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Record W2789007859 · doi:10.2196/games.9530

Empirical Evidence for the Outcomes of Therapeutic Video Games for Adolescents With Anxiety Disorders: Systematic Review

2018· review· en· W2789007859 on OpenAlexvenueno aff
Steven Barnes, Julie Prescott

Bibliographic record

VenueJMIR Serious Games · 2018
Typereview
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyPsychological interventioneHealthPsychologySocial anxietyScopusClinical psychologyExtant taxonmHealthCognitive behavioral therapyMEDLINEPsychotherapistPsychiatryHealth care

Abstract

fetched live from OpenAlex

BACKGROUND: Extant evidence suggests that the proportion of adolescents suffering from anxiety disorders (ADs) has increased by up to 70% since the mid-1980s, with experience of anxiety at this stage associated with significant negative short- and long-term life outcomes. The existing therapeutic interventions (eg, cognitive behavioral therapy, CBT; attention bias modification, ABM) have proven to have clinically measurable benefits in reducing anxiety, but their efficacy is often compromised by social and practical barriers. The growing discrepancy between demand for, and access to, clinical interventions for anxiety has led to the development of a range of eHealth (health care practice supported by electronic processes and communication) and mHealth (versions of eHealth using mobile devices) interventions. One such protocol is therapeutic games, which aim to provide clinical frameworks in dynamic, adaptable, and personalized virtual environments. Although some evidence exists to suggest therapeutic games are associated with reductions in subjective anxiety and observed stress reactivity, there is currently, to our knowledge, no systematic review of the adherence to, and effectiveness of, therapeutic games for adolescent anxiety. OBJECTIVE: The aim of this review was to establish the effectiveness of therapeutic games in making clinically measurable reductions in anxiety symptoms in adolescent samples. METHODS: A systematic search of the existing academic literature published between 1990 and July 2017 was conducted using the databases Journal of Medical Internet Research, Journal Storage, Psychology Articles, Psychology Info, ScienceDIRECT, and Scopus. Records linked to empirical papers on therapeutic games for anxiety using adolescent samples were evaluated. RESULTS: A total of 5 studies (N=410 participants) met the inclusion criteria, and 3 gamified anxiety interventions for adolescents were identified. The papers included a mixture of randomized controlled trials, quasi-experimental studies, and usability studies comprising quantitative and qualitative measures, with varying degrees of mixed methods. Extant evidence shows potential for therapeutic games to create clinically measurable reductions in symptoms of anxiety in adolescent samples, though findings are complicated in some cases by a low sample size, and in other cases by research design and methodological complications, including anxiety reductions in control groups caused by a control-game selection. CONCLUSIONS: Although research in this field appears to be extremely limited, as demonstrated by the small number of papers meeting the inclusion criteria for this review, early findings suggest that therapeutic games have potential in helping to engage adolescents with anxiety and lead to clinically measurable reductions in symptoms.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.078
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.011
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.078
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.008
Bibliometrics0.0100.008
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.149
GPT teacher head0.465
Teacher spread0.316 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations74
Published2018
Admission routes1
Has abstractyes

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