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Record W4388836338 · doi:10.2196/51812

Assessing the Impact of a Serious Game (MedSMARxT: Adventures in PharmaCity) in Improving Opioid Safety Awareness Among Adolescents and Parents: Quantitative Study

2023· article· en· W4388836338 on OpenAlexvenueno aff
Olufunmilola Abraham, Tyler James McCarthy, Jen Zaborek

Bibliographic record

VenueJMIR Formative Research · 2023
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesInstitute for Clinical and Translational Research, University of Wisconsin, MadisonNational Institutes of Health
KeywordsSnowball samplingPsychological interventionMedicineDemographicsPsychologyClinical psychologyPsychiatryDemography

Abstract

fetched live from OpenAlex

BACKGROUND: The opioid crisis continues to worsen across the United States, affecting people of all demographics. Few evidence-based interventions exist for educating families, particularly those with adolescents, about opioid prescription safety. Serious games have demonstrated impacts in improving medication-related outcomes for various health conditions. The characterizing goal of this serious game is to improve opioid safety knowledge and awareness among adolescents and their families. OBJECTIVE: T: Adventures in PharmaCity, designed to foster opioid safety awareness among adolescents and their parents. METHODS: A national sample of parents and their adolescent children was recruited through Qualtrics research panels, social media, listservs, and snowball sampling. Eligible participants were adolescents aged between 12 and 18 years and their parents. Study participants were required to reside in the United States; speak, read, and understand English; and have access to a computer with a webcam. Parent-child dyads completed pregame and postgame surveys and participated in gameplay for up to 30 minutes. Primary outcome scales have been previously evaluated by the study team. RESULTS: A total of 60 adolescent participants and 68 parent participants met full attention criteria for inclusion in this study. Statistical analysis confirmed that both adolescents' and parents' concept scores improved from baseline regarding opioid safety self-efficacy (adolescent: mean 0.35, SD 0.60; P<.001; parent: mean 0.28, SD 0.42; P<.001), perceived knowledge (adolescent: mean 1.08, SD 1.04; P<.001; parent: mean 0.56, SD 0.55; P<.001), behavioral intent (adolescent: mean 0.26, SD 0.39; P<.001; parent: mean 0.25, SD 0.32; P<.001), safe storage (adolescent: mean 0.12, SD 0.27; P<.001; parent: mean 0.03, SD 0.11; P=.03), disposal knowledge (adolescent: mean 0.10, SD 0.27; P=.006; parent: mean 0.07, SD 0.16; P<.001), and knowledge about misuse behavior (adolescent: mean 0.05, SD 0.14; P=.002; parent: mean 0.04, SD 0.10; P<.001). Participant groups, stratified by who completed and who did not complete gameplay, improved their knowledge and awareness, with no significant differences between subgroups. CONCLUSIONS: T: Adventures in PharmaCity is an intervention with the capability of teaching parents and adolescents about safe opioid prescription practices. Further studies and game refinement are needed to demonstrate the effectiveness of a game-based intervention in clinical settings and community pharmacies.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.071
GPT teacher head0.487
Teacher spread0.415 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2023
Admission routes1
Has abstractyes

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