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Record W4412373205 · doi:10.1080/09687637.2025.2527640

‘I am somebody now’—exploring meanings and experiences of gaining employment among people in substance use disorder treatment

2025· article· en· W4412373205 on OpenAlexaff
Erlend Marius, Ingrid Amalia Havnes, Ronny Rene Raveen, June Ullevoldsæter Lystad, Espen Ajo Arnevik, Eline Borger Rognli

Bibliographic record

VenueDrugs Education Prevention and Policy · 2025
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsCentre for Addiction and Mental Health
FundersHelse Sør-Øst RHF
KeywordsSubstance usePsychologySubstance abuseSociologyPsychiatry

Abstract

fetched live from OpenAlex

Background Many individuals with severe Substance Use Disorders (SUD) want to work. This study explores the experiences of what gaining employment represents for patients receiving Individual Placement and Support (IPS) early in their SUD treatment.Methods Semi-structured interviews were conducted among 17 patients in specialized SUD treatment who received IPS through participating in a randomized trial. Interviews were thematically analyzed in an interdisciplinary group.Results The analysis generated three main themes: Employment promoting positive change in self-experience, where employment was described as improving well-being, confidence, health stability and awareness of personal challenges; Employment as a bridge for reconnecting with society, where work was experienced to enable social participation, feelings of usefulness and identity reconstruction; and Employment as a risk factor for destabilization and relapse showing how employment could have negative impacts, and potentially trigger substance use.Conclusion Gaining employment during SUD treatment can support both personal development and social integration but may also involve risks. Tailored employment support that responds to the complexities of SUD and is delivered through interwoven collaboration between health care and employment support services may improve treatment outcomes. This has important implications for future policy and service development and warrants further exploration.

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

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.086
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.032
GPT teacher head0.340
Teacher spread0.309 · 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

Machine predicted; a candidate call from one teacher head, not a consensus.

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

Citations2
Published2025
Admission routes1
Has abstractyes

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