Concept analysis of recovery from substance use
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.020 | 0.015 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.007 | 0.013 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".