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Virtual serious games for women’s health education: A scoping review protocol v1

2025· review· en· W4410436046 on OpenAlexaff
K. Jordan, Christine Kurtz Landy, Celina Da Silva, Mahdieh Dastjerdi

Bibliographic record

Venuenot available
Typereview
Languageen
FieldPsychology
TopicEducational Games and Gamification
Canadian institutionsYork University
Fundersnot available
KeywordsProtocol (science)Internet privacyComputer sciencePolitical sciencePsychologyMedicineAlternative medicine

Abstract

fetched live from OpenAlex

Objective:This scoping review aimsto identify and map the current state of research on virtual serious games (VSGs) designed for women’s health education, with a focus on intendedusers, design characteristics, and assessed outcomes. Inclusion criteria:Quantitative, qualitative, and mixed methods study designs examining the use of virtual serious games intended for women’s health education. Grey literature sources such as conference abstracts, text, opinion papers,dissertations,and other unpublished material will be excluded. There is no limit on the publication period; however, sources are limited to English. Methods:The proposed review will be conducted in accordance with the JBI methodology for scoping reviews [18] and reported following the Preferred Reporting Items of Systematic Review and Meta-Analysis Extension for Scoping Reviews (PRISMA-ScR) [19]. Databases to be searched will include MEDLINE (OVID), CINHAL – Cumulative Index to Nursing and Allied Health Literature (EBSCO), Web of Science (Clarivate), PsycINFO (OVID), and Embase (OVID) databases. Hand-searching by reviewing selected articles' reference lists will complement the search and ensure relevant studies are not missed. All databases will be searched with no restrictions on the time frame. Search results from each database will be imported into EndNote20 and transferred into Covidence, where duplicates will be removed. Source selection (both at the title/abstract screening and full-text screening) will be performed by two reviewers, independentlyusing the inclusion and exclusion criteria. Any disagreements will be resolved through discussion or by the decision of a third reviewer. The primary researcher will extract data from the sources using a custom data extraction tool and verified by a second reviewer. Qualitative content analysis for basic coding of data to a particular category and descriptive statistical analysis (i.e., frequency counting) will be conducted relating to the study’s research questions. The SR results will be presented in tabular format and accompanied by a narrative summary describing how the results relate to the review objectives and questions. Expected Results: The expected results of this scoping review are to provide a comprehensive overview of existing VSGs developed for women's education, highlighting the target user groups, key design features, and the types of outcomes that have been evaluated. This will help identify gaps in the literature and inform future development and research in the area.

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)0.090
metaresearch head score (Gemma)0.067
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.110
Threshold uncertainty score0.474

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0900.067
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0100.010
Bibliometrics0.0150.012
Science and technology studies0.0050.004
Scholarly communication0.0080.008
Open science0.0050.007
Research integrity0.0080.006
Insufficient payload (model declined to judge)0.1100.025

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 head0.069
GPT teacher head0.513
Teacher spread0.443 · 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 designNot applicable
Domainnot available
GenreProtocol

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

Citations0
Published2025
Admission routes1
Has abstractyes

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