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Record W2555597190 · doi:10.1108/jcrpp-09-2016-0021

Using the “recovery” and “rehabilitation” paradigms to support desistance of substance-involved offenders: exploration of dual and multi-focus interventions

2016· article· en· W2555597190 on OpenAlexaff
Sarah Elison, Glyn Davies, Jonathan Ward, Samantha Weston, Stephanie Dugdale, John R. Weekes

Bibliographic record

VenueJournal of Criminological Research Policy and Practice · 2016
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsCarleton University
Fundersnot available
KeywordsPsychological interventionDual diagnosisRehabilitationSubstance usePsychologyIntervention (counseling)Substance abuseDual (grammatical number)RecidivismPsychotherapistPsychiatry

Abstract

fetched live from OpenAlex

Purpose The links between substance use and offending are well evidenced in the literature, and increasingly, substance misuse recovery is being seen as a central component of the process of rehabilitation from offending, with substance use identified as a key criminogenic risk factor. In recent years, research has demonstrated the commonalities between recovery and rehabilitation, and the possible merits of providing interventions to substance-involved offenders that address both problematic sets of behaviours. The purpose of this paper is to provide an overview of the links between substance use and offending, and the burgeoning literature around the parallel processes of recovery and rehabilitation. Design/methodology/approach This is provided as a rationale for a new treatment approach for substance-involved offenders, Breaking Free Online (BFO), which has recently been provided as part of the “Gateways” throughcare pathfinder in a number of prisons in North-West England. The BFO programme contains specific behaviour change techniques that are generic enough to be applied to change a wide range of behaviours, and so is able to support substance-involved offenders to address their substance use and offending simultaneously. Findings This dual and multi-target intervention approach has the potential to address multiple, associated areas of need simultaneously, streamlining services and providing more holistic support for individuals, such as substance-involved offenders, who may have multiple and complex needs. Practical implications Given the links between substance use and offending, it may be beneficial to provide multi-focussed interventions that address both these behaviours simultaneously, in addition to other areas of multiple and complex needs. Specifically, digital technologies may provide an opportunity to widen access to such multi-focussed interventions, through computer-assisted therapy delivery modalities. Additionally, using digital technologies to deliver such interventions can provide opportunities for joined-up care by making interventions available across both prison and community settings, following offenders on their journey through the criminal justice system. Originality/value Recommendations are provided to other intervention developers who may wish to further contribute to widening access to such dual- and multi-focus programmes for substance-involved offenders, based on the experiences developing and evidencing the BFO programme.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designmedium
models splitAgreement compares identical category sets and study designs across arms.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.376
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.688
GPT teacher head0.554
Teacher spread0.134 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2016
Admission routes1
Has abstractyes

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