Mobile Technology-based Interventions for Adult Users of Alcohol Fowler 2016

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  Mobile technology-based interventions for adult users of alcohol: Asystematic review of the literature Lauren A. Fowler ⁎ , Sidney L. Holt, Deepti Joshi George Washington University, United States H I G H L I G H T S ã  This review summarizes the current literature on mobile technology-based interventions among adult users of alcohol. ã  Five relevant databases were searched for peer-reviewed articles from 2004 to 2015. Eight studies met inclusion criteria. ã  The majority found positive effects of the intervention, although the interventions were primarily preliminary in nature. ã  Findings highlight the promising, yet preliminary state of research in this area. ã  M-tech interventions have the potential to compliment established treatment modalities for alcohol use among adults. a b s t r a c ta r t i c l e i n f o  Article history: Received 17 January 2016Received in revised form 13 May 2016Accepted 6 June 2016Available online 7 June 2016 Background:  Worldwide,16% of peopleaged 15 and olderengageinharmful useof alcohol. Harmful alcohol useleads to a host of preventable negative social and health consequences. Mobile technology-based interventionsprovideaparticularlypromisingavenueforthewidespreadandcost-effectivedeliveryoftreatmentthatisacces-sible, affordable, individualized, and destigmatized to both alcohol-dependent and nondependent individuals.  Aims: The present reviewsought to summarize the currentliteratureonmobiletechnology-basedinterventionsamong adult users of alcohol and determine the ef  󿬁 cacy of such interventions. Methods: FivedatabasesweresearchedinDecember2015(Jan.2004 – Dec.2015).Inclusioncriteriawere:partic-ipantsaged18orolder,interventionsdeliveredthroughmobile-technology,andoutcomemeasurementofalco-hol reduction/cessation. Findings:  Eight studies met inclusion criteria. The majority of the studies reviewed found positive effects of theintervention, even though the interventions themselves varied in design, length, dosage, and target population,and were pilot or preliminary in nature. Conclusions:  Findings from this review highlight the promising, yet preliminary state of research in this area.Studies with adequate power and valid design are necessary to evaluate the potential of mobile technology-based interventions on long-term alcohol behavior outcomes. Furthermore, future research should elucidatewhat the most effective length of time is for a mobile technology-based intervention, how often individualsshouldreceive messagesfor maximum bene 󿬁 t, and determinethecomparative effectiveness of mobile technol-ogy interventions with other ef  󿬁 cacious interventions.© 2016 Elsevier Ltd. All rights reserved. Keywords: AlcoholSMSText messagingInterventionSubstance use Contents 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261.1. Traditional treatments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261.2. Mobile technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271.3. Purpose. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 272. Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282.1. Selection of studies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282.2. Inclusion criteria. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Addictive Behaviors 62 (2016) 25 – 34 ⁎  Corresponding author. E-mail address:  lfowler@gwu.edu (L.A. Fowler).http://dx.doi.org/10.1016/j.addbeh.2016.06.0080306-4603/© 2016 Elsevier Ltd. All rights reserved. Contents lists available at ScienceDirect Addictive Behaviors  journal homepage: www.elsevier.com/locate/addictbeh  2.3. Data synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283. Results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293.1. Description of studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293.1.1. Participants and setting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293.1.2. Type of intervention . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 313.1.3. Comparison and control groups . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 313.1.4. Intervention length & dosage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 313.1.5. Follow-up . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 323.2. Intervention effectiveness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 324. