Modeling Change Trajectories for Mental Health Symptoms and Functioning During Psychotherapy
Class
Article
College
Emma Eccles Jones College of Education and Human Services
Faculty Mentor
Rick Cruz
Presentation Type
Poster Presentation
Abstract
Psychological symptoms are routinely measured in clinic settings using self-report surveys. Researchers can use this data to understand client progress and make necessary changes in treatment. Past studies focused on modeling client progress have generally used a formula called the reliable change index (RCI) to measure if clients’ symptoms have significantly improved or deteriorated, along with clinical thresholds, which are used to indicate whether clients have moved from clinical to typical symptom levels throughout treatment. These measures are simple and useful given they use two data points (beginning and end of treatment) to communicate client progress. However, contemporary practice often uses more frequent (e.g., weekly) assessment, and thus methodology incorporating data from every assessment is used to provide more nuanced information about change trajectories. Little research has been performed concerning how these two approaches may be used to provide complementary or unique information. In this study, we use secondary data to compare these two analytic methods. Deidentified data from 42 clients at a Clinical Psychology doctpresentation training clinic in Virginia were used to evaluate the study questions. Assessment measures included the Brief Adjustment Scale (BASE-6), Generalized Anxiety Disorder Scale (GAD-7), and the Patient Health Questionnaire (PHQ-9). For each measure, RCI metrics and clinical significance thresholds were obtained from existing research and clients were grouped according to their pre-to-post treatment RCI and whether they had passed the clinical significance threshold during treatment. Multilevel models were constructed to describe change trajectories for each of these groups. From these models, descriptive and visual output was produced providing a foundation by which to compare results for each group of clients. This study will provide information concerning the nature of client progress across different analytic methods, and will adv
Location
The South Atrium
Start Date
4-12-2018 3:00 PM
End Date
4-12-2018 4:15 PM
Modeling Change Trajectories for Mental Health Symptoms and Functioning During Psychotherapy
The South Atrium
Psychological symptoms are routinely measured in clinic settings using self-report surveys. Researchers can use this data to understand client progress and make necessary changes in treatment. Past studies focused on modeling client progress have generally used a formula called the reliable change index (RCI) to measure if clients’ symptoms have significantly improved or deteriorated, along with clinical thresholds, which are used to indicate whether clients have moved from clinical to typical symptom levels throughout treatment. These measures are simple and useful given they use two data points (beginning and end of treatment) to communicate client progress. However, contemporary practice often uses more frequent (e.g., weekly) assessment, and thus methodology incorporating data from every assessment is used to provide more nuanced information about change trajectories. Little research has been performed concerning how these two approaches may be used to provide complementary or unique information. In this study, we use secondary data to compare these two analytic methods. Deidentified data from 42 clients at a Clinical Psychology doctpresentation training clinic in Virginia were used to evaluate the study questions. Assessment measures included the Brief Adjustment Scale (BASE-6), Generalized Anxiety Disorder Scale (GAD-7), and the Patient Health Questionnaire (PHQ-9). For each measure, RCI metrics and clinical significance thresholds were obtained from existing research and clients were grouped according to their pre-to-post treatment RCI and whether they had passed the clinical significance threshold during treatment. Multilevel models were constructed to describe change trajectories for each of these groups. From these models, descriptive and visual output was produced providing a foundation by which to compare results for each group of clients. This study will provide information concerning the nature of client progress across different analytic methods, and will adv