BLEND-A: blending internet treatment into conventional face-to-face treatment for alcohol use disorder - a study protocol

Angelina Isabella Mellentin, Silke Behrendt, Randi Bilberg, Matthijs Blankers, Marie Paldam Folker, Kristine Tarp, Jakob Uffelmann, Anette Søgaard Nielsen, Angelina Isabella Mellentin, Silke Behrendt, Randi Bilberg, Matthijs Blankers, Marie Paldam Folker, Kristine Tarp, Jakob Uffelmann, Anette Søgaard Nielsen

Abstract

Background: A major challenge to psychological treatment for alcohol use disorder (AUD) is patient non-compliance. A promising new treatment approach that is hypothesized to increase patient compliance is blended treatment, consisting of face-to-face contact with a therapist combined with modules delivered over the internet within the same protocol. While this treatment concept has been developed and proven effective for a variety of mental disorders, it has not yet been examined for AUD.

Aims: The study described in this protocol aims to examine and evaluate patient compliance with blended AUD treatment as well as the clinical and cost effectiveness of such treatment compared to face-to-face treatment only.

Methods: The study design is a pragmatic, stepped-wedge cluster randomized controlled trial. The included outpatient institutions (planned number of patients: n = 1800) will be randomized in clusters to implement either blended AUD treatment or face-to-face treatment only, i.e. treatment as usual (TAU). Both treatment approaches consist of motivational interviewing and cognitive behavioral therapy. Data on sociodemographics, treatment (e.g. intensity, duration), type of treatment conclusion (compliance vs. dropout), alcohol consumption, addiction severity, consequences of drinking, and quality of life, will be collected at treatment entry, at treatment conclusion, and 6 months after treatment conclusion. The primary outcome is compliance at treatment conclusion, and the secondary outcomes include alcohol consumption and quality of life at six-months follow-up. Data will be analyzed with an Intention-to-treat approach by means of generalized linear mixed models with a random effect for cluster and fixed effect for each step. Also, analyses evaluating cost-effectiveness will be conducted.

Discussion: Blended treatment may increase treatment compliance and thus improve treatment outcomes due to increased flexibility of the treatment course. Since this study is conducted within an implementation framework it can easily be scaled up, and when successful, blended treatment has the potential to become an alternative offer in many outpatient clinics nationwide and internationally.

Trial registration: Clinicaltrials.gov .: NCT04535258 , retrospectively registered 01.09.20.

Keywords: Alcohol use disorder; Blended treatment; Cognitive behavior therapy; Guided internet-based treatment; Motivational interviewing.

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Enrollment of groups of participating institutions (clusters) to the BLEND-A intervantion

