Abstract
The present study aimed to (a) explore 2 indices of emotional congruence-temporal similarity and directional discrepancy-between clients' and therapists' ratings of their emotions as they cofluctuate session-by-session; and (b) examine whether client/therapist emotional congruence predicts clients' symptom relief and improved functioning. The sample comprised 109 clients treated by 62 therapists in a university setting. Clients and therapists self-reported their negative (NE) and positive emotions (PE) after each session. Symptom severity and functioning level were assessed at the beginning of each session using the clients' self-reports. To assess emotional congruence, an adaptation of West and Kenny's (2011) Truth and Bias model was applied. To examine the consequences of emotional congruence, polynomial regression, and response surface analyses were conducted (Edwards & Parry, 1993). Clients and therapists were temporally similar in both PE and NE. Therapists experienced less intense PE on average, but did not experience more or less intense NE than their clients. Those therapists who experienced more intense NE than their clients were more temporally similar in their emotions to their clients. Therapist/client incongruence in both PE and NE predicted poorer next-session symptomatology; incongruence in PE was also associated with lower client next-session functioning. Session-level symptoms were better when therapists experienced more intense emotions (both PE and NE) than their clients. The findings highlight the importance of recognizing the dynamic nature of emotions in client-therapist interactions and the contribution of session-by-session emotional dynamics to outcomes.
Original language | English |
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Pages (from-to) | 51-64 |
Number of pages | 14 |
Journal | Journal of Counseling Psychology |
Volume | 65 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2018 |
Bibliographical note
Publisher Copyright:© 2018 American Psychological Association.
Keywords
- Congruence
- Emotions
- Response surface analysis
- Truth and bias model