A Qualitative Study Investigating the Continued Adoption of Breaking Free Online Across a National Substance Misuse Organisation: Theoretical Conceptualisation of Staff Perceptions

  • Stephanie DugdaleEmail author
  • Sarah Elison
  • Glyn Davies
  • Jonathan Ward
  • Martha Dalton


There is evidence for the effectiveness of computer-assisted therapies (CAT) in healthcare; however, implementing CAT can be challenging due to new technologies being perceived as ‘disruptive’. This study used normalisation process theory (NPT) to investigate how Breaking Free Online (BFO), a treatment programme for substance misuse, is embedded as normal practice within Crime Reduction Initiatives (CRI), a health and social care charity. Interviews were conducted with CRI staff regarding their perceptions of the normalisation of BFO. Thematic analyses were used and findings structured around NPT. Results suggest that staff understood the benefits of BFO, particularly for those with a dual diagnosis. However, there was some confusion surrounding job roles and difficulties with the availability of resources. Whilst normalisation of BFO is progressing within CRI, there are still some challenges. Clarification of the roles of staff and peer mentors is an area in which further work is being conducted.


Staff Member Service User Normalisation Process Substance Misuse Normalisation Process Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Compliance with Ethical Standards

Competing Interests

Mrs Stephanie Dugdale, Dr Sarah Elison, Mr Glyn Davies and Dr Jonathan Ward are all employees of Breaking Free Online where the Breaking Free Online treatment programme has been developed.

Authors’ Contributions

SD developed the interview schedule and conducted all interviews, in addition to analysing the data and drafting the manuscript content. SE advised on data analyses, manuscript contents and editorial amendments. GD and JW provided guidance on manuscript content and advised on amendments and edits. MD provided final editorial amendments prior to the final manuscript submission. All authors read and approved the manuscript before submission.


