The Effects of the Family Behavior Support Application (FBSApp) with Virtual, Strategy-Based Coaching on Caregiver and Child Behaviors

The Effects of the Family Behavior Support Application (FBSApp) with Virtual, Strategy-Based Coaching on Caregiver and Child Behaviors | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Effects of the Family Behavior Support Application (FBSApp) with Virtual, Strategy-Based Coaching on Caregiver and Child Behaviors Claire Winchester, Erin Barton, Brandy Locchetta, Marina Velez, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6940507/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract We tested the Family Behavior Support application (FBSApp), a mobile app designed to support caregivers in their use of functional assessment-based intervention strategies to address their children’s challenging behaviors at home and support healthy social-emotional development. Two caregiver/child dyads participated in a single-case multiple baseline across behaviors (i.e., strategies) design. We used systematic, ongoing coaching via telehealth to support caregivers’ use of app-recommended intervention strategies in the context of a targeted home routine. Intervention resulted in increases in caregiver’s use of prevent and new response strategies, increases in child use of replacement behaviors, and decreases in child challenging behaviors. Functional relations were not identified due to a lack of change in one (i.e., Teach strategies) of three tiers for Family 1, and lack of sufficient experimental control due to withdrawal during the first tier for Family 2. Though we did not identify functional relations, our study is meaningful given we used a rigorous single case research design and had interesting, idiosyncratic results. These findings underscore the importance of individualized approaches and contribute to the broader discourse on personalized intervention strategies. Future research is needed to continue to examine efficient ways to support families in virtual settings. Figures Figure 1 Figure 2 Figure 3 Introduction Challenging behavior (CB) has long been recognized as a primary area of concern for families of young children (Doubet & Ostrosky, 2015), and particularly so for families of young children with disabilities (Bromley et al., 2004). CB presents a significant barrier to meaningful participation in home routines, community activities, and educational settings (Lucyshyn et al., 2007), which can cause parental stress and reductions in family quality of life (Fox et al., 1997; Joachim et al., 2010). Further, CB identified in the preschool years is predictive of later adjustment difficulties and negative long-term outcomes (Frey et al., 2015), highlighting the need for effective early intervention on CB. Given the body of evidence supporting the family unit as one of the most significant contributors in fostering children’s success (Dempsey & Keen, 2008), identifying interventions for CB that can be effectively integrated into family life is imperative. Researchers have documented the importance of providing support to families in naturally occurring settings and routines (Fixsen et al., 2005), and the Division of Early Childhood (DEC) recommends including family members in assessment and intervention procedures to promote positive outcomes (2014). Many researchers have demonstrated that caregivers can implement evidence-based intervention strategies with high levels of fidelity when effective supports are provided, leading to improvements in child and family outcomes (Fettig & Barton, 2014; Gerow et al., 2018). Though in-home services are an ideal mode for family-centered intervention, they are often time- and resource-intensive and can be especially limited for families in rural communities or families living in poverty (Kasprzak et al., 2012; Meadan et al., 2013). Caregiver coaching programs delivered virtually (e.g., via Zoom or other teleconferencing software) may be an accessible and effective alternative (Çelik et al., 2022; Meadan et al., 2016). Virtual models enable practitioners to involve endogenous implementers (i.e., caregivers, other family members) that regularly spend time with the child while also intervening on behavior directly in the environment in which it occurs. Further, technological access is steadily increasing, with the vast majority of American households having access to a computer and internet (U.S. Department of Commerce, 2022). Thus, gere is increasing support for virtual service delivery for families of young children. Research on the use of virtual, telehealth models for caregiver coaching is growing, especially since the COVID-19 pandemic. Researchers have found virtual coaching to be effective for increasing caregivers’ use of Enhanced Milieu Teaching (Peters et al., 2023), naturalistic communication teaching strategies (Douglas et al., 2018; Meadan et al., 2016), and function-based interventions (Lindgren et al., 2020). Caregivers have also reported feeling less isolated and more supported (McDevitt, 2021), and more confident in their ability to interact with their child (Meadan et al., 2016). While there is promising evidence for these approaches, research on teaching caregivers how to implement function-based interventions via tele-coaching remains quite limited, although some studies have demonstrated the feasibility and effectiveness of parent training to address challenging behaviors (Akemoglu et al., 2020; Ruppert et al., 2016). Future research should continue to explore and expand this area to better address the needs of families. While these models can greatly improve access, researchers have identified important barriers, including a lack of fluency with the technology, difficulty building rapport and maintaining communication with caregivers, and limited caregiver engagement with coaching materials and resources. Additionally, research on virtual service delivery has been limited and has not extensively focused on how to foster effective collaboration and build strong, holistic partnerships between professionals and caregivers. Further research is needed to vet methods for effective virtual service delivery that is meaningful and accessible to caregivers and supports a holistic caregiver-professional partnership (Harbin, Choi, & Fettig, 2024). We examined the effects of the Family Behavior Support application (FBSApp; Barton, 2022), a mobile application designed to support caregivers in implementing function-based, positive behavior support strategies at home with their young children with disabilities or delays and CB. The app is designed to promote collaboration between caregivers and support professionals (i.e., early interventionists, behavior therapists) while also providing accessible and targeted support and resources for caregivers at home. Previous research has supported the use of the FBSApp with strategy-based coaching to increase caregivers’ use of targeted intervention strategies and reduce children’s CB across routines (Barton et al., 2024; Authors, 2024; Authors, 2024). We conducted the current study to further explore the characteristics of systematic coaching (e.g., instructional content, dosage, method of feedback delivery) functionally related to caregiver strategy use and child behavior change. The following research questions guided our study:(a)Does caregiver use of the FBSApp with virtual, strategy-based coaching increase caregiver use of targeted strategies?(b) Does caregiver use of targeted strategies generalize to a novel routine and maintain when coaching is systematically faded? (c) Does caregiver use of the FBSApp with virtual, strategy-based coaching decrease child CB and increase child use of replacement behaviors? Methods Participants We began recruitment after obtaining approval from the university’s institutional review board. Procedures included distributing materials (e.g., flyers) via social media and contacting relevant childcare, service provision, and educational agencies in an urban city in southeast US. Families were screened according to the following child inclusion criteria: (a) age between 24 and 71 months; (b) medical diagnosis or educational eligibility category, or at-risk for disability according to the Ages and Stages Questionnaire: Social-Emotional, 2 nd edition (ASQ-SE-2; Squires et al., 2015); and (c) caregiver-reported CB occurring in the home setting a minimum of three times per week. Three families met inclusion criteria and were consented for participation in the study; one family (i.e., Family 3) withdrew before data collection began. Family 1 consisted of a mother-son dyad. Elijah was a 4-year-old, White/Hispanic male with social anxiety disorder. Elijah did not receive any additional services and attended a private childcare facility. His mother, Brooke, was a White female who worked full-time. She reported the target CB to be verbal aggression (e.g., screaming, swearing) and elopement, with occasional physical aggression toward mom and sister (e.g., hitting, throwing things). The targeted routine was the transition to bedtime, and the generalization routine was mealtime (i.e., dinner). A 2-year-old, typically-developing sister was also present in the home; Brooke was the sole caregiver for the majority of the study. Family 2 consisted of a father-daughter dyad. Zara was a 4-year-old, Black female with autism spectrum disorder (ASD) and language delay. Zara received speech-language services and attended a public preschool, both temporarily in a virtual setting due to COVID-19 restrictions. Her father, Christian, was a Black male who worked full-time. He reported the target CB to be verbal refusal, tantrums (e.g., excessive crying, screaming), and elopement. The targeted routine was mealtime (i.e., lunch), and the generalization routine was brushing teeth. Other individuals present in the home were a 3-year-old sister and a 5-year-old brother (also with an ASD diagnosis), and the mother, who also worked full-time. Family 3 consisted of a mother-son dyad. James was a 4-year-old, White male with anxiety disorder and developmental delay. James attended a public preschool and received private mental health services. His mother, Melissa, was a White female who worked full-time. She reported the target CB to be verbal aggression (e.g., screaming, swearing), physical aggression toward mom, sister, and peers (e.g., hitting, kicking), and elopement. A 2-year-old, typically-developing sister was also present in the home; Melissa was the sole caregiver. Family 3 withdrew prior to baseline data collection for reasons unrelated to the study. They had considered using mealtimes as the targeted routine prior to withdrawing. Research Personnel Two research assistants within the second author’s research lab were responsible for implementing all coaching procedures. Both coaches were White female master’s students in early childhood special education accruing hours toward behavior analysis certification. The coach for Family 1 had previous experience coaching families using the FBSApp; the coach for Family 2 had previous experience working with young children but did not have experience coaching families. Two White, female doctoral students in early childhood special education advised and supervised the coaches. They both had previous classroom teaching and supervisory experience. Five master’s students and one doctoral student were trained to code data by the one of the supervisors prior to the study start. All coders were female students (white, non-Hispanic = 5; white, Hispanic = 1) in an early childhood special education graduate program. Setting and Materials All study procedures took place in the families’ homes. Observation sessions were conducted in the context of the target routine. During intake, each family identified two routines in which challenging behavior occurred: a target routine and a generalization routine . The target routine was the activity or time of day when challenging behavior was most likely to occur and intervention would be most beneficial. The generalization routine was an additional context where challenging behavior occurred, but it was not the primary focus of intervention. Families were issued an iPad which they used to access the FBSApp and attended all observations, trainings, and coaching sessions via Zoom teleconferencing software. Coaches used a laptop to attend and record all sessions via Zoom. Data were collected via ProCoderDV (Tapp, 2003) and graphed and analyzed in Microsoft Excel. The Family Behavior Support application (FBSApp) is a tool for supporting caregivers in using function-based intervention strategies to address their young child’s CB and support health social-emotional development at home. The function-generating algorithm uses antecedent-behavior-consequence (ABC) data input by caregivers to create an individualized behavior support plan (BSP) based on the hypothesized function (i.e., purpose) of the child’s CB. Caregivers can access infographics and videos containing descriptions and models of strategies. Throughout, caregivers can document and track their progress and can collaborate with other caregivers and support professionals (e.g., therapists, behavior analysts) within the app. Dependent Variables and Coding Procedures Measurement System Research assistants coded data immediately following observations. We only collected data on behaviors under the function(s) that was listed on the family specific BSP, with the exception of prevent strategies. Although the coaches instructed caregivers on specific prevent strategies (see Tables 1 and 2), the caregivers still had access to information on all prevent strategies through the FBSApp since prevent strategies are not tied to specific functions. We used timed event sampling to mark the onset of all dependent variables, except caregiver prompts and responses to CB; these variables were dependent on the occurrence of an establishing statement or CB respectively and were categorized following their onset. For all dependent variables, a minimum of 5 s was required between the offset of the preceding behavior and onset of the following behavior within the same category to be considered two separate instances. Definitions and examples for Family 1 and Family 2 are included in Tables 1 and 2, respectively. Table 1 Family 1 Function, Target Strategy Definitions, and Examples Function Prevent Child Replacement Behavior New Response Gain attention Positive descriptive feedback Definition: Vocal statements containing both positive language and a description of a specific behavior in which the child engaged Example: Caregiver says, “You did such a good job getting dressed!” General positive attention Definition: Vocal statement, physical gesture, or touch not dependent on the child engaging in a specific behavior Example: Caregiver imitates child’s sounds while playing with toy cars Ask for attention Definition: Vocal request for the target caregiver’s attention Example: Child says, “Mama play?” when caregiver walks by play area Ask for help Definition: Vocal request for assistance with activity, play, routine, etc. Example: Child says, “Help,” while holding out toy toward caregiver Minimize attention Definition: Provision of minimal or low-quality attention that does not specifically reference any aspect of the challenging behavior Example: Caregiver turns away and plays with sibling when child throws a toy Escape demand Predictable schedules Definition: Vocal or visual presentation of a sequence of at least two activities or behaviors to prepare child for upcoming events, activities, or tasks Example: Caregiver says, “First we’re going to eat dinner, then bath time, and then bed” Ask for help Definition: Vocal request for assistance with activity, play, routine, etc. Example: Child says, “Help,” while holding out toy toward caregiver Ask to be done Definition: Vocal request stating a desire not to complete the current or proposed activity/task without a request for an alternative Example: Child says, “No peas, please” when caregiver sets down plate of food Prompt follow-through Definition: Vocal or physical prompting to complete the task that preceded the instance of challenging