Evidence map›Paper›PMID 33256148›Full record

ArticleInternational journal of environmental research and public health2020

Hedonic and Utilitarian Motivations of Home Motion-Sensing Game Play Behavior in China: An Empirical Study.

Yuqi Liu, Yao Song, Ryoichi Tamura

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
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  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Yuqi LiuSchool of Design, Kyushu University, Fukuoka 8158540, Japan.
Yao SongSchool of Design, The Hong Kong Polytechnic University, Hong Kong 999077, China.
Ryoichi TamuraSchool of Design, Kyushu University, Fukuoka 8158540, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As an important branch of video games and the integration of emerging motion-sensing technology, home motion-sensing games cannot only bring hedonic entertainment but also promote utilitarian benefits including exercise and social interaction for people to improve their physical and psychological health. As one of the most populous countries in the world, China has the largest number of households in the world but quite a low home game penetration rate due to the 13 year game industry winter for international enterprises. Whether Chinese customers have the intention of using motion-sensing games to improve their health status in the home environment will directly determine the commercial potential of the relevant industry in the Chinese market. In order to understand the motives of users and explore the market possibility and prospects of the game industry, this study adopts empirical research and structural equation modeling to construct a motivation model of Chinese consumers toward motion-sensing gameplay behavior in the household environment. We distributed 515 questionnaires to conduct a survey; 427 valid responses have been received, and 203 data, which meet the inclusion criteria of the required game experience, have been analyzed by SPSS25.0 and AMOS25.0. A structural equation model for the gameplay motivation has been constructed. The result shows that the three functional motivators, exercise (Path efficient = 0.40,

Indexed as

MotivationMovementVideo GamesAdolescentAdultChinaEmpirical ResearchFemaleHumansMaleSocial BehaviorSurveys and QuestionnairesYoung AdultChinese marketempirical studymotion-sensing gamemotivationwellness and health

Identifiers

PMID33256148
PMCPMC7730092

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.