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 324.1. Summary of evidence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 324.2. Limitations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 324.3. Concluding remarks and future directions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32Role of funding sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33Con 󿬂 ict of interest . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33References. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 1. Introduction Misuseandabuseofalcoholremainsaseriouspublichealthconcern.Misuseof alcoholistheleading risk factorfor prematuredeathanddis-ability among people between the ages of 15 and 49 (Lim et al., 2012);nearlyaquarterofalldeathsamongthoseaged20to39areattributabletoalcohol(WorldHealthOrganization[WHO],2014a).Worldwide,16%ofdrinkersaged15yearsorolderengageinharmfulalcoholuse(WHO,2014b). Harmful drinking — drinking that causes damage to physicaland/or mental health — is associated with short-term risks such as inju-ries (e.g., motor vehicle crashes, drownings, and burns), violence (e.g.,homicide, suicide, and sexual assault) and risky sexual behaviors (e.g.,unprotected sex and multiple sex partners) as well as long-term riskssuch as mental health problems (e.g., depression and anxiety), poorschool performance, poor productivity and unemployment, familyproblems, and alcohol dependence or alcoholism (Centers for DiseaseControlandPrevention[CDC],2014).Currently,only15 – 25%ofindivid-uals with drinking problems seek treatment (National Institute onAlcohol Abuse and Alcoholism [NIAAA], 2014). There is an urgentneed for effective interventions that reduce or eliminate treatmentbarriers. 1.1. Traditional treatments Brief interventions (e.g. one-time brief interventions) and motiva-tional enhancements (e.g. in-person motivational interviewing,psychoeducationaltherapy)havebeenidenti 󿬁 edastwohighlyeffectiveformsofalcoholabusetreatment(Hester&Miller,2002).Forexample,ameta-analysis of 31 alcohol-related studies using motivationalinterviewing found a combined effect size (across measures and timepoints) of 0.22 (95% CI: 0.10, 0.34) for blood alcohol concentration and0.08 (95% CI:  − 0.02. 0.19) for alcohol-related problems (Hettema,Steele,&Miller,2005),indicatingthatmotivationalinterviewingcanre-duce alcohol consumption and alcohol-related consequences. Further-more, alcohol screenings and brief interventions have been shown tobeeffectiveamongnon-treatmentseekingpopulationsandacrossava-riety of settings (Moyer, Finney, Swearingen,& Vergun,2002).Infact, arecent review of systematic reviews found moderate effects of brief in-terventions among non-dependent alcohol users (Álvarez-Bueno,Rodríguez-Martín, García-Ortiz, Gómez-Marcos, & Martínez-Vizcaíno,2015). Cognitive-behavioral therapies are also highly effective attreating problem drinking (Nauert, 2012). Overall, both cognitive andbehavioral changes following these traditional alcohol treatments (i.e.,brief interventions, motivational enhancements, and cognitive behav-ioral therapies) have been widely documented in the literature(Samson & Tanner-Smith, 2015; Scott-Sheldon, Carey, Elliott, Garey, &Carey, 2014; Scott-Sheldon, Demartini, Carey, & Carey, 2009;Tanner-Smith&Lipsey,2015),and,importantly,theliteratureindicatesthat individuals accept these treatment modalities (Hungerford,Pollock, & Todd, 2000).Despitetheeffectivenessandacceptanceoftheseinterventions,sub-stantialbarriersexistintheimplementationofandaccesstotraditionalperson-deliveredinterventions.Theseinterventionsareresourceinten-sive, depend a great deal on the skill of the clinician (i.e.,  󿬁 delity to theintervention technique), cannot be simultaneously tailored to a largenumberofindividuals,lackwidespreadaccessibility,andarepotentiallystigmatizing. Barriers such asaccessibility andstigmamay help explainlow rates of treatment-seeking behaviors among problem drinkers.Traditionalinterventionsrequiresubstantialtimeandmoneyaswellas trained providers. For instance, cognitive-behavioral therapies typi-callyinvolve between10 and20 sessions(MayoClinic,2015)deliveredby a therapist with a doctorate or master's degree in a mental health,medical, or related  󿬁 eld (Beck Institute for Cognitive BehaviorTherapy, n.d.). Furthermore, motivational enhancements involve fourcarefully tailored treatment sessions that each last approximately 1 h(Miller, Zweben, DiClemente, & Rychtarik, 1992; Miller, 2000). Existingresearch has shown that tailored interventions are more effective thangroup and/or untailored interventions (Ryan & Lauver, 2002), particu-larly