Akbar, M., Egli, M., Cho, Y.-E., Song, B.-J., & Noronha, A. (2018). Medications for alcohol use disorders: An overview. Pharmacology & Therapeutics, 185, 64–85. https://doi.org/10.1016/j.pharmthera.2017.11.007.
Article
Google Scholar
Andersson, G., Titov, N., Dear, B. F., Rozental, A., & Carlbring, P. (2019). Internet-delivered psychological treatments: From innovation to implementation. World Psychiatry, 18(1), 20–28. https://doi.org/10.1002/wps.20610.
Article
Google Scholar
Andrews, D. A., Bonta, J., & Wormith, J. S. (2006). The recent past and near future of risk and/or need assessment. Crime and Delinquency, 52(1), 7.
Article
Google Scholar
AshaRani, P. V., Hombali, A., Seow, E., Ong, W. J., Tan, J. H., & Subramaniam, M. (2020). Non-pharmacological interventions for methamphetamine use disorder: A systematic review. Drug and Alcohol Dependence, 212, 108060.
Article
Google Scholar
Boden, J. M., & Fergusson, D. M. (2011). Alcohol and depression. Addiction, 106(5), 906–914.
Article
Google Scholar
Bonta, J., & Andrews, D. (2007). Risk-need-responsivity model for offender assessment and rehabilitation. Rehabilitation, 6, 1–22.
Google Scholar
Boumparis, N., Schulte, M. H. J., & Riper, H. (2019). Digital mental health for alcohol and substance use disorders. Current treatment options in psychiatry, 6(4), 352–366. https://doi.org/10.1007/s40501-019-00190-y.
Article
Google Scholar
Brady, K. T., & Sinha, R. (2005). Co-occurring mental and substance use disorders: The neurobiological effects of chronic stress. American Journal of Psychiatry, 162(8), 1483–1493. https://doi.org/10.1176/appi.ajp.162.8.1483.
Article
Google Scholar
Brecht, M.-L., & Herbeck, D. (2014). Time to relapse following treatment for methamphetamine use: A long-term perspective on patterns and predictors. Drug and Alcohol Dependence, 139, 18–25. https://doi.org/10.1016/j.drugalcdep.2014.02.702.
Article
Google Scholar
Carroll, K., Ball, S., Martino, S., Nich, C., Babuscio, T., & Rounsaville, B. (2009). Enduring effects of a computer-assisted training program for cognitive behavioral therapy: A 6-month follow-up of CBT4CBT. Drug and Alcohol Dependence, 100(1), 178–181.
Article
Google Scholar
Chen, Q., Sterner, G., Segel, J., & Feng, Z. (2022). Trends in opioid-related crime incidents and comparison with opioid overdose outcomes in the United States. International Journal of Drug Policy, 101, 103555. https://doi.org/10.1016/j.drugpo.2021.103555.
Article
Google Scholar
Chiang, M., Lombardi, D., Du, J., Makrum, U., Sitthichai, R., Harrington, A., … Fan, X. (2019). Methamphetamine-associated psychosis: Clinical presentation, biological basis, and treatment options. Human Psychopharmacology: Clinical and Experimental, 34(5), e2710.
Article
Google Scholar
Cumming, C., Kinner, S. A., McKetin, R., Li, I., & Preen, D. (2020). Methamphetamine use, health and criminal justice system outcomes: A systematic review. Drug and Alcohol Review, 39(5), 505–518. https://doi.org/10.1111/dar.13062.
Article
Google Scholar
Cumming, C., Troeung, L., Young, J. T., Kelty, E., & Preen, D. B. (2016). Barriers to accessing methamphetamine treatment: A systematic review and meta-analysis. Drug and Alcohol Dependence, 168, 263–273.
Article
Google Scholar
Davies, G., Elison, S., Ward, J., & Laudet, A. (2015). The role of lifestyle in perpetuating substance dependence: A new explanatory model, the lifestyle balance model. Substance Abuse Treatment, Prevention, and Policy, 10(2), e1–e18.
Google Scholar
Davies, G., Ward, J., Elison, S., Weston, S., Dugdale, S., & Weekes, J. (2017). Implementation and evaluation of the breaking free online and pillars of recovery treatment and recovery programmes for substance-involved offenders: Reflections from the north-west prisons ‘gateways’ pathfinder. Advancing Corrections, 3, 95–113.
