Identifying Which Relational Cues Users Find Helpful to Allow Tailoring of e-Coach Dialogues
Relational cues are extracts from actual verbal dialogues that help build the therapist–patient working alliance and stronger bond through the depiction of empathy, respect and openness. ECAs (Embodied conversational agents) are human-like virtual agents that exhibit verbal and non-verbal behaviours...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-10-01
|
| Series: | Multimodal Technologies and Interaction |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2414-4088/7/10/93 |
| _version_ | 1797572715939364864 |
|---|---|
| author | Sana Salman Deborah Richards Mark Dras |
| author_facet | Sana Salman Deborah Richards Mark Dras |
| author_sort | Sana Salman |
| collection | DOAJ |
| description | Relational cues are extracts from actual verbal dialogues that help build the therapist–patient working alliance and stronger bond through the depiction of empathy, respect and openness. ECAs (Embodied conversational agents) are human-like virtual agents that exhibit verbal and non-verbal behaviours. In the digital health space, ECAs act as health coaches or experts. ECA dialogues have previously been designed to include relational cues to motivate patients to change their current behaviours and encourage adherence to a treatment plan. However, there is little understanding of who finds specific relational cues delivered by an ECA helpful or not. Drawing the literature together, we have categorised relational cues into empowering, working alliance, affirmative and social dialogue. In this study, we have embedded the dialogue of Alex, an ECA, to encourage healthy behaviours with all the relational cues (empathic Alex) or with none of the relational cues (neutral Alex). A total of 206 participants were randomly assigned to interact with either empathic or neutral Alex and were also asked to rate the helpfulness of selected relational cues. We explore if the perceived helpfulness of the relational cues is a good predictor of users’ intention to change the recommended health behaviours and/or development of a working alliance. Our models also investigate the impact of individual factors, including gender, age, culture and personality traits of the users. The idea is to establish whether a certain group of individuals having similarities in terms of individual factors found a particular cue or group of cues helpful. This will establish future versions of Alex and allow Alex to tailor its dialogue to specific groups, as well as help in building ECAs with multiple personalities and roles. |
| first_indexed | 2024-03-10T21:00:39Z |
| format | Article |
| id | doaj.art-64418b6b410b410384cbdfd66ff72f24 |
| institution | Directory Open Access Journal |
| issn | 2414-4088 |
| language | English |
| last_indexed | 2024-03-10T21:00:39Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Multimodal Technologies and Interaction |
| spelling | doaj.art-64418b6b410b410384cbdfd66ff72f242023-11-19T17:35:14ZengMDPI AGMultimodal Technologies and Interaction2414-40882023-10-017109310.3390/mti7100093Identifying Which Relational Cues Users Find Helpful to Allow Tailoring of e-Coach DialoguesSana Salman0Deborah Richards1Mark Dras2School of Computing, Macquarie University, Sydney, NSW 2109, AustraliaSchool of Computing, Macquarie University, Sydney, NSW 2109, AustraliaSchool of Computing, Macquarie University, Sydney, NSW 2109, AustraliaRelational cues are extracts from actual verbal dialogues that help build the therapist–patient working alliance and stronger bond through the depiction of empathy, respect and openness. ECAs (Embodied conversational agents) are human-like virtual agents that exhibit verbal and non-verbal behaviours. In the digital health space, ECAs act as health coaches or experts. ECA dialogues have previously been designed to include relational cues to motivate patients to change their current behaviours and encourage adherence to a treatment plan. However, there is little understanding of who finds specific relational cues delivered by an ECA helpful or not. Drawing the literature together, we have categorised relational cues into empowering, working alliance, affirmative and social dialogue. In this study, we have embedded the dialogue of Alex, an ECA, to encourage healthy behaviours with all the relational cues (empathic Alex) or with none of the relational cues (neutral Alex). A total of 206 participants were randomly assigned to interact with either empathic or neutral Alex and were also asked to rate the helpfulness of selected relational cues. We explore if the perceived helpfulness of the relational cues is a good predictor of users’ intention to change the recommended health behaviours and/or development of a working alliance. Our models also investigate the impact of individual factors, including gender, age, culture and personality traits of the users. The idea is to establish whether a certain group of individuals having similarities in terms of individual factors found a particular cue or group of cues helpful. This will establish future versions of Alex and allow Alex to tailor its dialogue to specific groups, as well as help in building ECAs with multiple personalities and roles.https://www.mdpi.com/2414-4088/7/10/93embodied conversational agentse-Coache-healthrelational cuesempathic agents |
| spellingShingle | Sana Salman Deborah Richards Mark Dras Identifying Which Relational Cues Users Find Helpful to Allow Tailoring of e-Coach Dialogues Multimodal Technologies and Interaction embodied conversational agents e-Coach e-health relational cues empathic agents |
| title | Identifying Which Relational Cues Users Find Helpful to Allow Tailoring of e-Coach Dialogues |
| title_full | Identifying Which Relational Cues Users Find Helpful to Allow Tailoring of e-Coach Dialogues |
| title_fullStr | Identifying Which Relational Cues Users Find Helpful to Allow Tailoring of e-Coach Dialogues |
| title_full_unstemmed | Identifying Which Relational Cues Users Find Helpful to Allow Tailoring of e-Coach Dialogues |
| title_short | Identifying Which Relational Cues Users Find Helpful to Allow Tailoring of e-Coach Dialogues |
| title_sort | identifying which relational cues users find helpful to allow tailoring of e coach dialogues |
| topic | embodied conversational agents e-Coach e-health relational cues empathic agents |
| url | https://www.mdpi.com/2414-4088/7/10/93 |
| work_keys_str_mv | AT sanasalman identifyingwhichrelationalcuesusersfindhelpfultoallowtailoringofecoachdialogues AT deborahrichards identifyingwhichrelationalcuesusersfindhelpfultoallowtailoringofecoachdialogues AT markdras identifyingwhichrelationalcuesusersfindhelpfultoallowtailoringofecoachdialogues |