Evidence map›Paper›PMID 37277692›Full record

ArticleJournal of gambling studies2024

For Better and For Worse: Frequent Gamblers Use Dual Counterfactuals to Justify Continued Gambling.

Christina I Anthony, Elizabeth Cowley, Alex Blaszczynski

Abstract read
In one paragraph

Article in Journal of gambling studies, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Christina I AnthonyUniversity of Sydney Business School, Rm 4006, H70, Sydney, NSW, 2006, Australia. christina.anthony@sydney.edu.au.ORCID http://orcid.org/0000-0002-4772-3148
Elizabeth CowleyUniversity of Sydney Business School, Rm 4006, H70, Sydney, NSW, 2006, Australia.
Alex BlaszczynskiFaculty of Science, University of Sydney, Sydney, NSW, 2006, Australia.

Funding

Australian Research Council DP0880919Australian Research Council LP0560634
6 · The paper itself

Abstract

How might frequent gamblers convince themselves to keep playing despite persistent losses or after a win that should be savored? The purpose of this research is to examine the unexplored question of how frequent gamblers' use counterfactual thinking to motivate their desire to continue gambling. Using a sample of n = 69 high and n = 69 low frequency gamblers in a field setting, we found that infrequent gamblers tended to consider how the perceived outcome of losing "could have been better" (i.e., upward counterfactual thinking), and how a winning outcome "could have been worse" (i.e., downward counterfactual thinking). This pattern of counterfactual thinking is considered typical in many settings and may, in a gambling context, support a potentially more responsible approach by helping infrequent gamblers to learn from past mistakes to avoid significant future losses and to savor wins to protect returns gained. Alternatively, we found that frequent gamblers were more likely to generate 'dual counterfactuals' which include both upward and downward counterfactuals in response to losses and wins. We argue that this dual pattern of counterfactual thinking may allow frequent gamblers to more easily justify their desire to continue gambling. Findings suggest that challenging gamblers counterfactual thinking patterns could assist clinicians in moderating the potential for high-risk behaviors.

Indexed as

Behavior, AddictiveGamblingMotivationAdultFemaleHumansInternal-External ControlMaleMiddle AgedRewardThinkingYoung AdultAffectCounterfactual thinkingFrequent gamblersMotivated reasoningResponsible gambling

Identifiers

PMID37277692
PMCPMC11272697

What OpenQuestion holds

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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.