AI Medical Compendium Journal:
Psychotherapy research : journal of the Society for Psychotherapy Research

Showing 1 to 10 of 11 articles

Predicting working alliance in psychotherapy: A multi-modal machine learning approach.

Psychotherapy research : journal of the Society for Psychotherapy Research
OBJECTIVE: Session-by-session tracking of the working alliance enables clinicians to detect alliance deterioration and intervene accordingly, which has shown to improve treatment outcome, and reduce dropout. Despite this, regular use of alliance self...

Decoding emotions: Exploring the validity of sentiment analysis in psychotherapy.

Psychotherapy research : journal of the Society for Psychotherapy Research
OBJECTIVE: Given the importance of emotions in psychotherapy, valid measures are essential for research and practice. As emotions are expressed at different levels, multimodal measurements are needed for a nuanced assessment. Natural Language Process...

Predicting dropout from psychological treatment using different machine learning algorithms, resampling methods, and sample sizes.

Psychotherapy research : journal of the Society for Psychotherapy Research
The occurrence of dropout from psychological interventions is associated with poor treatment outcome and high health, societal and economic costs. Recently, machine learning (ML) algorithms have been tested in psychotherapy outcome research. Dropout...

Detecting defense mechanisms from Adult Attachment Interview (AAI) transcripts using machine learning.

Psychotherapy research : journal of the Society for Psychotherapy Research
OBJECTIVE: Defensive functioning (i.e., unconscious process used to manage real or perceived threats) may play a role in the development of various psychopathologies. It is typically assessed via observer rating measures, however, human coding of def...

Predicting first session working alliances using deep learning algorithms: A proof-of-concept study for personalized psychotherapy.

Psychotherapy research : journal of the Society for Psychotherapy Research
OBJECTIVE: The aim of this proof-of-concept study is to develop a predictive model based on deep learning algorithms to predict working alliances after the first therapeutic session and to provide a basis for clinical decisions.

For whom should psychotherapy focus on problem coping? A machine learning algorithm for treatment personalization.

Psychotherapy research : journal of the Society for Psychotherapy Research
OBJECTIVE: We aimed to develop and test an algorithm for individual patient predictions of problem coping experiences (PCE) (i.e., patients' understanding and ability to deal with their problems) effects in cognitive-behavioral therapy. In an outpat...

A scoping review of machine learning in psychotherapy research.

Psychotherapy research : journal of the Society for Psychotherapy Research
Machine learning (ML) offers robust statistical and probabilistic techniques that can help to make sense of large amounts of data. This scoping review paper aims to broadly explore the nature of research activity using ML in the context of psychologi...

Understanding the relationship between patient language and outcomes in internet-enabled cognitive behavioural therapy: A deep learning approach to automatic coding of session transcripts.

Psychotherapy research : journal of the Society for Psychotherapy Research
Understanding patient responses to psychotherapy is important in developing effective interventions. However, coding patient language is a resource-intensive exercise and difficult to perform at scale. Our aim was to develop a deep learning model to...

Generalized linear mixed-model (GLMM) trees: A flexible decision-tree method for multilevel and longitudinal data.

Psychotherapy research : journal of the Society for Psychotherapy Research
Decision-tree methods are machine-learning methods which provide results that are relatively easy to interpret and apply by human decision makers. The resulting decision trees show how baseline patient characteristics can be combined to predict trea...

Predicting personalized process-outcome associations in psychotherapy using machine learning approaches-A demonstration.

Psychotherapy research : journal of the Society for Psychotherapy Research
Personalized treatment methods have shown great promise in efficacy studies across many fields of medicine and mental health. Little is known, however, about their utility in process-outcome research. This study is the first to apply personalized tr...