The structure and dynamics of client session reactions: A
longitudinal network analysis

k 2022

The structure and dynamics of client session reactions: A longitudinal network analysis

ŘIHÁČEK, Tomáš, Robert ELLIOTT and Jesse OWEN

Basic information

Original name

The structure and dynamics of client session reactions: A longitudinal network analysis

Authors

ŘIHÁČEK, Tomáš, Robert ELLIOTT and Jesse OWEN

Edition

53nd Annual International Meeting of the Society for Psychotherapy Research, 2022

Other information

Language

English

Type of outcome

Prezentace na konferencích

Field of Study

50100 5.1 Psychology and cognitive sciences

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Organization unit

Faculty of Social Studies

Keywords in English

Client session reactions; longitudinal network analysis

Abstract

V originále

Objective: Understanding complex relationships among various aspects of clients’ session experience is essential for effective therapy. This study aimed to test the feasibility of applying longitudinal network modeling to understand the structure and dynamics of clients’ session reactions. Method: Data from three samples were combined (two general outpatient samples of emotion-focused therapy (EFT) and one study comparing EFT and cognitive-behavioral therapy for trauma). One hundred and twenty-three psychotherapy clients answered the Revised Session Reactions Scale after every session. Data collected after sessions 2 to 5 (413 observations) were used to fit a lag-1 dynamic latent variable model for panel data. The temporal, contemporaneous, and between-person networks were obtained and analyzed exploratively. Data from session 1 and sessions 6+ could not be used due to the nonstationarity of model parameters and low sample size. Results: Session reactions that played the most central role in the temporal prediction of other reactions included distancing from one’s thoughts, feelings, or memories and new discoveries related to the self. Both types of experience predicted, among others, the therapeutic relationship and a sense of relief. Feeling involved in therapy had a marginal role in the network. Conclusions: Longitudinal network modeling proved to be a promising approach to exploring clients’ session experience and, in a broader sense, to the analysis of psychotherapy process data. It yielded innovative and clinically meaningful findings of the interrelatedness of complex session-by-session processes.

Links

TL03000049, research and development project

Name: Deep learning v psychoterapii: Strojová analýza nahrávek terapeutických sezení (Acronym: DeePsy)

Investor: Technology Agency of the Czech Republic

Citovat

ŘIHÁČEK, Tomáš, Robert ELLIOTT and Jesse OWEN. The structure and dynamics of client session reactions: A longitudinal network analysis. In 53nd Annual International Meeting of the Society for Psychotherapy Research. 2022.

@proceedings{1882875,
   author = {Řiháček, Tomáš and Elliott, Robert and Owen, Jesse},
   booktitle = {53nd Annual International Meeting of the Society for Psychotherapy Research},
   keywords = {Client session reactions; longitudinal network analysis},
   language = {eng},
   title = {The structure and dynamics of client session reactions: A longitudinal network analysis},
   year = {2022}
}

TY  - CONF
ID  - 1882875
AU  - Řiháček, Tomáš - Elliott, Robert - Owen, Jesse
PY  - 2022
TI  - The structure and dynamics of client session reactions: A longitudinal network analysis
KW  - Client session reactions
KW  - longitudinal network analysis
N2  - Objective: Understanding complex relationships among various aspects of clients’ session experience is essential for effective therapy. This study aimed to test the feasibility of applying longitudinal network modeling to understand the structure and dynamics of clients’ session reactions. Method: Data from three samples were combined (two general outpatient samples of emotion-focused therapy (EFT) and one study comparing EFT and cognitive-behavioral therapy for trauma). One hundred and twenty-three psychotherapy clients answered the Revised Session Reactions Scale after every session. Data collected after sessions 2 to 5 (413 observations) were used to fit a lag-1 dynamic latent variable model for panel data. The temporal, contemporaneous, and between-person networks were obtained and analyzed exploratively. Data from session 1 and sessions 6+ could not be used due to the nonstationarity of model parameters and low sample size. Results: Session reactions that played the most central role in the temporal prediction of other reactions included distancing from one’s thoughts, feelings, or memories and new discoveries related to the self. Both types of experience predicted, among others, the therapeutic relationship and a sense of relief. Feeling involved in therapy had a marginal role in the network. Conclusions: Longitudinal network modeling proved to be a promising approach to exploring clients’ session experience and, in a broader sense, to the analysis of psychotherapy process data. It yielded innovative and clinically meaningful findings of the interrelatedness of complex session-by-session processes.
ER  -

ŘIHÁČEK, Tomáš, Robert ELLIOTT and Jesse OWEN. The structure and dynamics of client session reactions: A longitudinal network analysis. In \textit{53nd Annual International Meeting of the Society for Psychotherapy Research}. 2022.

Detailed Information on Publication Record