Academic Journal
Predicting Dropouts of the Unified Protocol for Transdiagnostic Treatment of Emotional Disorders: Joint Modelling of Survival and Longitudinal Data.
| Τίτλος: | Predicting Dropouts of the Unified Protocol for Transdiagnostic Treatment of Emotional Disorders: Joint Modelling of Survival and Longitudinal Data. |
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| Συγγραφείς: | Ferreira Â; CIPsi-Psychology Research Center, School of Psychology, University of Minho, Braga, Portugal., Sousa I; Department of Mathematics and Applications, School of Sciences, University of Minho, Braga, Portugal., Ribeiro E; CIPsi-Psychology Research Center, School of Psychology, University of Minho, Braga, Portugal. |
| Πηγή: | Clinical psychology & psychotherapy [Clin Psychol Psychother] 2026 Jul-Aug; Vol. 33 (4), pp. e70313. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: John Wiley & Sons Country of Publication: England NLM ID: 9416196 Publication Model: Print Cited Medium: Internet ISSN: 1099-0879 (Electronic) Linking ISSN: 10633995 NLM ISO Abbreviation: Clin Psychol Psychother Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Chichester, West Sussex, England : John Wiley & Sons, c1993- |
| Ιατρικοί όροι (MeSH): | Patient Dropouts*/statistics & numerical data , Patient Dropouts*/psychology , Psychotherapy*/methods, Humans ; Female ; Male ; Adult ; Longitudinal Studies ; Middle Aged ; Proportional Hazards Models |
| Περίληψη: | Understanding when and who is at greater risk of dropping out can help therapists and mental health professionals develop strategies to keep clients engaged, thereby improving the overall effectiveness of therapy. In the present study, we aimed to explore the hazard of dropout, both early and late in treatment, and evaluate the predictive power of both static (i.e., baseline client characteristics) and dynamic predictors (i.e., treatment process variables), in a sample of 97 clients treated with the Unified Protocol for Transdiagnostic Treatment of Emotional Disorders. Thirty-one clients (31.96%) discontinued treatment, with the highest dropout rate observed at the end of Session 4. Stratified Cox modelling showed a significant effect of younger age INLINEMATH , non-student status INLINEMATH and higher baseline anxiety severity INLINEMATH , on the risk of dropping out until Session 4 (i.e., the early phase of treatment). Beyond Session 4, only lower depressive severity measured at intake began to significantly affect the risk of dropout INLINEMATH . Additionally, joint modelling (JM) of survival and longitudinal data for the early phase of treatment provided evidence of the predictive power of lower distress levels INLINEMATH and lower therapeutic alliance quality INLINEMATH on the clients' decision to discontinue treatment prematurely. After Session 4, no factor showed a significant association with dropout risk within the JM approach. The results suggest that early sessions are critical for the client's retention, and the JM approach is indispensable for studying psychotherapy dropout, especially in the context of endogenous time-varying predictors. Implications for clinical and research contexts are discussed. (© 2026 John Wiley & Sons Ltd.) |
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| Grant Information: | UID/01662 Portuguese Foundation for Science and Technology; SFRH/BD/131337/2017 Portuguese Foundation for Science and Technology |
| Contributed Indexing: | Keywords: dropout; joint modelling; psychotherapy; survival analysis; therapeutic alliance |
| Entry Date(s): | Date Created: 20260805 Date Completed: 20260805 Latest Revision: 20260927 |
| Update Code: | 20260927 |
| PubMed Central ID: | PMC13439339 |
| DOI: | 10.1002/cpp.70313 |
| PMID: | 42554000 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1099-0879 |
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| DOI: | 10.1002/cpp.70313 |