Towards a Unified Model of Gamification and Motivation
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The Unified Gamification and Motivation (UGM) model provides a framework for understanding how including gamification elements in therapeutic intervention can enhance treatment engagement.
“The Unified Gamification and Motivation (UGM) model lends a framework for understanding how including gamification elements in therapeutic intervention can enhance treatment engagement [24].”
From Examining the effectiveness of gamification in mental health apps for depression: Systematic review and meta-analysis (2021) · cites this paper as [24]
The citation lists haven’t been fetched yet
References 44 · Cited by 9
- Authors
- Dykens, I. T., Wetzel, A., Dorton, S. L., & Batchelor, E.
- Affiliations
- Sonalysts (United States) (US)
- Corresponding author
- Dorton, Stephen L.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2021
- Pages
- 53-70
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W3186228703
- Cited by
- 9
- References
- 44
- Citations by year
- 2026: 4 · 2024: 2 · 2023: 1 · 2022: 1 · 2021: 1
- FWCI
- 4.03
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Games and Gamification
- Social Sciences › Sociology and Political Science › Digital Games and Media
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- gamification, motivation, game elements, user engagement, psychology of motivation, training outcomes, user performance
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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