References

    1. NICE. National Institute for Health & Clinical Excellence: Diagnosis, assessment and management of harmful drinking and alcohol dependence. National Clinical Practice Guideline 115. Great Britain: The British Psychological Society and The Royal College of Psychiatrists; 2011.
    1. Authority DH. Kvalitet i alkoholbehandling – et rådgivningsmateriale. Copenhagen: Sundhedsstyrelsen; 2008. p. 33.
    1. Martin GW, Rehm J. The effectiveness of psychosocial modalities in the treatment of alcohol problems in adults: a review of the evidence. Can J Psychiatr. 2012;57(6):350–358. doi: 10.1177/070674371205700604.
    1. Rehm J, et al. Alcohol dependence and treatment utilization in Europe - a representative cross-sectional study in primary care. BMC Fam Pract. 2015;16:90. doi: 10.1186/s12875-015-0308-8.
    1. Degenhardt L, et al. Estimating treatment coverage for people with substance use disorders: an analysis of data from the world mental health surveys. World Psychiatry. 2017;16(3):299–307. doi: 10.1002/wps.20457.
    1. Koski-Janne A, Cunningham J. Interest in different forms of self-help in a general population sample of drinkers. Addict Behav. 2001;26(1):91–99. doi: 10.1016/S0306-4603(00)00092-7.
    1. Davies EL, et al. Intention to reduce drinking alcohol and preferred sources of support: an international cross-sectional study. J Subst Abus Treat. 2019;99:80–87. doi: 10.1016/j.jsat.2019.01.011.
    1. Wallhed Finn S, Bakshi AS, Andreasson S. Alcohol consumption, dependence, and treatment barriers: perceptions among nontreatment seekers with alcohol dependence. Subst Use Misuse. 2014;49(6):762–769. doi: 10.3109/10826084.2014.891616.
    1. Khadjesari Z, et al. Negotiating the ‘grey area between normal social drinking and being a smelly tramp’: a qualitative study of people searching for help online to reduce their drinking. Health Expect. 2015;18(6):2011–2020. doi: 10.1111/hex.12351.
    1. Probst C, et al. Alcohol use disorder severity and reported reasons not to seek treatment: a cross-sectional study in European primary care practices. Subst Abuse Treat Prev Policy. 2015;10:32. doi: 10.1186/s13011-015-0028-z.
    1. Nielsen B, Nielsen AS, Wraae O. Factors associated with compliance of alcoholics in outpatient treatment. J Nerv Ment Dis. 2000;188(2):101–107. doi: 10.1097/00005053-200002000-00006.
    1. Schwarz A-S, Nielsen B, Nielsen AS. Changes in profile of patients seeking alcohol treatment and treatment outcomes following policy changes. J Public Health. 2018;26(1):59-67.
    1. Andersson G. Internet-delivered psychological treatments. Annu Rev Clin Psychol. 2016;12:157–179. doi: 10.1146/annurev-clinpsy-021815-093006.
    1. Rogers MA, et al. Internet-delivered health interventions that work: systematic review of meta-analyses and evaluation of website availability. J Med Internet Res. 2017;19(3):e90. doi: 10.2196/jmir.7111.
    1. Andersson G. Internet interventions: past, present and future. Internet Interv. 2018;12:181–188. doi: 10.1016/j.invent.2018.03.008.
    1. Vlaescu G, et al. Features and functionality of the Iterapi platform for internet-based psychological treatment. Internet Interv. 2016;6:107–114. doi: 10.1016/j.invent.2016.09.006.
    1. Nielssen O, et al. Procedures for risk management and a review of crisis referrals from the MindSpot Clinic, a national service for the remote assessment and treatment of anxiety and depression. BMC Psychiatry. 2015;15(1):304. doi: 10.1186/s12888-015-0676-6.
    1. Riper H, et al. Effectiveness of guided and unguided low-intensity internet interventions for adult alcohol misuse: a meta-analysis. PLoS One. 2014;9(6):e99912. doi: 10.1371/journal.pone.0099912.
    1. Dedert EA, et al. Electronic interventions for alcohol misuse and alcohol use disorders: a systematic review. Ann Intern Med. 2015;163(3):205–214. doi: 10.7326/M15-0285.
