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Record W4386036085 · doi:10.2196/46697

A Novel Casual Video Game With Simple Mental Health and Well-Being Concepts (Match Emoji): Mixed Methods Feasibility Study

2023· article· en· W4386036085 on OpenAlexvenueno aff
Russell Pine, James Mbinta, Lisa Te Morenga, Theresa Fleming

Bibliographic record

VenueJMIR Serious Games · 2023
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
FundersCure Kids
KeywordsCasualEmojiSimple (philosophy)Computer scienceMental healthVideo gamePsychologyHuman–computer interactionMultimediaSocial mediaWorld Wide WebPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Adolescence is a crucial phase for early intervention and prevention of mental health problems. Casual video games are popular and have promise as a novel mechanism for reaching young people, but this potential has seldom been explored. OBJECTIVE: This study aimed to explore the acceptability, feasibility, and possible indicators of therapeutic changes after playing a purpose-built novel casual video game (Match Emoji) with simple mental health and well-being content among young adolescents. METHODS: We conducted a single-arm, nonrandomized trial of Match Emoji with 12- to 14-year-old school students (N=45; 26 [57%] New Zealand European, 12 [26%] Māori; 7 [15%] Asian or Pacific; 27 [60%] boys, 3 [6%] non-binary). Participants were invited to play Match Emoji for 15 minutes, 2-3 times a week over 2 weeks (a total of 60 minutes). Acceptability was assessed through the frequency and duration of use (analytics analyzed at the end of the 2-week intervention period and at weeks 4 and 6) and through participant reports. The Child and Adolescent Mindfulness Measure (CAMM), General Help-Seeking Questionnaire (GHSQ), Flourishing Scale (FS), and Revised Children's Anxiety and Depression Scale (RCADS) were assessed at baseline and week 2 to indicate possible effects. Focus groups were held in week 4. RESULTS: Most participants (n=39, 87%) used Match Emoji for at least 60 minutes over the 2-week intervention, with 80% (36/45) continuing to play the game after the intervention period. Mean change (from baseline to 2 weeks) on each measure was 1.38 (95% CI -0.03 to 2.79; P=.06) for CAMM; 0.8 (95% CI -2.71 to 4.31; P=.64) for GHSQ; -1.09 (95% CI -2.83 to 0.66; P=.21) for FS; and -3.42 (95% CI -6.84 to -0.001; P=0.49) for RCADS. Focus group feedback suggested that Match Emoji was enjoyable and helpful. CONCLUSIONS: The casual video game with mental health content appeared to be acceptable and provided a promising indication of possible therapeutic effects. This approach is worthy of further investigation. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/31588.

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)0.007
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.048
GPT teacher head0.481
Teacher spread0.433 · 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

Citations7
Published2023
Admission routes1
Has abstractyes

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