Evidence map›Paper›PMID 35590275›Full record

ArticleBMC public health2022

Addressing gambling harms by reducing the supply of electronic gambling machines: a comparative study of Italy and Finland.

Virve Marionneau, Gabriele Mandolesi, Sara Rolando, Janne Nikkinen

Abstract read
In one paragraph

Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Virve MarionneauCentre for Research on Addiction, Control, and Governance (CEACG), Faculty of Social Sciences, University Researcher, University of Helsinki, Helsinki, Finland. virve.marionneau@helsinki.fi.
Gabriele MandolesiUniversità Lumsa, Rome, Italy.
Sara RolandoResearch and Training Institute ECLECTICA, Turin, Italy.
Janne NikkinenCentre for Research on Addiction, Control, and Governance (CEACG), Faculty of Social Sciences, University Researcher, University of Helsinki, Helsinki, Finland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundElectronic gambling machines (EGMs) are amongst the most harmful forms of gambling. The high availability of EGMs is also linked to increased consumption. To reduce the burden of EGMs on public health, policies to reduce their numbers have recently been introduced in Italy and Finland. This study compares the aims and justifications of these legislative changes, as well as their overall impacts on total consumption.

methodsThe objectives and justifications of policies to reduce the number of EGMs were based on qualitative media analysis. The impacts on total consumption were measured using financial figures provided by gambling providers in Italy and Finland.

resultsResults show that the reductions in EGM numbers were justified in terms of public health concerns in both countries, but the amplitude of policies varied. In Italy, the reductions were more ambitious than in Finland, and included reductions in the number of gambling locations. The financial data nevertheless indicated that the reductions may not have been significant enough.

conclusionsPublic health concerns were initially highlighted in the media discussions, but eventually in both countries reduction policies were less ambitious due to industry lobbying and state revenue interests. The reductions therefore do not appear to have been effective in reducing total consumption and the burden on public health.

Indexed as

Behavior, AddictiveGamblingElectronicsFinlandHumansPolicyPublic HealthElectronic gambling machinesFinlandGamblingItalyTotal consumption

Identifiers

PMID35590275
PMCPMC9119843

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.