John Marsden1, Brian Eastwood2, Robert Ali3, Pete Burkinshaw4, Gagandeep Chohan5, Alex Copello5, Daniel Burn4, Michael Kelleher6, Luke Mitcheson6, Steve Taylor4, Nick Wilson7, Chris Whiteley8, Edward Day9. 1. Addictions Department, Institute of Psychiatry, King's College London, United Kingdom; South London and Maudsley NHS Mental Health Foundation Trust, United Kingdom; Alcohol, Drug and Tobacco Division, Health and Wellbeing Directorate, Public Health England, United Kingdom. Electronic address: john.marsden@kcl.ac.uk. 2. Addictions Department, Institute of Psychiatry, King's College London, United Kingdom; Alcohol, Drug and Tobacco Division, Health and Wellbeing Directorate, Public Health England, United Kingdom. 3. Drug and Alcohol Services South Australia and Discipline of Pharmacology, School of Medical Sciences, University of Adelaide, Australia. 4. Alcohol, Drug and Tobacco Division, Health and Wellbeing Directorate, Public Health England, United Kingdom. 5. Birmingham and Solihull NHS Mental Health Foundation Trust, United Kingdom. 6. Addictions Department, Institute of Psychiatry, King's College London, United Kingdom; South London and Maudsley NHS Mental Health Foundation Trust, United Kingdom; Alcohol, Drug and Tobacco Division, Health and Wellbeing Directorate, Public Health England, United Kingdom. 7. Blenheim CDP, United Kingdom. 8. East London NHS Foundation Trust, United Kingdom. 9. Addictions Department, Institute of Psychiatry, King's College London, United Kingdom; Birmingham and Solihull NHS Mental Health Foundation Trust, United Kingdom; School of Clinical & Experimental Medicine, University of Birmingham, United Kingdom.
Abstract
BACKGROUND: Convergent research reveals heterogeneity in substance use disorders (SUD). The Addiction Dimensions for Assessment and Personalised Treatment (ADAPT) is designed to help clinicians tailor therapies. METHODS: Multicentre study in 21 SUD clinics in London, Birmingham (England) and Adelaide (Australia). 132 clinicians rated their caseload on a beta version with 16 ordinal indicators of addiction severity, health and social problem complexity, and recovery strengths constructs. In Birmingham, two in-treatment outcomes were recorded after 15-months: 28-day drug use (Treatment Outcome Profile; n=703) and Global Assessment of Functioning (GAF; DSM-IV Axis V; n=695). Following item-level screening (inter-rater reliability [IRR]; n=388), exploratory structural equation models (ESEM), latent profile analysis (LPA), and mixed-effects regression evaluated construct, concurrent and predictive validity characteristics, respectively. RESULTS: 2467 patients rated (majority opioid or stimulant dependent, enrolled in opioid medication assisted or psychological treatment). IRR-screening removed two items and ESEM models identified and recalibrated remaining indicators (root mean square error of approximation 0.066 [90% confidence interval 0.055-0.064]). Following minor re-specification and satisfactory measurement invariance evaluation, ADAPT factor scores discriminated patients by sample, addiction therapy and drug use. LPA identified three patient sub-types: Class 1 (moderate severity, moderate complexity, high strengths profile; 46.9%); Class 2 (low severity, low complexity, high strengths; 25.4%) and Class 3 (high severity, high complexity, low strengths; 27.7%). Class 2 had higher GAF (z=4.30). Class 3 predicted follow-up drug use (z=2.02) and lower GAF (z=3.51). CONCLUSION: The ADAPT is a valid instrument for SUD treatment planning, clinical review and outcome evaluation. Scoring and application are discussed.
BACKGROUND: Convergent research reveals heterogeneity in substance use disorders (SUD). The Addiction Dimensions for Assessment and Personalised Treatment (ADAPT) is designed to help clinicians tailor therapies. METHODS: Multicentre study in 21 SUD clinics in London, Birmingham (England) and Adelaide (Australia). 132 clinicians rated their caseload on a beta version with 16 ordinal indicators of addiction severity, health and social problem complexity, and recovery strengths constructs. In Birmingham, two in-treatment outcomes were recorded after 15-months: 28-day drug use (Treatment Outcome Profile; n=703) and Global Assessment of Functioning (GAF; DSM-IV Axis V; n=695). Following item-level screening (inter-rater reliability [IRR]; n=388), exploratory structural equation models (ESEM), latent profile analysis (LPA), and mixed-effects regression evaluated construct, concurrent and predictive validity characteristics, respectively. RESULTS: 2467 patients rated (majority opioid or stimulant dependent, enrolled in opioid medication assisted or psychological treatment). IRR-screening removed two items and ESEM models identified and recalibrated remaining indicators (root mean square error of approximation 0.066 [90% confidence interval 0.055-0.064]). Following minor re-specification and satisfactory measurement invariance evaluation, ADAPT factor scores discriminated patients by sample, addiction therapy and drug use. LPA identified three patient sub-types: Class 1 (moderate severity, moderate complexity, high strengths profile; 46.9%); Class 2 (low severity, low complexity, high strengths; 25.4%) and Class 3 (high severity, high complexity, low strengths; 27.7%). Class 2 had higher GAF (z=4.30). Class 3 predicted follow-up drug use (z=2.02) and lower GAF (z=3.51). CONCLUSION: The ADAPT is a valid instrument for SUD treatment planning, clinical review and outcome evaluation. Scoring and application are discussed.
Authors: John Marsden; Mike Kelleher; Eilish Gilvarry; Luke Mitcheson; Zoë Hoare; Dyfrig Hughes; Jatinder Bisla; Angela Cape; Fiona Cowden; Edward Day; Jonathan Dewhurst; Rachel Evans; Andrea Hearn; Joanna Kelly; Natalie Lowry; Martin McCusker; Caroline Murphy; Robert Murray; Tracey Myton; Sophie Quarshie; Gemma Scott; Sophie Turner; Rob Vanderwaal; April Wareham Journal: Trials Date: 2022-08-19 Impact factor: 2.728
Authors: Joanne Neale; Silia Vitoratou; Emily Finch; Paul Lennon; Luke Mitcheson; Daria Panebianco; Diana Rose; John Strang; Til Wykes; John Marsden Journal: Drug Alcohol Depend Date: 2016-06-15 Impact factor: 4.492
Authors: John Marsden; Camille Goetz; Tim Meynen; Luke Mitcheson; Garry Stillwell; Brian Eastwood; John Strang; Nick Grey Journal: Contemp Clin Trials Commun Date: 2017-11-02
Authors: John Marsden; Camille Goetz; Tim Meynen; Luke Mitcheson; Garry Stillwell; Brian Eastwood; John Strang; Nick Grey Journal: EBioMedicine Date: 2018-02-02 Impact factor: 8.143