Effects and Limitations of a Unique, Nationwide, Self-Exclusion Service for Gambling Disorder and Its Self-Perceived Effects and Harms in Gamblers: Protocol for a Qualitative Interview Study
Bibliographic record
Abstract
BACKGROUND: Voluntary self-exclusion from gambling is a common but underdeveloped harm reduction tool in the management of gambling problems or gambling disorders. Large-scale, multi-operator, and operator-independent self-exclusion services are needed. A recent nationwide multi-operator self-exclusion service in Sweden (Spelpaus), involving both land- and web-based gambling sites, is promising, but recent data have revealed limitations to this system and possibilities to breach one's self-exclusion through overseas web-based gambling. More knowledge is needed about the benefits and challenges of such an extensive self-exclusion service, and its effects as perceived by gamblers. OBJECTIVE: This study protocol describes the rationale and design of a qualitative interview study addressing the effects and limitations perceived by individuals with gambling problems and their concerned significant others. The study aims to provide an in-depth experience of this novel self-exclusion service and to inform stakeholders and policymakers in order to further improve harm reduction tools against gambling problems. METHODS: Individuals with gambling problems will be recruited primarily through social media and also from a treatment unit, if needed, for a qualitative interview study. Recorded interview material will be analyzed through content analysis, and recruitment will continue until saturation in the material is reached. This study will provide in-depth information about a harm reduction tool that is promising and commonly used, but which has proven to be breached by a significant number of users, potentially limiting its efficiency. The aim is to interview a sufficient number of gamblers until saturation has been obtained in the interview material. Saturation will be considered through a continuous analysis, comparing recently collected data to previously collected data. RESULTS: Results will be reported as the themes and subthemes identified after the thorough analysis and coding of the transcribed text material and will be accompanied by citations representing relevant themes and subthemes. Results are planned to be provided before the end of 2023. CONCLUSIONS: This study will likely provide new insights into user perspectives on a multi-operator self-exclusion service that involves both web- and land-based gambling operators, and which according to previous literature attracts many gamblers but also appears to have limitations and challenges in the target group of individuals with gambling problems. Policy and legislation implications, as well as clinical implications for treatment providers, will be discussed. Results and conclusions will be disseminated to policy makers in Sweden and internationally, as well as to peer organizations, treatment providers, and the research community. TRIAL REGISTRATION: ClinicalTrials.gov NCT05693155; https://clinicaltrials.gov/study/NCT05693155. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/47528.
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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 | 0.068 | 0.053 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".