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Record W4391101206 · doi:10.2196/51596

Effects of a Rice-Farming Simulation Video Game on Nature Relatedness, Nutritional Status, and Psychological State in Urban-Dwelling Adults During the COVID-19 Pandemic: Randomized Waitlist Controlled Trial

2024· article· en· W4391101206 on OpenAlexaboutno aff
Seulki Lee, Chisung Yuh, Yu‐Bin Shin, Heon‐Jeong Lee, Young‐Mee Lee, Jungsil Lee, Chul‐Hyun Cho

Bibliographic record

VenueJournal of Medical Internet Research · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsnot available
FundersInstitute for Information and Communications Technology PromotionMinistry of Science and ICT, South KoreaIran Telecommunication Research CenterNational Research Foundation of KoreaNational Research Foundation
KeywordsRandomized controlled trialAnxietyQuality of life (healthcare)Mental healthPsychological interventionDistressMedicinePsychologyGerontologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: During the COVID-19 pandemic, urban inhabitants faced significant challenges in maintaining connections with nature, adhering to nutritional guidelines, and managing mental well-being. OBJECTIVE: Recognizing the urgent need for innovative approaches, this study was designed to explore the potential benefits of a specific digital intervention, the rice-farming simulation game Sakuna: Of Rice and Ruin, for nature relatedness, nutritional behaviors, and psychological well-being. METHODS: A total of 66 adults without any prior major psychiatric disorders residing in an urban area were recruited for the study. They were randomly assigned to 2 groups through block randomization: the immediate intervention group (IIG; 34/66, 52%) and the waitlist group (32/66, 48%). Participants in the IIG were instructed to play the game for at least 4 days per week for 3 weeks, with each session lasting from 30 minutes to 3 hours. Assessments were performed at baseline, week 1, and week 3. The Nature Relatedness Scale (NR) and Nutrition Quotient Scale were used to evaluate nature relatedness and nutritional state, respectively. Furthermore, psychological state was assessed using the World Health Organization Quality of Life-Brief Version (WHOQOL-BREF), Brief Fear of Negative Evaluation Scale, Social Avoidance and Distress Scale, Toronto Alexithymia Scale, State-Trait Anxiety Inventory, Center for Epidemiologic Studies Depression Scale Revised, and Korean Resilience Quotient. RESULTS: This study's results revealed significant time interactions between the IIG and waitlist group for both the total NR score (P=.001) and the score of the self subdomain of NR (P<.001), indicating an impact of the game on nature relatedness. No group×time interactions were found for the total Nutrition Quotient Scale and subdomain scores, although both groups showed increases from baseline. For psychological state, a significant group×time interaction was observed in the total WHOQOL-BREF score (P=.049), suggesting an impact of the game on quality of life. The psychological (P=.01), social (P=.003), and environmental (P=.04) subdomains of the WHOQOL-BREF showed only a significant time effect. Other psychological scales did not display any significant changes (all P>.05). CONCLUSIONS: Our findings suggest that the rice-farming game intervention might have positive effects on nature relatedness, nature-friendly dietary behaviors, quality of life, anxiety, depression, interpersonal relationships, and resilience among urban adults during the COVID-19 pandemic. The impact of pronature games in confined urban environments provides valuable evidence of how digital technologies can be used to enhance urban residents' affinity for nature and psychological well-being. This understanding can be extended in the future to other digital platforms, such as metaverses. TRIAL REGISTRATION: Clinical Research Information Service (CRIS) KCT0007657; http://tinyurl.com/yck7zxp7.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.045
GPT teacher head0.414
Teacher spread0.369 · 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 designRandomized trial
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

Citations3
Published2024
Admission routes1
Has abstractyes

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