Using Progress Feedback to Enhance Treatment Outcomes: A Narrative Review.

We face increasing demand for greater access to effective routine mental health services, including telehealth. However, treatment outcomes in routine clinical practice are only about half the size of those reported in controlled trials. Progress feedback, defined as the ongoing monitoring of patients' treatment response with standardized measures, is an evidence-based practice that continues to be under-utilized in routine care. The aim of the current review is to provide a summary of the current evidence base for the use of progress feedback, its mechanisms of action and considerations for successful implementation. We reviewed ten available meta-analyses, which report small to medium overall effect sizes. The results suggest that adding feedback to a wide range of psychological and psychiatric interventions (ranging from primary care to hospitalization and crisis care) tends to enhance the effectiveness of these interventions. The strongest evidence is for patients with common mental health problems compared to those with very severe disorders. Effect sizes for not-on-track cases, a subgroup of cases that are not progressing well, are found to be somewhat stronger, especially when clinical support tools are added to the feedback. Systematic reviews and recent studies suggest potential mechanisms of action for progress feedback include focusing the clinician's attention, altering clinician expectations, providing new information, and enhancing patient-centered communication. Promising approaches to strengthen progress feedback interventions include advanced systems with signaling technology, clinical problem-solving tools, and a broader spectrum of outcome and progress measures. An overview of methodological and implementation challenges is provided, as well as suggestions for addressing these issues in future studies. We conclude that while feedback has modest effects, it is a small and affordable intervention that can potentially improve outcomes in psychological interventions. Further research into mechanisms of action and effective implementation strategies is needed.

Why do patients go off track? Examining potential influencing factors for being at risk of psychotherapy treatment failure.

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.

The influence of extra-therapeutic social support on the association between therapeutic bond and treatment outcome.

Objective: Both good therapeutic bond as well as extra-therapeutic social support seem to enhance treatment outcomes. Some features of the therapeutic bond are similar to experiences in extra-therapeutic relationships (e.g., feelings of trust or belongingness). Patients with a lack of social support might benefit particularly from a good therapeutic bond, because a well-formed bond can partly substitute relationship needs. This study replicates former research (main effects of bond and social support) and investigates the hypothesized interaction between both constructs. Method: Data from 1206 adult patients receiving cognitive-behavioral outpatient therapy were analyzed. Patients rated early therapeutic bond, their impairment, as well as their social support. Multilevel regression analyses were applied to test for main effects and interactions between bond and social support predicting therapy outcome post treatment. Results: Consistent with prior research, both therapeutic bond and social support predicted therapy outcome. Among patients with high social support, the impact of the therapeutic bond was minimal, while patients with low social support benefited most from a good therapeutic bond. Conclusions: Results suggest that both the therapeutic bond and social support play a role in therapy outcomes and that good therapeutic bond quality might be especially important if a patient lacks social support.

What happens when the therapist leaves? The impact of therapy transfer on the therapeutic alliance and symptoms.

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.