What is a public health approach to substance use? Protocol for a qualitative systematic review
Bibliographic record
Abstract
INTRODUCTION: The concept of a 'public health approach' to substance use is frequently but inconsistently invoked. This inconsistency is reflected in public policy, with governments using the term 'public health approach' in contradictory ways. This aim of this study is to clarify what is meant and understood when the term 'public health approach' is used in the context of substance use. METHODS AND ANALYSIS: We will conduct a systematic search of Medline, Embase, Scopus, CINAHL, PsycINFO, Sociological Abstracts and PAIS Index. Eligible articles will be from peer-reviewed journals, in English, with full text available. There will be no limits on year of publication. Substance use must be the primary topic of the article. Editorials, commentaries and letters to the editor will be included, but not commentaries on other articles, unless the definition of a public health approach is central to the commentary. Data selection and collection will be conducted independently by two researchers, with a third separately resolving any disagreement. To answer the research question, we will extract authors' definitions of a public health approach to substance use as well as any descriptions of the central principles, characteristics and components of such an approach. To synthesise the data, we will employ thematic synthesis. Coding will be conducted by one researcher and verified by a second; two researchers will then group the codes into themes using an inductive process. Finally, the full research team will develop a set of analytic themes, which will be presented as a narrative. ETHICS AND DISSEMINATION: Ethics approval is not needed since the research will only involve published work. Our findings will be disseminated in a peer-reviewed journal and, if possible, at conferences. PROSPERO REGISTRATION NUMBER: CRD42021270632.
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 | 0.198 | 0.173 |
| Meta-epidemiology (narrow) | 0.005 | 0.007 |
| Meta-epidemiology (broad) | 0.011 | 0.010 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.009 | 0.014 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.094 | 0.018 |
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".