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Record W3207415141 · doi:10.2196/31172

Exploring Middle School Students’ Perspectives on Using Serious Games for Cancer Prevention Education: Focus Group Study

2021· article· en· W3207415141 on OpenAlexvenueno aff
Olufunmilola Abraham, Lisa Szela, Mahnoor Khan, Amrita Geddam

Bibliographic record

VenueJMIR Serious Games · 2021
Typearticle
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsnot available
FundersNational Institutes of HealthNational Center for Advancing Translational SciencesInstitute for Clinical and Translational Research, University of Wisconsin, MadisonUniversity of Wisconsin-Madison
KeywordsCancer preventionFocus groupPsychological interventionCurriculumPromotion (chess)Health promotionMedicinePopulationCancerPsychologyMedical educationGerontologyPublic healthNursingPedagogyEnvironmental healthPolitical scienceMarketing

Abstract

fetched live from OpenAlex

BACKGROUND: Cancer in the United States is a leading cause of mortality. Educating adolescents about cancer risks can improve awareness and introduce healthy lifestyle habits. Public health efforts have made significant progress in easing the burden of cancer through the promotion of early screening and healthy lifestyle advocacy. However, there are limited interventions that educate the adolescent population about cancer prevention. Previous studies have demonstrated the effectiveness of serious games (SGs) to teach adolescents about healthy lifestyle choices, but few research efforts have examined the utility of using SGs to educate youth specifically on cancer prevention. OBJECTIVE: This study aimed to investigate middle school students' preferences for the use of SGs for cancer prevention education. The study also characterized the students' perceptions of desired game design features for a cancer prevention SG. METHODS: Focus groups were held to allow adolescents to review a game playbook and discuss gaming behaviors and preferences for an SG for cancer education. The game playbook was developed based on "Cancer, Clear & Simple," a curriculum intended to educate individuals about cancer, prevention, self-care, screening, and detection. In the game, the player learns that they have cancer and is given the opportunity to go back in time to reduce their cancer risk. A focus group discussion guide was developed and consisted of questions about aspects of the playbook and the participants' gaming experience. The participants were eligible if they were 12 to 14 years old, could speak and understand English, and had parents who could read English or Spanish. Each focus group consisted of 5 to 10 persons. The focus groups were audio recorded and professionally transcribed; they were then analyzed content-wise and thematically by 2 study team members. Intercoder reliability (kappa coefficient) among the coders was reported as 0.97. The prevalent codes were identified and categorized into themes and subthemes. RESULTS: A total of 18 focus groups were held with 139 participants from a Wisconsin middle school. Most participants had at least "some" gaming experience. Three major themes were identified, which were educational video games, game content, and purpose of game. The participants preferred customizable characters and realistic story lines that allowed players to make choices that affect the characters' outcomes. Middle school students also preferred SGs over other educational methods such as lectures, books, videos, and websites. The participants desired SGs to be available across multiple platforms and suggested the use of SGs for cancer education in their school. CONCLUSIONS: Older children and adolescents consider SGs to be an entertaining tool to learn about cancer prevention and risk factors. Their design preferences should be considered to create a cancer education SG that is acceptable and engaging for youth.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.566
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.116
GPT teacher head0.416
Teacher spread0.300 · 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 teacher head, not a consensus.

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

Citations7
Published2021
Admission routes1
Has abstractyes

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