A Preliminary Investigation of the Role of Anthropomorphism in Designing Telehealth Bots for Older Adults
Bibliographic record
Abstract
Autonomous virtual agents (VAs) are increasingly used commercially in critical information spaces such as healthcare. Existing VA research has focused on microscale interaction patterns such as usability and artificial intelligence. However, the macroscale patterns of users' information practices and their relationship with the design and adoption of VAs have been largely understudied, especially when it comes to older adults (OAs), who stand to benefit greatly from VAs. We conducted a preliminary investigation to understand the role design elements, such as anthropomorphic aspects of VAs, play in OAs' perception of VAs and in OAs' preferences for VAs' participation within their health information practices. Some unexpected findings indicate that the fidelity of anthropomorphic features influences perception in ways that are dependent on the context of the information tasks. This suggests that research on improving the design and increasing the adoption of VAs should factor the interplay between fidelity of VA representation and information context.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".