Metrics for Peer Counseling: Triangulating Success Outcomes for Online Therapy Platforms

要旨

Extensive research has been published on the conversational factors of effective volunteer peer counseling on online mental health platforms (OMHPs). However, studies differ in how they define and measure success outcomes, with most prior work examining only a single success metric. In this work, we model the relationship between previously reported linguistic predictors of effective counseling with four outcomes following a peer-to-peer session on a single OMHP: retention in the community, following up on a previous session with a counselor, users' evaluation of a counselor, and changes in users' mood. Results show that predictors correlate negatively with community retention but positively with users following up with and giving higher evaluations to individual counselors. We suggest actionable insights for therapy platform design and outcome measurement based on findings that the relationship between predictors and outcomes of successful conversations depends on differences in measurement construct and operationalization.

著者
Tony Wang
Georgia Institute of Technology, Atlanta, Georgia, United States
Haard K. Shah
7 Cups of Tea, Parlin, New Jersey, United States
Raj Sanjay. Shah
Georgia Institute of Technology, Atlanta, Georgia, United States
Yi-Chia Wang
Independent Researcher, San Mateo, California, United States
Robert E. Kraut
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Diyi Yang
Stanford University, Stanford, California, United States
論文URL

https://doi.org/10.1145/3544548.3581372

動画

会議: CHI 2023

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2023.acm.org/)

セッション: Mental Health

Room Y03+Y04
6 件の発表
2023-04-26 01:35:00
2023-04-26 03:00:00