Evidence map›Paper›PMID 36810767›Full record

ArticleScientific reports2023

Exploring user experience and performance of a tedious task through human-agent relationship.

Chao Zhou, Yulong Bian, Shu Zhang, Ziyang Zhang, Yaoyuan Wang, Yong-Jin Liu

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
4.0field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 12 citations in OpenAlex.

  1. Trial
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Chao Zhou *Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China.
Yulong Bian *Department of Computer Science and Technology, Tsinghua University, Beijing, 100084, China.
Shu ZhangDepartment of Computer Science and Technology, Tsinghua University, Beijing, 100084, China.
Ziyang ZhangAdvanced Computing and Storage Laboratory, Huawei Technologies Co Ltd, Shenzhen, 518000, China.
Yaoyuan WangAdvanced Computing and Storage Laboratory, Huawei Technologies Co Ltd, Shenzhen, 518000, China.
Yong-Jin LiuDepartment of Computer Science and Technology, Tsinghua University, Beijing, 100084, China. liuyongjin@tsinghua.edu.cn.
Tsinghua University · CNHuawei Technologies (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Positive human-agent relationships can effectively improve human experience and performance in human-machine systems or environments. The characteristics of agents that enhance this relationship have garnered attention in human-agent or human-robot interactions. In this study, based on the rule of the persona effect, we study the effect of an agent's social cues on human-agent relationships and human performance. We constructed a tedious task in an immersive virtual environment, designing virtual partners with varying levels of human likeness and responsiveness. Human likeness encompassed appearance, sound, and behavior, while responsiveness referred to the way agents responded to humans. Based on the constructed environment, we present two studies to explore the effects of an agent's human likeness and responsiveness to agents on participants' performance and perception of human-agent relationships during the task. The results indicate that when participants work with an agent, its responsiveness attracts attention and induces positive feelings. Agents with responsiveness and appropriate social response strategies have a significant positive effect on human-agent relationships. These results shed some light on how to design virtual agents to improve user experience and performance in human-agent interactions.

Indexed as

AttentionEmotionsHumansMan-Machine Systems

Identifiers

PMID36810767
PMCPMC9944929
OpenAlexW4321455477

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.