    1. Donoghue K, et al. The effectiveness of electronic screening and brief intervention for reducing levels of alcohol consumption: a systematic review and meta-analysis. J Med Internet Res. 2014;16(6):e142. doi: 10.2196/jmir.3193.
    1. Kaner EF, et al. Personalised digital interventions for reducing hazardous and harmful alcohol consumption in community-dwelling populations. Cochrane Database Syst Rev. 2017;9:CD011479.
    1. Hedman E. Therapist guided internet delivered cognitive behavioural therapy. Bmj. 2014;348:g1977. doi: 10.1136/bmj.g1977.
    1. Riper H, et al. Effectiveness and treatment moderators of internet interventions for adult problem drinking: an individual patient data meta-analysis of 19 randomised controlled trials. PLoS Med. 2018;15(12):e1002714. doi: 10.1371/journal.pmed.1002714.
    1. Darvell MJ, Kavanagh DJ, Conolly JM. A qualitative exploration of internet-based treatment for comorbid depression and alcohol misuse. Internet Interv. 2015;2:174–183. doi: 10.1016/j.invent.2015.03.003.
    1. Wilhelmsen M, et al. Motivation to persist with internet-based cognitive behavioural treatment using blended care: a qualitative study. BMC Psychiatry. 2013;13:296. doi: 10.1186/1471-244X-13-296.
    1. Andersson G, Cuijpers P. Internet-based and other computerized psychological treatments for adult depression: a meta-analysis. Cogn Behav Ther. 2009;38(4):196–205. doi: 10.1080/16506070903318960.
    1. Richards D, Richardson T. Computer-based psychological treatments for depression: a systematic review and meta-analysis. Clin Psychol Rev. 2012;32(4):329–342. doi: 10.1016/j.cpr.2012.02.004.
    1. Sundstrom C, et al. High- versus low-intensity internet interventions for alcohol use disorders: results of a three-armed randomized controlled superiority trial. Addiction. 2020;115(5):863–874. doi: 10.1111/add.14871.
    1. Wentzel J, et al. Mixing online and face-to-face therapy: how to benefit from blended Care in Mental Health Care. JMIR Ment Health. 2016;3(1):e9. doi: 10.2196/mental.4534.
    1. Sundstrom C, et al. High-intensity therapist-guided internet-based cognitive behavior therapy for alcohol use disorder: a pilot study. BMC Psychiatry. 2017;17(1):197. doi: 10.1186/s12888-017-1355-6.
    1. Erbe D, et al. Blending face-to-face and internet-based interventions for the treatment of mental disorders in adults: systematic review. J Med Internet Res. 2017;19(9):e306. doi: 10.2196/jmir.6588.
    1. Vaart R, et al. Blending online therapy into regular face-to-face therapy for depression: content, ratio and preconditions according to patients and therapists using a Delphi study. BMC Psychiatry. 2014;14:355. doi: 10.1186/s12888-014-0355-z.
    1. Månsson KN, et al. Development and initial evaluation of an Internet-based support system for face-to-face cognitive behavior therapy: a proof of concept study. J Med Internet Res. 2013;15(12):e280. doi: 10.2196/jmir.3031.
    1. Smit F, et al. Modeling the cost-effectiveness of health care systems for alcohol use disorders: how implementation of eHealth interventions improves cost-effectiveness. J Med Internet Res. 2011;13(3):e56. doi: 10.2196/jmir.1694.
    1. van der Vaart R, et al. Blending online therapy into regular face-to-face therapy for depression: content, ratio and preconditions according to patients and therapists using a Delphi study. BMC Psychiatry. 2014;14:355. doi: 10.1186/s12888-014-0355-z.
    1. Kooistra LC, et al. Blended vs. face-to-face cognitive behavioural treatment for major depression in specialized mental health care: study protocol of a randomized controlled cost-effectiveness trial. BMC Psychiatry. 2014;14:290. doi: 10.1186/s12888-014-0290-z.