behavior by (a) providing new information, or (b) adapting task to promote success Example: Caregiver holds towel out to child after saying, “Time to dry off” Table 2 Family 2 Function, Target Strategy Definitions, and Examples Function Caregiver Prevent Child Replacement Behavior Caregiver New Response Escape demand Positive descriptive feedback Definition: Vocal statements containing (a) positive language, and (b) a description of a specific behavior in which the child engaged Example: “You did such a good job getting dressed!” General positive attention Definition: Vocal statement, physical gesture, or touch not dependent on the child engaging in a specific behavior Example: Caregiver imitates child’s sounds while playing with toy cars Ask to be done Definition: Vocal request stating a desire not to complete the current or proposed activity/task without a request for an alternative Example: Child says, “No peas, please” when caregiver sets down plate of food Follow Directions (engage in non-preferred tasks) Definition: Engaging in a behavior that functionally matches the caregiver’s instruction Example: Child puts spoonful of peas into their mouth 5s after caregiver says, “Take a bite, please” Ignore request Definition: Removal of attention following child’s request not to complete the current or proposed activity/task Example: Caregiver continues brushing their own teeth and does not respond when child verbally refuses to comply with caregiver’s direction to brush teeth Caregiver Behaviors Prevent Strategies. Caregiver use of prevent strategies was defined as vocal or physical behavior which involved changing the antecedents that typically occur before CB to make CB less likely to occur and desirable behavior more likely to occur. Strategies included behaviors that contribute to creating high-quality environments and interactions. Teach Trials. To assess caregiver implementation of strategies for teaching replacement behaviors to their child, we measured the frequency of teach trials and the presence of prompts within each trial. A teach trial was initiated by the caregiver through a vocal presentation of an establishing statement. This statement functioned as an establishing operation by either increasing the value of a reinforcer or indicating its availability (e.g., “If you want me to play, you can say, ‘Play, please.’” ). Nonexamples of establishing statements included vocalizations that required compliance with a demand to access reinforcement (e.g., “Once you rinse your hair, you can be all done,” which signaled escape from a demand but did not create an opportunity for teaching a functionally equivalent replacement behavior). For each teach trial, we recorded whether the caregiver provided a prompt following the establishing statement to facilitate the child's use of the replacement behavior. Prompts were defined as additional forms of support, including open questions (e.g., “What do you need to say?” ), choice prompts (e.g., “Do you want to say, ‘Play, please,’ or ‘Toy, please’?” ), model prompts (e.g., “Say, ‘Play, please.’” ), verbal prompts (e.g., “Ask me to play first.” ), or gestural prompts (e.g., pointing to a visual cue). To qualify as a prompt, the caregiver’s assistance had to occur within 10 s of the offset of the establishing statement. Repeating the same establishing statement (e.g., “If you want me to play, you can say, ‘Play, please,’” restated verbatim) was not coded as a prompt. New Response. For each instance of CB, we marked the occurrence or non-occurrence of a new response strategy. Caregiver use of new response strategies was defined as a response to CB that was functionally incompatible, such that it reduced the likelihood of future CB (see Tables 1 and 2). Nonexamples for new response strategies were responses that reinforced the CB such that it would increase the likelihood of occurrence in the future. Child Behaviors CB. We collected data on the frequency of CB, which was broadly defined as behavior that interferes with the child’s meaningful engagement in their environment or social interactions (Smith & Fox, 2003). Common topographies included physical aggression, verbal aggression, tantrumming, and noncompliance in the form of elopement or verbal refusal. Self-stimulatory behaviors that did not meet any other criteria (e.g., hand-flapping) were not considered CB. Replacement Behaviors. We collected data on the frequency of child behaviors that would serve as a replacement for CB according to the hypothesized function identified by FBSApp. A replacement behavior was broadly defined as a child’s appropriate request for functionally equivalent reinforcement from the target caregiver, or engagement in the caregiver’s identified behavior of concern intended to increase. For Family 1, only functional requests for attention or escape from a task were marked. For Family 2, functional requests to escape from a task and engagement in non-preferred tasks (i.e., eating non-preferred foods for intervention and brushing teeth for generalization) were marked; this was at the request of the caregivers since they expressed a desire to both honor appropriate requests but also increase the child’s cooperation with daily self-help routines. Effect Sizes As a complement to visual analysis, we calculated effect sizes to aid in the interpretation of our results (Maggin et al., 2019). The log response ratio (LRR) effect size is the natural log of proportionate change in the mean level between conditions (Pustejovsky, 2018); LRR increasing (LRRi) is used for behaviors that are expected to increase in intervention conditions (e.g., caregiver use of strategies), and LRR decreasing (LRRd) is used for behaviors that are expected to decrease in intervention conditions (e.g., child CB). We used the Single Case Effect Size Calculator web application (Pustejovsky et al., 2022) to calculate LRR effect sizes for each A-B comparison of a dependent variable (e.g., caregiver use of prevent strategies from baseline to intervention) for each family. To facilitate interpretation, we also converted the LRR into percent change. Interobserver Agreement (IOA) All coders were trained prior to the start of data collection. First, coders were provided with a decision tree and coding manual with operational definitions, examples, and non-examples of dependent variables. Next, coders met to review the manual and code a practice video together. Coders then coded non-study practice videos independently until at least 80% agreement was reached on each dependent variable across two videos. To estimate IOA, two coders independently coded sessions for all participants on all dependent variables. For variables captured with timed-event recording, IOA was estimated using a point-by-point agreement method (Ledford et al., 2018) with a 3 s agreement time-window. For variables captured using a categorical method (i.e., caregiver new response, caregiver use of prompts in teach trials), IOA was estimated using an agreement method with each behavior marked as an agreement or disagreement (Ledford et al., 2018). Coders were masked to all study conditions. Throughout the study, meetings were conducted to review formative IOA and to discuss and resolve discrepancies; if the disagreement could not be resolved between the primary and secondary coders, the third author made the final decision. We graphed primary and secondary data concurrently and monitored IOA throughout the study. Experimental Design We used a concurrent multiple baseline across behaviors (sessions; Gast et al., 2018) single case experimental design to evaluate the efficacy of coaching caregivers on individual categories of target strategies sequentially (i.e., prevent, teach, new response). The order in which strategies were targeted was randomized for both families. Because Family 2 withdrew from the study after the first tier, the intervention was ultimately introduced in an A-B design. Condition change decisions were made based on the primary dependent variables, caregiver behaviors. Intervention: Coaching Procedures Coaching procedures were designed as a companion to FBSApp to be used by professionals supporting families (see Table 3 for coaching across conditions). All materials developed and used by coaches were closely aligned with existing features and resources within the app (e.g., infographics, tutorial videos). Coaching included the following components: (a) virtual meetings, (b) behavior skills training (BST; Miltenberger, 2012), (c) focused observations with live debriefs, and (d) supportive observations with email feedback. While systematic in nature, coaching procedures were flexible enough to allow for individualization, ensuring alignment with the family’s preferences, needs, and goals. Prior to the onset of the study, coaches received a 60-min virtual training facilitated by their supervisor. During this training, supervisors presented an overview of coaching components and procedures, the coaching timeline, fidelity documents, and support materials (i.e., email templates, note templates). The supervisors’ implementation fidelity was collected by a research assistant via video using a checklist. Table 3 Coaching Procedures Condition ABC Data Training App Orientation Access to FBSApp BST Focused Observations Supportive Observations Pre-Baseline X X - - - - Baseline - - X - - - Prevent - - X X X X Teach - - X X X X New Response to CB - - X X X X Generalization - - X - - - Maintenance - - X - - - Initial Meetings Pre-baseline observations were conducted to gather data to enter into the FBSApp and to ensure challenging behaviors occurred during the target routines identified by families during intake. The families did not have access to the FBSApp during pre-baseline observations. Two meetings took place between pre-baseline and baseline observations. The first meeting between the caregiver and coach lasted approximately 60 min, during which the coach outlined their role in supporting the family, identified their communication preferences (e.g., text or email), and walked them through app installation. The coach then delivered direct instruction on: (a) CB as a form of communication, (b) the functions of CB, and (c) ABC data collection. The coach then helped the caregiver enter one instance of ABC data, using a video from the family’s pre-baseline observations. Families were instructed to continue to collect instances of ABC data following the first meeting. After families entered at least three instances of ABC data, the FBSApp generated a hypothesis statement and solicited agreement that the statement reflected the family’s experience. If the family disagreed, they were prompted to enter more ABC data. Once the caregiver agreed with the hypothesis statement, a BSP was generated based on the agreed-upon function. In the second meeting prior to baseline sessions, the coach met with the caregiver for 45-60 min to review the BSP. Prior to reviewing the plan, the coach confirmed that the caregiver agreed with the hypothesized function. The coach then gave an overview of the prevent, teach, and new response to CB strategies provided in the BSP. This overview was a general orientation to the purpose of each strategy, and the coach did not train the caregiver on specific strategy implementation. Baseline observations commenced following the second meeting. Behavior Skills Training Prior to the onset of intervention in each tier, the coach conducted a 20-30 min BST on the targeted strategy (i.e., prevent, teach, or new response). In each training, the coach gave a didactic review of the strategy and showed a video model of how the strategy could be used. Next, caregivers engaged in role play and discussed of how they would use the strategy in an example scenario. Lastly, caregivers generated their own example of a situation where this strategy would be helpful with their child and practiced how they would use it while the coach gave them feedback. Observations Throughout the study, approximately three weekly virtual observations were conducted during the target routine. Observations lasted 15 minutes and began when the caregiver signaled the onset of the routine. Across all observations, the coach was silent and did not interrupt the routine. During pre-baseline, baseline, generalization, and maintenance sessions, no feedback was provided to caregivers post session. After intervention sessions, however, observations alternated between two types: focused observations, followed by a live debrief, and supportive observations, followed by email feedback. This sequence continued until the caregiver demonstrated mastery of the targeted skill. Due to highly individualized routines that warranted idiosyncratic strategy usage, we did not use consistent criteria to determine caregiver mastery. During all observations, debriefs, and feedback, caregivers were consistently referred back to the app for guidance, with specific strategies and resources within the app highlighted to support their continued learning and implementation of target strategies. Focused observations were designed to provide immediate and detailed feedback on caregiver performance. During these observations, the coach collected in-vivo, informal data (used solely to guide feedback) and identified areas for feedback. Focused observations were followed within 24 hr by a live debrief lasting an average of 18 min for Family 1 (range = 11–29 min) and 14 min for Family 2 (range = 9–16 min). During the debrief, the coach discussed the caregiver’s use of strategies, reviewed data the family entered in the app, and provided both constructive and supportive feedback related to the target tier’s strategies. Constructive feedback was designed to help caregivers refine their use of strategies by introducing changes to their current practices, while supportive feedback reinforced effective implementation of strategies already in use. Supportive observations , by contrast, emphasized encouraging caregivers and maintaining momentum in the intervention process. Like focused observations, supportive observations involved informal data collection, but the subsequent feedback was delivered via email instead of a live debrief. These emails included: (a) positive affirmations, (b) 1–3 supportive feedback statements with specific examples tied to the current or previous tier’s strategies, (c) broad connections to app-generated strategies, (d) reminders to enter data in the app, and (e) response prompts to engage caregivers further. By offering a mix of affirmations and constructive suggestions through different formats, focused and supportive observations worked together to guide caregivers toward mastery of the intervention strategies. Adaptations for Family 2 The FBSApp generated “escape from demand” as the function of Zara’s CB. Traditionally, the function-based new response strategy for escape from a demand is to “prompt follow through” on the task, which the app-generated BSP indicated. Since the family identified mealtime as their focus, the coach adapted the new response strategy from “prompt follow through” to “ignore.” Empirical evidence suggests prompting follow through of eating new foods (i.e., escape extinction) is not ideal (Chazin et al., 2022) and was not preferable for this family. Subsequently, the family shared that since rates of CB were so low following intervention on only prevent strategies, they no longer felt the intensity of the intervention was needed and requested to end the study. Results Family 1 Figure 1 depicts caregiver use of strategies across phases. While there were therapeutic changes in caregiver strategy use in the first and second tiers, we did not identify a functional relation since there was not a replication of effect in the third tier. As depicted in Figure 2, child use of replacement behaviors increased across intervention but was highly variable. There were statistically significant effect sizes calculated for CB and caregiver use of prevent strategies. Challenging Behavior and New Response. While multiple functions were hypothesized for the child’s use of CB in Family 1, the first tier depicts only new response strategies in line with gain attention because we