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Record W3049148282 · doi:10.1111/medu.14352

Stereoscopic three‐dimensional visualisation technology in anatomy learning: A meta‐analysis

2020· review· en· W3049148282 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMedical Education · 2020
Typereview
Languageen
FieldEngineering
TopicAnatomy and Medical Technology
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMeta-analysisCINAHLMEDLINEStereoscopyCritical appraisalConfidence intervalPsychologyData extractionComputer scienceMedical educationMedicineArtificial intelligenceNursingPsychological interventionPathologyAlternative medicineInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVES: The features that contribute to the apparent effectiveness of three-dimensional visualisation technology [3DVT] in teaching anatomy are largely unknown. The aim of this study was to conduct a systematic review and meta-analysis of the role of stereopsis in learning anatomy with 3DVT. METHODS: The review was conducted and reported according to PRISMA Standards. Literature search of English articles was performed using EMBASE, MEDLINE, CINAHL EBSCOhost, ERIC EBSCOhost, Cochrane CENTRAL, Web of Science and Google Scholar databases until November 2019. Study selection, data extraction and study appraisal were performed independently by two authors. Articles were assessed for methodological quality using the Medical Education Research Study Quality Instrument and the Cochrane Collaboration's tool for assessing the risk of bias. For quantitative analysis, studies were grouped based on relative between-intervention differences in instructional methods and type of control conditions. RESULTS: A total of 3934 citations were obtained of which 67 underwent a full-text review. Ultimately, 13 randomised controlled trials were included in the meta-analysis. When interactive, stereoscopic 3D models were compared to interactive, monoscopic 3D models within a single level of instructional design, for example isolating stereopsis as the only true manipulated element in the experimental design, an effect size [ES] of 0.53 (95% confidence interval [CI] 0.26-0.80; P < .00001) was found. In comparison with 2D images within multiple levels of instructional design, an effect size of 0.45 (95% CI 0.10-0.81; P < .002) was found. Stereopsis had no effect on learning when utilised with non-interactive 3D images (ES = -0.87, 95% CI -2.09-0.35; P = .16). CONCLUSION: Stereopsis is an important distinguishing element of 3DVT that has a significant positive effect on acquisition of anatomical knowledge when utilised within an interactive 3D environment. A distinction between stereoscopic and monoscopic 3DVT is essential to make in anatomical education and research.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.366
Teacher spread0.335 · 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