Google Scholar
Deas, D., & Brown, E. S. (2006). Adolescent substance abuse and psychiatric comorbidities. Journal of Clinical Psychiatry, 67(7), e02. https://doi.org/10.4088/jcp.0706e02.
Article
Google Scholar
Donelan, C. J., Hayes, E., Potee, R. A., Schwartz, L., & Evans, E. A. (2021). COVID-19 and treating incarcerated populations for opioid use disorder. Journal of Substance Abuse Treatment, 124, 108216.
Article
Google Scholar
Dugdale, S., Elison, S., Davies, G., Ward, J., & Dalton, M. (2017). A qualitative study investigating the continued adoption of breaking free online across a national substance misuse organisation: Theoretical conceptualisation of staff perceptions. The Journal of Behavioral Health Services and Research, 44(1), 89–101. https://doi.org/10.1007/s11414-016-9512-0.
Article
Google Scholar
Dugdale, S., Ward, J., Hernen, J., Elison, S., Davies, G., & Donkor, D. (2016). Using the behavior change technique taxonomy v1 to conceptualize the clinical content of breaking free online: A computer-assisted therapy program for substance use disorders. Substance Abuse Treatment, Prevention, and Policy, 11(1), 26.
Article
Google Scholar
Elison, S., Davies, G., & Ward, J. (2016). Initial development and psychometric properties of a new measure of substance misuse ‘recovery progression’: The recovery progression measure (RPM). Substance Use and Misuse, 51(9), 1195–1206.
Article
Google Scholar
Elison, S., Dugdale, S., Ward, J., & Davies, G. (2017). The ‘rapid recovery progression measure’ (rapid-RPM) a brief assessment of psychosocial functioning change during problematic substance use recovery progression. Substance Use and Misuse, 52(9), 1160–1169.
Article
Google Scholar
Elison, S., Jones, A., Ward, J., Dugdale, S., & Davies, G. (2017). Examining effectiveness of tailorable computer-assisted therapy programmes for substance misuse: Programme usage and clinical outcomes data from breaking free online. Addictive Behaviors, 74, 140–147.
Article
Google Scholar
Elison, S., Ward, J., Davies, G., Lidbetter, N., Dagley, M., & Hulme, D. (2014). An outcomes study of eTherapy for dual diagnosis using breaking free online. Advances In Dual Diagnosis, 7(2), 52–62.
Article
Google Scholar
Elison, S., Ward, J., Williams, C., Espie, C., Davies, G., Dugdale, S., … Smith, K. (2017). Feasibility of a UK community-based, eTherapy mental health service in greater Manchester: Repeated-measures and between-groups study of ‘living life to the full interactive’, ‘Sleepio’ and ‘breaking free online’ at ‘self help services’. BMJ Open, 7(7), 1–10.
Article
Google Scholar
Elison, S., Weston, S., Davies, G., Dugdale, S., & Ward, J. (2015). Findings from mixed-methods feasibility and effectiveness evaluations of the “breaking free online” treatment and recovery programme for substance misuse in prisons. Drugs: Education, Prevention and Policy, 23(2), 1–10.
Google Scholar
Elison-Davies, S., Hayhurst, K., Jones, A., Welch, Z., Davies, G., & Ward, J. (2021). Associations between participant characteristics, digital intervention engagement and recovery outcomes for participants accessing ‘breaking free online’ at ‘change grow live’. Journal of Substance Use, 26(5), 497–504. https://doi.org/10.1080/14659891.2020.1851407.
Article
Google Scholar
Elison-Davies, S., Märtens, K., Yau, C., Davies, G., & Ward, J. (2021). Associations between baseline participant demographic, clinical and complexity characteristics on treatment outcomes for individuals accessing ‘breaking free online’, a computer-assisted therapy program for opioid use disorders. American Journal of Drug and Alcohol Abuse, 47(3), 360–372.
Article
Google Scholar
Goldsmid, S., & Willis, M. (2016). Methamphetamine use and acquisitive crime: Evidence of a relationship. Trends and Issues in Crime and Criminal Justice, 516, 1–14.
Google Scholar
Gossop, M., Best, D., Marsden, J., & Strang, J. (1997). Test–retest reliability of the severity of dependence scale. Addiction, 92(3), 353–353.