detected a ceiling effect for new response to escape demand (see Discussion). New response data for the escape demand function are available by request. During pre-baseline, CB was variable at low to moderate levels ( range = 5–14). Frequency of new response strategies was low in relation to the occurrence of CB ( range = 1–7). In baseline, CB was highly variable at low to moderate levels ( range = 0–11) with an outlier at session 26 and a decreasing trend. New response strategies remained low in relation to CB, indicating the caregiver often responded to CB in a way that reinforced the behavior ( range = 0–11). New response data were low and stable during the last three baseline sessions. During intervention, the CB data patterns indicate an extinction burst, as there are spikes in frequency (session 11 and 27) followed by decreases and gradual cessation (session 29). CB data were variable at overall lower levels than baseline ( range = 0–14; outlier = 20). The frequency of new response strategies increased in relation to instances of CB (range = 0–14). During maintenance, CB ( range = 2–7) and new response (range = 0–4) remained at levels similar to intervention. The LRRd effect size estimate for CB was -0.68 (95% CI = [-1.45, -0.09]), which equates to a 50% decrease in CB from baseline to intervention (95% CI = [-77%, -10%]), and is statistically significant given that the confidence interval does not include zero. The LRRi effect size estimate for new response strategies was 0.43 (95% CI = [-0.12, 0.99]), equating to a 54% increase from baseline to intervention (95% CI = [-12%, 169%]), which is not statistically significant (i.e., the confidence interval includes zero). Prevent Strategies . During pre-baseline, the frequency of prevent strategies was low ( range = 3–7). Prevent remained at low levels ( range = 1–6) in baseline, with an outlier at session 11. Data were stable during the last three baseline sessions. Upon introduction of the intervention, prevent strategies increased immediately to 13 and were highly variable throughout intervention ( range = 2–14) but at overall consistently higher levels compared to baseline. When support was faded, prevent maintained at high levels ( range = 11–15). The LRRi effect size estimate for prevent strategies was 0.91 (95% CI = [0.43, 1.4]). This equates to a 149% increase from baseline to intervention (95% CI = [53%, 306%]) and is statistically significant. Teach Strategies. Prompts for replacement behaviors remained at 0 across all sessions. Frequency of establishing statements was high during pre-baseline ( range = 24–30) and highly variable across baseline ( range = 5–32). Upon introduction of coach support, level of establishing statements decreased slightly to low to moderate levels but remained highly variable, with significant overlap with baseline ( range = 2–16). During maintenance, frequency of establishing statements increased to moderate levels ( range = 9–19). The LRRi effect size estimate for teach strategies was 0.43 (95% CI = [-0.12, 0.99]), equating to a 54% increase from baseline to intervention (95% CI = [-12%, 169%]), and is not statistically significant. Replacement Behaviors. Replacement behaviors were low across pre-baseline and baseline conditions ( range = 0–1). Replacement behaviors remained low during intervention on new response strategies. Levels increased during intervention on prevent strategies, ranging from low to moderate levels ( range = 0­–4), and immediately decreased following intervention on teach strategies ( range = 0­–1). Once coaching support was removed, replacement behaviors increased to low to moderate levels ( range = 1–4). The LRRi effect size estimate for replacement behaviors was 0.65 (95% CI = [-0.61, 1.91]). This is equivalent to a 92% increase from baseline to intervention (95% CI = [-45%, 578%]) and is not statistically significant. Family 2 Data for Family 2 are displayed in Figure 3. We cannot identify a functional relation given there were not three potential demonstrations for replications of effect. However, there were positive changes in both caregiver and child behavior with coaching support on prevent strategies alone. Caregiver use of prevent strategies immediately increased. For child behaviors, engagement in non-preferred tasks increased in both intervention and generalization settings while task refusal and CB decreased. There were statistically significant effect sizes calculated for caregiver use of prevent strategies. Prevent Strategies. Caregiver use of prevent strategies was at low to moderate levels in baseline ( range = 2–10) with a decreasing trend. Upon introduction of coach support, levels increased immediately to 10 and were highly variable across intervention (range = 2–23). The LRRi effect size estimate for prevent strategies was statistically significant at 0.8 (95% CI = [0.1, 1.5]), which equates to a 123% increase from baseline to intervention (95% CI = [10%, 351%]). Engagement in Non-preferred Task. During baseline, child engagement in non-preferred tasks in the intervention routine (i.e., eating non-preferred foods) was stable at low levels, with one outlier at session 22. Once coach support for prevent strategies was implemented, engagement in non-preferred tasks increased and was variable at high levels ( range = 18­–40) with one outlier at zero. The LRRi effect size estimate was 1.4 (95% CI = [-0.3, 3.1]), equating to a 306% increase from baseline to intervention (95% CI = [-26%, 2135%]). Task Refusal. In baseline, vocal task refusal was variable ( range = 2­–14). In the first session of intervention, data immediately increased to 13, then decreased and stabilized at near-zero levels in the final sessions. The LRRd effect size estimate was -0.25 (95% CI = [-1.55, 1.04]), equal to a 22% decrease from baseline to intervention (95% CI = [-79%, 183]). CB. During baseline, CB was low ( range = 2-6) with one outlier at session 17. In the first intervention session, CB increased to 9, then immediately decreased to 0 and stabilized at low levels for the remaining intervention sessions. The LRRd effect size estimate was -0.71 (95% CI = -2.46, 1.04]), equating to a 51% decrease from baseline to intervention (95% CI = [-91%, 184%]). IOA and Procedural Fidelity IOA by family, condition, and variable is displayed in Table 4. IOA was collected for 39% of sessions for Family 1 and 38% of sessions for Family 2, with a range of 33–50% across conditions for each family. Mean agreement across variables and conditions was 75% for Family 1 ( range = 13­–100), and 81% for Family 2 ( range = 23–100). Procedural fidelity (PF) data were collected for 100% of sessions across coaching trainings, components, conditions, and participants via checklist using session video recordings. Initial coach training by the supervisors was implemented with 100% fidelity. Coaching fidelity data were collected by a masked observer research assistant for 100% of initial and BST meetings; coaching supervisors collected PF on focused and supportive observations and their subsequent debriefs (live or via email). If fidelity in any coaching component fell below 90%, the supervisor provided email feedback on the elements missed. This happened nine times during coaching for Family 1 and three times during coaching for Family 2. If fidelity fell below 80% for any component, the supervisor scheduled a virtual meeting with the coach for a discussion, modeling, or role-play. This happened twice for the Family 1 coach and once for the Family 2 coach. Mean fidelity was 94% across initial meetings and BST ( range = 81–100). Mean fidelity across conditions and components ranged from 72% to 100% for Family 1, and 85% to 100% for Family 2. PF agreement data were collected for 100% of sessions across components, conditions, and participants; agreement was 98% for Family 1 ( range = 89­–100) and 97% for Family 2 ( range = 91–100). Fidelity by component, participant, and condition is displayed in Table 4. Table 4 Interobserver Agreement (IOA) and Procedural Fidelity (PF) by Condition for Each Family Family 1 IOA PF CB New Response Prevent EO Prompt RB Initial meetings BST FO Debrief SO PB 85 100 75 74 100 50 97 (94-100) -- 100 100 100 Baseline 85 (70–100) 98 (96–100) 43 (14–71) 68 (66-69) 100 13 (0–25)* -- -- 100 100 100 Int 77 (50–100) 97 (88–100) 68 (33­–100) 72 (25–100) 100 56 (0–100) -- 95 (84–100) 97 (90–100) 87 (40–100) 100 Maint 50 100 42 72 100 100 -- -- 100 100 100 Gen 60 100 100 75 100 100 -- -- 100 100 97 (92–100) Family 2 IOA PF CB Task refusal Engagement in non-preferred task Prevent Initial meetings BST FO Debrief SO PB -- -- -- -- 89 (82–96) -- 100 100 96 (92–100) Baseline 23 (13-33)* 75 (50–100) 100 91 (81–100) -- -- 100 100 100 Int 100 100 78 (77–79) 61 (50–71) -- 100 100 85 (60–100) 96 (92–100) Maint -- -- -- -- -- -- -- -- -- Gen 100 100 73 67 -- -- 100 100 100 Note. PB = pre-baseline; Int = intervention; Maint = maintenance; Gen = generalization; CB = challenging behavior; EO = establishing operation; RB = replacement behavior; BST = Behavior Skills Training; FO = focused observation; SO = supportive observation. Maintenance was not conducted for Family 2. * Coder retraining occurred due to low interobserver agreement. Discussion We examined the effects of the FBSApp on caregiver use of targeted intervention strategies at home with their young children with disabilities or delays and CBs. Though we did not identify functional relations, our study is meaningful given the use of a rigorous single case research design and the presence of interesting, idiosyncratic results. These findings highlight the importance of individualized approaches, emphasizing that personalized intervention strategies may yield variable yet valuable outcomes. Furthermore, the results contribute to the broader discourse on tailoring interventions to meet the unique needs of children and families, underscoring the complexity of caregiver-implemented practices in diverse home settings. Although we did not identify functional relations, our results are promising, meaningful, and support previous findings (Barton et al., 2024 ). We employed a single-case research design and observed interesting, albeit idiosyncratic, results. Our rigorous single-case design allowed us to delve deeply into the specific context and nuances of individual cases, providing rich, detailed data that offer valuable insights despite the absence of clear functional relations. Research contributions should be based on their methodological rigor rather than the presence or magnitude of behavior change (Cook & Therrien, 2017 ). Our idiosyncratic results highlight the unique ways different variables may interact in real-world settings, crucial for understanding the complex nature of early childhood special education. Four primary contributions and implications for research are discussed below. Individual Differences Across Families Importantly, each caregiver/family responded to the FBSApp in different ways, which has been observed in previous research within (Moes & Frea, 2002 ) and across studies (Fettig & Barton, 2014 ). For example, Family 2 experienced immediate effects across all behaviors with just preventive strategies. This suggests that universal, prevention-focused strategies may be sufficient for families with children exhibiting low-intensity CB. More intensive BSPs and coaching might not be necessary for all children or families, a critical consideration given the limited resources available to families at home across many communities. We used these data to restructure the FBSApp so families could access universal strategies immediately. Additionally, we observed promising changes in generalization data for Family 1, although the data are insufficient for experimental conclusions. Our data suggest that caregivers and children may generalize skills learned during the intervention routine to novel routines or settings. Future research should evaluate generalization to untrained settings. There is a dearth of research examining generalization by families across routines or strategies (Fettig & Barton, 2014 ). Family 1 also experienced multiple history events (e.g., exposure to COVID and multiple quarantines, moving during tier 2, a medication change during tier 3, and the father's return from imprisonment during tier 3) without corresponding shifts in their data. This supports the usability of the FBSApp in carefully considering family strengths and resources within their historical and immediate contexts (Charis, Fettig, & Zimmerman, 2023). Study Design Although we used a rigorous single-case research design, the relation between variables was not perfectly independent, as is recommended for time-lagged designs. These are important methodological implications for future research. For example, other designs might be more appropriate. Future researchers should use different designs to validate coaching approaches within and across families given the dynamic and idiosyncratic needs of families. For example, we presented demands and removed attention, which can evoke CB for some children. We hypothesize that the decrease in establishing statements coincides with an increase in effort allocated to other strategies, corresponding with an increase in CB as establishing statements were no longer evoking CB. This will impact data patterns and might not be observable within time-lagged designs. Effect Sizes We calculated effect sizes to provide a complete picture of intervention effects. However, these should be interpreted with caution and in conjunction with visual analysis (Maggin et al., 2019 ). Large confidence intervals indicate substantial variability within and across conditions. This is confirmed with visual analysis and is particularly true for Family 2, who had fewer data points and significant variability (especially in child behaviors). Overall, the individual differences noted across families support the use of individualized instructional adaptations when supporting family implementation of targeted intervention strategies. Our idiosyncratic findings are important and should not be discounted given the lack of functional relations. Publishing rigorous studies with complex or non-effects is crucial for developing a comprehensive understanding of evidence-based practices and preventing inflation of effect sizes in reviews and meta-analyses (Travers et al., 2016 ). Our findings demonstrated that the FBSApp plus coaching was effective for some strategies across families, which might be important for guiding special education research, policy, and practice (Cook & Therrien, 2017 ). Technology-Based Interventions Recent studies have increasingly focused on leveraging mobile apps and other digital tools to support families and caregivers in implementing intervention strategies. Research indicates that these tools can provide accessible, cost-effective solutions that offer flexibility for families (Khetani et al., 2018 ; Meadan & Daczewitz, 2015 ). The use of real-time data collection and feedback mechanisms within these apps enhances their effectiveness (Barton et al., 2020 ) and allows interventions to be tailored to fit the unique needs and contexts of each family (Dunst et al., 2019 ), which is further supported by the current study. Accessible, technology-based interventions like the FBSApp might address service and support disparities faced by families from diverse racial, ethnic, and socioeconomic backgrounds (Guralnick, 2020 ; Meadan & Daczewitz, 2015 ). The COVID-19 pandemic has profoundly impacted early childhood education, highlighting the need for flexible, remote, and hybrid intervention models. Recent studies have explored the challenges and opportunities presented by the pandemic, underscoring the importance of developing resilient and adaptable support systems for families, such as the FBSApp (Cahill et al., 2021). Limitations There are several important limitations to note. First, while Zoom allows for virtual support, it was not always convenient for families. Issues with zoom might have impacted our ability to build rapport with families, which should be examined in future research. Second, we decided to intervene for Family 1 despite decreasing