Cited by 219Digital Mental Health InterventionsEducational Games and GamificationAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes

The DOI matches its Crossref record; 57 of the 57 references it cites were found in a registry or an index; none of the 56 sources its claims cite is checked for support yet.

Game-Based Digital Interventions for Depression Therapy: A Systematic Review and Meta-Analysis

Open access
Li, Jinhui, Theng, Yin-Leng, Foo, Schubert·2014·Cyberpsychology, Behavior, and Social Networking

Abstract

The aim of this study was to review the existing literature on game-based digital interventions for depression systematically and examine their effectiveness through a meta-analysis of randomized controlled trials (RCTs). Database searching was conducted using specific search terms and inclusion criteria. A standard meta-analysis was also conducted of available RCT studies with a random effects model. The standard mean difference (Cohen's d) was used to calculate the effect size of each study. Nineteen studies were included in the review, and 10 RCTs (eight studies) were included in the meta-analysis. Four types of game interventions-psycho-education and training, virtual reality exposure therapy, exercising, and entertainment-were identified, with various types of support delivered and populations targeted. The meta-analysis revealed a moderate effect size of the game interventions for depression therapy at posttreatment (d=-0.47 [95% CI -0.69 to -0.24]). A subgroup analysis showed that interventions based on psycho-education and training had a smaller effect than those based on the other forms, and that self-help interventions yielded better outcomes than supported interventions. A higher effect was achieved when a waiting list was used as the control. The review and meta-analysis support the effectiveness of game-based digital interventions for depression. More large-scale, high-quality RCT studies with sufficient long-term data for treatment evaluation are needed.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This systematic review and meta-analysis examined game-based digital interventions for depression, identifying 19 studies and meta-analyzing 10 RCTs from 8 studies. Game interventions showed a moderate posttreatment effect on depression (d=−0.47, 95% CI −0.69 to −0.24), with subgroup differences by game type, support type, and control condition.

Key findings

  • Nineteen studies were included in the review, covering four game types: psycho-education and training, virtual reality exposure therapy, exercising, and entertainment.
  • The meta-analysis of 10 RCTs (8 studies; 636 participants) found a moderate effect size for depression at posttreatment: d=−0.47 [95% CI −0.69 to −0.24], Z=−4.09, p<0.0001, with moderate heterogeneity (I²=47%). After removing one possible outlier, the effect was d=−0.35 [95% CI −0.53 to −0.16] and heterogeneity fell to I²=18%.
  • Subgroup analyses showed virtual reality exposure therapy had the largest effect (d=−0.67 [95% CI −1.19 to −0.14]), followed by entertainment (d=−0.42 [95% CI −1.23 to 0.39]), psycho-education and training (d=−0.41 [95% CI −0.67 to −0.14]), and exercising (d=−0.24 [95% CI −0.86 to 0.39]).
  • Nontherapist-involved interventions had a larger effect than therapist-involved interventions (d=−0.54 vs. d=−0.44), and waiting-list controls yielded a larger effect (d=−0.66 [95% CI −1.14 to −0.18]) than treatment as usual (d=−0.39 [95% CI −0.68 to −0.11]) or active treatment (d=−0.53 [95% CI −1.10 to 0.03]).

Methods

  • Systematic review searching seven health and technology databases for English-language studies published before May 2013, using terms for digital games and depression/mental health; eligible studies had to evaluate depression symptoms with a reliable and valid depression scale.
  • Meta-analysis included only RCTs with a controlled condition (e.g., waiting list, treatment as usual, or active treatment); non-RCTs, studies with uninterpretable/incomplete data, and studies with game-based control conditions were excluded.
  • Ten RCTs from 8 studies were analyzed in Review Manager 5.2 using a random-effects model and Cohen’s d; heterogeneity was assessed with I² and Q statistics, and a priori subgroup analyses used a mixed-effects model. Risk of bias was assessed by two reviewers using Cochrane domains.

Limitations

  • The paper states that only a small number of studies met inclusion criteria, leading to relatively few RCTs for meta-analysis; broad ranges of target groups, support types, and depression severity produced considerable heterogeneity, limiting generalizability.
  • The paper states that long-term data are lacking; only the RCTs by Emmelkamp et al. and Proudfoot et al. reported some remaining benefits at 6-month follow-up, and attrition rates were not presented in the meta-analysis.
  • Evident from the text: several subgroup estimates were based on only one trial (entertainment, exercising, elderly), and many risk-of-bias domains were rated unclear due to incomplete reporting; one study had high risk of bias in random sequence generation, and two had high risk due to incomplete outcome data.

