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Record W3201896993 · doi:10.2196/30747

Changes in Self-Reported Web-Based Gambling Activity During the COVID-19 Pandemic: Cross-sectional Study

2021· article· en· W3201896993 on OpenAlexvenueno aff
Emma Claesdotter‐Knutsson, Anders Håkansson

Bibliographic record

VenueJMIR Serious Games · 2021
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
FundersCrafoordska Stiftelsen
KeywordsPsychologyPandemicAddictionBehavioral addictionCoronavirus disease 2019 (COVID-19)Logistic regressionClinical psychologyMental healthPsychiatryCross-sectional studyDemographyMedicineDisease

Abstract

fetched live from OpenAlex

BACKGROUND: The COVID‑19 pandemic has affected not only somatic health with over 3.7 million deaths worldwide, but also has had a huge impact on psychological health, creating what amounts to a mental health crisis. The negative effect of the pandemic on traditional addictions is well described and concerning, and the same has been seen for gambling. OBJECTIVE: This study explores self-reported web-based gambling behavior during the COVID‑19 pandemic in Sweden. We investigated overall changes, but also changes in specific web-based gambling types, and whether they are associated with certain risk factors or lifestyle changes. METHODS: Our study is based on an anonymous web-based survey of web panel participants in Sweden (N=1501) designed to study a range of behavioral changes during the COVID‑19 pandemic. Increases in gambling were analyzed using logistic regression models against sociodemographic data and psychological distress. RESULTS: The majority of the respondents who gambled reported no changes in their gambling habits during the COVID‑19 pandemic. We found significant associations with the problem gambling severity index (PGSI), the Kessler score (indicating psychological distress), employment status, changes in alcohol habits, and self-exclusion when looking at overall changes in gambling activity in the pandemic. In the subgroup that reported an increase in gambling activity, we found an association with both the PGSI and Kessler scores. The PGSI score was also an independent predictor for all specific web-based gambling (horses, sports, poker, and casino) whereas the Kessler score only had a significant impact on changes in casino gambling. In addition, male gender was an independent predictor for gambling on sports and casino gambling. CONCLUSIONS: The majority of respondents who gambled reported no changes in their gambling activity during the COVID‑19 pandemic. The group that reported an increase in overall gambling activity during the COVID-19 pandemic represent a group with gambling problems and psychological distress. The group that reported increased sports and casino gambling were often male, and this group seemed to experience more psychological distress.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.902

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.150
GPT teacher head0.450
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2021
Admission routes1
Has abstractyes

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