    1. Romijn G, et al. Cost-effectiveness of blended vs. face-to-face cognitive behavioural therapy for severe anxiety disorders: study protocol of a randomized controlled trial. BMC Psychiatry. 2015;15:311. doi: 10.1186/s12888-015-0697-1.
    1. Kemmeren LL, et al. Effectiveness of blended depression treatment for adults in specialised mental healthcare: study protocol for a randomised controlled trial. BMC Psychiatry. 2016;16:113. doi: 10.1186/s12888-016-0818-5.
    1. Kleiboer A, et al. European COMPARative effectiveness research on blended depression treatment versus treatment-as-usual (E-COMPARED): study protocol for a randomized controlled, non-inferiority trial in eight European countries. Trials. 2016;17(1):387. doi: 10.1186/s13063-016-1511-1.
    1. Siemer L, et al. Blended smoking cessation treatment: exploring measurement, levels, and predictors of adherence. J Med Internet Res. 2018;20(8):e246. doi: 10.2196/jmir.9969.
    1. Rozental A, et al. Negative effects of internet interventions: a qualitative content analysis of patients' experiences with treatments delivered online. Cogn Behav Ther. 2015;44(3):223–236. doi: 10.1080/16506073.2015.1008033.
    1. Newman MG, et al. A review of technology-assisted self-help and minimal contact therapies for drug and alcohol abuse and smoking addiction: is human contact necessary for therapeutic efficacy? Clin Psychol Rev. 2011;31(1):178–186. doi: 10.1016/j.cpr.2010.10.002.
    1. Topooco N, et al. Attitudes towards digital treatment for depression: a European stakeholder survey. Internet Interventions. 2017;8:1–9. doi: 10.1016/j.invent.2017.01.001.
    1. Tarp KHH, et al., Lessons learned from the processes of translating, developing, and implementing blended guided internet-based and face-to-face treatment of alcohol use disorder: experiences from the BLEND-A study pilot phase. 2020. .
    1. Chan A-W, et al. SPIRIT 2013 statement: defining standard protocol items for clinical trials. Ann Intern Med. 2013;158(3):200–207. doi: 10.7326/0003-4819-158-3-201302050-00583.
    1. Hemming K, Taljaard M, Grimshaw J. Introducing the new CONSORT extension for stepped-wedge cluster randomised trials. Trials. 2019;20(1):68. doi: 10.1186/s13063-018-3116-3.
    1. Hemming K, Lilford R, Girling AJ. Stepped-wedge cluster randomised controlled trials: a generic framework including parallel and multiple-level designs. Stat Med. 2015;34(2):181–196. doi: 10.1002/sim.6325.
    1. Schwarz A-S, Nielsen B, Nielsen AS. Changes in profile of patients seeking alcohol treatment and treatment outcomes following policy changes. J Public Health. 2018;26(1):59–67. doi: 10.1007/s10389-017-0841-0.
    1. Becker U, et al. KVALITET I ALKOHOLBEHANDLING - et rådgivningsmaterial [Quality in Treatment for Alcohol Dependence - advisory material]: Sundhedsstyrelsen, Center for Forebyggels [National Health Authorities]; 2008.
    1. Sundhedsstyrelsen . National Klinisk Retningslinje for behandling af alkoholafhængighed [in Danish] 2015.
    1. Kokkevi A, Hartgers C. "EuropASI: European adaptation of a multidimensional assessment instrument for drug and alcohol dependence". European Addiction Research. 1995;1(4):208-210.
    1. McLellan AT. et al, The fifth edition of the Addiction Severity Index. 1992;9(3):199–213.
    1. Babor TF, et al. AUDIT - The Alcohol Use Disorder Identification Test. Guidelines for use in Primary Care. 2. Switzerland: World Health Organization; 2001.
    1. Skinner HA, Allen BA. Alcohol dependence syndrome: measurement and validation. J Abnorm Psychol. 1982;91(3):199–209. doi: 10.1037/0021-843X.91.3.199.
    1. Skinner HA, Horn JL. Alcohol Dependence Scale (ADS) User's Guide. Ontario: Addiction Research Foundation; 1984. p. 76.
    1. Miller W, Tonigan J, Longabaugh R. The Drinker Inventory of Consequences (DrInC): An instrument for assessing adverse consequences of alcohol abuse. Test manual. 1995.
