Abstract
Background
Fidelity, or the degree to which an intervention is implemented as designed, is essential for effective implementation. There has been a growing emphasis on assessing fidelity of evidence-based practices for autistic children in schools. Fidelity measurement should be multidimensional and focus on core intervention components and assess their link with program outcomes. This study evaluated the relation between intervention fidelity ratings from multiple sources, tested the relation between fidelity ratings and child outcomes, and determined the relations between core intervention components and child outcomes in a study of an evidence-based psychosocial intervention designed to promote inclusion of autistic children at school, Remaking Recess.
Method
This study extends from a larger randomized controlled trial examining the effect of implementation support on Remaking Recess fidelity and child outcomes. Schools were randomized to receive the intervention or the intervention plus implementation support. Observers, intervention coaches, and school personnel completed fidelity measures to rate completion and quality of intervention delivery. A measure of peer engagement served as the child outcome. Pearson correlation coefficients were calculated to determine concordance between raters. Two sets of hierarchical linear models were conducted using fidelity indices as predictors of peer engagement.
Results
Coach- and self-rated completion and quality scores, observer- and self-rated quality scores, and observer- and coach-rated quality fidelity scores were significantly correlated. Higher observer-rated completion and quality fidelity scores were predictors of higher peer engagement scores. No single intervention component emerged as a significant predictor of peer engagement.
Conclusions
This study demonstrates the importance of using a multidimensional approach for measuring fidelity, testing the link between fidelity and child outcomes, and examining how core intervention components may be associated with child outcomes. Future research should clarify how to improve multi-informant reports to provide “good enough” ratings of fidelity that provide meaningful information about outcomes in community settings.
Plain Language Summary
Fidelity is defined as how closely an intervention is administered in the way the creators intended. Fidelity is important because it allows researchers to determine what exactly is leading to changes. In recent years, there has been an interest in examining fidelity of interventions for autistic children who receive services in school. This study looked at the relationship between fidelity ratings from multiple individuals, the relationship between fidelity and child outcomes, and the relationship between individual intervention component and child changes in a study of Remaking Recess, an intervention for autistic children at school. Schools were randomly selected to receive the intervention only or the intervention plus implementation support from the research team. Observers, intervention coaches, and individuals delivering the intervention themselves completed fidelity measures. Child engagement with peers was measured before and after the intervention. Several measures of self-, coach-, and observer-report fidelity were associated with each other. Higher observer-reported fidelity was associated with higher child peer engagement scores. No single intervention step was linked to child peer engagement and both treatment groups had similar outcomes in terms of fidelity. This study shows the importance of having multiple raters assess different parts of intervention fidelity, looking at the link between fidelity and child outcomes, and seeing how individual intervention steps may be related to outcomes. Future research should aim to find out which types of fidelity ratings are “good enough” to lead to positive changes following treatment so that those aspects can be used and targeted in the future.
Introduction
Fidelity, or the degree to which an intervention is implemented as designed (Proctor et al., 2011), is commonly viewed as essential to effective implementation (Edmunds et al., 2022). In routine care settings, fidelity is an important measure of intervention implementation success (McLeod et al., 2013; Stirman, 2020), as researchers have demonstrated that fidelity is a crucial antecedent to desired outcomes (Durlak & DuPre, 2008; Schultes et al., 2015). Fidelity can help to explain variation in outcomes, such that understanding providers’ fidelity to implementation is critical to determining whether outcomes can be attributed to the particular intervention or to factors related to implementation (Schoenwald & Garland, 2013; Schultes et al., 2015). Thus, there is increased attention on not only intervention outcomes but also the level to which programs are implemented as intended to determine if how providers use an intervention impacts overall outcomes.