  1. 1.
    Carroll K, Ball S, Martino S, et al. Computer-assisted delivery of cognitive-behavioral therapy for addiction: A randomized trial of CBT4CBT. The American Journal of Psychiatry. 2008;165(7):881–888.Google Scholar
  2. 2.
    Elison S, Humphreys L, Ward J, et al. A Pilot Outcomes Evaluation for Computer Assisted Therapy for Substance Misuse- An Evaluation of Breaking Free Online. Journal of Substance Use. 2013;19(4):1–6.Google Scholar
  3. 3.
    Elison S, Ward J, Davies G, et al. An outcomes study of eTherapy for dual diagnosis using Breaking Free Online. Advances in Dual Diagnosis. 2014;7(2):52–62.CrossRefGoogle Scholar
  4. 4.
    Elison S, Ward J, Davies G, et al. Implementation of computer-assisted therapy for substance misuse: a qualitative study of Breaking Free Online using Roger’s diffusion of innovation theory. Drugs and Alcohol Today. 2014;14(4):207–218.CrossRefGoogle Scholar
  5. 5.
    Elison S, Davies G, Ward J. Sub-group analyses of a heterogeneous sample of service users accessing computer-assisted therapy (CAT) for substance dependence using Breaking Free Online. Journal of Medical Internet Research. 2015;2(2):e13.Google Scholar
  6. 6.
    Kay-Lambkin FJ, Baker AL, Lewin TJ, et al. Computer-based psychological treatment for comorbid depression and problematic alcohol and/or cannabis use: a randomized controlled trial of clinical efficacy. Addiction. 2009;104(3):378–388.CrossRefPubMedGoogle Scholar
  7. 7.
    Kay-Lambkin F, Baker A, Lewin T, et al. Acceptability of a Clinician-Assisted Computerized Psychological Intervention for Comorbid Mental Health and Substance Use Problems: Treatment Adherence Data from a Randomized Controlled Trial. Journal of Medical Internet Research. 2011;13(1):254–264.CrossRefGoogle Scholar
  8. 8.
    Carroll KM, Rounsaville BJ. Computer-assisted therapy in psychiatry: Be brave—it’s a new world. Current Psychiatry Reports. 2010;12(5):426–432.CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Andrews G, Cuijpers P, Craske MG, et al. Computer therapy for the anxiety and depressive disorders is effective, acceptable and practical health care: a meta-analysis. PloS one. 2010;5(10):e13196.CrossRefPubMedPubMedCentralGoogle Scholar
  10. 10.
    Kaltenthaler E, Brazier J, De Nigris E, et al. Computerised cognitive behaviour therapy for depression and anxiety update: a systematic review and economic evaluation. Health Technology Assessment. 2006;10(33):1–186.CrossRefGoogle Scholar
  11. 11.
    Edmondson AC, Bohmer RM, Pisano GP. Disrupted routines: Team learning and new technology implementation in hospitals. Administrative Science Quarterly. 2001;46(4):685–716.CrossRefGoogle Scholar
  12. 12.
    Rogers E. Diffusion of innovations. New York: Simon and Schuster; 1995.Google Scholar
  13. 13.
    Rogers E. Diffusion of preventive innovations. Addictive Behaviors. 2002;27(6):989–993.CrossRefPubMedGoogle Scholar
  14. 14.
    Rogers E. A Prospective and Retrospective Look at the Diffusion Model. Journal of Health Communication. 2004;9(sup1):13–19.Google Scholar
  15. 15.
    Barnett J, Vasileiou K, Djemil F, et al. Understanding innovators’ experiences of barriers and facilitators in implementation and diffusion of healthcare service innovations: a qualitative study. BMC Health Services Research. 2011;11(1):342.CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Craig P, Dieppe P, Macintyre S, et al. Developing and evaluating complex interventions: the new Medical Research Council guidance. BMJ. 2008;337(sep29_1):a1655-a1655.Google Scholar
  17. 17.
    Simpson DD, Dansereau DF. Assessing organizational functioning as a step toward innovation. Science & Practice Perspectives. 2007;3(2):20–28.CrossRefGoogle Scholar
  18. 18.
    May C, Finch T, Mair F, et al. Understanding the implementation of complex interventions in health care: the normalization process model. BMC Health Services Research. 2007;7(1):148.CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Mair FS, May C, O’Donnell C, et al. Factors that promote or inhibit the implementation of e-health systems: an explanatory systematic review. Bulletin of the World Health Organization. 2012;90(5):357–364.CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Lewin S, Glenton C, Oxman AD. Use of qualitative methods alongside randomised controlled trials of complex healthcare interventions: Methodological study. BMJ. 2009;339.Google Scholar
  21. 21.
    Oakley A, Strange V, Bonell C, et al. Health services research: process evaluation in randomised controlled trials of complex interventions. BMJ. 2006;332(7538):413.CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    NVivo 10. NVivo qualitative data analysis software; QSR Internation Pty, Limited. Version 10, 2012. 2012.Google Scholar
  23. 23.
    Braun V, Clarke V. Using thematic analysis in psychology. Qualitative Research in Psychology. 2006;3(2):77–101.CrossRefGoogle Scholar
  24. 24.
    Amering M, Schmolke M. Recovery in mental health: reshaping scientific and clinical responsibilities. Vol 7: John Wiley & Sons; 2009.Google Scholar
  25. 25.
    Flores PJ. Addiction as an attachment disorder: Implications for group therapy. International Journal of Group Psychotherapy. 2001;51(1: Special issue):63–81.Google Scholar
  26. 26.
    Flores PJ. Group psychotherapy with addicted populations: An integration of twelve-step and psychodynamic theory. New York: Routledge; 2013.Google Scholar
  27. 27.
    Miller WR, Sorensen JL, Selzer JA, et al. Disseminating evidence-based practices in substance abuse treatment: A review with suggestions. Journal of Substance Abuse Treatment. 2006;31(1):25–39.CrossRefPubMedGoogle Scholar
  28. 28.
    Cohen WM, Levinthal DA. Absorptive capacity: a new perspective on learning and innovation. Administrative Science Quarterly. 1990:128–152.Google Scholar
  29. 29.
    White WL. Recovery: Its history and renaissance as an organizing construct concerning alcohol and other drug problems. Alcohol Treatment Quarterly. 2005;23(1):3–15.CrossRefGoogle Scholar
  30. 30.
    White WL. Peer-based Addiction Recovery Support- History, Theory, Practice, and Scientific Evaluation. Counselor. 2009;10(5):54–59.Google Scholar
  31. 31.
    Murray E, Treweek S, Pope C, et al. Normalisation process theory: a framework for developing, evaluating and implementing complex interventions. BMC Medicine. 2010;8(1):63.CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Doughty C, Tse S. Can consumer-led mental health services be equally effective? An integrative review of CLMH services in high-income countries. Community Mental Health Journal. 2011;47(3):252–266.CrossRefPubMedGoogle Scholar
  33. 33.
    Nilsen ES, Myrhaug HT, Johansen M, et al. Methods of consumer involvement in developing healthcare policy and research, clinical practice guidelines and patient information material. Cochrane Database of Systematic Reviews. 2006;3.Google Scholar
  34. 34.
    Best D, Laudet A. The potential of recovery capital. London: RSA; 2010.Google Scholar
  35. 35.
    Burns J, Marks D. Can Recovery Capital Predict Addiction Problem Severity? Alcohol Treatment Quarterly. 2013;31(3):303–320.CrossRefGoogle Scholar
  36. 36.
    Peele S, Brodsky A. The Truth About Addiction and Recovery. New York: Simon and Schuster; 1991.Google Scholar
  37. 37.
    Dugdale S, Elison S, Davies G, et al. Using the Transtheoretical Model to explore the impact of peer mentoring on peer mentors’ own recovery from substance misuse. Journal of Groups in Addiction and Recovery. Accepted.Google Scholar

Copyright information

© National Council for Behavioral Health 2016

Authors and Affiliations

  • Stephanie Dugdale
    • 1
    Email author
  • Sarah Elison
    • 1
  • Glyn Davies
    • 1
  • Jonathan Ward
    • 1
  • Martha Dalton
    • 2
  1. 1.Breaking Free OnlineManchesterUK
  2. 2.Crime Reduction InitiativesLeedsUK

Personalised recommendations