Development of the Addiction Dimensions for Assessment and Personalised Treatment (ADAPT)

John Marsden; Brian Eastwood; Robert Ali; Pete Burkinshaw; Gagandeep Chohan; Alex Copello; Daniel Burn; Michael Kelleher; Luke Mitcheson; Steve Taylor; Nick Wilson; Chris Whiteley; Edward Day

doi:10.1016/j.drugalcdep.2014.03.018

Development of the Addiction Dimensions for Assessment and Personalised Treatment (ADAPT)

John Marsden^*, Brian Eastwood, Robert Ali, Pete Burkinshaw, Gagandeep Chohan, Alex Copello, Daniel Burn, Michael Kelleher, Luke Mitcheson, Steve Taylor, Nick Wilson, Chris Whiteley, Edward Day

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

28 Citations (Scopus)

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.

Original language	English
Pages (from-to)	121-131
Number of pages	11
Journal	Drug and alcohol dependence
Volume	139
DOIs	https://doi.org/10.1016/j.drugalcdep.2014.03.018
Publication status	Published - 1 Jun 2014

Keywords

ADAPT
Substance use disorder
Treatment
Assessment
Personalised
SUBSTANCE-USE DISORDERS
TREATMENT OUTCOMES
SEVERITY INDEX
MODEL
SCALE
INVOLVEMENT
PERFORMANCE
SERVICES
SMOKING
HEROIN

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.drugalcdep.2014.03.018

Cite this

@article{c9dbb73490fa48d4ab24578cacf71ba9,

title = "Development of the Addiction Dimensions for Assessment and Personalised Treatment (ADAPT)",

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.",

keywords = "ADAPT, Substance use disorder, Treatment, Assessment, Personalised, SUBSTANCE-USE DISORDERS, TREATMENT OUTCOMES, SEVERITY INDEX, MODEL, SCALE, INVOLVEMENT, PERFORMANCE, SERVICES, SMOKING, HEROIN",

author = "John Marsden and Brian Eastwood and Robert Ali and Pete Burkinshaw and Gagandeep Chohan and Alex Copello and Daniel Burn and Michael Kelleher and Luke Mitcheson and Steve Taylor and Nick Wilson and Chris Whiteley and Edward Day",

year = "2014",

month = jun,

day = "1",

doi = "10.1016/j.drugalcdep.2014.03.018",

language = "English",

volume = "139",

pages = "121--131",

journal = "Drug and alcohol dependence",

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T1 - Development of the Addiction Dimensions for Assessment and Personalised Treatment (ADAPT)

AU - Marsden, John

AU - Eastwood, Brian

AU - Ali, Robert

AU - Burkinshaw, Pete

AU - Chohan, Gagandeep

AU - Copello, Alex

AU - Burn, Daniel

AU - Kelleher, Michael

AU - Mitcheson, Luke

AU - Taylor, Steve

AU - Wilson, Nick

AU - Whiteley, Chris

AU - Day, Edward

PY - 2014/6/1

Y1 - 2014/6/1

N2 - 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.

AB - 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.

KW - ADAPT

KW - Substance use disorder

KW - Treatment

KW - Assessment

KW - Personalised

KW - SUBSTANCE-USE DISORDERS

KW - TREATMENT OUTCOMES

KW - SEVERITY INDEX

KW - MODEL

KW - SCALE

KW - INVOLVEMENT

KW - PERFORMANCE

KW - SERVICES

KW - SMOKING

KW - HEROIN

U2 - 10.1016/j.drugalcdep.2014.03.018

DO - 10.1016/j.drugalcdep.2014.03.018

M3 - Article

SN - 0376-8716

VL - 139

SP - 121

EP - 131

JO - Drug and alcohol dependence

JF - Drug and alcohol dependence

ER -

Development of the Addiction Dimensions for Assessment and Personalised Treatment (ADAPT)

Abstract

Keywords

UN SDGs

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