Introduction of an Emerging Technology Device Through PowerPoint® Training
Bibliographic record
Abstract
Successful inclusion of assistive technology in intervention is limited by training and the level of comfort with technology of treating occupational therapists. Experienced and new therapists need exposure and training on high technology assistive devices newly introduced on the market. The purpose of the study was to identify the effect of a PowerPoint presentation to introduce an emerging high technology device on two groups: 30 licensed occupational therapists and 27 students in an entry level master of occupational therapy program. The PowerPoint developed introduced and educated participants on the Assistive Dining Device. Participants completed a demographic form, the Survey of Technology Use and the Quebec User Evaluation of Satisfaction with assistive Technology. Participants also to rated their satisfaction with the information presented. Results showed 98% of the participants were satisfied with the information presented and 95% of the participants were satisfied with their acquired knowledge base to recommend the device for client use. Master of occupational therapy students were similar in personal characteristics to occupational therapists but were both more satisfied with the Assistive Dining Device characteristics and had a more positive attitude toward technology. Participants who had a less positive attitude toward technology also had a slightly lower mean satisfaction with the Assistive Dining Device than those who had a more positive attitude toward technology. PowerPoint presentations appear to be one effective means of communicating information about new technologies. Further study needs to be done to evaluate the effectiveness of similar media included in packaging and marketing of assistive technology devices.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.002 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".