Ageing and older people who use illicit opioids, cocaine or methamphetamine: a scoping review and literature map
Bibliographic record
Abstract
AIMS: To provide an overview of research literature on ageing and older people who use illicit opioids and stimulants by documenting the conceptual frameworks used and content areas that have been investigated. METHODS: We conducted a scoping review of literature relating to ageing and older people who use illicit stimulants and opioids, defining 'older' as 40 years and above. Primary studies, secondary studies and editorials were included. Searches were conducted in PubMed and Embase in July 2020 and March 2021; the Cochrane library was searched in November 2021. Charted data included methodological details, any conceptual frameworks explicitly applied by authors and the content areas that were the focus of the publication. We developed a hierarchy of content areas and mapped this to provide a visual guide to the research area. RESULTS: Of the 164 publications included in this review, only 16 explicitly applied a conceptual framework. Seven core content areas were identified, with most publications contributing to multiple content areas: acknowledgement of drug use among older people (n = 64), health status (n = 129), health services (n = 109), drug use practices and patterns (n = 84), social environments (n = 74), the criminal legal system (n = 28) and quality of life (n = 15). CONCLUSIONS: The literature regarding older people who use illicit drugs remains under-theorized. Conceptual frameworks are rarely applied and few have been purposely adapted to this population. Health status and health services access and use are among the most frequently researched topics in this area.
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 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 | 0.020 | 0.071 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.052 | 0.036 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".