Exploring the Impact of a Persuasive Serious Video Game (Farmily) on Promoting Home Gardening Among Novices: Design and Randomized Controlled Trial
Bibliographic record
Abstract
Background Home gardens worldwide provide sustenance, economic support, and access to fresh produce and promote household well-being, health, self-sufficiency, and food security. However, they face significant challenges worldwide and necessitate innovative promotion approaches. Serious video games have proven effective in promoting agricultural knowledge. However, more research is needed on the persuasive potential of agriculture games to influence players’ thoughts, attitudes, and behaviors. This provides an opportunity to examine the impact of persuasive games on promoting home gardening among novices. Objective This study aims to describe the design and development of Farmily, a persuasive video game promoting home gardening among novices. In addition, it evaluated the effectiveness of Farmily and compared its impact with that of a traditional home gardening workshop. Furthermore, the study explored how game enjoyment relates to the game’s outcomes. Methods A randomized controlled trial with 50 novice gardening participants aged 20 to 50 years was carried out. Participants were randomly assigned to a control group (1.5-hour workshop) or an experimental group (1.5-hour Farmily session). Pre- and postintervention assessments were conducted. We evaluated Farmily’s impact on knowledge, attitudes, perceived self-efficacy, and intentions regarding initiating home gardens. In addition, we investigated the user enjoyment and its relationship with the game’s effect outcomes. Results The experimental group significantly improved their knowledge (t24=4.26; P<.001), attitude (z24=2.98; P=.003), self-efficacy (t24=2.6; P=.02), and intention to initiate home gardens (z24=4.15; P<.001). The experimental group showed similar effectiveness in knowledge transfer (t24=–1.71; P=.09) and a more significant impact on attitude (z24=2.73; P=.006), self-efficacy (t24=2.21; P=.03), and intention to start a home garden (t24=–5.33; P<.001) than the control group. Farmily was well received by the intervention group, generating high enjoyment. Furthermore, user enjoyment substantially correlated with user attitudes (r23=0.72; P<.001) and self-efficacy (r23=0.67; P<.001), yet no discernible association was observed among user enjoyment, knowledge (r23=0.26; P=.20), and intention (r23=0.06; P=.77). Conclusions Evidence indicates that Farmily appears to be a viable tool for promoting home gardening among novices in the short term. Farmily demonstrated similar effects in knowledge improvement to those of a traditional workshop and had a more significant impact on the other variables. In addition, we found that the player’s gaming experience positively relates to the player’s attitudes and self-efficacy. A well-powered randomized controlled trial with more diverse samples and extended follow-up periods will be conducted to establish the long-term efficacy of Farmily and gain a deeper understanding of the influence of enjoyment on game outcomes.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
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".