Article
Google Scholar
Hamilton, I. (2014). The 10 most important debates surrounding dual diagnosis. Advances In Dual Diagnosis, 7(3), 118–128. https://doi.org/10.1108/ADD-05-2014-0013.
Article
Google Scholar
Homer, B. D., Solomon, T. M., Moeller, R. W., Mascia, A., DeRaleau, L., & Halkitis, P. N. (2008). Methamphetamine abuse and impairment of social functioning: A review of the underlying neurophysiological causes and behavioral implications. Psychological Bulletin, 134(2), 301.
Article
Google Scholar
Joe, G. W., Rowan-Szal, G. A., Greener, J. M., Simpson, D. D., & Vance, J. (2010). Male methamphetamine-user inmates in prison treatment: During-treatment outcomes. Journal of Substance Abuse Treatment, 38(2), 141–152. https://doi.org/10.1016/j.jsat.2009.08.002.
Article
Google Scholar
Johnson, R. J., Ross, M. W., Taylor, W. C., Williams, M. L., Carvajal, R. I., & Peters, R. J. (2006). Prevalence of childhood sexual abuse among incarcerated males in county jail. Child Abuse and Neglect, 30(1), 75–86. https://doi.org/10.1016/j.chiabu.2005.08.013.
Article
Google Scholar
Jones, A. A., Gicas, K. M., Seyedin, S., Willi, T. S., Leonova, O., Vila-Rodriguez, F., … Vertinsky, A. T. (2020). Associations of substance use, psychosis, and mortality among people living in precarious housing or homelessness: A longitudinal, community-based study in Vancouver, Canada. PLoS medicine, 17(7), e1003172.
Article
Google Scholar
Juel, A., Kristiansen, C. B., Madsen, N. J., Munk-Jørgensen, P., & Hjorth, P. (2017). Interventions to improve lifestyle and quality-of-life in patients with concurrent mental illness and substance use. Nordic Journal of Psychiatry, 71(3), 197–204.
Article
Google Scholar
Kang, D., Fairbairn, C. E., & Ariss, T. A. (2019). A meta-analysis of the effect of substance use interventions on emotion outcomes. Journal of Consulting and Clinical Psychology, 87(12), 1106–1123. https://doi.org/10.1037/ccp0000450.
Article
Google Scholar
Kay-Lambkin, F. J., Baker, A. L., Lewin, T. J., & Carr, V. J. (2009). Computer-based psychological treatment for comorbid depression and problematic alcohol and/or cannabis use: A randomized controlled trial of clinical efficacy. Addiction, 104(3), 378–388. https://doi.org/10.1111/j.1360-0443.2008.02444.x.
Article
Google Scholar
Kotov, R., Gamez, W., Schmidt, F., & Watson, D. (2010). Linking "big" personality traits to anxiety, depressive, and substance use disorders: A meta-analysis. Psychological Bulletin, 136(5), 768–821. https://doi.org/10.1037/a0020327.
Article
Google Scholar
Krebs, A., D’Amato, C., Khade, N., Edgemon, T., Newsome, J., & Schweitzer Smith, M. (2021). Survey of Correctional Agencies to Determine the Impact of the COVID-19 Pandemic: University of Cincinnati.
Kroenke, K., Spitzer, R. L., Williams, J. B., & Löwe, B. (2009). An ultra-brief screening scale for anxiety and depression: The PHQ–4. Psychosomatics, 50(6), 613–621.
Google Scholar
Lanesman, T. H., Gouse, H., Bantjes, J., Stein, D. J., & Lochner, C. (2019). Correlates and predictors of impulsivity in adults with methamphetamine use disorder. Journal of Substance Use, 24(4), 361–367. https://doi.org/10.1080/14659891.2019.1572803.
Article
Google Scholar
Lee, N. K., & Rawson, R. A. (2008). A systematic review of cognitive and behavioural therapies for methamphetamine dependence [10.1080/09595230801919494]. Drug and Alcohol Review, 27(3), 309–317. https://doi.org/10.1080/09595230801919494.
Article
Google Scholar
Liu, Y., Hao, B., Shi, Y., Xue, L., Wang, X., Chen, Y., & Zhao, H. (2017). Violent offences of methamphetamine users and dilemmas of forensic psychiatric assessment. Forensic Sciences Research, 2(1), 11–17.
