Evidence map›Paper›PMID 40127464›Full record

ArticleJMIR serious games2025

Feasibility and Usability of an Artificial Intelligence-Powered Gamification Intervention for Enhancing Physical Activity Among College Students: Quasi-Experimental Study.

Yanan Gao, Jinxi Zhang, Zhonghui He, Zhixiong Zhou

Abstract read
In one paragraph

Article in JMIR serious games, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. 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

4 authors.

Yanan GaoSchool of Physical Education and Sport Science, Fujian Normal University, Fuzhou, China.ORCID http://orcid.org/0000-0002-3641-5449
Jinxi ZhangInstitute of Artificial Intelligence in Sports, Capital University of Physical Education and Sports, 11 Beisanhuan West Road, Beijing, 100191, China, 86 13552505679.ORCID http://orcid.org/0000-0002-8048-6703
Zhonghui HeThe Department of Physical Education, Peking University, Beijing, China.ORCID http://orcid.org/0000-0001-7059-3022
Zhixiong ZhouInstitute of Artificial Intelligence in Sports, Capital University of Physical Education and Sports, 11 Beisanhuan West Road, Beijing, 100191, China, 86 13552505679.ORCID http://orcid.org/0000-0003-3369-1429

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Physical activity (PA) is vital for physical and mental health, but many college students fail to meet recommended levels. Artificial intelligence (AI)-powered gamification interventions through mobile app have the potential to improve PA levels among Chinese college students. Objective: This study aimed to assess the feasibility and usability of an AI-powered gamification intervention. Methods: A quasi-experimental study spanning 2 months was conducted on a sample of college students aged 18 to 25 years old from 18 universities in Beijing. PA data were recorded using the ShouTi Fitness app, and participant engagement was evaluated through surveys. User satisfaction was gauged through the System Usability Scale, while the intervention's feasibility was assessed through Spearman rank correlation analysis, Mann-Whitney tests, and additional descriptive analyses. Results: As of July 2023, we enrolled 456 college students. In total, 18,073 PA sessions were recorded, with men completing 8068 sessions and women completing 10,055 sessions. The average PA intensity was 7 metabolic equivalent of energy (MET)s per session. Most participants preferred afternoon sessions and favored short-duration sessions, with men averaging 66 seconds per session and women 42 seconds. The System Usability Scale score for the intervention based on app is 65.2. Users responded positively to the integration of AI and gamification elements, including personalized recommendations, action recognition, smart grouping, dynamic management, collaborative, and competition. Specifically, 341 users (75%) found the AI features very interesting, 365 (80%) were motivated by the gamification elements, 364 (80%) reported that the intervention supported their fitness goals, and 365 (80%) considered the intervention reliable. A significant positive correlation was observed between the duration of individual PA and intervention duration for men (ρ=0.510, P<.001), although the correlation was weaker for women (ρ=0.258, P=.046). However, the frequency of PA declined after 35 days. Conclusions: This study provides pioneering evidence of the feasibility and usability of the AI-powered gamification intervention. While adherence was successfully demonstrated, further studies or interventions are needed to directly assess the impact on PA levels and focus on optimizing long-term adherence strategies and evaluating health outcomes.

Indexed as

artificial intelligencedigital healthdigital interventionfeasibility studygamificationphysical activity

Identifiers

PMID40127464
PMCPMC11957469

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.