at promoting positive health behaviors such as quitting smoking(Copeland,Martin,Geiselman,Rash,&Kendzor,2006),reducingalcoholintake (Suffoletto et al., 2015), getting vaccinated (Gowda, Schaffer, Kopec, Markel, & Dempsey, 2013), being screened for breast cancer(Ishikawa et al., 2012), and taking multivitamins (Milan & White, 2010).Alimitationoftraditionalbehavioraltherapiesisthattheseinter-ventions, while effective for both individuals and groups, can be quiteresource intensive for group treatments (Center for Substance AbuseTreatment, 1999; Velasquez, Crouch, Stephens, & DiClemente, 2015).Duetotheirresourceintensity,traditionalbehavioralinterventionscan-not be easily and simultaneously tailored to large numbers of individ-uals. Furthermore, traditional behavioral therapies depend a great dealon the skill of the clinician/therapist. Therapeutic style forms the coreof motivational enhancement therapy (MET) and the therapist charac-teristic of   “ accurate empathy ”  has been shown to bea powerfulpredic-tor of therapeutic success with problem drinkers (Miller et al., 1992;Miller, 2000). Brief interventions require clinicians to possess speci 󿬁 cknowledge, skills, and abilities in order to be effective (Barry, 1999;U.S. Department of Health & Human Services, 2005). Most importantly,thelowratesoftreatment-seekingbehaviormaybeexplainedbyalackofaccesstocareand/orafailuretoseekwhatisoftenstigmatizedtreat-ment (Cunningham, Kypri, & McCambridge, 2011). For instance, in theUnitedStatesandCanada,adequateaccesstocognitive-behavioralther-apy remains a major barrier to improving clinical outcomes (Payne & 26  L.A. Fowler et al. / Addictive Behaviors 62 (2016) 25 –  34  Myhr,2010;Adelman,Panza,Bartley,Bontempo,&Bloch,2014).Evenif access to care was not an issue, research has shown that substance usedisorders are more stigmatized than other health conditions and thatstigma is a signi 󿬁 cant barrier for accessing substance abuse treatmentservices (Livingston, Milne, Fang, & Amari, 2012).Giventhenatureofthebarriersinherentintheseeffectivetradition-altreatmentmodalities,technology-basedinterventions(e.g.,computerand mobile technology) have an opportunity to complement or en-hance the effects of these established treatments among both clinicaland subclinical users of alcohol. Speci 󿬁 cally, mobile technology-basedinterventions provide a promising avenue for the widespread andcost-effective delivery of treatment that is accessible, affordable, de-pendable,individualized,anddestigmatizedtobothalcohol-dependentand nondependent drinkers. 1.2. Mobile technologies Mobile technology-based interventions are particularly well-suitedto address the aforementioned limitations of traditional interventionsand potentially complement or enhance established effective interven-tions. Mobile technology-based interventions utilize text messages,Webaccess,and/or mobileapplicationsand are delivered via platformssuchasmobilephones,smartphones,personaldigitalassistants (PDA),or tablets. Many of these interventions are founded on the same highlyeffectivepsychosocialtreatments(e.g.,briefinterventions,motivationalenhancement therapy, cue exposure therapy, cognitive-behavioraltherapy) as traditional interventions (Gustafson et al., 2014; Mason,Benotsch,Way, Kim,& Snipes,2014;Witkiewitz et al., 2014). However,these interventions have been modi 󿬁 ed to  󿬁 t within a portable elec-tronic format which provides distinct advantages over human-deliv-ered intervention approaches.Mobile technology-based interventions can be delivered with high 󿬁 delity — accurately and consistently, as srcinally speci 󿬁 ed by the de-velopers, in order to achieve intended outcomes — through automatedsystems that easily allow for message tailoring based on individualneeds and responses (Suffoletto, Callaway, Kristan, Kraemer, & Clark,2012; Weitzel, Bernhardt, Usdan, Mays, & Glanz, 2007). The  󿬁 delity of traditionalinterventionmethodsdependsontheabilityofthetherapistor clinician to deliver the intervention adequately and consistently(Mayo Clinic,2015; Miller et al., 1992) and in such a wayastodiscour-age the premature termination of treatmentby the client (Hogue et al.,2008;Horner,Rew,&Torres,2006).Mobiletechnologiesoffersolutionstothesechallengesbystandardizingtreatmentandassessmentdeliveryvia pre-programmed mobile application intervention modules and au-tomated text messages (Agyapong, Ahern, McLoughlin, & Farren,2012; Budman, Portnoy, & Villapiano, 2003; Substance Abuse andMental Health Services Administration (SAMHSA), 2015b). This notonly reduces the dependence on the therapist/clinician, but eases theburden on the client, thus encouraging the clients' continuation and/or completion of treatment. Furthermore, the automated and adaptivesystems employed by mobile technologies have the capacity to deliverpersonalized text messages to large numbers of people at low costs(Arbanowski et al., 2004; Gibbons, 2007; SAMHSA, 2015b); thiswould,forexample,allowmodi 󿬁 cationoffuturemessagesbasedonin-dividualbehavioraldifferencesreportedatbaselineorothertimepointsintheintervention.Forexample,participantsina6monthmobiletech-nology-based alcohol use intervention who report binge drinking be-havior at baseline might receive additional messages tailoredspeci 󿬁 cally to reduce binge drinking while those participants who donot report binge drinking behavior would not receive these messages.Other information collected at baseline, including demographic infor-mation, could be used to personalize text messages. Tailoring of mes-sages can also occur simultaneously as participants report theirbehavior and cognitionsatassessments duringtheintervention period.Forexample,participantswhoidentifyaspeci 󿬁 csetofpotentialbarriersto reducing their alcohol consumption on an assessment during theintervention period could then receive messages that address thosebarriers.Another bene 󿬁 t of mobile technology-based interventions isthat mobile applications can be easily and affordably downloaded(Free et al., 2013) and mobile phones are continuously dropping incost (Ben-Zeev et al., 2014). In fact, underserved populations in theUS now use smartphones as their primary method for accessing re-sources ontheinternet(Ben-Zeevetal.,2014).Giventhestigmasur-rounding both addiction and treatment, the anonymity afforded byinterventions that are delivered via text messaging and/or mobileapplications can be an important factor for seeking help throughthis modality (Savic, Best, Rodda, & Lubman, 2013; Heron & Smyth,2010). Most importantly, mobile technology is widely accessible toboth treatment-seeking and non-treatment-seeking populations.Approximately 85% of the world's population owns a mobile phoneand of those 75% use text messaging (Pew Research Center, 2012).Additionally, as of 2014, approximately 21% of the global populationowned a smartphone with an operating system capable of runningsoftware applications (Statista, 2015), making interventions utiliz-ing this modality increasingly convenient to access.Notably, however, mobile technology-based interventions mayhave limitations in regards to their application to vulnerable orhard-to-reach populations, such as prison inmates, individuals withdisabilities (e.g. blindness), severe clinical populations, low-incomepopulations, or older populations. Such populations may not haveaccess to mobile phones, may not use mobile phones, or may nothave the same mobile phone number for an extended period of time. Despite this, US government assistance programs increase ac-cessibility of basic cell phone and functions such as text messagingfor vulnerable populations (Ben-Zeev et al., 2014).Mobiletechnology-basedinterventionshavebeenestablishedasev-idence-based, recommended approaches towards substance use pre-vention by the CDC (Mason, Ola, Zaharakis, & Zhang, 2014). Over thepast decade, the development of interventions for substance use disor-ders that can be accessed and delivered via mobile technologies has in-creased rapidly (Litvin, Abrantes & Brown, 2013). Research has found ahighwillingnesstousemobiletechnologiesamongbothalcohol-depen-dent (Savic et al., 2013) and non-dependent (Sankaranarayanan & Sallach, 2014) populations and individuals perceive supportive textmessages as a useful aid in their recovery (Agyapong, Milnes,McLoughlin, & Farren, 2013). These interventions have the potential tobe particularly pertinent as they are available on the person at alltimes and provide opportunities for real-time monitoring and deliveryofsubstanceuseinterventionsinthecontextsinwhichtheyareneededmost (Giroux, Bacon, King, Dulin, & Gonzalez, 2014).Althoughthere havebeenseveralrecentreviews of mobiletechnol-ogies used in substance use interventions, they differ from the presentstudy.Forexample,Mason,Ola,etal.