Evidence map›Paper›PMID 33074155›Full record

ArticleJMIR mHealth and uHealth2020

Archetypes of Gamification: Analysis of mHealth Apps.

Manuel Schmidt-Kraepelin, Philipp A Toussaint, Scott Thiebes, Juho Hamari, Ali Sunyaev

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

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

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  12. Current best practices and future opportunities for reproducible findings using large-scale neuroimaging in psychiatry.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024
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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

5 authors.

Manuel Schmidt-Kraepelin *Department of Economics and Management, Karlsruhe Institute of Technology, Karlsruhe, Germany.ORCID 0000-0003-1280-3874
Philipp A Toussaint *Department of Economics and Management, Karlsruhe Institute of Technology, Karlsruhe, Germany.ORCID 0000-0002-1617-3307
Scott ThiebesDepartment of Economics and Management, Karlsruhe Institute of Technology, Karlsruhe, Germany.ORCID 0000-0002-6917-1831
Juho HamariGamification Group, Faculty of Information Technology and Communication Sciences, Tampere University, Tampere, Finland.ORCID 0000-0002-6573-588X
Ali SunyaevDepartment of Economics and Management, Karlsruhe Institute of Technology, Karlsruhe, Germany.ORCID 0000-0002-4353-8519

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNowadays, numerous health-related mobile apps implement gamification in an attempt to draw on the motivational potential of video games and thereby increase user engagement or foster certain health behaviors. However, research on effective gamification is still in its infancy and researchers increasingly recognize methodological shortcomings of existing studies. What we actually know about the phenomenon today stems from fragmented pieces of knowledge, and a variety of different perspectives. Existing research primarily draws on conceptual knowledge that is gained from research prototypes, and isolated from industry best practices. We still lack knowledge on how gamification has been successfully designed and implemented within the industry and whether certain gamification approaches have shown to be particularly suitable for certain health behaviors.

objectiveWe address this lack of knowledge concerning best practices in the design and implementation of gamification for health-related mobile apps by identifying archetypes of gamification approaches that have emerged in pertinent health-related mobile apps and analyzing to what extent those gamification approaches are influenced by the underlying desired health-related outcomes.

methodsA 3-step research approach is employed. As a first step, a database of 143 pertinent gamified health-related mobile apps from the Apple App Store and Google Play Store is set up. Second, the gamification approach of each app within the database is classified based on an established taxonomy for gamification in health-related apps. Finally, a 2-step cluster analysis is conducted in order to identify archetypes of the most dominant gamification approaches in pertinent gamified health-related mobile apps.

resultsEight archetypes of gamification emerged from the analysis of health-related mobile apps: (1) competition and collaboration, (2) pursuing self-set goals without rewards, (3) episodical compliance tracking, (4) inherent gamification for external goals, (5) internal rewards for self-set goals, (6) continuous assistance through positive reinforcement, (7) positive and negative reinforcement without rewards, and (8) progressive gamification for health professionals. The results indicate a close relationship between the identified archetypes and the actual health behavior that is being targeted.

conclusionsBy unveiling salient best practices and discussing their relationship to targeted health behaviors, this study contributes to a more profound understanding of gamification in mobile health. The results can serve as a foundation for future research that advances the knowledge on how gamification may positively influence health behavior change and guide practitioners in the design and development of highly motivating and effective health-related mobile health apps.

Indexed as

Mobile ApplicationsTelemedicineVideo GamesHealth BehaviorHumansMotivationexergames, persuasive technologygamificationmHealthmobile phonesquantified-selfsmartphones

Identifiers

PMID33074155
PMCPMC7605978

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.