Background Routine outcome monitoring can support clinicians to detect patients who deteriorate [not-on-track (NOT)] early in psychotherapy. Implemented Clinical Support Tools can direct clinicians’ attention towards potential obstacles to a positive treatment outcome and provide suggestions for suitable interventions. However, few studies have compared NOT patients to patients showing expected progress [on-track (OT)] regarding such obstacles. This study aimed to identify domains that have predictive value for NOT trajectories and to compare OT and NOT patients regarding these domains and the items of the underlying scales. Methods During treatment, 413 outpatients filled in the Hopkins-Symptom-Checklist-11 (depressive and anxious symptom distress) before every therapy session as a routine outcome measure. Further, the Assessment for Signal Clients, Affective Style Questionnaire, and Outcome Questionnaire-30 were applied every fifth session. These questionnaires measure the following domains, which were investigated as potential obstacles to treatment success: risk/suicidality, therapeutic alliance, motivation, social support and life events, as well as emotion regulation. Two groups (OT and NOT patients) were formed by defining a cut-off (failure boundary) as the 90% confidence interval (upper bound) of the respective patients’ expected recovery curves. In order to differentiate group membership based on the respective problem areas, multilevel logistic regression analyses were performed. Further, OT and NOT patients were compared with regard to the domains’ and items’ cut-offs by performing Pearson chi-square tests and independent samples t-tests. Results The life events and motivation scale as well as the risk/suicidality scale proved to be significant predictors of being not-on-track. NOT patients also crossed the cut-off significantly more often on the domains risk/suicidality, social support, and life events. For both OT and NOT patients, the emotion regulation domain’s cut-off was most commonly exceeded. Conclusion Life events, motivation, and risk/suicidality seem to be directly linked to treatment failure and should be further investigated for the use in clinical support tools.
Background The therapeutic alliance is an important factor in psychotherapy, affecting both therapy processes and outcome. Therapy transfers may impair the quality of the therapeutic alliance and increase symptom severity. The aim of this study is to investigate the impact of patient transfers in cognitive behavioural therapy on alliance and symptoms in the sessions after the transfer. Method Patient‐ and therapist‐rated therapeutic alliance and patient‐reported symptom severity were measured session‐to‐session. Differences in the levels of alliance and symptom severity before (i.e., with the original therapist) and after (i.e., with the new therapist) the transfer session were analysed. The development of alliance and symptom severity was explored using multilevel growth models. Results A significant drop in the alliance was found after the transfer, whereas no differences were found with regard to symptom severity. After an average of 2.93 sessions, the therapeutic alliance as rated by patients reached pretransfer levels, whereas it took an average of 5.05 sessions for therapist‐rated alliance levels to be at a similar level as before the transfer. Inter‐individual differences were found with regard to the development of the therapeutic alliance over time. Conclusions Therapy transfers have no long lasting negative effects on either symptom impairment or the therapeutic alliance.
Zusammenfassung. Theoretischer Hintergrund: Chronische Depressionen gehen mit einer langwierigen Belastung einher und verursachen hohe Krankheitskosten. Ein möglicher Ansatz zur Behandlung könnte die Loving Kindness Meditation (LKM) sein. Methode: In dieser Pilot-Studie wurde ein LKM-Gruppenprogramm eingesetzt und bezüglich der Effektivität untersucht. N = 2207 Fälle aus Wartelistendaten wurden stufenweise zu der LKM-Gruppe (n = 12) zugeordnet. Zwei Kontrollgruppen (n = 134 und n = 12) wurden gebildet, indem zunächst die Ein-und Ausschlusskriterien angewandt wurden und dann die verbliebene Stichprobe basierend auf der Kovariatenverteilung mittels Propensity Score Matching (PSM) angepasst wurde. Die Gruppen wurden anhand des OQ-30 verglichen. Ergebnisse: Im Prä-Post-Vergleich zeigten sich im OQ-30 signifikante Verbesserungen. Allerdings zeigte sich das so nicht in den symptomspezifischen Instrumenten (BDI-II und HAM-D). Im Vergleich zu der gesamten Wartelistenstichprobe (n = 134) ergaben sich signifikante Verbesserungen im OQ-30. Verglichen mit der PSM-Wartelistenkontrollgruppe zeigten sich marginal signifikante Unterschiede im OQ-30, signifikante Unterschiede konnten bezüglich der Depressionsitems des OQ-30 nachgewiesen werden. In der Interventionsgruppe ergaben sich mehr reliable Verbesserungen im OQ-30 als in den Wartelistenkontrollgruppen. Schlussfolgerung: Die Pilotstudie zeigte eine geringere Abbruchquote als Vorgängerpilotstudien und eine gute Prä-Post Effektstärke im OQ-30, sowie im Vergleich zu den beiden Wartelistekontrollgruppen. Allerdings zeigten sich keine konsistenten Prä-Post Effekte in den Depressionsskalen. Eine weitere umfangreichere Studie mit aktiver Kontrollgruppe wäre nötig, um das Programm hinsichtlich seiner Effektivität, bezüglich des Abbruchs sowie der Heterogenität der Effekte in den Depressionsskalen weiter untersuchen zu können.
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