Given the established importance of fidelity, there has been a growing emphasis on the more consistent assessment of fidelity in “real-world” settings, such as community agencies and schools (Bond & Drake, 2020; Sanetti et al., 2020). However, measuring fidelity is not always straightforward or feasible in these settings due to a lack of agreement on the best and most pragmatic methods for assessing intervention fidelity (Harn et al., 2017; Schoenwald et al., 2011; Sutherland & McLeod, 2022). Current best practice in fidelity measurement is direct observation (Sanetti et al., 2020), specifically the use of observational coding systems with trained raters (Schoenwald et al., 2011). There are several practical concerns, however, to using observation to measure fidelity, especially in schools, such as time, cost, and level of training required (Sanetti et al., 2021; Schoenwald et al., 2011). Alternatives to observer-rated fidelity include self-report or participant-rated measures, though researchers have raised significant concerns regarding informant accuracy (e.g., social desirability, lack of knowledge regarding the core components of the intervention; Schoenwald et al., 2011). Despite documented limitations to self-reported fidelity ratings, there are perceived benefits for this type of measurement for evidence-based practice (EBP) implementation in schools, including the opportunity to serve as a “self-check” of EBP implementation and the potential to inform supervisory meetings in which EBP feedback is delivered (Hogue, 2022).
While fidelity measurement is reported to vary based on rater, a few studies have used multiple raters and compared ratings, a practice that has the potential to enhance the validity of fidelity measurement via triangulation of ratings (Bond & Drake, 2020; Lillehoj et al., 2004; Schultes et al., 2015). Hansen et al. (2014) compared teacher and observer fidelity ratings for a middle school based EBP and found that teachers rated their fidelity higher than did observers. Brookman-Frazee et al. (2021) examined therapist and observer fidelity ratings of EBP delivery in children’s mental health services and found greater concordance between self- and observer- rated fidelity when an EBP had greater structure. Dickson and Suhrheinrich (2021) compared observer, supervisor, and provider fidelity ratings for the delivery of an EBP for autistic youth and found that supervisors had greater concordance with observers than did providers. Despite these findings, questions remain as to how to pragmatically measure fidelity in school-based research and the association between EBP fidelity and student outcomes.
Moreover, while it may seem as though “more is better” when it comes to fidelity, instead, researchers need to identify the intervention components associated with desired outcomes to determine which components must be delivered to fidelity and which can be adapted to fit the context (Durlak & DuPre, 2008; Sutherland & McLeod, 2022). As a result, research has shifted to identifying the essential, or core, components of an intervention, or those posited to affect outcomes, and optimizing fidelity measures to capture these components while allowing for an “adaptable periphery” to improve fit-to-context (Edmunds et al., 2022). Therefore, it is crucial that fidelity measurement focus on core intervention components and assess their link with program outcomes (Schultes et al., 2015).
Fidelity and Autism-Specific Interventions
There is emerging systematic research examining the implementation of EBPs for autistic children in schools, and the association with student outcomes (e.g., Kratz et al., 2019; Locke, Kang-Yi, et al., 2019; Mandell et al., 2013; Pellecchia et al., 2015; Stahmer et al., 2015; Suhrheinrich et al., 2021). While schools are the primary setting in which autistic youth receive intervention, EBPs are not consistently implemented in schools (Dingfelder & Mandell, 2011). Furthermore, research suggests that intervention fidelity for autism-focused EBPs often is poor (e.g., Pellecchia et al., 2015; Locke et al., 2015, 2019; Mandell et al., 2013; Stahmer et al., 2015); however, students may still demonstrate improved outcomes. For instance, pilot studies and randomized controlled trials support the effectiveness of Remaking Recess, an evidence-based social engagement intervention that promotes the inclusion of autistic children on school playgrounds, in public elementary settings (Kretzmann et al., 2015; Locke, Kang-Yi, et al., 2019; Locke, Shih, et al., 2019; Shih et al., 2019). Studies of Remaking Recess, however, have shown low fidelity, in terms of both quality and adherence, with school personnel using approximately 50% of the intervention components, yet autistic children still demonstrated improved peer engagement (Kretzmann et al., 2015; Locke et al., 2015, 2019, 2020; Shih et al., 2019). These studies collected fidelity reports from multiple sources to assess the consistency between various reports, as well as their predictive ability for youth outcomes. Independent observer-, coach-, and school personnel self-report ratings of fidelity have consistently improved over an intervention training period (Kretzmann et al., 2015; Locke et al., 2015, 2019, 2020) but have declined at 6-week follow-up (Locke et al., 2020; Shih et al., 2019). Interestingly, Locke et al. (2020) found a higher mean quality fidelity score for self- vs. observer-ratings, but a higher observer- vs. self-rated strategy use fidelity score. Self-rated use also has been found to be higher (90%) than both coach- (76%), and observer-rated (52%) at a post-treatment timepoint, a pattern that maintained at follow-up (self = 85%, coach = 62%, observer = 40%; Shih et al., 2019). These findings are consistent with data from Locke et al. (2019), who found self-rated fidelity to be higher than coach-rated at baseline (self = 54.4%, coach = 38.8%) and at exit (self = 94%, coach = 79.6%). Previous results highlight the importance of capturing fidelity from multiple sources, examining how those ratings do or do not align, and testing how ratings relate to youth social outcomes. Notably, the links between Remaking Recess fidelity overall or to individual core components of the intervention and youth outcomes have not been examined.
