Virtual Reality Support for Joint Attention Using the Floreo Joint Attention Module: Usability and Feasibility Pilot Study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Advances in virtual reality (VR) technology offer new opportunities to design supports for the core behaviors associated with autism spectrum disorder (ASD) that promote progress toward optimal outcomes. Floreo has developed a novel mobile VR platform that pairs a user receiving instruction on target skills with an adult monitor. OBJECTIVE: The primary objective of this pilot study was to explore the feasibility of using Floreo's Joint Attention Module in school-aged children with autism in a special education setting. A secondary objective was to explore a novel joint attention measure designed for use with school-aged children and to observe whether there was a suggestion of change in joint attention skills from preintervention to postintervention. METHODS: A total of 12 participants (age range: 9 to 16 years) received training with the Joint Attention Module for 14 sessions over 5 weeks. RESULTS: No serious side effects were reported, and no participants dropped out of the study because of undesirable side effects. On the basis of monitor data, 95.4% (126/132) of the time participants tolerated the headset, 95.4% (126/132) of the time participants seemed to enjoy using Floreo's platform, and 95.5% (128/134) of the time the VR experience was reported as valuable. In addition, scoring of the joint attention measure suggested a positive change in participant skills related to the total number of interactions, use of eye contact, and initiation of interactions. CONCLUSIONS: The study results suggest that Floreo's Joint Attention Module is safe and well tolerated by students with ASD, and preliminary data also suggest that its use is related to improvements in fundamental joint attention skills.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it