trends in child CB, given the undesirable effects of extended baseline conditions. Third, as expected, IOA was lower for variables that were free operant and required more inference-based decisions (e.g., prevent, teach, CB, and replacement behaviors; Yoder et al., 2018 ). Free operant behaviors, which occur at any time and are not tied to specific antecedents or discrete responses, inherently introduce more opportunities for discrepancies between observers. This is particularly true when the behavior requires subjective judgment or when contextual factors are not explicitly observable, increasing the likelihood of differences in coding decisions (Kazdin, 2011 ). Additionally, IOA was lower for low-rate behaviors, consistent with existing research showing that behaviors occurring infrequently present challenges for agreement due to their rarity and increased susceptibility to random error (Ledford & Gast, 2018 ). For example, a single discrepancy in coding a low-frequency behavior (e.g., observing one versus zero instances) can result in significant reductions in percentage agreement, as demonstrated in session 6 for Family 1: the primary coder recorded one instance of replacement behavior, while the secondary coder recorded none, resulting in 0% agreement. Such differences may disproportionately affect reliability metrics for low-rate behaviors compared to high-frequency behaviors, where single discrepancies have a smaller relative impact. To address these challenges, we graphed primary and secondary data on the same graph, allowing us to observe important differences across observers that were not readily captured by percentages of agreement alone (e.g., discrepancies in coding replacement behaviors). This method provides greater transparency and granularity in data interpretation, supplementing numeric IOA values with a visual representation of observer differences. Graphs displaying primary and secondary data are available via OpenScience Framework, supporting further exploration and replication of these findings. Conclusions CBs are a major stressor for families and impact their quality of life. However, access to home-based supports is often difficult for families. We examined the use of a mobile technology—the FBSApp—that has strong potential to support families in using strategies that reduce their child’s CB and might be more accessible and efficient than other in person supports. Although we had idiosyncratic results and no functional relations, our data are promising. Our findings underscore the importance of individualized approaches and contribute to the broader discourse on individual intervention strategies that are family-centered and consider historical and immediate contexts. The rigor of our methodology ensures that our results are robust and reliable, providing a solid foundation for future research and potential replication studies. Overall, our study adds depth to the field by illustrating the complexity and individuality of educational experiences and interventions. Future research is needed to continue examining efficient ways to support families, including the use of the FBSApp and other mobile technologies (Buzhardt, & Meadan, 2022 ). Declarations Author Contribution All authors participated in the research, wrote sections of the manuscript, and reviewed the final manuscript. Data Availability Additional details regarding the participants, coding, and coaching procedures can be found on OpenScienceFramework (https://doi.org/10.17605/OSF.10/XK3GA). References Akemoglu, Y., Muharib, R., & Meadan, H. (2020). A systematic and quality review of parent-implemented language and communication interventions conducted via telepractice. Journal of Behavioral Education , 29 , 282-316. Authors. (2024). Xxxx. Manuscript under review. Authors. (2024). Xxxx. Manuscript under review. Barton, E. E. (2022). Family Behavior Support App (version 1.0.1) [Mobile app]. App Store. https://apps.apple.com/us/app/family-behavior-support-app/id1598406686 Barton, E. E., Reichow, B., Wolery, M., & Chen, C. (2020). Technology-aided instruction and intervention for students with ASD: A meta-analysis. Journal of Autism and Developmental Disorders, 50 (1), 176-191. doi:10.1007/s10803-019-04260-8 Barton, E. E., Winchester, C., Velez, M. S., Todt, M., Locchetta, B. M., & Skiba, E. (2024). Field Testing the Family Behavior Support Mobile Application (FBSApp) During a Global Pandemic. Journal of Autism and Developmental Disorders . https://doi.org/10.1007/s10803-024-06373-8 Bromley, J., Hare, D. J., Davison, K., & Emerson, E. (2004). Mothers supporting children with ASD: Social support, mental health status and satisfaction with services. Autism: The International Journal of Research and Practice , 8 (4), 409–423. Buzhardt, J., & Meadan, H. (2022). Introduction to the special issue: A new era for remote early intervention and assessment. Journal of Early Intervention , 44 (2), 103-109. Çelik, S., Tomris, G., & Tuna, D. M. (2022). The COVID-19 pandemic: Evaluation of the emergency remote parent training program based on at-home support for children with down syndrome. Children and Youth Services Review, 133, 106325. Cook, B. G., & Therrien, W. J. (2017). Null effects and publication bias in special education research. Behavioral Disorders , 42 (4), 149-158. Chazin, K. T., Velez, M. S., & Ledford, J. R. (2022). Reducing escape without escape extinction: a systematic review and meta-analysis of escape-based interventions. Journal of Behavioral Education, 31 , 186-215. Division for Early Childhood. (2014). DEC recommended practices in early intervention/early childhood special education 2014 . http://ww.dec-sped.org/recommendedpractices Doubet, S. L., & Ostrosky, M. M. (2015). The impact of challenging behavior on families: I don’t know what to do. Topics in Early Childhood Special Education , 34 (4), 223–233. Douglas, S. N., Kammes, R., & Nordquist, E. (2018). Online communication training for parents of children with autism spectrum disorder. Communication Disorders Quarterly , 39 (3), 415-425. Dunst, C. J., Trivette, C. M., & Hamby, D. W. (2019). Meta-analysis of family-centered helpgiving practices research. Mental Retardation and Developmental Disabilities Research Reviews, 12 (2), 110-119. doi:10.1002/mrdd.20120 Fettig, A., & Barton, E. E. (2014). Functional assessment-based parent intervention to reduce children’s challenging behaviors: A literature review. Topics in Early Childhood Special Education, 34 , 49-61. Fixsen, D. L., Naoom, S. F., Blase, K. A., Friedman, R. M., & Wallace, F. (2005). Implementation research: A synthesis of the literature . University of South Florida, Louis de la Parte Florida Mental Health Institute, National Implementation Research Network. Fox, L., Vaughn, B. J., Dunlap, G., & Bucy, M. (1997). Parent-professional partnership in behavioral support: a qualitative analysis of one family’s experience. Journal of the Association for Persons with Severe Handicaps , 22 (4), 198–207. Frey, A. J., Small, J. W., Feil, E. G., Seeley, J. R., Walker, H. M., & Forness, S. (2015). First step to success: applications to preschoolers at risk. Education and Training in Autism and Developmental Disabilities , 50 (4), 397–407. Gast, D. L., Lloyd, B. P., & Ledford, J. R. (2018). Multiple baseline and multiple probe designs. In Ledford, J. R., & Gast, D. L. (Eds). Single case research methodology: Applications in special education and behavioral sciences (pp. 239-281). Routledge. Gerow, S., Hagan-Burke, S., Rispoli, M., Gregori, E., Mason, R., & Ninci, J. (2018). A review of parent-implemented functional communication training for children with ASD. Behavior Modification , 42 (3), 335-363. Guralnick, M. J. (2020). Early intervention approaches to enhance the peer-related social competence of young children with developmental delays: A historical perspective. Infants & Young Children, 33 (4), 268-284. doi:10.1097/IYC.0000000000000169 Harbin, S. G., Choi, G., & Fettig, A. (2024). Reconceptualizing Family-Centered Partnerships in Parent-Implemented Interventions. Infants & Young Children , 37 (3), 256-269. Joachim, S., Sanders, M. R., & Turner, K. M. T. (2010). Reducing preschoolers’ disruptive behavior in public with a brief parent discussion group. Child Psychiatry and Human Development , 41 (1), 47–60. Kasprzak, C., Hurth, J., Rooney, R., Goode, S. E., Danaher, J. C., Whaley, K. T., Ringwalt, S. S., & Cate, D. (2012). States’ accountability and progress in serving young children with disabilities. Topics in Early Childhood Special Education, 32 , 151-163. Kazdin, A. E. (2011). Single-case research designs: Methods for clinical and applied settings (2nd ed.). New York, NY: Oxford University Press. Khetani, M. A., McManus, B. M., Arestad, K., Richardson, Z., Charlifue-Smith, R., Rosenberg, C., & Rigau, B. (2018). Technology-based functional assessment in early childhood intervention: a pilot study. Pilot and Feasibility Studies , 4 , 1-9. Ledford, J. R., Lane, J. D., & Gast, D. L. (2018). Dependent variables, measurement, and reliability. In Ledford, J. R., & Gast, D. L. (Eds), Single Case Research Methodology: Applications in Special Education and Behavioral Sciences. (pp. 97–131). Routledge. Ledford, J. R., & Gast, D. L. (2018). Single case research methodology: Applications in special education and behavioral sciences (3rd ed.). Routledge. Lucyshyn, J. M., Albin, R. W., Horner, R. H., Mann, J. C., Mann, J. A., & Wadsworth, G. (2007). Family implementation of positive behavior support for a child with autism: longitudinal, single-case, experimental, and descriptive replication. Journal of Positive Behavior Interventions , 9 (3), 131–150. Maggin, D. M., Cook, B. G., & Cook, L. (2019). Making sense of single-case design effect sizes. Learning Disabilities Research & Practice, 34 (3), 124-132. McDevitt, S. E. (2022). While quarantined: An online parent education and training model for families of children with autism in China. Research in Developmental Disabilities. https://doi.org/10.1016/j.ridd.2020.103851 Meadan, H., & Daczewitz, M. E. (2015). Internet-based intervention training for parents of young children with disabilities: A promising service-delivery model. Early child development and care , 185 (1), 155-169. Meadan, H., Meyer, L. E., Snodgrass, M. R., & Halle, J. W. (2013). Coaching parents of young children with autism in rural areas using internet-based technologies. Rural Special Education Quarterly, 32 (3), 3-10. Meadan, H., Snodgrass, M. R., Meyer, L. E., Fisher, K. W., Chung, M. Y., & Halle, J. W. (2016). Internet-based parent-implemented intervention for young children with autism. Journal of Early Intervention , 38 (1), 3-23. Miltenberger, R. G. (2012). Behavior skills training procedures. In R. G. Miltenberger (Ed.), Behavior Modification: Principles and Procedures (pp.217-235). Wadsworth Publishing. Moes, D. R., & Frea, W. D. (2002). Contextualized behavioral support in early intervention for children with autism and their families. Journal of Autism and Developmental Disorders , 32 (6), 519-533. Peters, S. Z., Brumbaugh, K. M., & Blackwell, A. (2023). The Effects of Virtual Caregiver Coaching in Antigua & Barbuda on the Implementation of EMT Language Support Strategies in Naturalistic Environments. International Journal of Telerehabilitation , 15 (2), 1-14. doi: 10.5195/ijt.2023.6586 Pustejovsky, J. E. (2018). Using response ratios for meta-analyzing single-case designs with behavioral outcomes. Journal of School Psychology, 68, 99-112. Pustejovsky, J. E, Chen, M., & Swan, D. M. (2022). Single-case effect size calculator (Version 0.6.1). [Web application]. https://jepusto.shinyapps.io/SCD-effect-sizes/ Smith, B. J., & Fox, L. (2003). Systems of Service Delivery: A Synthesis of Evidence Relevant to Young Children at Risk of or Who Have Challenging Behavior. University of South Florida Center for Evidence-Based Practice: Young Children with Challenging Behavior. Squires, J., Bricker, D., & Twombly, E. (2015). Ages & Stages Questionnaires®: Social Emotional, Second Edition (ASQ®:SE-2): A parent-completed child monitoring system for social-emotional behaviors. Brookes Publishing Co. Tapp, J. (2003). ProcoderDV. Vanderbilt Kennedy Center. Travers, J. C., Cook, B. G., Therrien, W. J., & Coyne, M. D. (2016). Replication research and special education. Remedial and Special Education , 37 (4), 195-204. U.S. Department of Commerce, Census Bureau. (2020, February). American Community Survey (ACS), 2018. Wahman, C. L., Fettig, A., & Zimmerman, K. (2023). Social and emotional intervention research as justice: A case for accountability. Remedial and Special Education , 44 (5), 423-438. Yoder, P. J., Lloyd, B. P., & Symons, F. J. (2018). Observational Measurement of Behavior. Brookes Publishing Co. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6940507","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":494964749,"identity":"44ceb2fc-354e-4e10-aadb-058aa9c2d98e","order_by":0,"name":"Claire Winchester","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Claire","middleName":"","lastName":"Winchester","suffix":""},{"id":494964750,"identity":"58705735-cda3-44cc-8a7e-5db03a01bc14","order_by":1,"name":"Erin Barton","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIiWNgGAWjYFACxgYQArMeAAkePqK18DAwMBuAtLARaxFIC5sEiENQC7/04bYHjDvs8u3Ze49Vfs2xk2FjYH746AYeLZJ9ie0GjGeSLXt4zqXdlt2WDHQYm7FxDh4tBmcY2yQY25gNeCRyzG5LbmMGauFhk8anxR6ipR6spVhyWz1hLQY8YC2HwVoYP247TFiLBMiWxDPHDXjOnDGWZtx2nIeNmYBf+HvYn0l83FFtwN7eY/jx57Zqe3725oeP8WkBgwQozcwDJgkpRwaMP0hRPQpGwSgYBSMGAACF9DyiDB60sAAAAABJRU5ErkJggg==","orcid":"","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Erin","middleName":"","lastName":"Barton","suffix":""},{"id":494964751,"identity":"f9df80ca-30c6-4d74-895e-d163b59a42bc","order_by":2,"name":"Brandy Locchetta","email":"","orcid":"","institution":"University of West Georgia","correspondingAuthor":false,"prefix":"","firstName":"Brandy","middleName":"","lastName":"Locchetta","suffix":""},{"id":494964752,"identity":"01f82f0d-b602-4ccb-879c-8fe409587c85","order_by":3,"name":"Marina Velez","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Marina","middleName":"","lastName":"Velez","suffix":""},{"id":494964754,"identity":"7383be05-bc54-4d3b-bf28-e84492481308","order_by":4,"name":"Mollie Todt","email":"","orcid":"","institution":"Vanderbilt University","correspondingAuthor":false,"prefix":"","firstName":"Mollie","middleName":"","lastName":"Todt","suffix":""}],"badges":[],"createdAt":"2025-06-20 16:23:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6940507/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6940507/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88339624,"identity":"2a05e538-da8f-4aa5-a99d-22aec19c732d","added_by":"auto","created_at":"2025-08-05 12:25:29","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":68557,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eFrequency of strategy use and challenging behavior for Family 1.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote. \u003c/em\u003eRanges of the y-axes are different for each tier to reflect the difference in the total frequency for each behavior. Generalization data are represented by triangles and open bars. First tier: open bars represent challenging behavior and closed triangles represent caregiver new response. Second tier: open triangles represent prevent strategies. Third tier: closed triangles represent presentation of an establishing operation and open triangles represent prompting.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6940507/v1/6fb0f280dbc9fe17087629d8.jpg"},{"id":88339625,"identity":"3594e64c-b1f1-4392-8674-ef7caa918132","added_by":"auto","created_at":"2025-08-05 12:25:29","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":36597,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eFrequency of child engagement in replacement behaviors for Family 1.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e. Corresponding generalization data are represented by open triangles.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6940507/v1/f84b0082bc24b7a0c3f808f2.jpg"},{"id":88339627,"identity":"7c4fa334-56e6-4f4d-aeb0-8a8306f524b6","added_by":"auto","created_at":"2025-08-05 12:25:29","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":38225,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eFrequency of strategy use and child behavior for Family 2.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e. Ranges of the y-axes are different for each tier to reflect the difference in the appropriate frequency for each behavior. Corresponding generalization data are represented by open triangles.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6940507/v1/ffcaef7000e7c4de80e216ad.jpg"},{"id":94599919,"identity":"52ce407f-7cc0-4af1-a6da-99855aa7e3aa","added_by":"auto","created_at":"2025-10-28 19:08:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1405832,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6940507/v1/06364f39-a5ca-4739-8c28-59770ff00654.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Effects of the Family Behavior Support Application (FBSApp) with Virtual, Strategy-Based Coaching on Caregiver and Child Behaviors","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChallenging behavior (CB) has long been recognized as a primary area of concern for families of young children (Doubet \u0026amp; Ostrosky, 2015), and particularly so for families of young children with disabilities (Bromley et al., 2004). CB presents a significant barrier to meaningful participation in home routines, community activities, and educational settings (Lucyshyn et al., 2007), which can cause parental stress and reductions in family quality of life (Fox et al., 1997; Joachim et al., 2010). Further, CB identified in the preschool years is predictive of later adjustment difficulties and negative long-term outcomes (Frey et al., 2015), highlighting the need for effective early intervention on CB.\u003c/p\u003e\n\u003cp\u003eGiven the body of evidence supporting the family unit as one of the most significant contributors in fostering children’s success (Dempsey \u0026amp; Keen, 2008), identifying interventions for CB that can be effectively integrated into family life is imperative. Researchers have documented the importance of providing support to families in naturally occurring settings and routines (Fixsen et al., 2005), and the Division of Early Childhood (DEC) recommends including family members in assessment and intervention procedures to promote positive outcomes (2014). Many researchers have demonstrated that caregivers can implement evidence-based intervention strategies with high levels of fidelity when effective supports are provided, leading to improvements in child and family outcomes (Fettig \u0026amp; Barton, 2014; Gerow et al., 2018).\u003c/p\u003e\n\u003cp\u003eThough in-home services are an ideal mode for family-centered intervention, they are often time- and resource-intensive and can be especially limited for families in rural communities or families living in poverty (Kasprzak et al., 2012; Meadan et al., 2013). Caregiver coaching programs delivered virtually (e.g., via Zoom or other teleconferencing software) may be an accessible and effective alternative (Çelik et al., 2022; Meadan et al., 2016). Virtual models enable practitioners to involve endogenous implementers (i.e., caregivers, other family members) that regularly spend time with the child while also intervening on behavior directly in the environment in which it occurs. Further, technological access is steadily increasing, with the vast majority of American households having access to a computer and internet (U.S. Department of Commerce, 2022). Thus, gere is increasing support for virtual service delivery for families of young children.\u003c/p\u003e\n\u003cp\u003eResearch on the use of virtual, telehealth models for caregiver coaching is growing, especially since the COVID-19 pandemic. Researchers have found virtual coaching to be effective for increasing caregivers’ use of Enhanced Milieu Teaching (Peters et al., 2023), naturalistic communication teaching strategies (Douglas et al., 2018; Meadan et al., 2016), and function-based interventions (Lindgren et al., 2020). Caregivers have also reported feeling less isolated and more supported (McDevitt, 2021), and more confident in their ability to interact with their child (Meadan et al., 2016). While there is promising evidence for these approaches, research on teaching caregivers how to implement function-based interventions via tele-coaching remains quite limited, although some studies have demonstrated the feasibility and effectiveness of parent training to address challenging behaviors (Akemoglu et al., 2020; Ruppert et al., 2016). Future research should continue to explore and expand this area to better address the needs of families.\u003c/p\u003e\n\u003cp\u003eWhile these models can greatly improve access, researchers have identified important barriers, including a lack of fluency with the technology, difficulty building rapport and maintaining communication with caregivers, and limited caregiver engagement with coaching materials and resources. Additionally, research on virtual service delivery has been limited and has not extensively focused on how to foster effective collaboration and build strong, holistic partnerships between professionals and caregivers. Further research is needed to vet methods for effective virtual service delivery that is meaningful and accessible to caregivers and supports a holistic caregiver-professional partnership (Harbin, Choi, \u0026amp; Fettig, 2024).\u003c/p\u003e\n\u003cp\u003eWe examined the effects of the Family Behavior Support application (FBSApp; Barton, 2022), a mobile application designed to support caregivers in implementing function-based, positive behavior support strategies at home with their young children with disabilities or delays and CB. The app is designed to promote collaboration between caregivers and support professionals (i.e., early interventionists, behavior therapists) while also providing accessible and targeted support and resources for caregivers at home. Previous research has supported the use of the FBSApp with strategy-based coaching to increase caregivers’ use of targeted intervention strategies and reduce children’s CB across routines (Barton et al., 2024; Authors, 2024; Authors, 2024). We conducted the current study to further explore the characteristics of systematic coaching (e.g., instructional content, dosage, method of feedback delivery) functionally related to caregiver strategy use and child behavior change. The following research questions guided our study:(a)Does caregiver use of the FBSApp with virtual, strategy-based coaching increase caregiver use of targeted strategies?(b) Does caregiver use of targeted strategies generalize to a novel routine and maintain when coaching is systematically faded? (c) Does caregiver use of the FBSApp with virtual, strategy-based coaching decrease child CB and increase child use of replacement behaviors?\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe began recruitment after obtaining approval from the university\u0026rsquo;s institutional review board. Procedures included distributing materials (e.g., flyers) via social media and contacting relevant childcare, service provision, and educational agencies in an urban city in southeast US. Families were screened according to the following child inclusion criteria: (a) age between 24 and 71 months; (b) medical diagnosis or educational eligibility category, or at-risk for disability according to the Ages and Stages Questionnaire: Social-Emotional, 2\u003csup\u003end\u003c/sup\u003e edition (ASQ-SE-2; Squires et al., 2015); and (c) caregiver-reported CB occurring in the home setting a minimum of three times per week. Three families met inclusion criteria and were consented for participation in the study; one family (i.e., Family 3) withdrew before data collection began.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFamily 1\u0026nbsp;\u003c/strong\u003econsisted of a mother-son dyad. Elijah was a 4-year-old, White/Hispanic male with social anxiety disorder. Elijah did not receive any additional services and attended a private childcare facility. His mother, Brooke, was a White female who worked full-time. She reported the target CB to be verbal aggression (e.g., screaming, swearing) and elopement, with occasional physical aggression toward mom and sister (e.g., hitting, throwing things). The targeted routine was the transition to bedtime, and the generalization routine was mealtime (i.e., dinner). A 2-year-old, typically-developing sister was also present in the home; Brooke was the sole caregiver for the majority of the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFamily 2\u0026nbsp;\u003c/strong\u003econsisted of a father-daughter dyad. Zara was a 4-year-old, Black female with autism spectrum disorder (ASD) and language delay. Zara received speech-language services and attended a public preschool, both temporarily in a virtual setting due to COVID-19 restrictions. Her father, Christian, was a Black male who worked full-time. He reported the target CB to be verbal refusal, tantrums (e.g., excessive crying, screaming), and elopement. The targeted routine was mealtime (i.e., lunch), and the generalization routine was brushing teeth. Other individuals present in the home were a 3-year-old sister and a 5-year-old brother (also with an ASD diagnosis), and the mother, who also worked full-time.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFamily 3\u0026nbsp;\u003c/strong\u003econsisted of a mother-son dyad. James was a 4-year-old, White male with anxiety disorder and developmental delay. James attended a public preschool and received private mental health services. His mother, Melissa, was a White female who worked full-time. She reported the target CB to be verbal aggression (e.g., screaming, swearing), physical aggression toward mom, sister, and peers (e.g., hitting, kicking), and elopement. A 2-year-old, typically-developing sister was also present in the home; Melissa was the sole caregiver. Family 3 withdrew prior to baseline data collection for reasons unrelated to the study. They had considered using mealtimes as the targeted routine prior to withdrawing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eResearch Personnel\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo research assistants within the second author\u0026rsquo;s research lab were responsible for implementing all coaching procedures. Both coaches were White female master\u0026rsquo;s students in early childhood special education accruing hours toward behavior analysis certification. The coach for Family 1 had previous experience coaching families using the FBSApp; the coach for Family 2 had previous experience working with young children but did not have experience coaching families. Two White, female doctoral students in early childhood special education advised and supervised the coaches. They both had previous classroom teaching and supervisory experience. Five master\u0026rsquo;s students and one doctoral student were trained to code data by the one of the supervisors prior to the study start. All coders were female students (white, non-Hispanic = 5; white, Hispanic = 1) in an early childhood special education graduate program.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSetting and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll study procedures took place in the families\u0026rsquo; homes. Observation sessions were conducted in the context of the target routine. During intake, each family identified two routines in which challenging behavior occurred: a \u003cem\u003etarget routine\u003c/em\u003e and a \u003cem\u003egeneralization routine\u003c/em\u003e. The \u003cem\u003etarget routine\u003c/em\u003e was the activity or time of day when challenging behavior was most likely to occur and intervention would be most beneficial. The \u003cem\u003egeneralization routine\u003c/em\u003e was an additional context where challenging behavior occurred, but it was not the primary focus of intervention. Families were issued an iPad which they used to access the FBSApp and attended all observations, trainings, and coaching sessions via Zoom teleconferencing software. Coaches used a laptop to attend and record all sessions via Zoom. Data were collected via ProCoderDV (Tapp, 2003) and graphed and analyzed in Microsoft Excel. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe\u003cstrong\u003e\u0026nbsp;Family Behavior Support application (FBSApp)\u003c/strong\u003e is a tool for supporting caregivers in using function-based intervention strategies to address their young child\u0026rsquo;s CB and support health social-emotional development at home. The function-generating algorithm uses antecedent-behavior-consequence (ABC) data input by caregivers to create an individualized behavior support plan (BSP) based on the hypothesized function (i.e., purpose) of the child\u0026rsquo;s CB. Caregivers can access infographics and videos containing descriptions and models of strategies. Throughout, caregivers can document and track their progress and can collaborate with other caregivers and support professionals (e.g., therapists, behavior analysts) within the app.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDependent Variables and Coding Procedures\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eMeasurement System\u003c/em\u003e\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResearch assistants coded data immediately following observations. We only collected data on behaviors under the function(s) that was listed on the family specific BSP, with the exception of prevent strategies. Although the coaches instructed caregivers on specific prevent strategies (see Tables 1 and 2), the caregivers still had access to information on all prevent strategies through the FBSApp since prevent strategies are not tied to specific functions. We used timed event sampling to mark the onset of all dependent variables, except caregiver prompts and responses to CB; these variables were dependent on the occurrence of an establishing statement or CB respectively and were categorized following their onset. For all dependent variables, a minimum of 5 s was required between the offset of the preceding behavior and onset of the following behavior within the same category to be considered two separate instances. Definitions and examples for Family 1 and Family 2 are included in Tables 1 and 2, respectively.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"870\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 870px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003e\u003cem\u003eFamily 1 Function, Target Strategy Definitions, and Examples\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFunction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevent\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 270px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChild Replacement Behavior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 246px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNew Response\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGain attention\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePositive descriptive feedback\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eDefinition:\u003c/u\u003e Vocal statements containing both positive language and a description of a specific behavior in which the child engaged\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eExample:\u003c/u\u003e Caregiver says, \u0026ldquo;You did such a good job getting dressed!\u0026rdquo;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eGeneral positive attention\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eDefinition:\u003c/u\u003e Vocal statement, physical gesture, or touch \u003cem\u003enot\u003c/em\u003e dependent on the child engaging in a specific behavior\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eExample:\u003c/u\u003e Caregiver imitates child\u0026rsquo;s sounds while playing with toy cars\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAsk for attention\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eDefinition:\u003c/u\u003e Vocal request for the target caregiver\u0026rsquo;s attention\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eExample:\u003c/u\u003e Child says, \u0026ldquo;Mama play?