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Integrity signals

Registry

Crossref · 10.1089/cyber.2013.0481

Cites

57 of 57 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

0 of 56 cited sources checked · 0 supported · 0 flagged

Show all 41 claims

  • It may state two separate claims as one. 22
  • Probably not a substantial claim. 17
34 of 34
  • The paper relies on this without support.

    The included game-based digital interventions are sufficiently similar to be pooled in a single meta-analysis.

    “To estimate the effects of game-based digital interventions on depression, we applied the standard mean difference (Cohen's d) to calculate the effect size for each study in the posttreatment period, weighted by sample size, using a random effects model.”
  • The paper relies on this without support.

    The different control conditions (waiting lists, treatment as usual, other active treatments) are sufficiently comparable to be combined in the overall meta-analysis.

    “The meta-analysis only included RCTs that encompassed a controlled condition (such as waiting lists, treatment as usual, or other active treatments).”
  • The paper relies on this without support.

    The depression scales used across studies measure the same underlying construct and can be pooled as self-reported depression outcomes.

    “Eligible studies had to contain an evaluation of the treatment's effects on participants' depression symptoms using a reliable and valid depression scale.”
  • The paper relies on this without support.

    The search of seven databases and the selected search terms identified all relevant studies.

    “A search of seven main health and technology databasesa was conducted to identify studies published in English before May 2013.”
  • The paper relies on this without support.

    No treatment is worse than some treatment.

    “This may be because no treatment is worse than some treatment.”
  • The paper relies on this without support.

    Virtual reality exposure therapy is more cost effective than exposure in vivo and allows therapists to control appropriate exposure stimuli for patients.

    “Compared with exposure in vivo, which requires going outside, virtual reality exposure therapy is more cost effective, and allows therapists to control the appropriate exposure stimuli for patients.”
6 of 6

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?

Statistics recomputed

Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.

  • Consistentz = -4.09reported p < .0001 · recomputed p < .001

    “(Z=−4.09, p < .0001”

1 of 1

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Active-treatment result is marked significant despite a confidence interval crossing zero

    Minor

    The active-treatment comparison is marked *** (p<0.01), but its reported 95% confidence interval includes zero. Its reported Z of 1.85 also corresponds to a two-sided p-value of approximately 0.064.

  • Nontherapist subgroup significance marking is too strong

    Minor

    The reported Z of 3.27 corresponds to a two-sided p-value of approximately 0.0011, which does not meet the table's **** threshold of p<0.001.

  • Two game-type comparisons have incorrect significance markings

    Minor

    The reported Z values of 3.00 and 2.49 correspond to two-sided p-values of approximately 0.0027 and 0.013, respectively. Neither meets the table's stated **** threshold of p<0.001.

3 of 3

Citations

Cites

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Show all 57 references

Research works printed but not linked: 4

  1. The Cochrane Collaboration, 2012, Review Manager (RevMan)
  2. Lipsey MW, 2001, Applied Social Research Methods Series, 49
  3. Russoniello CV, 2009, Studies in Health Technology & Informatics, 144, 189
  4. Lenhart A, 2008, Pew Internet and American Life Project

Cited by

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Metadata

Authors
Li, J., Theng, Y.-L., & Foo, S.
Affiliations
Nanyang Technological University (SG)
Venue
Cyberpsychology, Behavior, and Social Networking
Published
2014-08
Volume
17
Issue
8
Pages
519-527
ISSN
  • 2152-2715 (ISSN-L)
  • 2152-2723
OpenAlex
W2038850367
Cited by
219
References
57
Citations by year
2026: 6 · 2025: 21 · 2024: 24 · 2023: 28 · 2022: 28 · 2021: 25 · 2020: 26 · 2019: 16 · 2018: 12 · 2017: 13 · 2016: 11 · 2015: 5 · 2014: 2
FWCI
1.25
Type
journal article
Language
en
Open access
Locations
  • Cyberpsychology Behavior and Social Networking (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
  • DR-NTU (Nanyang Technological University) (submittedVersion)
Funders
  • National Research Foundation
  • National Research Foundation Singapore
Topics
  • Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
  • Social Sciences › Psychology › Developmental and Educational Psychology › Educational Games and Gamification
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Keywords
depression treatment, serious games, virtual reality exposure therapy, psychoeducation, exercise intervention, self-help intervention, waitlist control, treatment effectiveness
MeSH terms
Depression, Female, Game Theory, Humans

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