Harms associated with gambling: abbreviated systematic review protocol
Bibliographic record
Abstract
Abstract Background According to the Gambling Commission, in 2018, almost half of the general population aged 16 and over had participated in gambling in the 4 weeks before being surveyed. Such surveys suggest that the proportion of people who are classed as ‘problem’ gamblers is relatively small; however, this may be related to the ways data are collected and gambling behaviour is classified. Concern about the harms associated with gambling is rising, and in response, Public Health England (PHE) has initiated this review to identify the harms associated with this activity. Harms to the gambler, their close associates and the wider society will all be included. Methods Abbreviated systematic review processes will be employed. Ovid MEDLINE, Ovid Embase, Ovid Psycinfo, NICE Evidence and EBSCO SocIndex; a range of websites (for grey literature); and reference lists of included studies will be searched. Experts will be asked to identify other relevant literature. Literature published in years 2005–2019, published in English, from a country within the Organisation for Economic Development (OECD) and following an observational, qualitative or systematic review design will be included. AMSTAR2 (systematic reviews), the Newcastle-Ottawa Scale (observational studies) and the Critical Appraisal Skills Programme (CASP) qualitative checklist (qualitative studies) will be used to assess the risk of bias. A narrative synthesis will be used to summarise the results. The body of evidence will also be assessed according to the principles laid out in the CERQual approach. Discussion This protocol provides details of the framework that has been set up to guide this systematic review. The results of this review will provide an extensive assessment of the breadth and magnitude of harms associated with gambling. This will be one of the most comprehensive reviews of gambling-related harms undertaken to date. Systematic review registration PROSPERO CRD42019154757
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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 | 0.082 | 0.105 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.017 | 0.016 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.008 | 0.008 |
| Insufficient payload (model declined to judge) | 0.132 | 0.017 |
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".