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Record W4390597713 · doi:10.1016/j.invent.2023.100707

Evaluating the impact of motivational interviewing on engagement and outcomes in a web-based self-help intervention for gambling disorder: A randomised controlled trial

2024· article· en· W4390597713 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueInternet Interventions · 2024
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental HealthUniversity of Calgary
FundersAlberta Gambling Research Institute, University of Calgary
KeywordsMotivational interviewingIntervention (counseling)Randomized controlled trialClinical psychologyPsychologyWeb applicationBrief interventionPsychotherapistMedicinePsychiatryWorld Wide WebComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

Background: Self-paced internet interventions for gambling problems offer cost-effective, accessible, and private alternatives to traditional psychotherapy for a population that rarely seeks help. However, these interventions have been relatively slow to develop, evaluate, and deploy at scale relative to those for other addictive behaviors. Moreover, user engagement remains low despite the high interest. Motivational interviews have improved the effectiveness gambling bibliotherapy but have not been augmented with an analogous web-based self-guided program. Objectives: This trial aimed to replicate and extend prior work by translating a paperback workbook to the internet and pairing it with a single motivational interview. It was hypothesized that the motivational interview would enhance program engagement and gambling outcomes. Methods: = 155). The program was based on principles of cognitive-behavioral therapy and motivational interviewing. Gambling severity, expenditures, frequency, and duration were assessed via online questionnaires at baseline and 3-, 6-, and 12-months post-baseline, along with secondary outcomes (i.e., depression, anxiety, nonspecific psychological distress, alcohol consumption). Results: Baseline characteristics were indicative of severe gambling problems and concurrent mental health problems but not problematic alcohol consumption in this sample. Both treatment groups demonstrated roughly equal improvements across all gambling outcomes and most secondary outcomes over time, except alcohol consumption, which did not meaningfully change. Changes were most prominent by 3 months, followed by more gradual change by 6 and 12 months. Only 57 % of gamblers who were assigned to receive a motivational interview completed that interview. About 40 % of users did not complete any program modules and 11 % completed all four. No group differences in program engagement were observed, although the number of modules completed was associated with greater reductions in gambling behaviors in both groups. Discussion: The problem of user engagement with web-based self-help programs remains. There is a dose-response relationship between engagement and outcomes when engagement is measured in terms of therapeutic content completed. Conclusions: The addition of a motivational interview to a web-based self-help program for gambling problems was unsuccessful in improving engagement or outcomes. Future work should aim to make self-guided programs more engaging rather than solely making users more engaged. Trial registration: Registered on 7 July 2020 (ISRCTN13009468).

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.231
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.000
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 head0.265
GPT teacher head0.524
Teacher spread0.259 · 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