    1. Janssen MF, et al. Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient groups: a multi-country study. Qual Life Res. 2013;22(7):1717–1727. doi: 10.1007/s11136-012-0322-4.
    1. Janssen B, Szende A. In: Szende A, Janssen B, Cabases J, editors. Population Norms for the EQ-5D, in Self-Reported Population Health: An International Perspective based on EQ-5D. Dordrecht (NL): Springer Netherlands; 2014. p. 19–30.
    1. Brooke, J.J.U.e.i.i . SUS: a quick and dirty'usability. 1996. p. 189.
    1. REDCap. July 16th, 2014; Available from: .
    1. Titzler I, et al. Barriers and facilitators for the implementation of blended psychotherapy for depression: a qualitative pilot study of therapists' perspective. Internet Interv. 2018;12:150–164. doi: 10.1016/j.invent.2018.01.002.
    1. Hemming K, et al. The stepped wedge cluster randomised trial: rationale, design, analysis, and reporting. BMJ. 2015;350:h391. doi: 10.1136/bmj.h391.
    1. Husereau D, et al. Consolidated health economic evaluation reporting standards (CHEERS) statement. BMJ. 2013;346:f1049. doi: 10.1136/bmj.f1049.
    1. Ramsey SD, et al. Cost-effectiveness analysis alongside clinical trials II-an ISPOR good research practices task force report. Value Health. 2015;18(2):161–172. doi: 10.1016/j.jval.2015.02.001.
    1. Drummond M, Sculpher M. And K.C.e. al., Methods for the economic evaluation of health care programmes. 4th edition. Oxford: Oxford University Press; 2015.
    1. Sundhedsdatastyrelsen . Alkoholbehandlingen i Danmark 2014. 2016.
    1. Hemming K, Taljaard M. Sample size calculations for stepped wedge and cluster randomised trials: a unified approach. J Clin Epidemiol. 2016;69:137–146. doi: 10.1016/j.jclinepi.2015.08.015.
    1. Gainsbury S, Blaszczynski A. A systematic review of internet-based therapy for the treatment of addictions. Clin Psychol Rev. 2011;31(3):490–498. doi: 10.1016/j.cpr.2010.11.007.
    1. White A, et al. Online alcohol interventions: a systematic review. J Med Internet Res. 2010;12(5):e62. doi: 10.2196/jmir.1479.
    1. Postel MG, et al. Attrition in web-based treatment for problem drinkers. J Med Internet Res. 2011;13(4):e117. doi: 10.2196/jmir.1811.
    1. Riper H, et al. Effectiveness of E-self-help interventions for curbing adult problem drinking: a meta-analysis. J Med Internet Res. 2011;13(2):e42. doi: 10.2196/jmir.1691.
    1. Van Ballegooijen W, et al. Adherence to Internet-based and face-to-face cognitive behavioural therapy for depression: a meta-analysis. PLoS One. 2014;9(7):e100674. doi: 10.1371/journal.pone.0100674.
    1. Mohr DC, et al. Interest in behavioral and psychological treatments delivered face-to-face, by telephone, and by internet. Ann Behav Med. 2010;40(1):89–98. doi: 10.1007/s12160-010-9203-7.
    1. Nielsen AS. Behandlernes oplevelse af behandlingen af alkoholmisbrugere. En kvalitativ analyse. Nord Alkohol Narkotikatidskrift. 2003;20(3):315–331.
    1. Bornstein RFJPPR, Practice. The Dependent Patient: Diagnosis, Assessment, and Treatment. 2005;36(1):82.
    1. Leitner A, et al. Patients’ perceptions of risky developments during psychotherapy. Journal of Contemporary Psychotherapy. 2013;43(2):95–105. doi: 10.1007/s10879-012-9215-7.
    1. Ekstrom V, Johansson M. Sort of a nice distance: a qualitative study of the experiences of therapists working with internet-based treatment of problematic substance use. Addict Sci Clin Pract. 2019;14(1):44. doi: 10.1186/s13722-019-0173-1.
    1. Waller G, Turner H. Therapist drift redux: why well-meaning clinicians fail to deliver evidence-based therapy, and how to get back on track. Behav Res Ther. 2016;77:129–137. doi: 10.1016/j.brat.2015.12.005.

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