Article
Google Scholar
Maltman, K., Savic, M., Manning, V., Dilkes-Frayne, E., Carter, A., & Lubman, D. I. (2020). ‘Holding on’and ‘letting go’: A thematic analysis of Australian parent’s styles of coping with their adult child’s methamphetamine use. Addiction Research & Theory, 28(4), 345–353.
Article
Google Scholar
Mattila, E., Lappalainen, R., Välkkynen, P., Sairanen, E., Lappalainen, P., Karhunen, L., … Ermes, M. (2016). Usage and dose response of a Mobile acceptance and commitment therapy app: Secondary analysis of the intervention arm of a randomized controlled trial. JMIR mHealth and uHealth, 4(3), e90.
Article
Google Scholar
McKetin, R., Boden, J., Foulds, J., Najman, J., Ali, R., Degenhardt, L., … Weatherburn, D. (2020). The contribution of methamphetamine use to crime: Evidence from Australian longitudinal data. Drug and Alcohol Dependence, 216, 108262. https://doi.org/10.1016/j.drugalcdep.2020.108262.
Article
Google Scholar
McKetin, R., Kothe, A., Baker, A., Lee, N., Ross, J., & Lubman, D. (2018). Predicting abstinence from methamphetamine use after residential rehabilitation: Findings from the methamphetamine treatment evaluation study [10.1111/dar.12528]. Drug and Alcohol Review, 37(1), 70–78. https://doi.org/10.1111/dar.12528.
Article
Google Scholar
McKetin, R., Leung, J., Stockings, E., Huo, Y., Foulds, J., Lappin, J., … Degenhardt, L. (2019). Mental health outcomes associated with of the use of amphetamines: A systematic review and meta-analysis. EClinical Medicine, 16, 81–97.
Article
Google Scholar
Michie, S., Richardson, M., Johnston, M., Abraham, C., Francis, J., Hardeman, W., … Wood, C. E. (2013). The behavior change technique taxonomy (v1) of 93 hierarchically clustered techniques: Building an international consensus for the reporting of behavior change interventions. Annals of Behavioral Medicine, 46(1), 81–95.
Article
Google Scholar
Monaghesh, E., & Hajizadeh, A. (2020). The role of telehealth during COVID-19 outbreak: A systematic review based on current evidence. BMC Public Health, 20(1), 1193. https://doi.org/10.1186/s12889-020-09301-4.
Article
Google Scholar
Moos, R. H. (2007). Theory-based active ingredients of effective treatments for substance use disorders. Drug and Alcohol Dependence, 88(2), 109–121.
Article
Google Scholar
Moxley, V. B. A., Hoj, T. H., & Novilla, M. L. B. (2020). Predicting homelessness among individuals diagnosed with substance use disorders using local treatment records. Addictive Behaviors, 102, 106160. https://doi.org/10.1016/j.addbeh.2019.106160.
Article
Google Scholar
Potvin, S., Pelletier, J., Grot, S., Hébert, C., Barr, A. M., & Lecomte, T. (2018). Cognitive deficits in individuals with methamphetamine use disorder: A meta-analysis. Addictive Behaviors, 80, 154–160. https://doi.org/10.1016/j.addbeh.2018.01.021.
Article
Google Scholar
Radtke, T., Ostergaard, M., Cooke, R., & Scholz, U. (2017). Web-based alcohol intervention: Study of systematic attrition of heavy drinkers. Journal of Medical Internet Research, 19(6), e217.
Article
Google Scholar
Robinson, J., Sareen, J., Cox, B. J., & Bolton, J. M. (2011). Role of self-medication in the development of comorbid anxiety and substance use disorders: A longitudinal investigation. Archives of General Psychiatry, 68(8), 800.
Article
Google Scholar
Rubenis, A. J., Baker, A. L., & Arunogiri, S. (2021). Methamphetamine use and technology-mediated psychosocial interventions: A mini-review. Addictive Behaviors, 121, 106881. https://doi.org/10.1016/j.addbeh.2021.106881.
Article
Google Scholar
Šefránek, M., & Miovský, M. (2017). Treatment outcome evaluation in therapeutic communities in the Czech Republic: Changes in methamphetamine use and related problems one year after discharge. Journal of Groups in Addiction & Recovery, 12(2–3), 68–85. https://doi.org/10.1080/1556035X.2017.1280718.
