Detecting premature departure in online text-based counseling using logic-based pattern matching.

ABSTRACT:

Background

More so than face-to-face counseling, users of online text-based services might drop out from a session before establishing a clear closure or expressing the intention to leave. Such premature departure may be indicative of heightened risk or dissatisfaction with the service or counselor. However, there is no systematic way to identify this understudied phenomenon.

Purpose

This study has two objectives. First, we developed a set of rules and used logic-based pattern matching techniques to systematically identify premature departures in an online text-based counseling service. Second, we validated the importance of premature departure by examining its association with user satisfaction. We hypothesized that the users who rated the session as less helpful wer

SUBMITTER: Xu Y 

PROVIDER: S-EPMC8632835 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature