In Search of Lost Time: Discrete- Versus Continuous-Time Models of Working Alliance and Symptom Severity

被引:0
作者
Wester, Robin Anno [1 ]
Koch, Tobias [2 ]
Muench, Fabian [2 ]
Driver, Charles [3 ]
Lutz, Wolfgang [4 ]
Rubel, Julian [1 ]
机构
[1] Osnabruck Univ, Dept Clin Psychol & Psychotherapy, Lise Meitner Str 3, D-49069 Osnabruck, Germany
[2] Friedrich Schiller Univ Jena, Dept Psychol, Jena, Germany
[3] Univ Zurich, Dept Psychol, Zurich, Switzerland
[4] Univ Trier, Dept Psychol, Trier, Germany
关键词
working alliance; cognitive behavioral therapy; mechanism of change; continuous-time models; COGNITIVE-BEHAVIORAL THERAPY; INTERPERSONAL PROBLEMS; DYNAMIC PSYCHOTHERAPY; ROUTINE CARE; PANEL-DATA; SESSION; PATTERNS; DEPRESSION; IMPROVEMENT; MECHANISMS;
D O I
10.1037/ccp0000929
中图分类号
B849 [应用心理学];
学科分类号
040203 ;
摘要
Objective: The therapeutic alliance is one of the most stable predictors of symptom burden over the course of therapy. So far, this effect has only been examined on the basis of sessions. Continuous-time models (CTM) allow this relationship to be modeled as a continuous process in which the actual time interval between measurements is considered. The aim of the present study was to compare the fit of discrete-time models (DTM) of the alliance-symptom relationship with CTM using different time variables (sessions vs. actual time interval). Method: Data from 1,413 patients at a university psychotherapy outpatient clinic were analyzed. The alliance and symptom burden were assessed each session with the Bernese Session Report and the Hopkins Symptom Checklist-Short-Form, respectively. Different DTM and CTM were estimated using the R-package ctsem and compared in their fit via the Akaike information criterion. Results: CTMs with session as the time unit fitted the data best. Significant negative within-person effects of alliance and symptom burden were found. These effects showed a significant positive correlation, implying that individuals with a stronger effect of the alliance on symptom severity also showed a stronger effect of symptom severity on the alliance. Conclusions: When modeling the relationship of symptom severity and alliance, it seems to be of more importance to capture the fact that a session occurred than to capture the exact time intervals between sessions. Future studies should examine this finding for other psychotherapeutic factors. Interpersonal factors might explain the positive association of the reciprocal alliance-symptom effects.
引用
收藏
页码:27 / 39
页数:13
相关论文
共 40 条
  • [21] Closed-form approximations of moments and densities of continuous-time Markov models
    Kristensen, Dennis
    Lee, Young Jun
    Mele, Antonio
    JOURNAL OF ECONOMIC DYNAMICS & CONTROL, 2024, 168
  • [22] Estimating animal utilization densities using continuous-time Markov chain models
    Wilson, Kenady
    Hanks, Ephraim
    Johnson, Devin
    METHODS IN ECOLOGY AND EVOLUTION, 2018, 9 (05): : 1232 - 1240
  • [23] An Information-flow-Based Sensitivity Analysis Method for Continuous-Time Models
    Yin, Yimin
    Duan, Xiaojun
    2018 IEEE/ACIS 16TH INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING RESEARCH, MANAGEMENT AND APPLICATION (SERA), 2018, : 25 - 30
  • [24] Recursive online IV method for identification of continuous-time slowly time-varying models in closed loop
    Padilla, A.
    Garnier, H.
    Young, P. C.
    Yuz, J.
    IFAC PAPERSONLINE, 2017, 50 (01): : 4008 - 4013
  • [25] Consequences of Sampling Frequency on the Estimated Dynamics of AR Processes Using Continuous-Time Models
    Batra, Rohit
    Johal, Simran K. K.
    Chen, Meng
    Ferrer, Emilio
    PSYCHOLOGICAL METHODS, 2023,
  • [26] Approximate Bayesian inference for discretely observed continuous-time multi-state models
    Tancredi, Andrea
    BIOMETRICS, 2019, 75 (03) : 966 - 977
  • [27] IDENTIFICATION OF LINEAR AND NONLINEAR CONTINUOUS-TIME MODELS FROM SAMPLED-DATA SETS
    TSANG, KM
    BILLINGS, SA
    JOURNAL OF SYSTEMS ENGINEERING, 1995, 5 (04): : 249 - 267
  • [28] Bond valuation under a discrete-time regime-switching term-structure model and its continuous-time extension
    Elliott, Robert J.
    Siu, Tak Kuen
    Badescu, Alex
    MANAGERIAL FINANCE, 2011, 37 (11) : 1025 - 1047
  • [29] Long-memory recursive prediction error method for identification of continuous-time fractional models
    Victor, Stephane
    Duhe, Jean-Francois
    Melchior, Pierre
    Abdelmounen, Youssef
    Roubertie, Francois
    NONLINEAR DYNAMICS, 2022, 110 (01) : 635 - 648
  • [30] Long-memory recursive prediction error method for identification of continuous-time fractional models
    Stéphane Victor
    Jean-François Duhé
    Pierre Melchior
    Youssef Abdelmounen
    François Roubertie
    Nonlinear Dynamics, 2022, 110 : 635 - 648