Objectives of Current Study
There were three objectives of the current study. (a) To evaluate the relationship between intervention fidelity ratings provided by multiple sources. Although findings from the literature were mixed, we expected that fidelity ratings supplied by providers, coaches, and observers would be associated positively with one another. (b) To examine the relationship between fidelity ratings and youth outcomes. Based on prior research, we hypothesized that self-, coach-, and observer-rated fidelity would be associated positively with youth social engagement outcomes. (c) To examine the relationship between each core component of Remaking Recess and youth outcomes. We hypothesized that quality scores on all components of Remaking Recess would be positively associated with youth outcomes.
Method
The present study was a part of a larger trial examining the impact of implementation support on fidelity of Remaking Recess and child social outcomes (Locke, Shih, et al., 2019). The study was approved by the Institutional Review Boards from the research university, as well as each school district that participated.
Study Design
A randomized controlled design was used with three measurement timepoints: Baseline (start of implementation); Endpoint (post-implementation); and Follow-up (6 weeks post-implementation). Randomization was completed at the school level, with schools randomly assigned to one of two conditions: (a) training in Remaking Recess (n = 6), or (b) training in Remaking Recess with implementation support (n = 6), as reported in Locke, Shih et al., 2019. An independent data management core generated a random number sequence to assign randomization.
Procedure
After schools were identified and agreed to participate, research staff distributed recruitment materials to both school personnel and eligible families and met with interested participants to further explain the study and their role as participants. Additionally, research staff met with consented children to explain the study to them in comprehensible language to obtain their assent. Subsequently, school personnel began implementing Remaking Recess based on the condition to which they were randomly assigned. Observers assessed the enrolled children’s social engagement on the playground at each timepoint for the duration of the school year. Observers were naïve to study procedures and provider intervention condition. See Figure 1 for CONSORT Diagram and see Locke, Shih et al., 2019 for complete study protocol.
CONSORT Diagram
Intervention
Participating school personnel were individually paired with a “coach” from the research team with whom they met for didactic and interactive training in their natural environment (i.e., at school during lunch). Training sessions lasted for 30 to 45 minutes and occurred 12 times over 6 weeks. During training sessions, coaches presented information on a target Remaking Recess skill (i.e., what the skill looks like, how it applies to autistic children, and why it is important for a child’s development), modeled the skill, and facilitated a practice session where school personnel tried the skill while the coach provided in vivo feedback. School personnel were encouraged to practice skills with students they supported throughout the rest of the week as homework. Enrolled personnel at all schools received training in Remaking Recess.
Remaking Recess coaching sessions focused on the following skills: (a) Attending to child engagement on the playground (i.e., scanning and circulating the environment for children who may need additional support and identifying children’s social engagement states; (b) Transitioning child to an activity (i.e., following children’s lead, strengths, and interests); (c) Facilitating an activity (i.e., providing developmentally- and age-appropriate activities/games to scaffold children’s engagement with peers and individualizing the intervention to specific children to help school personnel generalize the intervention to other students in their care); (d) Fostering communication (i.e., supporting children’s social communicative behaviors, including initiations and responses, and conversations with peers and creating opportunities to facilitate reciprocal social interactions; (e) Participating in an activity (i.e., sustain children’s engagement within their preferred activities/games and fading out of an activity/gameing to facilitate student independence); (f) Providing direct instruction of social skills (i.e., coaching children through difficult situations with peers, should they arise); and (g) Employing peer models (i.e., working with peers to engage autistic children; Kretzmann et al., 2015; Locke et al., 2015).
