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Record W4409792379 · doi:10.2196/68814

Adolescents’ and Parents’ Perspectives on Using the MedSMARxT Families Intervention in Emergency Departments for Opioid Medication Safety Education: Mixed Methods Study

2025· article· en· W4409792379 on OpenAlexvenueno aff
Olufunmilola Abraham, Sara Nadi, Irene Hurst

Bibliographic record

VenueJMIR Serious Games · 2025
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsnot available
FundersNational Center for Advancing Translational Sciences
KeywordsPreprintIntervention (counseling)OpioidMedicinePsychologyMedical emergencyMedical educationFamily medicineNursingComputer scienceInternal medicineWorld Wide Web

Abstract

fetched live from OpenAlex

Background: The opioid crisis has significantly impacted adolescents and their families. This is attributed in part to increased opioid prescriptions in pediatric emergency departments (EDs) due to acute pain conditions and injuries. Although EDs frequently prescribe opioids, no effective preventative interventions have been implemented to educate adolescents and their families on safe opioid use. This study evaluates the MedSMA℞T Families intervention, which consists of an engaging serious game, Adventures in PharmaCity, and a personalized Family Medication Safety Plan (FMSP) with the aim of reducing opioid misuse and promoting opioid medication safety. The MedSMA℞T Families intervention was developed to educate adolescents and adults prescribed opioids on safe practices such as opioid storage and disposal. Objective: This study aimed to explore and characterize adolescents' and parents' experiences and perspectives on implementing the MedSMA℞T Families intervention in the ED to improve opioid education and safety among adolescents. Methods: A total of 93 participants, including 16 children and 77 parents, were recruited from the pediatric ED at a tertiary academic hospital to play the MedSMA℞T game in the ED. A total of 16 participants, including 8 children and 8 parents, were followed up with interviews to gather qualitative feedback. Participants engaged with the MedSMA℞T game-Adventures in PharmaCity-and the FMSP. Data were collected through gameplay observation and 75-minute semistructured interviews via Zoom. Quantitative in-game data were analyzed using descriptive analysis and qualitative data were analyzed using thematic analysis with NVivo (version 14; Lumivero). Results: Parents spent an average of 22.16 (SD 4.97) minutes playing the game, while children spent an average of 21.99 (SD 8.06) minutes. Families appreciated the game's design and noted usability challenges and suggested enhancements for clearer gameplay instructions. Participants reported increased knowledge of opioid safety, highlighted the importance of communication with health care providers, and a desire for a mobile app to assist with medication management. The FMSP was perceived as valuable for promoting awareness of safe practices and connected well to the knowledge gained from the game. Conclusions: The MedSMA℞T Families intervention was well received as a beneficial educational tool to educate adolescents and their families on safe opioid use. Additionally, it highlights a clear need for more accessible digital tools to increase opioid education. This feedback indicates a strong interest in improving educational resources to ensure safe opioid management within families.

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)0.011
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.014
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.017
GPT teacher head0.399
Teacher spread0.382 · 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 designQualitative
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

Citations2
Published2025
Admission routes1
Has abstractyes

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