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Record W4296261051 · doi:10.1111/inm.13066

Concept analysis of recovery from substance use

2022· article· en· W4296261051 on OpenAlexaff
Hailie Brophy, Michele P. Dyson, Katherine Rittenbach

Bibliographic record

VenueInternational Journal of Mental Health Nursing · 2022
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsAlberta Health ServicesUniversity of CalgaryAlberta HealthUniversity of Alberta
Fundersnot available
KeywordsPsycINFOCINAHLMEDLINESubstance useProcess (computing)PsychologyMedicineComputer sciencePsychiatryPolitical sciencePsychological intervention

Abstract

fetched live from OpenAlex

In this paper, we provide an analysis of the concept of recovery from substance use. We performed a literature search in CINAHL Plus, PsycINFO, MEDLINE, and Embase using key terms that focused on the concept of recovery from substance use. We also conducted a grey literature search and included select resources. Inclusive years for the search ranged from January 1, 2000 to March 10, 2022. Records were screened for eligibility by two independent reviewers; data were extracted by one reviewer and confirmed by a second. A total of 22 literature sources were included. Identified core attributes of recovery include: (i) recovery as a process, (ii) recovery as more than managing substance use, (iii) recovery as life improvements, and (iv) recovery as a person-centred, individual concept. Antecedents, consequences, and empirical referents are identified, and model and contrary cases are presented. We propose the following definition for recovery: Recovery from substance use is defined by the affected individual, who sets goals and objectives for life improvements that include managing their substance use, but this is not the sole focus. Recovery is a person-centred, individualized process that can be measured by referents that suit the individual's own goals and objectives. What may constitute "recovery" and "recovered" requires definition by each individual.

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 score0.140
Threshold uncertainty score0.649

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)0.0010.000

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 head0.041
GPT teacher head0.367
Teacher spread0.326 · 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

Citations21
Published2022
Admission routes1
Has abstractyes

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