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Personalised Serious Games and Gamification in Healthcare: Survey and Future Research Directions

Stéphanie Carlier, Femke De Backere, Filip De Turck

TL;DR

Future research should standardize personalized SGG development, focusing on component reuse to streamline design and enhance evaluation, and reusability of personalisation algorithms and domain knowledge is underemphasized.

Abstract

Serious games and gamification (SGG) in eHealth have positive health impacts, but a personalized approach is needed due to diverse user contexts. This introduces challenges in achieving personalization in SGG. A literature search on Web of Science and PubMed identified 31 articles: 22 on serious games and 9 on gamification. These strategies are most applied in behavior change and rehabilitation, with machine learning and AI showing promise for personalization. Reusability of personalisation algorithms and domain knowledge is underemphasized, reported in only 10 articles. Future research should standardize personalized SGG development, focusing on component reuse to streamline design and enhance evaluation.

Personalised Serious Games and Gamification in Healthcare: Survey and Future Research Directions

TL;DR

Future research should standardize personalized SGG development, focusing on component reuse to streamline design and enhance evaluation, and reusability of personalisation algorithms and domain knowledge is underemphasized.

Abstract

Serious games and gamification (SGG) in eHealth have positive health impacts, but a personalized approach is needed due to diverse user contexts. This introduces challenges in achieving personalization in SGG. A literature search on Web of Science and PubMed identified 31 articles: 22 on serious games and 9 on gamification. These strategies are most applied in behavior change and rehabilitation, with machine learning and AI showing promise for personalization. Reusability of personalisation algorithms and domain knowledge is underemphasized, reported in only 10 articles. Future research should standardize personalized SGG development, focusing on component reuse to streamline design and enhance evaluation.

Paper Structure

This paper contains 28 sections, 9 figures, 5 tables.

Table of Contents

  1. Introduction
  2. Method
  3. Search Strategy
  4. Inclusion Criteria and Study Selection
  5. Findings
  6. Overview
  7. Player and Knowledge Models
  8. Personalisation Methods
  9. Artificial Neural Networks (ANN)
  10. Recommender systems
  11. Random Forest Classification
  12. Deep Learning
  13. Reinforcement Learning
  14. Data Mining
  15. Interpolation
  16. ...and 13 more sections

Figures (9)

  • Figure 1: Flow chart of the literature search procedure.
  • Figure 2: Six domains within health care have been identified, of which rehabilitation and behaviour change contained the most articles. Two articles combined two domains(*), namely behaviour change and health education.
  • Figure 3: The Hexad Player Framework maps game elements on 6 distinct player types, based on the intrinsic or extrinsic motivation of users marczewski_even_2015.
  • Figure 4: Recipe ontology used for modelling user and expert knowledge in the serious game ' Express Cooking Train" by Mitsis et al. mitsis_ontology-based_2019.
  • Figure 5: An example of a primitive element (a) and a mixed element (b) in the knowledge model of Pardos et al. pardos_enriching_2023
  • ...and 4 more figures