of a computer‐delivered brief alcohol intervention among college students living off‐campus. Alcoholism, Clinical and Experimental Research 2016;40(Suppl 1):62a.
Bock 2016 {published data only}
    1. Bock BC, Barnett NP, Thind H, Rosen R, Walaska K, Traficante R, et al. A text message intervention for alcohol risk reduction among community college students: TMAP. Addictive Behaviors 2016;63:107‐13. [DOI: 10.1016/j.addbeh.2016.07.012] - DOI - PMC - PubMed
Duroy 2016 {published data only}
    1. Duroy D, Boutron I, Baron G, Ravaud P, Estellat C, Lejoyeux M. Impact of a computer‐assisted Screening, Brief Intervention and Referral to Treatment on reducing alcohol consumption among patients with hazardous drinking disorder in hospital Emergency Departments. The randomized BREVALCO trial. Drug and Alcohol Dependence 2016;165:236‐44. [DOI: 10.1016/j.drugalcdep.2016.06.018] - DOI - PubMed
Gajecki 2017 {published data only}
    1. Gajecki M, Andersson C, Rosendahl, Sinadinovic K, Fredriksson M, Berman AH. Skills training via smartphone app for university students with excessive alcohol consumption: a randomized controlled trial. International Journal of Behavioral Medicine 2017 Feb 21 [Epub ahead of print]. [DOI: 10.1007/s12529-016-9629-9] - DOI - PMC - PubMed
Leeman 2016 {published data only}
    1. Leeman RF, DeMartini KS, Gueorguieva R, Nogueira C, Corbin WR, Neighbors C, et al. Randomized controlled trial of a very brief, multicomponent web‐based alcohol intervention for undergraduates with a focus on protective behavioral strategies. Journal of Consulting and Clinical Psychology 2016;84(11):1008‐15. - PMC - PubMed
Muench 2017 {published data only}
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Ondersma 2016 {published data only}
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References to ongoing studies

ISRCTN10323951 {published data only}
    1. ISRCTN10323951. Testing the effectiveness of two web‐based interventions aiming to reduce alcohol consumption. http://www.isrctn.com/ISRCTN10323951 (first received 7th September 2015).
    1. Schaub MP, Blankers M, Lehr D, Boss L, Riper H, Dekker J, et al. Efficacy of an internet‐based self‐help intervention to reduce co‐occurring alcohol misuse and depression symptoms in adults: study protocol of a three‐arm randomised controlled trial. BMJ Open 2016;6(5):e011457. - PMC - PubMed
ISRCTN40104069 {published data only}
    1. Garnett C, Crane D, Michie S, West R, Brown J. Evaluating the effectiveness of a smartphone app to reduce excessive alcohol consumption: protocol for a factorial randomised control trial. BMC Public Health 2016;16:536. [DOI: 10.1186/s12889-016-3140-8] - DOI - PMC - PubMed
    1. ISRCTN40104069. Evaluating the effectiveness of a smartphone app to reduce alcohol consumption in hazardous and/or harmful drinkers. http://www.isrctn.com/ISRCTN40104069 (first received 10 February 2016).
ISRCTN45300218 {published data only}
    1. Deluca P, Coulton S, Alam MF, Cohen D, Donoghue K, Gilvarry E, et al. Linked randomised controlled trials of face‐to‐face and electronic brief intervention methods to prevent alcohol related harm in young people aged 14‐17 years presenting to Emergency Departments (SIPS Junior). BMC Public Health 2015;15(1):345. - PMC - PubMed
    1. ISRCTN45300218. Developing and evaluating interventions for adolescents with alcohol use disorders who present through emergency departments: randomised feasibility study and exploratory randomised controlled trial. http://www.isrctn.com/ISRCTN45300218 (first received 5th June 2014).
NCT02064998 {published data only}
    1. Berman AH, Gajecki M, Fredriksson M, Sinadinovic K, Andersson C. Mobile phone apps for university students with hazardous alcohol use: study protocol for two consecutive randomized controlled trials. JMIR Research Protocols 2015;4(4):e139. - PMC - PubMed
    1. NCT02064998. Two consecutive randomized controlled trials using mobile phone applications for risky alcohol use. https://clinicaltrials.gov/ct2/show/NCT02064998?term=NCT02064998&rank=1 (first received 14th February 2014).

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