\u0026rdquo; when caregiver walks by play area\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAsk for help\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eDefinition:\u003c/u\u003e Vocal request for assistance with activity, play, routine, etc.\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eExample:\u003c/u\u003e Child says, \u0026ldquo;Help,\u0026rdquo; while holding out toy toward caregiver\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMinimize attention\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eDefinition:\u003c/u\u003e Provision of minimal or low-quality attention that does not specifically reference any aspect of the challenging behavior\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eExample:\u003c/u\u003e Caregiver turns away and plays with sibling when child throws a toy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEscape demand\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictable schedules\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eDefinition:\u003c/u\u003e Vocal or visual presentation of a sequence of at least two activities or behaviors to prepare child for upcoming events, activities, or tasks\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eExample:\u003c/u\u003e Caregiver says, \u0026ldquo;First we\u0026rsquo;re going to eat dinner, then bath time, and then bed\u0026rdquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAsk for help\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eDefinition:\u003c/u\u003e Vocal request for assistance with activity, play, routine, etc.\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eExample:\u003c/u\u003e Child says, \u0026ldquo;Help,\u0026rdquo; while holding out toy toward caregiver\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAsk to be done\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eDefinition:\u003c/u\u003e Vocal request stating a desire not to complete the current or proposed activity/task \u003cem\u003ewithout\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003ea request for an alternative\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eExample:\u003c/u\u003e Child says, \u0026ldquo;No peas, please\u0026rdquo; when caregiver sets down plate of food\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrompt follow-through\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eDefinition:\u003c/u\u003e Vocal or physical prompting to complete the task that preceded the instance of challenging behavior by (a) providing new information, or (b) adapting task to promote success\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eExample:\u003c/u\u003e Caregiver holds towel out to child after saying, \u0026ldquo;Time to dry off\u0026rdquo;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"870\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 870px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003e\u003cem\u003eFamily 2 Function, Target Strategy Definitions, and Examples\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFunction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCaregiver Prevent\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 270px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eChild Replacement Behavior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 240px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCaregiver New Response\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEscape demand\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 264px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePositive descriptive feedback\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eDefinition:\u003c/u\u003e Vocal statements containing (a) positive language, and (b) a description of a specific behavior in which the child engaged\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eExample:\u003c/u\u003e \u0026ldquo;You did such a good job getting dressed!\u0026rdquo;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eGeneral positive attention\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eDefinition:\u003c/u\u003e Vocal statement, physical gesture, or touch \u003cem\u003enot\u003c/em\u003e dependent on the child engaging in a specific behavior\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eExample:\u003c/u\u003e Caregiver imitates child\u0026rsquo;s sounds while playing with toy cars\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 270px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAsk to be done\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eDefinition:\u003c/u\u003e Vocal request stating a desire not to complete the current or proposed activity/task \u003cem\u003ewithout\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003ea request for an alternative\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eExample:\u003c/u\u003e Child says, \u0026ldquo;No peas, please\u0026rdquo; when caregiver sets down plate of food\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eFollow Directions (engage in non-preferred tasks)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eDefinition:\u003c/u\u003e Engaging in a behavior that functionally matches the caregiver\u0026rsquo;s instruction\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eExample:\u003c/u\u003e Child puts spoonful of peas into their mouth 5s after caregiver says, \u0026ldquo;Take a bite, please\u0026rdquo;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 240px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIgnore request\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eDefinition:\u003c/u\u003e Removal of attention following child\u0026rsquo;s request not to complete the current or proposed activity/task\u003c/p\u003e\n \u003cp\u003e\u003cu\u003eExample:\u003c/u\u003e Caregiver continues brushing their own teeth and does not respond when child verbally refuses to comply with caregiver\u0026rsquo;s direction to brush teeth\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCaregiver Behaviors\u003c/em\u003e\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevent Strategies.\u0026nbsp;\u003c/strong\u003eCaregiver use of prevent strategies was defined as vocal or physical behavior which involved changing the antecedents that typically occur before CB to make CB less likely to occur and desirable behavior more likely to occur. Strategies included behaviors that contribute to creating high-quality environments and interactions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTeach Trials.\u0026nbsp;\u003c/strong\u003eTo assess caregiver implementation of strategies for teaching replacement behaviors to their child, we measured the frequency of teach trials and the presence of prompts within each trial. A teach trial was initiated by the caregiver through a vocal presentation of an establishing statement. This statement functioned as an establishing operation by either increasing the value of a reinforcer or indicating its availability (e.g., \u003cem\u003e\u0026ldquo;If you want me to play, you can say, \u0026lsquo;Play, please.\u0026rsquo;\u0026rdquo;\u003c/em\u003e). Nonexamples of establishing statements included vocalizations that required compliance with a demand to access reinforcement (e.g., \u003cem\u003e\u0026ldquo;Once you rinse your hair, you can be all done,\u0026rdquo;\u003c/em\u003e which signaled escape from a demand but did not create an opportunity for teaching a functionally equivalent replacement behavior).\u003c/p\u003e\n\u003cp\u003eFor each teach trial, we recorded whether the caregiver provided a prompt following the establishing statement to facilitate the child\u0026apos;s use of the replacement behavior. Prompts were defined as additional forms of support, including open questions (e.g., \u003cem\u003e\u0026ldquo;What do you need to say?\u0026rdquo;\u003c/em\u003e), choice prompts (e.g., \u003cem\u003e\u0026ldquo;Do you want to say, \u0026lsquo;Play, please,\u0026rsquo; or \u0026lsquo;Toy, please\u0026rsquo;?\u0026rdquo;\u003c/em\u003e), model prompts (e.g., \u003cem\u003e\u0026ldquo;Say, \u0026lsquo;Play, please.\u0026rsquo;\u0026rdquo;\u003c/em\u003e), verbal prompts (e.g., \u003cem\u003e\u0026ldquo;Ask me to play first.\u0026rdquo;\u003c/em\u003e), or gestural prompts (e.g., pointing to a visual cue). To qualify as a prompt, the caregiver\u0026rsquo;s assistance had to occur within 10 s of the offset of the establishing statement. Repeating the same establishing statement (e.g., \u003cem\u003e\u0026ldquo;If you want me to play, you can say, \u0026lsquo;Play, please,\u0026rsquo;\u0026rdquo;\u003c/em\u003e restated verbatim) was not coded as a prompt.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNew Response.\u0026nbsp;\u003c/strong\u003eFor each instance of CB, we marked the occurrence or non-occurrence of a new response strategy. Caregiver use of new response strategies was defined as a response to CB that was functionally incompatible, such that it \u003cem\u003ereduced\u003c/em\u003e the likelihood of future CB (see Tables 1 and 2). Nonexamples for new response strategies were responses that reinforced the CB such that it would \u003cem\u003eincrease\u003c/em\u003e the likelihood of occurrence in the future.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eChild Behaviors\u003c/em\u003e\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCB.\u0026nbsp;\u003c/strong\u003eWe collected data on the frequency of CB, which was broadly defined as behavior that interferes with the child\u0026rsquo;s meaningful engagement in their environment or social interactions (Smith \u0026amp; Fox, 2003). Common topographies included physical aggression, verbal aggression, tantrumming, and noncompliance in the form of elopement or verbal refusal. Self-stimulatory behaviors that did not meet any other criteria (e.g., hand-flapping) were not considered CB. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReplacement Behaviors.\u0026nbsp;\u003c/strong\u003eWe collected data on the frequency of child behaviors that would serve as a replacement for CB according to the hypothesized function identified by FBSApp. A replacement behavior was broadly defined as a child\u0026rsquo;s appropriate request for functionally equivalent reinforcement from the target caregiver, or\u003cem\u003e\u0026nbsp;\u003c/em\u003eengagement in the caregiver\u0026rsquo;s identified behavior of concern intended to increase. For Family 1, only functional requests for attention or escape from a task were marked. For Family 2, functional requests to escape from a task and engagement in non-preferred tasks (i.e., eating non-preferred foods for intervention and brushing teeth for generalization) were marked; this was at the request of the caregivers since they expressed a desire to both honor appropriate requests but also increase the child\u0026rsquo;s cooperation with daily self-help routines.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEffect Sizes\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs a complement to visual analysis, we calculated effect sizes to aid in the interpretation of our results (Maggin et al., 2019). The log response ratio (LRR) effect size is the natural log of proportionate change in the mean level between conditions (Pustejovsky, 2018); LRR increasing (LRRi) is used for behaviors that are expected to increase in intervention conditions (e.g., caregiver use of strategies), and LRR decreasing (LRRd) is used for behaviors that are expected to decrease in intervention conditions (e.g., child CB). We used the Single Case Effect Size Calculator web application (Pustejovsky et al., 2022) to calculate LRR effect sizes for each A-B comparison of a dependent variable (e.g., caregiver use of prevent strategies from baseline to intervention) for each family. To facilitate interpretation, we also converted the LRR into percent change.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInterobserver Agreement\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(IOA)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll coders were trained prior to the start of data collection. First, coders were provided with a decision tree and coding manual with operational definitions, examples, and non-examples of dependent variables. Next, coders met to review the manual and code a practice video together. Coders then coded non-study practice videos independently until at least 80% agreement was reached on each dependent variable across two videos. To estimate IOA, two coders independently coded sessions for all participants on all dependent variables. For variables captured with timed-event recording, IOA was estimated using a point-by-point agreement method (Ledford et al., 2018) with a 3 s agreement time-window. For variables captured using a categorical method (i.e., caregiver new response, caregiver use of prompts in teach trials), IOA was estimated using an agreement method with each behavior marked as an agreement or disagreement (Ledford et al., 2018). Coders were masked to all study conditions. Throughout the study, meetings were conducted to review formative IOA and to discuss and resolve discrepancies; if the disagreement could not be resolved between the primary and secondary coders, the third author made the final decision. We graphed primary and secondary data concurrently and monitored IOA throughout the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExperimental Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe used a concurrent multiple baseline across behaviors (sessions; Gast et al., 2018) single case experimental design to evaluate the efficacy of coaching caregivers on individual categories of target strategies sequentially (i.e., prevent, teach, new response). The order in which strategies were targeted was randomized for both families. Because Family 2 withdrew from the study after the first tier, the intervention was ultimately introduced in an A-B design. Condition change decisions were made based on the primary dependent variables, caregiver behaviors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIntervention: Coaching Procedures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCoaching procedures were designed as a companion to FBSApp to be used by professionals supporting families (see Table 3 for coaching across conditions). All materials developed and used by coaches were closely aligned with existing features and resources within the app (e.g., infographics, tutorial videos). Coaching included the following components: (a) virtual meetings, (b) behavior skills training (BST; Miltenberger, 2012), (c) focused observations with live debriefs, and (d) supportive observations with email feedback. While systematic in nature, coaching procedures were flexible enough to allow for individualization, ensuring alignment with the family\u0026rsquo;s preferences, needs, and goals. Prior to the onset of the study, coaches received a 60-min virtual training facilitated by their supervisor. During this training, supervisors presented an overview of coaching components and procedures, the coaching timeline, fidelity documents, and support materials (i.e., email templates, note templates). The supervisors\u0026rsquo; implementation fidelity was collected by a research assistant via video using a checklist.