Extrinsic Factors Influencing the Person’s Motivation for Engagement and Retention in the Addiction Recovery Process. A Systematic Literature Review
Bibliographic record
Abstract
Background Globally, up to 80% of patients enrolled for addiction care are lost to follow-up within the first three months of treatment. This review synthesizes evidence on extrinsic factors that influence motivation for engaging in addiction recovery and corresponding empirical definitions. Methods A systematic search for peer-reviewed articles was conducted through electronic databases, including Ovid MEDLINE, PsychINFO, CINHAL, and scanning references. The included articles were published in English or French between 1946 and 2018. Results The identified sixteen articles indicated that extrinsic factors for the person’s engagement and retention in the addiction recovery process included: motivation-enhancing healthcare structures, therapeutic relationships, and supportive social networks. Results also indicated that empirical definitions of motivation for engagement and retention in the addiction recovery process varied across studies. Conclusion Extrinsic factors can influence the person’s motivation for engagement and retention in the addiction recovery. Research with full operational definitions of motivation for engagement and retention in the addiction recovery is needed. Keywords: Addiction recovery; engagement; extrinsic factors; motivation; retention
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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 | 0.013 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.011 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".