Literature DB >> 22799560

Decision support aids with anthropomorphic characteristics influence trust and performance in younger and older adults.

Richard Pak1, Nicole Fink, Margaux Price, Brock Bass, Lindsay Sturre.   

Abstract

This study examined the use of deliberately anthropomorphic automation on younger and older adults' trust, dependence and performance on a diabetes decision-making task. Research with anthropomorphic interface agents has shown mixed effects in judgments of preferences but has rarely examined effects on performance. Meanwhile, research in automation has shown some forms of anthropomorphism (e.g. etiquette) have effects on trust and dependence on automation. Participants answered diabetes questions with no-aid, a non-anthropomorphic aid or an anthropomorphised aid. Trust and dependence in the aid was measured. A minimally anthropomorphic aide primarily affected younger adults' trust in the aid. Dependence, however, for both age groups was influenced by the anthropomorphic aid. Automation that deliberately embodies person-like characteristics can influence trust and dependence on reasonably reliable automation. However, further research is necessary to better understand the specific aspects of the aid that affect different age groups. Automation that embodies human-like characteristics may be useful in situations where there is under-utilisation of reasonably reliable aids by enhancing trust and dependence in that aid. Practitioner Summary: The design of decision-support aids on consumer devices (e.g. smartphones) may influence the level of trust that users place in that system and their amount of use. This study is the first step in articulating how the design of aids may influence user's trust and use of such systems.

Entities:  

Mesh:

Year:  2012        PMID: 22799560     DOI: 10.1080/00140139.2012.691554

Source DB:  PubMed          Journal:  Ergonomics        ISSN: 0014-0139            Impact factor:   2.778


  10 in total

1.  A Little Anthropomorphism Goes a Long Way.

Authors:  Ewart J de Visser; Samuel S Monfort; Kimberly Goodyear; Li Lu; Martin O'Hara; Mary R Lee; Raja Parasuraman; Frank Krueger
Journal:  Hum Factors       Date:  2017-02       Impact factor: 2.888

2.  A multidisciplinary approach to designing and evaluating Electronic Medical Record portal messages that support patient self-care.

Authors:  Daniel Morrow; Mark Hasegawa-Johnson; Thomas Huang; William Schuh; Renato Ferreira Leitão Azevedo; Kuangxiao Gu; Yang Zhang; Bidisha Roy; Rocio Garcia-Retamero
Journal:  J Biomed Inform       Date:  2017-03-24       Impact factor: 6.317

3.  Driving With Agents: Investigating the Influences of Anthropomorphism Level and Physicality of Agents on Drivers' Perceived Control, Trust, and Driving Performance.

Authors:  Peiyao Cheng; Fangang Meng; Jie Yao; Yiran Wang
Journal:  Front Psychol       Date:  2022-06-15

4.  Determinants of Laypersons' Trust in Medical Decision Aids: Randomized Controlled Trial.

Authors:  Marvin Kopka; Malte L Schmieding; Felix Balzer; Markus A Feufel; Tobias Rieger; Eileen Roesler
Journal:  JMIR Hum Factors       Date:  2022-05-03

5.  You Look Human, But Act Like a Machine: Agent Appearance and Behavior Modulate Different Aspects of Human-Robot Interaction.

Authors:  Abdulaziz Abubshait; Eva Wiese
Journal:  Front Psychol       Date:  2017-08-23

6.  Looking for Age Differences in Self-Driving Vehicles: Examining the Effects of Automation Reliability, Driving Risk, and Physical Impairment on Trust.

Authors:  Ericka Rovira; Anne Collins McLaughlin; Richard Pak; Luke High
Journal:  Front Psychol       Date:  2019-04-26

7.  Heuristic thinking and altruism toward machines in people impacted by COVID-19.

Authors:  Celso M de Melo; Jonathan Gratch; Frank Krueger
Journal:  iScience       Date:  2021-02-23

8.  Automation Inner Speech as an Anthropomorphic Feature Affecting Human Trust: Current Issues and Future Directions.

Authors:  Alessandro Geraci; Antonella D'Amico; Arianna Pipitone; Valeria Seidita; Antonio Chella
Journal:  Front Robot AI       Date:  2021-04-23

9.  Inferring Trust From Users' Behaviours; Agents' Predictability Positively Affects Trust, Task Performance and Cognitive Load in Human-Agent Real-Time Collaboration.

Authors:  Sylvain Daronnat; Leif Azzopardi; Martin Halvey; Mateusz Dubiel
Journal:  Front Robot AI       Date:  2021-07-08

Review 10.  From Trust in Automation to Decision Neuroscience: Applying Cognitive Neuroscience Methods to Understand and Improve Interaction Decisions Involved in Human Automation Interaction.

Authors:  Kim Drnec; Amar R Marathe; Jamie R Lukos; Jason S Metcalfe
Journal:  Front Hum Neurosci       Date:  2016-06-30       Impact factor: 3.169

  10 in total

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