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"819\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"7\" style=\"width: 819px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003e\u003cem\u003eCoaching Procedures\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16.0858%;\"\u003e\n \u003cp\u003eCondition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eABC Data Training\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eApp Orientation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6729%;\"\u003e\n \u003cp\u003eAccess to FBSApp\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eBST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eFocused Observations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 145px;\"\u003e\n \u003cp\u003eSupportive Observations\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16.0858%;\"\u003e\n \u003cp\u003ePre-Baseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6729%;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 145px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16.0858%;\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6729%;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 145px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16.0858%;\"\u003e\n \u003cp\u003ePrevent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6729%;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 145px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16.0858%;\"\u003e\n \u003cp\u003eTeach\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6729%;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 145px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16.0858%;\"\u003e\n \u003cp\u003eNew Response to CB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6729%;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 145px;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16.0858%;\"\u003e\n \u003cp\u003eGeneralization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6729%;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 145px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 16.0858%;\"\u003e\n \u003cp\u003eMaintenance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 102px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 13.6729%;\"\u003e\n \u003cp\u003eX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 108px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 145px;\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eInitial Meetings\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePre-baseline observations were conducted to gather data to enter into the FBSApp and to ensure challenging behaviors occurred during the target routines identified by families during intake. The families did not have access to the FBSApp during pre-baseline observations. Two meetings took place between pre-baseline and baseline observations. The first meeting between the caregiver and coach lasted approximately 60 min, during which the coach outlined their role in supporting the family, identified their communication preferences (e.g., text or email), and walked them through app installation. The coach then delivered direct instruction on: (a) CB as a form of communication, (b) the functions of CB, and (c) ABC data collection. The coach then helped the caregiver enter one instance of ABC data, using a video from the family\u0026rsquo;s pre-baseline observations. Families were instructed to continue to collect instances of ABC data following the first meeting. After families entered at least three instances of ABC data, the FBSApp generated a hypothesis statement and solicited agreement that the statement reflected the family\u0026rsquo;s experience. If the family disagreed, they were prompted to enter more ABC data. Once the caregiver agreed with the hypothesis statement, a BSP was generated based on the agreed-upon function.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the second meeting prior to baseline sessions, the coach met with the caregiver for 45-60 min to review the BSP. Prior to reviewing the plan, the coach confirmed that the caregiver agreed with the hypothesized function. The coach then gave an overview of the prevent, teach, and new response to CB strategies provided in the BSP. This overview was a general orientation to the purpose of each strategy, and the coach did not train the caregiver on specific strategy implementation. Baseline observations commenced following the second meeting.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eBehavior Skills Training\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrior to the onset of intervention in each tier, the coach conducted a 20-30 min BST on the targeted strategy (i.e., prevent, teach, or new response). In each training, the coach gave a didactic review of the strategy and showed a video model of how the strategy could be used. Next, caregivers engaged in role play and discussed of how they would use the strategy in an example scenario. Lastly, caregivers generated their own example of a situation where this strategy would be helpful with their child and practiced how they would use it while the coach gave them feedback.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eObservations\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThroughout the study, approximately three weekly virtual observations were conducted during the target routine. Observations lasted 15 minutes and began when the caregiver signaled the onset of the routine. Across all observations, the coach was silent and did not interrupt the routine. During pre-baseline, baseline, generalization, and maintenance sessions, no feedback was provided to caregivers post session. After intervention sessions, however, observations alternated between two types:\u0026nbsp;focused observations, followed by a live debrief, and\u0026nbsp;supportive observations, followed by email feedback. This sequence continued until the caregiver demonstrated mastery of the targeted skill. Due to highly individualized routines that warranted idiosyncratic strategy usage, we did not use consistent criteria to determine caregiver mastery. During all observations, debriefs, and feedback, caregivers were consistently referred back to the app for guidance, with specific strategies and resources within the app highlighted to support their continued learning and implementation of target strategies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFocused observations\u003c/strong\u003e were designed to provide immediate and detailed feedback on caregiver performance. During these observations, the coach collected in-vivo, informal data (used solely to guide feedback) and identified areas for feedback. Focused observations were followed within 24 hr by a live debrief lasting an average of 18 min for Family 1 (range = 11\u0026ndash;29 min) and 14 min for Family 2 (range = 9\u0026ndash;16 min). During the debrief, the coach discussed the caregiver\u0026rsquo;s use of strategies, reviewed data the family entered in the app, and provided both constructive and supportive feedback related to the target tier\u0026rsquo;s strategies. Constructive feedback was designed to help caregivers refine their use of strategies by introducing changes to their current practices, while supportive feedback reinforced effective implementation of strategies already in use.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupportive observations\u003c/strong\u003e, by contrast, emphasized encouraging caregivers and maintaining momentum in the intervention process. Like focused observations, supportive observations involved informal data collection, but the subsequent feedback was delivered via email instead of a live debrief. These emails included: (a) positive affirmations, (b) 1\u0026ndash;3 supportive feedback statements with specific examples tied to the current or previous tier\u0026rsquo;s strategies, (c) broad connections to app-generated strategies, (d) reminders to enter data in the app, and (e) response prompts to engage caregivers further. By offering a mix of affirmations and constructive suggestions through different formats, focused and supportive observations worked together to guide caregivers toward mastery of the intervention strategies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAdaptations for Family 2\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe FBSApp generated \u0026ldquo;escape from demand\u0026rdquo; as the function of Zara\u0026rsquo;s CB. Traditionally, the function-based new response strategy for escape from a demand is to \u0026ldquo;prompt follow through\u0026rdquo; on the task, which the app-generated BSP indicated. Since the family identified mealtime as their focus, the coach adapted the new response strategy from \u0026ldquo;prompt follow through\u0026rdquo; to \u0026ldquo;ignore.\u0026rdquo; Empirical evidence suggests prompting follow through of eating new foods (i.e., escape extinction) is not ideal (Chazin et al., 2022) and was not preferable for this family. Subsequently, the family shared that since rates of CB were so low following intervention on only prevent strategies, they no longer felt the intensity of the intervention was needed and requested to end the study.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eFamily 1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFigure 1 depicts caregiver use of strategies across phases. While there were therapeutic changes in caregiver strategy use in the first and second tiers, we did not identify a functional relation since there was not a replication of effect in the third tier. As depicted in Figure 2, child use of replacement behaviors increased across intervention but was highly variable. There were statistically significant effect sizes calculated for CB and caregiver use of prevent strategies.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChallenging Behavior and New Response.\u0026nbsp;\u003c/strong\u003eWhile multiple functions were hypothesized for the child\u0026rsquo;s use of CB in Family 1, the first tier depicts only new response strategies in line with gain attention because we detected a ceiling effect for new response to escape demand (see Discussion). New response data for the escape demand function are available by request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDuring pre-baseline, CB was variable at low to moderate levels (\u003cem\u003erange\u0026nbsp;\u003c/em\u003e= 5\u0026ndash;14). Frequency of new response strategies was low in relation to the occurrence of CB (\u003cem\u003erange\u0026nbsp;\u003c/em\u003e= 1\u0026ndash;7). In baseline, CB was highly variable at low to moderate levels (\u003cem\u003erange =\u0026nbsp;\u003c/em\u003e0\u0026ndash;11) with an outlier at session 26 and a decreasing trend. New response strategies remained low in relation to CB, indicating the caregiver often responded to CB in a way that reinforced the behavior (\u003cem\u003erange =\u0026nbsp;\u003c/em\u003e0\u0026ndash;11). New response data were low and stable during the last three baseline sessions. During intervention, the CB data patterns indicate an extinction burst, as there are spikes in frequency (session 11 and 27) followed by decreases and gradual cessation (session 29). CB data were variable at overall lower levels than baseline (\u003cem\u003erange =\u0026nbsp;\u003c/em\u003e0\u0026ndash;14; \u003cem\u003eoutlier\u0026nbsp;\u003c/em\u003e= 20). The frequency of new response strategies increased in relation to instances of CB \u003cem\u003e(range =\u0026nbsp;\u003c/em\u003e0\u0026ndash;14). During maintenance, CB (\u003cem\u003erange =\u0026nbsp;\u003c/em\u003e2\u0026ndash;7) and new response (range = 0\u0026ndash;4) remained at levels similar to intervention. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe LRRd effect size estimate for CB was -0.68 (95% CI = [-1.45, -0.09]), which equates to a 50% decrease in CB from baseline to intervention (95% CI = [-77%, -10%]), and is statistically significant given that the confidence interval does not include zero. The LRRi effect size estimate for new response strategies was 0.43 (95% CI = [-0.12, 0.99]), equating to a 54% increase from baseline to intervention (95% CI = [-12%, 169%]), which is not statistically significant (i.e., the confidence interval includes zero).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevent Strategies\u003c/strong\u003e\u003cstrong\u003e.\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eDuring pre-baseline, the frequency of prevent strategies was low (\u003cem\u003erange =\u0026nbsp;\u003c/em\u003e3\u0026ndash;7). Prevent remained at low levels (\u003cem\u003erange =\u0026nbsp;\u003c/em\u003e1\u0026ndash;6) in baseline, with an outlier at session 11. Data were stable during the last three baseline sessions. Upon introduction of the intervention, prevent strategies increased immediately to 13 and were highly variable throughout intervention (\u003cem\u003erange =\u0026nbsp;\u003c/em\u003e2\u0026ndash;14) but at overall consistently higher levels compared to baseline. When support was faded, prevent maintained at high levels (\u003cem\u003erange =\u0026nbsp;\u003c/em\u003e11\u0026ndash;15).\u0026nbsp;The LRRi effect size estimate for prevent strategies was 0.91 (95% CI = [0.43, 1.4]). This equates to a 149% increase from baseline to intervention (95% CI = [53%, 306%]) and is statistically significant.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTeach Strategies.\u003c/strong\u003e Prompts for replacement behaviors remained at 0 across all sessions. Frequency of establishing statements was high during pre-baseline (\u003cem\u003erange\u0026nbsp;\u003c/em\u003e= 24\u0026ndash;30) and highly variable across baseline (\u003cem\u003erange\u0026nbsp;\u003c/em\u003e= 5\u0026ndash;32). Upon introduction of coach support, level of establishing statements decreased slightly to low to moderate levels but remained highly variable, with significant overlap with baseline (\u003cem\u003erange =\u0026nbsp;\u003c/em\u003e2\u0026ndash;16). During maintenance, frequency of establishing statements increased to moderate levels (\u003cem\u003erange =\u0026nbsp;\u003c/em\u003e9\u0026ndash;19).\u0026nbsp;The LRRi effect size estimate for teach strategies was 0.43 (95% CI = [-0.12, 0.99]), equating to a 54% increase from baseline to intervention (95% CI = [-12%, 169%]), and is not statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReplacement Behaviors.\u0026nbsp;\u003c/strong\u003eReplacement behaviors were low across pre-baseline and baseline conditions (\u003cem\u003erange\u0026nbsp;\u003c/em\u003e= 0\u0026ndash;1). Replacement behaviors remained low during intervention on new response strategies. Levels increased during intervention on prevent strategies, ranging from low to moderate levels (\u003cem\u003erange\u0026nbsp;\u003c/em\u003e= 0\u0026shy;\u0026ndash;4), and immediately decreased following intervention on teach strategies (\u003cem\u003erange =\u0026nbsp;\u003c/em\u003e0\u0026shy;\u0026ndash;1). Once coaching support was removed, replacement behaviors increased to low to moderate levels (\u003cem\u003erange\u0026nbsp;\u003c/em\u003e= 1\u0026ndash;4).\u0026nbsp;The LRRi effect size estimate for replacement behaviors was 0.65 (95% CI = [-0.61, 1.91]). This is equivalent to a 92% increase from baseline to intervention (95% CI = [-45%, 578%]) and is not statistically significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFamily 2\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData for Family 2 are displayed in Figure 3. We cannot identify a functional relation given there were not three potential demonstrations for replications of effect. However, there were positive changes in both caregiver and child behavior with coaching support on prevent strategies alone. Caregiver use of prevent strategies immediately increased. For child behaviors, engagement in non-preferred tasks increased in both intervention and generalization settings while task refusal and CB decreased.\u0026nbsp;There were statistically significant effect sizes calculated for caregiver use of prevent strategies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevent Strategies.\u0026nbsp;\u003c/strong\u003eCaregiver use of prevent strategies was at low to moderate levels in baseline (\u003cem\u003erange =\u0026nbsp;\u003c/em\u003e2\u0026ndash;10) with a decreasing trend. Upon introduction of coach support, levels increased immediately to 10 and were highly variable across intervention (range = 2\u0026ndash;23).\u0026nbsp;The LRRi effect size estimate for prevent strategies was statistically significant at 0.8 (95% CI = [0.1, 1.5]), which equates to a 123% increase from baseline to intervention (95% CI = [10%, 351%]).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEngagement in Non-preferred Task.