Article
Google Scholar
Semple, S. J., Zians, J., Strathdee, S. A., & Patterson, T. L. (2008). Methamphetamine-using felons: Psychosocial and behavioral characteristics. American Journal on Addictions, 17(1), 28–35. https://doi.org/10.1080/10550490701756294.
Article
Google Scholar
Siefried, K. J., Acheson, L. S., Lintzeris, N., & Ezard, N. (2020). Pharmacological treatment of methamphetamine/amphetamine dependence: A systematic review. CNS Drugs, 34(4), 337–365. https://doi.org/10.1007/s40263-020-00711-x.
Article
Google Scholar
Şimşek, M., Dinç, M., & Ögel, K. (2019). Determinants of the addiction treatment drop-out rates in an addiction counseling Centre: A cross-sectional study. Psychiatry and Clinical Psychopharmacology, 29(4), 446–454. https://doi.org/10.1080/24750573.2018.1505283.
Article
Google Scholar
Skevington, S. M., Lotfy, M., & O'Connell, K. A. (2004). The World Health Organization's WHOQOL-BREF quality of life assessment: Psychometric properties and results of the international field trial. A report from the WHOQOL group. Quality of Life Research, 13(2), 299–310.
Article
Google Scholar
Sundström, C., Gajecki, M., Johansson, M., Blankers, M., Sinadinovic, K., Stenlund-Gens, E., & Berman, A. H. (2016). Guided and unguided internet-based treatment for problematic alcohol use – A randomized controlled pilot trial. PLoS One, 11(7), e0157817. https://doi.org/10.1371/journal.pone.0157817.
Article
Google Scholar
Torous, J., Lipschitz, J., Ng, M., & Firth, J. (2020). Dropout rates in clinical trials of smartphone apps for depressive symptoms: A systematic review and meta-analysis. Journal of Affective Disorders, 263, 413–419.
Article
Google Scholar
Wang, L., Weiss, J., Ryan, E. B., Waldman, J., Rubin, S., & Griffin, J. L. (2021). Telemedicine increases access to buprenorphine initiation during the COVID-19 pandemic. Journal of Substance Abuse Treatment, 124, 108272. https://doi.org/10.1016/j.jsat.2020.108272.
Article
Google Scholar
Ward, J., Elison-Davies, S., Davies, G., Dugdale, S., & Jones, A. (2019). Clinical and demographic patient characteristics, alcohol treatment goal preference and goal attainment during computer-assisted therapy with breaking free online. Journal of Substance Use, 24(6), 681–687.
Article
Google Scholar
Wiesner, M., Kim, H. K., & Capaldi, D. M. (2005). Developmental trajectories of offending: Validation and prediction to young adult alcohol use, drug use, and depressive symptoms. Development and Psychopathology, 17(1), 251–270. https://doi.org/10.1017/s0954579405050133.
Article
Google Scholar
Williams, C., & Garland, A. (2002). A cognitive–behavioural therapy assessment model for use in everyday clinical practice. Advances in Psychiatric Treatment, 8(3), 172–179.
Article
Google Scholar
Center for Behavioral Health Statistics and Quality. (2020). Results from the 2019 National Survey on drug use and health. https://www.samhsa.gov/data/
Dadhe, G., & Bettman, C. (2019). The lived experiences of adult crystal methamphetamine users: A qualitative study. Psychotherapy and Counselling Journal of Australia, 7(1), e1.
Elison-Davies, S., Wardell, J., Quilty, L., Ward, J., & Davies, G. (2021). Examining correlates of cannabis users’ engagement with a digital intervention for substance use disorder: An observational study of clients in UK services delivering ‘breaking free online’. Journal of Substance Abuse Treatment, 123(4), e1.
Eysenbach, G. (2005). The law of attrition. Journal of Medical Internet Research, 7(1), e1.
Office for Health Improvement and Disparities. (2021). National statistics: Adult substance misuse treatment statistics 2020 to 2021 - report. https://www.gov.uk/government/statistics/substance-misuse-treatment-for-adults-statistics-2020-to-2021/adult-substance-misuse-treatment-statistics-2020-to-2021-report