Participants
Providers and students were recruited from 12 public elementary schools in five districts in the Northeastern United States over a two-year period. The average school size was 600 students (SD = 176), and the average class size was 24.2 students (SD = 4.5). On average across schools, 50% of students received free/reduced lunch.
Providers
Twenty-eight school personnel were recruited to implement Remaking Recess with the autistic students they served who were also enrolled in the study. Inclusion criteria for providers included: (a) being employed by the school district (i.e., external/private consultants were excluded), and (b) having at least one autistic student on their caseload with whom they would be willing to work with during the recess period. Twenty-five school personnel served one autistic student each, while three school personnel provided support to two autistic students each. School personnel included 11 teachers and 17 other staff (classroom assistants, one-to-one assistants, and noontime aides). See Table 1 for demographic information for providers and students.
Participant Demographics
Students
Thirty-one autistic students were recruited to participate in the Remaking Recess intervention. Inclusion criteria for student participants included: (a) an educational classification or medical diagnosis of autism; (b) referral from a school administrator; (c) intelligence quotient scores above 65 as indicated in their school record; and (d) spent at least 80% of their day in a general education elementary setting (kindergarten through fifth grade).
Data Collection and Measures
Fidelity Measures
Remaking Recess intervention fidelity was measured from three perspectives: (a) observer-rated, (b) coach-rated, and (c) self-rated. Raters (observer and coach) scored fidelity on seven components of Remaking Recess—attended to child engagement on the playground, transitioned child to an activity, facilitated activity, participated in activity, fostered communication, employed peer models, and provided direct instruction of social skills. Completion of Remaking Recess was coded “0” for “No” and “1” for “Yes” based on school personnel’s completion of each component. The proportion of completed intervention components divided by the total possible components (seven) was utilized for analyses. Quality of Remaking Recess delivery, or how well school personnel used each component of the intervention, was rated on a 5-point Likert scale with “1” indicating “Not Well” to “5” indicating “Very Well” for each component of Remaking Recess that was completed during the intervention session. The average quality rating across all intervention components was utilized for analysis. If a component was not observed, there was no quality rating. School personnel were informed that they would be observed on the playground; however, they were not explicitly informed when data collection would occur or that data were being collected on their use of Remaking Recess steps. This allowed research staff to assess whether the implementation of the intervention naturally occurs without prompts by the research team.
School personnel used a parallel fidelity measure to self-rate their use and quality of intervention delivery. The self-rated form separated the aforementioned seven components into 13 specific sub-components, which mapped directly onto the original components. These were averaged to obtain scores for each of the seven component areas for ease of direct comparison with the observer- and coach-rated fidelity measures. For all raters, fidelity scores at Endpoint were used in analyses. This timepoint was used because it immediately followed school personnel completion of the coaching and consultation process for all Remaking Recess components.
Child Outcome Measure
Data Analysis
All study data were managed using Research Electronic Data Capture (REDCap), a secure, web-based application designed to support data maintenance for research studies (Harris et al., 2009). Analyses were conducted in RStudio.
For aim one, to determine the concordance between observer-, coach-, and self-rated fidelity, percent agreement and Pearson correlation coefficients were calculated. For aims two and three, to examine the relation between fidelity and child socialization outcomes, two sets of hierarchical linear models were conducted using fidelity indices as predictors of social engagement scores. All models were analyzed using maximum likelihood estimation to avoid list-wise deletion. All analyses were completed on an intent-to-treat basis. Predictor variables (overall fidelity scores and individual fidelity components) were standardized. We included nesting by school (i.e., children within school) as a random effect in the mixed models. Model assumptions were checked for all final models (i.e., normality of residuals, homoscedastic variances, and appropriate covariance structures). Provider characteristics (i.e., age, gender, ethnicity, education level, years experience working with autistic individuals, and role) were not significantly associated with social communication outcomes and, thus, were not included in the models. Child age and grade were significantly associated with social communication outcomes and were included as covariates in the models predicting child social engagement (child ethnicity and gender were not associated with outcomes). Provider years experience working with autistic individuals and role were significantly associated with observer-rated fidelity scores. Naïve observers tended to rate teachers Remaking Recess fidelity lower than other school personnel (i.e., paraprofessionals, aides, and counselors).
