The Role of Relevance in Shaping Perceptions of Sleep Hygiene Games Among University Students: Mixed Methods Study
Bibliographic record
Abstract
BACKGROUND: Sleep games are an emerging topic in the realm of serious health game research. However, designing features that are both enjoyable and effective at engaging users, particularly university students, to develop healthy sleep habits remains a challenge. OBJECTIVE: This study aims to investigate user preferences for 3 sleep game prototypes, that is, Hero's Sleep Journey, Sleep Tamagotchi, and Sleepland, and to explore their popularity and perceived utility in promoting sleep health. METHODS: A mixed methods approach was used in this study. Quantitative and qualitative data were collected through a co-design workshop involving 47 university students. Participants were presented with storyboard cards of game features and were asked to provide an overall rating on each game, as well as ratings for individual features. They were also encouraged to provide free-form comments on the features and suggest improvements. In addition, participants were asked to express their preferences among the 3 games regarding which game they would most like to play and which one they found most useful for promoting sleep health. RESULTS: Surprisingly, while Hero's Sleep Journey was the most popular choice among participants, Sleep Tamagotchi was perceived as the most beneficial for improving sleep health. Relevance emerged as an overarching theme in the qualitative data analysis, with 3 interconnected dimensions: psychological relevance to users' personal lives, logical relevance to sleep health, and situational relevance to users' circumstantial context. We discussed how the 3 dimensions of relevance address the autonomy and relatedness constructs outlined in the self-determination theory and proposed 3 design recommendations. CONCLUSIONS: Our serious sleep game prototypes demonstrated the potential to engage university students to develop healthy sleep hygiene. Future sleep game designs should aim to create a sense of relevance to users' personal lives, sleep health goals, and situational contexts. Rather than a one-size-fits-all approach, it is essential to develop a wide range of game genres and features to cater to diverse users. Aligning game features with sleep health goals and educating users on the design rationale through sleep knowledge are also important aspects. Furthermore, allowing users to customize their game experience and manage technology boundaries is necessary to nurture a sense of control and autonomy in the process of forming good sleep hygiene.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".