Investigating the Use of a Serious Game to Improve Opioid Safety Awareness Among Adolescents: Quantitative Study
Bibliographic record
Abstract
BACKGROUND: The misuse of opioid medications among adolescents is a serious problem in the United States. Serious games (SGs) are a novel way to promote the safe and responsible management of opioid medications among adolescents, thereby reducing the number of adolescent opioid misuse cases reported annually. OBJECTIVE: This study aimed to examine the effect of the SG MedSMART: Adventures in PharmaCity on adolescents' opioid safety knowledge, awareness, behavioral intent, and self-efficacy. METHODS: A nationally representative sample of adolescents aged 12 to 18 years were recruited online through Qualtrics panels from October to November 2020. Data collection consisted of a pregame survey, 30 minutes of gameplay, and a postgame survey. The pregame and postgame surveys included 66 items examining the participants' baseline opioid knowledge, safety, use, and demographic information. The postgame survey had 25 additional questions regarding the MedSMART game. Gameplay scenarios included 5 levels intended to mimic adolescents' daily life while educating the players about appropriate opioid storage and disposable practices, negative consequences of sharing opioid medications, and the use of Narcan. Survey questions were divided into 10 categories to represent key concepts and were summarized into concept scores. Differences in concept scores were described by overall mean (SD) when stratified by gender, race, school, grade, and age. Differences of change in concept score were analyzed using the Kruskal-Wallis and correlation tests. RESULTS: A total of 117 responses were analyzed. The results showed significant improvement on all concept scores except for Narcan knowledge (mean change -0.04, SD 0.29; P=.60) and safe storage (mean change 0.03, SD 0.20; P=.09). Female participants had greater improvement than males for safe disposal (female mean 0.12, SD 0.25 vs male mean 0.04, SD 0.17; P=.05). Male participants had higher improvement than female participants for misuse behavior (female mean 0.05, SD 0.28 vs male mean 0.14, SD 0.27; P=.04). Perceived knowledge for participants who had non-White or Hispanic racial backgrounds had higher improvement than for non-Hispanic White participants (non-White mean 1.10, SD 1.06 vs White mean 0.75, SD 0.91; P=.03). Older grades were associated with greater improvement in opioid knowledge (correlation coefficient -0.23, 95% CI -0.40 to -0.05; P=.01). There were 28 (23.9%) participants who played all 5 levels of the game and had better improvement in opioid use self-efficacy. CONCLUSIONS: Our findings suggest MedSMART: Adventures in PharmaCity can be used as an effective tool to educate adolescents on the safe and responsible use of prescribed opioid medications. Future testing of the effectiveness of this SG should involve a randomized controlled trial. Additionally, the feasibility of implementing and disseminating MedSMART: Adventures in PharmaCity in schools and health care settings such as adolescent health or primary care clinics, emergency departments, and pharmacies should be investigated.
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 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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".