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Record W2902574908 · doi:10.1016/j.pmrj.2018.07.004

Barriers, Facilitators and Interventions to Support Virtual Reality Implementation in Rehabilitation: A Scoping Review

2018· review· en· W2902574908 on OpenAlexaff
Stephanie Glegg, Danielle Levac

Bibliographic record

VenuePM&R · 2018
Typereview
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsSunny Hill Health Centre for ChildrenUniversity of British Columbia
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of Health
KeywordsPsychological interventionKnowledge translationRehabilitationContext (archaeology)Virtual realityMedical educationKnowledge managementPsychologyMedicineApplied psychologyNursingComputer scienceHuman–computer interactionPhysical therapy

Abstract

fetched live from OpenAlex

Virtual reality and active video games (VR/AVGs) are promising rehabilitation tools because of their potential to facilitate abundant, motivating, and feedback-rich practice. However, clinical adoption remains low despite a growing evidence base and the recent development of clinically accessible and rehabilitation-specific VR/AVG systems. Given clinicians' eagerness for resources to support VR/AVG use, a critical need exists for knowledge translation (KT) interventions to facilitate VR/AVG integration into clinical practice. KT interventions have the potential to support adoption by targeting known barriers to, and facilitators of, change. This scoping review of the VR/AVG literature uses the Theoretical Domains Framework (TDF) to (1) structure an overview of known barriers and facilitators to clinical uptake of VR/AVGs for rehabilitation; (2) identify KT strategies to target these factors to facilitate adoption; and (3) report the results of these strategies. Barriers/facilitators and evaluated or proposed KT interventions spanned all but 1 and 2 TDF domains, respectively. Most frequently cited barriers/facilitators were found in the TDF domains of Knowledge, Skills, Beliefs About Capabilities, Beliefs About Consequences, Intentions, Goals, Environmental Context and Resources, and Social Influences. Few studies empirically evaluated KT interventions to support adoption; measured change in VR/AVG use did not accompany improvements in self-reported skills, attitudes, and knowledge. Recommendations to target frequently identified barriers include technology development to meet end-user needs more effectively, competency development for end-users, and facilitated VR/AVG implementation in clinical settings. Subsequent research can address knowledge gaps in both clinical and VR/AVG implementation research, including on KT intervention effectiveness and unexamined TDF domain barriers. LEVEL OF EVIDENCE: IV.

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)0.022
metaresearch head score (Gemma)0.092
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 score0.022
Threshold uncertainty score0.114

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.092
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0050.007
Bibliometrics0.0130.010
Science and technology studies0.0020.001
Scholarly communication0.0050.004
Open science0.0030.003
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.076
GPT teacher head0.466
Teacher spread0.391 · 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

Citations223
Published2018
Admission routes1
Has abstractyes

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Same venuePM&RSame topicStroke Rehabilitation and RecoveryFrench-language works237,207