For the first set of models, we separately examined the association of each fidelity score (observer-, coach-, and self-rated Fidelity Component Completion [hereafter: Completion] and Fidelity Quality of Delivery [hereafter: Quality]) with social engagement. In the second set of models, the seven individual components of fidelity from each of the three raters were simultaneously examined as the independent variables. Intervention status was included as a covariate because the sample included providers in both Remaking Recess and Remaking Recess with implementation support groups. Covariates were held constant to facilitate comparison across models. As such, the results are interpreted as the extent to which the use of Remaking Recess core components relates to student social gains, independent of study group membership.
Results
Intervention Fidelity
Means, standard deviations, and zero-order correlations among all variables are given in Table 2. There was high variability of fidelity scores across raters (Completion M range min-to-max = 0.16–0.87; Quality M range = 1.58–2.71; see Figures 2 and 3). There also was a high variation in school personnel’s fidelity when implementing the prescribed core components across raters (Completion SD range = 0.25–0.30; Quality SD range = 1.04–2.04). Out of all intervention components, all raters endorsed that school personnel engaged in Attended to Child Engagement on the Playground, Transitioned to an Activity, and Set Up an Activity most consistently. All raters reported that providers least consistently Employed Peers to Direct and Redirect Each Other, while observers and coaches (but not the providers themselves) reported that personnel did not Foster Communication Between Peers as consistently as other components.
Implementation Completion Fidelity Scores Across Raters
Implementation Fidelity Quality Scores Across Raters
Mean, SDs, and Zero-Order Disaggregated Correlations for Variables Used in Analysis (n = 31)
*p < .05. **p < .01.
Percent agreement of fidelity ratings tended to be higher between Self- vs Coach-Ratings and lower between Self- vs Observer- and Coach- vs Observer-Ratings. In term of specific Remaking Recess components, percent agreement between raters tended to be lower overall for fidelity ratings of Fostering Communication, Participating in an Activity, Providing Direct Instruction of Social Skills, and Employing Peer Models. See Table 3 for specific proportion of components completed by reporter and agreement on occurrence.
Proportion of Components Completed by Reporter and Agreement on Occurrence (n = 31)
Coach- and self-rated overall Completion and Quality fidelity scores were significantly correlated (Completion: r = .50, p = .004; Quality: r = .49, p = .005). Observer- and self-rated Quality scores were significantly correlated (r = .43, p = .02), but correlations for overall Completion between these two raters were not significant. Observer- and coach-rated Quality scores were significantly correlated (r = .39, p = .03), but correlations for overall completion between these two raters were not significant. Table 1 depicts all correlations and descriptive statistics of the variables measuring intervention fidelity, as well as the students’ outcome variables.
Relation Between Overall Intervention Fidelity and Students’ Change in Social Engagement
The intercept-only (or “empty”) model was specified to evaluate the intraclass correlations. The mean change in child social engagement score was 0.21 (or 21% spent jointly engaged; Cohen’s d = 0.58, medium effect; Sullivan & Fein, 2012), which was significantly different from zero. Next, predictors were added to six separate models for each rater and type of fidelity measure. Both observer-rated Completion of Remaking Recess (b = 0.13, s.e. = 0.05, p = .02) and Quality of delivery (b = 0.15, s.e. = 0.05, p < .01) were significant predictors of child social engagement scores. More specifically, higher rates of Completion and higher Quality scores were predictors of higher social engagement scores. Self- and coach-rated Completion and Quality were not significant predictors of child social engagement outcomes (see Table 4 for model results). Intervention condition was not a significant covariate in any of the models (p’s > .39). See Figure 4 for predicted joint engagement change scores from fidelity ratings.
