Prediction of treatment outcome in psychotherapy by patient initial symptom distress profiles.

Abstract

Understanding how different groups of patients change at different rates is important for treatment selection, planning and evaluation. This study aimed to assess whether an approach to classifying patients on the basis of initial symptom distress profiles (ISDPs) derived from a self-rated questionnaire measuring psychological distress may be useful in predicting treatment response. The Clinical Outcome in Routine Evaluation-Outcome Measure were collected from 1,095 first line mental health service patients (M [SD] age ϭ 37.3 [14.3] years; 74% female) prior to every session. Latent profile analysis was performed on the questionnaires from the first session to classify participants into subtypes, which were then used to predict change rates. The best-fitting model identified 4 ISDP subtypes with significantly different treatment responses. Profile 1 predicted very slow change rate and indicated low initial distress coupled with low deviations among problem areas. Profile 2 predicted slow change rate with average initial distress and low emphasis on questions relating to risk of harming oneself and/or others. Profile 3 predicted fast improvement rate and showed high initial distress combined with low emphasis on the risk area. Profile 4 predicted moderate change rate and displayed very high initial distress accompanied with more emphasis on the risk area. Findings support the potential utility of ISDP subtypes to predict treatment response, suggesting that intake data that is easily collected by the clinician contain reliable information about treatment prognosis. The study is exploratory and needs to be replicated before stable conclusions can be drawn. Public Significance StatementThis study demonstrates the importance of considering specific compositions of patient rated psychological distress at the first treatment session to predict recovery rate. Better understanding of how baseline factors relate to outcome in psychotherapy enables guidance for clinicians and can facilitate treatment planning as well as evaluation of treatment response in ongoing treatments (treatment monitoring).

Variations in Well-Being as a Function of Paranormal Belief and Psychopathological Symptoms: A Latent Profile Analysis

“…Unusual Experiences 12-items). While scaled means were utilised to minimise this (which is advocated with LPA; Uckelstam et al, 2019), high scores on variables should be interpreted as relative rather than absolute.…”

Mental pain intensity and tolerance as predictors of psychotherapy process and outcome

“…These findings indicate that low MP has the potential to reduce therapeutic effectiveness and to further be associated with discomfort during the therapeutic sessions. Uckelstam et al (2019) examined whether the classification of patients on the basis of their initial symptom distress profiles predicted treatment response. They found that patients with low initial distress and low deviations among problem areas fitted a profile of a very slow change rate.…”

Prediction of Therapeutic Outcome in a Naturalistic Setting Using Pretreatment Psychological Distress Indicators

“…A principal interest of practice-oriented psychotherapy research is to identify factors that predict treatment outcome before therapy starts [Riedel et al, 2011;Lewis et al, 2012;Uckelstam et al, 2019]. Different conceptions of success make it difficult, however, to establish universal standards for the evaluation of psychological treatment.…”