Perceived Psychotherapist's Empathy and Therapy Motivation as Determinants of Long-Term Therapy Success-Results of a Cohort Study of Short Term Psychodynamic Inpatient Psychotherapy

Prediction of Chinese clients' satisfaction with psychotherapy by machine learning

Background

Effective psychotherapy should satisfy the client, but that satisfaction depends on many factors. We do not fully understand the factors that affect client satisfaction with psychotherapy and how these factors synergistically affect a client's psychotherapy experience.

Aims

This study aims to use machine learning to predict Chinese clients' satisfaction with psychotherapy and analyze potential outcome contributors.

Methods

In this cross-sectional investigation, a self-compiled online questionnaire was delivered through the WeChat app. The information of 791 participants who had received psychotherapy was used in the study. A series of features, for example, the participants' demographic features and psychotherapy-related features, were chosen to distinguish between participants satisfied and dissatisfied with the psychotherapy they received. With our dataset, we trained seven supervised machine-learning-based algorithms to implement prediction models.

Results

Among the 791 participants, 619 (78.3%) reported being satisfied with the psychotherapy sessions that they received. The occupation of the clients, the location of psychotherapy, and the form of access to psychotherapy are the three most recognizable features that determined whether clients are satisfied with psychotherapy. The machine-learning model based on the CatBoost achieved the highest prediction performance in classifying satisfied and psychotherapy clients with an F1 score of 0.758.

Conclusion

This study clarified the factors related to clients' satisfaction with psychotherapy, and the machine-learning-based classifier accurately distinguished clients who were satisfied or unsatisfied with psychotherapy. These results will help provide better psychotherapy strategies for specific clients, so they may achieve better therapeutic outcomes.

Determinants of quality of life improvements in anxiety and depressive disorders-A longitudinal study of inpatient psychotherapy

Background

Quality of life (QoL) is substantially impaired in patients with anxiety disorders (AD) and depressive disorders (DD) and improvements in symptom burden after psychotherapy are not always paralleled by similar improvements in QoL. So far, little is known about treatment outcome in terms of QoL and predictors of QoL improvements following inpatient psychotherapy with a focus on cognitive behavior therapy (CBT). The current study aimed at investigating the relationship between changes in symptoms and QoL across different life domains. Additionally, predictors of a positive treatment outcome were evaluated.

Methods

122 patients with AD and/or DD undergoing an 8-weeks inpatient CBT program completed self-report measures of psychopathological symptoms and QoL at pre- and post-treatment. Mixed effects models were used to investigate changes, a confirmatory factor analysis was applied to analyze the latent factor structure of the anxiety sensitivity index and binary logistic regression analyses were performed for predictors of QoL improvements.

Results

Patients showed moderate to strong decreases in anxious and depressive symptoms and moderate to strong improvements in general QoL, particularly in the psychological and physical QoL subdomains. Changes in symptom burden correlated most strongly with psychological and physical QoL. In addition, poor QoL before treatment and low levels of specific anxiety sensitivity symptoms (items 1 and 5) significantly predicted improvement in QoL.

Conclusion

Patients with poor QoL who are not as inhibited to openly express their anxious feelings particularly benefit from inpatient psychotherapy (individual and group) to improve their QoL. In contrast, our research suggests that patients who are too anxious to openly express their nervousness should receive additional social skills training, more focused treatment to build sufficient self-confidence to better engage in the treatment program.

Development of a measure quantifying helpful psychotherapy interventions: The Helpful Therapeutic Attitudes and Interventions Scale

BACKGROUND

Despite the number of empirical studies identifying the helpful factors correlated with beneficial psychotherapy outcomes, there is no validated scale that measures helpful therapeutic attitudes and interventions applied by therapists within the actual therapy process in China. In the current study, we developed the Helpful Therapeutic Attitudes and Interventions Scale (HTAIS) as an accessible client-rated instrument to measure useful interventions applied by the therapist during psychotherapy sessions.

MATERIALS AND METHODS

Based on the results of previous literature and our prior psychotherapy process studies, a 40-item measure was initially designed. Two studies with a total of 2,780 Chinese participants who received psychotherapy were carried out to evaluate the structure, reliability, and validity of the developed scale.

RESULTS

Principal component analysis yielded a three-component HTAIS containing 26 items. The scale included dimensions labeled "Empathy, respect and neutrality," "Using techniques to solve practical issues," and "In-depth exploration and expansion." Confirmatory factor analysis showed the construct validity of the derived three components model. And the developed scale had high internal consistency and test-retest reliability. The scale scores of the HTAIS were positively correlated with those of the Working Alliance Scale and Session Rating Scale, as well as clients' perceived therapy satisfaction, thus supporting its concurrent validity.

CONCLUSION

The HTAIS allows an immediate examination, as experienced by the client, of the extent to which certain useful therapeutics interventions have been conducted during therapy and could help to improve the clinician's subsequent therapy strategies. Future research is suggested to further validate the scale, especially to assess its psychometric properties in various populations with different clinical complaints.