Predicted Joint Engagement Change Scores From Fidelity Ratings
Multilevel Model Results Predicting Child Social Engagement From Fidelity Ratings Estimation (n = 31 Children From 12 Schools)
Relation Between Core Component Fidelity and Students’ Change in Social Engagement
In the second set of models, no single component of Remaking Recess (as measured by any of the three raters) emerged as a significant predictor of child social engagement outcomes (see Table 5 for model results).
Multilevel Model Results Predicting Child Social Engagement From Individual Remaking Recess Components Estimation (N = 31 Children From 12 Schools)
Discussion
Accurate fidelity measurement is important for understanding intervention outcomes (Schultes et al., 2015), as well as for training users in the adoption of EBPs (Novins et al., 2013). This study evaluated the relationship between multiple sources of fidelity ratings (observer, coach, and self) for a school-based social engagement intervention, Remaking Recess, for autistic students, the relationship between fidelity scores and child outcomes, and the relationship between Remaking Recess’ core components and child outcomes.
While there was high variability in fidelity scores across sources, we found positive associations between (a) observer- and coach-ratings of implementation quality, (b) observer- and self-ratings of implementation quality, and (c) coach- and self-ratings of implementation quality and intervention completion. Two key patterns in these findings emerged. First, agreement on specific components was variable, in that there tended to be lower rater agreement for Fostering Communication, Participating in an Activity, Providing Direct Instruction of Social Skills, and Employing Peer Models, particularly between observer- and self- and observer- and coach-ratings. One explanation for this may be that in previous studies of Remaking Recess, researchers have posited that Fostering Communication, Providing Direct Instruction of Social Skills, and Employing Peer Models are the most difficult components to master (Locke et al., 2019). Another reason for these findings might be that fully participating in play with children also may be more difficult for providers. Additionally, some of these components with lower agreement may also be more challenging for an observer to capture because school personnel have learned to administer them discreetly or before transitioning to recess (e.g., Providing Direct Instruction of Social Skills, Employing Peer Models). Finally, this may be explained by the fact that school personnel and their coaches may also have more contextual knowledge about the specific environment or child, which may have led to higher agreements between these raters.
A second pattern that emerged was that provider years working with autistic students was significantly positively associated with observer-ratings of fidelity and provider role was also significantly associated with observer-rated fidelity, in that observers rated teacher fidelity lower overall than other school personnel such as paraprofessionals, aides, and counselors (of note, these characteristics are not associated with child outcomes). While further research is needed to fully understand this pattern, one explanation for this may be that providers with more autism experience or who spend more dedicated time with autistic students are better able to implement Remaking Recess with fidelity. Additionally, differences in teachers’ perceptions of their role at recess compared to other professionals’ (which may more often involve serving as one-one-one support) could also contribute to differences in fidelity scores. Future Remaking Recess training for broad groups of educators may need to more explicitly address these perceptions.
Only observer ratings of completion and quality significantly predicted child social engagement scores, while no single Remaking Recess component emerged as a significant predictor of child social engagement. Taken together, these findings suggest that it is not one particular component of Remaking Recess driving child outcomes, but instead quality implementation of the packaged intervention as a whole, which may have implications for future training. Findings such as these support the interdependence of components that make up multi-component interventions. Future training efforts should emphasize the coordinated delivery of these components to promote the best chance of high-quality delivery, and thereby optimal outcomes. Our descriptive data also shows a strikingly lower proportion of components completed when rated by observer compared to self and coach, which may be explained by the fact that observers receive more rigorous training in fidelity measurement specifically than educators or coaches (i.e., observers need to achieve 80% reliability on fidelity codes throughout the study). Additionally, observers tend to have higher education levels and autism expertise. These findings highlight the importance of enhancing training on provider self-assessments to potentially increase the utility of these reports going forward.
