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Record W4409148518 · doi:10.2196/64068

Escape Game to Promote Students’ Mental Health Outcomes in the Aftermaths of COVID-19 Pandemic: Protocol for a Mixed Methods Study Evaluating a Cocreated Intervention

2025· article· en· W4409148518 on OpenAlexfundvenueno aff
David Labrosse, Clara Vié, M.D. DINA Y. MANSOUR HISHAM HARB, Ilaria Montagni

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsnot available
FundersAgence Universitaire de la FrancophonieAgence Nationale de la Recherche
KeywordsMental healthPsychologyMedical educationIntervention (counseling)PandemicCoping (psychology)Applied psychologyRandomized controlled trialEducational gameCoronavirus disease 2019 (COVID-19)MedicineClinical psychologyPsychiatryMathematics education

Abstract

fetched live from OpenAlex

BACKGROUND: The COVID-19 pandemic and the protracted lockdowns have heavily impacted university students' mental health. Digital Escape Games represent a good means to reach students and propose them solutions for their psychological well-being. OBJECTIVE: This study aimed to evaluate a cocreated digital Escape Game on students' mental health in the aftermath of the COVID-19 pandemic, called EscapeCovid Game. The evaluation of the effectiveness of this stand-alone intervention concerns mental health outcomes (mental health literacy, appraisal and change of beliefs about mental health, management of emotions, and development of coping strategies) and the appreciation and relevance of the game. METHODS: A randomized controlled trial with pre- and posttest data collection (online questionnaires with validated scales) is conducted among 500 students in Bordeaux, France, to evaluate the EscapeCovid Game cocreated with students, researchers, health professionals, and web developers. A subsample of students is randomly selected for responding to a semistructured interview following a mixed methods design. Recruitment is done through mail invitations from student associations and presentations in university classes. Half of the sample of the trial plays the Escape Game, while the other half receives an email with mental health-related information. Within the game, students discuss their personal experiences. The text is further used for the qualitative analyses. The whole study is carried out online. RESULTS: The EscapeCovid Game has been developed, tested, and finalized by the end of March 2023. As of November 4, 2024, a total of 191 students have answered the baseline questionnaire (90 intervention vs 101 control). A total of 23 students have played the game and 53 are in the control arm. Among participants, by the end of September 20, 2023, twenty were interviewed (10 intervention and 10 control) reaching sample saturation. According to preliminary results, the EscapeCovid Game has had a positive impact on all defined outcomes, while the email has been effective in increasing knowledge on resources available and on coping strategies and meditation techniques. We expect the trial to be completed by the end of June 2025. CONCLUSIONS: The mixed methods findings of this study are due to demonstrate the effectiveness of the EscapeCovid Game in improving students' mental health outcomes. Preliminary results from the qualitative substudy are promising: in the aftermath of the COVID-19 crisis, this intervention is intended to promote players' mental health through gamification, knowledge transfer, and a learning-by-doing approach. TRIAL REGISTRATION: ClinicalTrials.gov NCT06720792; https://clinicaltrials.gov/study/NCT06720792. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/64068.

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)0.020
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: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.043
Threshold uncertainty score0.143

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.014
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0030.002
Science and technology studies0.0030.003
Scholarly communication0.0020.002
Open science0.0040.003
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0430.007

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 head0.546
GPT teacher head0.773
Teacher spread0.227 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations1
Published2025
Admission routes2
Has abstractyes

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