17073
Understanding Child, Provider and Setting Characteristics That May Affect Fidelity of Implementation of Evidence-Based Practices
The relationship between fidelity of implementation (FI) in community settings and child outcomes has become a critical issue as a demand for broader use of empirically supported behavioral treatments (ESBTs) increases. Most studies examine one type of FI, procedural fidelity (Odom et al., 2010), which measures the degree to which the provider uses procedures required to execute the treatment as intended. Another important type of FI is therapist competence (the level of skill and judgment used in executing the treatment; Schoenwald et al., 2011). Most studies examining FI of ESBTs do not account for these broader level variables, such as provider education, child characteristics, setting and competence, which may be just as important for child outcomes. There is thus a need to carefully evaluate relationships between these broader variables and behaviors targeted by ESBTs to develop an understanding of the necessary ingredients for effective community care.
Objectives:
To evaluate relationships between child behavior (within session) and provider demographics, child characteristics, setting and general therapeutic behavior in the context of implementation of a naturalistic behavioral intervention, Pivotal Response Training (PRT).
Methods:
As part of a larger investigation of key components of PRT, 296 video samples from archival data of research and community providers using PRT between 2000 and 2011 were reviewed. Demographics were collected for participating providers and children (age, race/ethnicity; provider education). Each video unit was coded for specific child and adult behavior. Positive child behaviors included those associated with positive outcomes: active participation, functional object use, communication, and attention. Disruptive child behavior was also coded. Provider behaviors included those associated with good clinical skill: appropriate prompting, arrangement of the environment, presenting clear tasks, eliminating distractions, rapport, animation/affect, and management of unwanted behaviors. Videos were coded by trained, reliable coders who rated each element on a defined Likert scale. Hierarchical linear modeling (HLM) was used due to the nested structure of the data: (a) video units [level-1] nested within children [level-2] nested within providers [level-3]. Average disruption and average positive child behaviors were used as the target outcome variables.
Results:
Child race and age were significantly associated with disruptive behavior. White children had significantly higher average disruption scores and lower positive behavior scores than Asian and children of more than one race. Younger children had higher disruptive behavior than older children. Provider race was significantly associated with average positive behavior scores with Asian providers predicting significantly higher average positive child behavior scores over other races. On average, children in group settings (classrooms) had significantly lower positive behavior than children in one-to-one settings. Lack of variability in provider clinical skills limited our ability to conduct analyses on those variables. Additional fidelity data specific to PRT are currently being analyzed and will be presented.
Conclusions:
Provider, child and environmental characteristics may greatly affect child disruptive and positive behaviors within treatment sessions. These variables must be examined along with fidelity of implementation to help determine the effectiveness of evidence-based practices in community and research settings.