Our results strengthen prior identification of observers who are naïve to condition as providing more predictive fidelity data that are less susceptible to bias (Borrelli et al., 2005). Independent observer ratings, however, often are unrealistic in community-based practice settings (Stirman et al., 2017). In school-based implementation research, student privacy concerns frequently preclude video recording as a modality for data collection, yet obtaining live observations of sessions, particularly given the need for inter-rater reliability, is a challenge for even well-funded research studies (Breitenstein et al., 2010; Lillehoj et al., 2004). In addition, live observers are a time- and cost-intensive approach that involves training staff who are typically masked to participant condition (meaning that they cannot help to implement other aspects of the study), reimbursing staff for commuting to and from service settings, and paying staff for their time engaged in observation. COVID-19 concerns have exacerbated challenges with observational fidelity measurement in schools, given the restrictions the pandemic has placed on researchers’ abilities to physically enter school grounds. The use of provider (i.e., coach- and self-) fidelity ratings allow for the potential benefits of reduced costs and the promotion of a practice-based learning approach for intervention implementers (Becker-Haimes et al., 2021) and may be more feasible as schools continue to grapple with COVID-19 restrictions and changes to school policies regarding external in-person visitors. Additionally, coach- and self-ratings may provide insight into contextual factors such as individual child presentation or provider style, which may be helpful when considering the personalization or individuation of treatment to promote long-term sustainability.
Clearly, a balancing act is needed to use fidelity measurement that provides meaningful information on intervention recipient outcomes, while accounting for privacy, cost of measurement, and sustainability of implementation monitoring systems beyond a research study. These concerns suggest that pragmatic approaches to measurement, such as provider fidelity ratings, are important, particularly for implementation research that is focused on intervention uptake and sustainment (Becker-Haimes et al., 2021). Determining how to train cost-effective and sustainable fidelity monitors to provide “good enough” ratings that provide meaningful information related to student outcomes is an important next step for implementation research. Regardless of who is completing fidelity ratings, triangulating data across sources is one way to strengthen their validity (Bond & Drake, 2020). Ensuring multiple raters complete fidelity measurement at regular intervals may be an important consideration when relying on self or coach-ratings.
To our knowledge, this is one of a few studies connecting fidelity ratings with targeted child outcomes in school-based research (Lillenhoj et al., 2004). Future research should continue to incorporate fidelity measurement in empirical assessment to better understand how approaches impact accuracy, and how intervention fidelity affects intervention effectiveness. Additional research is needed to make more definitive conclusions about effective and efficient fidelity measurement systems that can provide meaningful information about recipient outcomes.
While this study provides insight into fidelity measurement across raters, some limitations must be acknowledged. Data were collected across a relatively small participant sample who were geographically located in the Northeastern United States. Future research should include larger, more representative samples from regions across the United States to promote generalizability of findings. Additionally, this study only focused on one intervention for autistic youth in school settings. Further research is needed to establish whether similar patterns occur when measuring fidelity to other interventions for autistic youth in the academic context to determine the universality of these findings and how to best address these issues of fidelity measurement throughout the field of implementation research.
Despite these limitations, this study demonstrated that high levels of observer-rated intervention completion and quality predicted child social engagement outcomes. The findings also suggest that, although observer-ratings were positively associated with each of coach-ratings and self-ratings of quality, coach- and self-ratings were not predictive of child outcomes. Future research should clarify how to improve coach- and self-ratings, perhaps used in combination, to provide “good enough” ratings of intervention completion and quality that provide meaningful information about child outcomes in community settings. Additional work is needed to understand how best to facilitate accurate yet feasible measurement of intervention adherence by self-raters and those who facilitate user implementation.
Footnotes
Acknowledgment
We thank the children, staff, and schools who participated in this study.
Availability of Data and Materials
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the Autism Science Foundation (Grants #13-ECA-01L), FARFund Early Career Award, and Health Resources and Services Administration (HRSA) of the U.S. Department of Health and Human Services (HHS) under cooperative agreement UT3MC39436, Autism Intervention Research Network on Behavioral Health. The information, content and/or conclusions are those of the author and should not be construed as the official position or policy of, nor should any endorsements be inferred by HRSA, HHS, or the U.S. Government.
Clinical Trial Registration
Not applicable.