(2014)conductedameta-analysisof14randomizedcontrolledtrials(RCTs)thatwererestrictedtoadoles-cent and young adult users and focused exclusively on text messaginginterventions.Theauthorsconcludedthattextmessaginginterventionshave a small but reliable effect on reducing substance use behaviors.However, a majority of the studies (n = 11) tested intervention effectsontobaccousewhereasonlythreetestedinterventioneffectsonalcoholuse. Free et al. (2013) identi 󿬁 ed 26 trials in which various mobile tech-nologies(e.g.,mobilephone,PDA,MP3)wereusedtopromotebehaviorchange. Only onetrial, however, aimed to reducealcohol consumption.Thusthereisnoclearsensefromtheexistingliteraturewhethermobiletechnologies are effective at reducing alcohol misuse. 1.3. Purpose Giventhatalcoholmisuseratesaresohighandthatonlyafractionof theindividuals who misuse alcohol seek treatment via traditional ther-apies(anestimated7.6%ofalcoholabusers;SAMHSA,2015a),interven-tionsthatareabletoreachawidenumberofindividualsinaconvenient 27 L.A. Fowler et al. / Addictive Behaviors 62 (2016) 25 –  34  and non-threatening (i.e., destigmatizing) way are not only useful butnecessary. Mobile technologies provide a low-cost, high  󿬁 delity, andeasilytailoredmethodofdoingthis.Whatisunclearinthealcoholtreat-ment literature is the ef  󿬁 cacy of mobile technology interventions atchanging harmful drinking behavior among adults. The purpose of thissystematicreviewistopresentthecurrentstateoftheliteratureonmo-bile technology-based interventions for alcohol-related outcomesamong clinical and subclinical adults. 2. Methods  2.1. Selection of studies A systematic literature search was conducted following theguidelines established by PRISMA (Moher, Liberati, Tetzlaff,Altman,&ThePRISMAGroup,2009).DuringDecember2015,thefol-lowing databases were searched: PubMed, Web of Science,MEDLINE, PsycARTICLES, and PsycINFO. The last threedatabases — MEDLINE, PsycARTICLES, and PsycINFO — were searchedsimultaneously. Researchers D.J. and L.F. searched MEDLINE,PsycINFO, and PsycARTICLES; researchers S.H. and L.F. searchedPubMed; and S.H. and D.J. searched Web of Science. Each pair identi- 󿬁 ed the same number of records. Databases were searched in foursteps. The  󿬁 rst group of search terms were  “ mobile ”  OR   “ phone ”  OR  “ smart phone ”  OR   “ SMS ”  OR   “ text ”  OR   “ app. ”  This search was com-bined with the word AND and the next step of search terms:  “ inter-vention ”  OR   “ program ”  OR   “ treatment. ”  Likewise, the previoussearch was combined with the next grouping of terms:  “ substanceuse ”  OR   “ substance abuse ”  OR   “ addiction ”  OR   “ dependence. ”  Finally,thelaststepusedthewordANDtocombineallthestepswiththelastterm “ alcohol. ” Searcheswerelimited toarticles publishedintheEn-glish language, in peer reviewed journals, from January 2004 to De-cember 2015. A total of 642 records were identi 󿬁 ed usingequivalentsearchtermsacrossdatabases.Afterremovingduplicates,472 records (titles and abstracts) were screened for eligibility in thepresentreviewindependentlyandseparatelybytwomembersoftheresearch team before conferring. Any records that appeared relevantwere pulled for a fulltext review. This screening process was repeat-ed a second time to ensure that all eligible articles were identi 󿬁 ed.RefertoFig.1fora 󿬂 owchartsummarizingthefull inclusionprocess.  2.2. Inclusion criteria Studies were eligible for inclusion in the review if they includedadults who were at least 18 years of age and reported using alcohol.Further, to be included in the systematic review, the studies musthave:acomparisoncondition,anoutcomemeasureofalcoholreduc-tion, cessation, orabstinence maintenance, and the article had to de-scribe a text message or mobile application intervention deliveredthrough mobile technology, which includes tablets, mobile phones,smart phones, and PDAs. Excluded were studies with personal con-tact —  including telephone or in-person therapy components — inthe intervention to limit the review to mobile technology-deliveredinterventions.Nineteen full text articles were reviewed for inclusion and a total of six studies were identi 󿬁 ed as meeting the inclusion criteria. After this,each researcher conducted a manual search of the reference lists of each of these six articles for relevant studies, thus providing us twomore studies that met the eligibility criteria for a total of eight studies.Final inclusion decisions were discussed and agreed upon by allresearchers.  2.3. Data synthesis Due to the heterogeneity among study populations, interventiondesigns, and outcome measures across studies, a quantitative Fig. 1.  Flowchart of systematic review process.28  L.A. Fowler et al. / Addictive Behaviors 62 (2016) 25 –  34
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