\u0026nbsp;\u003c/strong\u003eDuring baseline, child engagement in non-preferred tasks in the intervention routine (i.e., eating non-preferred foods) was stable at low levels, with one outlier at session 22. Once coach support for prevent strategies was implemented, engagement in non-preferred tasks increased and was variable at high levels (\u003cem\u003erange =\u0026nbsp;\u003c/em\u003e18\u0026shy;\u0026ndash;40) with one outlier at zero. The LRRi effect size estimate was 1.4 (95% CI = [-0.3, 3.1]), equating to a 306% increase from baseline to intervention (95% CI = [-26%, 2135%]).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTask Refusal.\u003c/strong\u003e In baseline, vocal task refusal was variable (\u003cem\u003erange\u0026nbsp;\u003c/em\u003e= 2\u0026shy;\u0026ndash;14). In the first session of intervention, data immediately increased to 13, then decreased and stabilized at near-zero levels in the final sessions. The LRRd effect size estimate was -0.25 (95% CI = [-1.55, 1.04]), equal to a 22% decrease from baseline to intervention (95% CI = [-79%, 183]).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCB.\u0026nbsp;\u003c/strong\u003eDuring baseline, CB was low (\u003cem\u003erange\u0026nbsp;\u003c/em\u003e= 2-6) with one outlier at session 17. In the first intervention session, CB increased to 9, then immediately decreased to 0 and stabilized at low levels for the remaining intervention sessions.\u0026nbsp;The LRRd effect size estimate was -0.71 (95% CI = -2.46, 1.04]), equating to a 51% decrease from baseline to intervention (95% CI = [-91%, 184%]).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIOA and Procedural Fidelity\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIOA by family, condition, and variable is displayed in Table 4. IOA was collected for 39% of sessions for Family 1 and 38% of sessions for Family 2, with a range of 33\u0026ndash;50% across conditions for each family. Mean agreement across variables and conditions was 75% for Family 1 (\u003cem\u003erange\u003c/em\u003e = 13\u0026shy;\u0026ndash;100), and 81% for Family 2 (\u003cem\u003erange\u003c/em\u003e = 23\u0026ndash;100).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eProcedural fidelity (PF) data were collected for 100% of sessions across coaching trainings, components, conditions, and participants via checklist using session video recordings. Initial coach training by the supervisors was implemented with 100% fidelity. Coaching fidelity data were collected by a masked observer research assistant for 100% of initial and BST meetings; coaching supervisors collected PF on focused and supportive observations and their subsequent debriefs (live or via email). If fidelity in any coaching component fell below 90%, the supervisor provided email feedback on the elements missed. This happened nine times during coaching for Family 1 and three times during coaching for Family 2. If fidelity fell below 80% for any component, the supervisor\u0026nbsp;scheduled a virtual meeting with the coach for a discussion, modeling, or role-play. This happened twice for the Family 1 coach and once for the Family 2 coach.\u0026nbsp;Mean fidelity was 94% across initial meetings and BST (\u003cem\u003erange\u003c/em\u003e = 81\u0026ndash;100). Mean fidelity across conditions and components ranged from 72% to 100% for Family 1, and 85% to 100% for Family 2. PF agreement data were collected for 100% of sessions across components, conditions, and participants; agreement was 98% for Family 1 (\u003cem\u003erange\u003c/em\u003e = 89\u0026shy;\u0026ndash;100) and 97% for Family 2 (\u003cem\u003erange\u003c/em\u003e = 91\u0026ndash;100). Fidelity by component, participant, and condition is displayed in Table 4.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u0026nbsp;\u003c/strong\u003e\u003cem\u003eInterobserver Agreement (IOA) and Procedural Fidelity (PF) by Condition for Each Family\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"864\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"16\" valign=\"bottom\" style=\"width: 864px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily 1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" style=\"width: 498px;\"\u003e\n \u003cp\u003eIOA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 366px;\"\u003e\n \u003cp\u003ePF\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 72px;\"\u003e\n \u003cp\u003eCB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 84px;\"\u003e\n \u003cp\u003eNew Response\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 78px;\"\u003e\n \u003cp\u003ePrevent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003eEO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 63px;\"\u003e\n \u003cp\u003ePrompt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eRB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eInitial meetings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003eBST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003eFO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003eDebrief\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003eSO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003ePB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 72px;\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 84px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 78px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 63px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003cp\u003e(94-100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 72px;\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003cp\u003e(70\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 84px;\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003cp\u003e(96\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 78px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003cp\u003e(14\u0026ndash;71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003cp\u003e(66-69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 63px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003cp\u003e(0\u0026ndash;25)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eInt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 72px;\"\u003e\n \u003cp\u003e77\u003c/p\u003e\n \u003cp\u003e(50\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 84px;\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003cp\u003e(88\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 78px;\"\u003e\n \u003cp\u003e68\u003c/p\u003e\n \u003cp\u003e(33\u0026shy;\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003cp\u003e(25\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 63px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e56\u003c/p\u003e\n \u003cp\u003e(0\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003cp\u003e(84\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003cp\u003e(90\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e87\u003c/p\u003e\n \u003cp\u003e(40\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eMaint\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 72px;\"\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 84px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 78px;\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 63px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003eGen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 72px;\"\u003e\n \u003cp\u003e60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 84px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 78px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 72px;\"\u003e\n \u003cp\u003e75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 63px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003cp\u003e(92\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"16\" style=\"width: 864px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamily 2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" style=\"width: 498px;\"\u003e\n \u003cp\u003eIOA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 366px;\"\u003e\n \u003cp\u003ePF\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 80px;\"\u003e\n \u003cp\u003eCB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 102px;\"\u003e\n \u003cp\u003eTask refusal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 138px;\"\u003e\n \u003cp\u003eEngagement in\u003c/p\u003e\n \u003cp\u003enon-preferred task\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 78px;\"\u003e\n \u003cp\u003ePrevent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eInitial meetings\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003eBST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003eFO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003eDebrief\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003eSO\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 100px;\"\u003e\n \u003cp\u003ePB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 80px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 102px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 138px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 78px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003cp\u003e(82\u0026ndash;96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003cp\u003e(92\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 100px;\"\u003e\n \u003cp\u003eBaseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 80px;\"\u003e\n \u003cp\u003e23\u003c/p\u003e\n \u003cp\u003e(13-33)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 102px;\"\u003e\n \u003cp\u003e\u0026nbsp;75\u003c/p\u003e\n \u003cp\u003e(50\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 138px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 78px;\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003cp\u003e(81\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 100px;\"\u003e\n \u003cp\u003eInt\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 80px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 102px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 138px;\"\u003e\n \u003cp\u003e78\u003c/p\u003e\n \u003cp\u003e(77\u0026ndash;79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 78px;\"\u003e\n \u003cp\u003e61\u003c/p\u003e\n \u003cp\u003e(50\u0026ndash;71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003cp\u003e(60\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003cp\u003e(92\u0026ndash;100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 100px;\"\u003e\n \u003cp\u003eMaint\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 80px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 102px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 138px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 78px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 100px;\"\u003e\n \u003cp\u003eGen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 80px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 102px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 138px;\"\u003e\n \u003cp\u003e73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 78px;\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e--\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 74px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote. PB = pre-baseline; Int = intervention; Maint = maintenance; Gen = generalization; CB = challenging behavior; EO = establishing operation; RB = replacement behavior; BST = Behavior Skills Training; FO = focused observation; SO = supportive observation. Maintenance was not conducted for Family 2.\u003c/p\u003e\n\u003cp\u003e* Coder retraining occurred due to low interobserver agreement.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe examined the effects of the FBSApp on caregiver use of targeted intervention strategies at home with their young children with disabilities or delays and CBs. Though we did not identify functional relations, our study is meaningful given the use of a rigorous single case research design and the presence of interesting, idiosyncratic results. These findings highlight the importance of individualized approaches, emphasizing that personalized intervention strategies may yield variable yet valuable outcomes. Furthermore, the results contribute to the broader discourse on tailoring interventions to meet the unique needs of children and families, underscoring the complexity of caregiver-implemented practices in diverse home settings. Although we did not identify functional relations, our results are promising, meaningful, and support previous findings (Barton et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eWe employed a single-case research design and observed interesting, albeit idiosyncratic, results. Our rigorous single-case design allowed us to delve deeply into the specific context and nuances of individual cases, providing rich, detailed data that offer valuable insights despite the absence of clear functional relations. Research contributions should be based on their methodological rigor rather than the presence or magnitude of behavior change (Cook \u0026amp; Therrien, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Our idiosyncratic results highlight the unique ways different variables may interact in real-world settings, crucial for understanding the complex nature of early childhood special education. Four primary contributions and implications for research are discussed below.\u003c/p\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003eIndividual Differences Across Families\u003c/h2\u003e\u003cp\u003eImportantly, each caregiver/family responded to the FBSApp in different ways, which has been observed in previous research within (Moes \u0026amp; Frea, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) and across studies (Fettig \u0026amp; Barton, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). For example, Family 2 experienced immediate effects across all behaviors with just preventive strategies. This suggests that universal, prevention-focused strategies may be sufficient for families with children exhibiting low-intensity CB. More intensive BSPs and coaching might not be necessary for all children or families, a critical consideration given the limited resources available to families at home across many communities. We used these data to restructure the FBSApp so families could access universal strategies immediately. Additionally, we observed promising changes in generalization data for Family 1, although the data are insufficient for experimental conclusions. Our data suggest that caregivers and children may generalize skills learned during the intervention routine to novel routines or settings. Future research should evaluate generalization to untrained settings. There is a dearth of research examining generalization by families across routines or strategies (Fettig \u0026amp; Barton, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Family 1 also experienced multiple history events (e.g., exposure to COVID and multiple quarantines, moving during tier 2, a medication change during tier 3, and the father's return from imprisonment during tier 3) without corresponding shifts in their data. This supports the usability of the FBSApp in carefully considering family strengths and resources within their historical and immediate contexts (Charis, Fettig, \u0026amp; Zimmerman, 2023).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec25\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design\u003c/h2\u003e\u003cp\u003eAlthough we used a rigorous single-case research design, the relation between variables was not perfectly independent, as is recommended for time-lagged designs. These are important methodological implications for future research. For example, other designs might be more appropriate. Future researchers should use different designs to validate coaching approaches within and across families given the dynamic and idiosyncratic needs of families. For example, we presented demands and removed attention, which can evoke CB for some children. We hypothesize that the decrease in establishing statements coincides with an increase in effort allocated to other strategies, corresponding with an increase in CB as establishing statements were no longer evoking CB. This will impact data patterns and might not be observable within time-lagged designs.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section2\"\u003e\u003ch2\u003eEffect Sizes\u003c/h2\u003e\u003cp\u003eWe calculated effect sizes to provide a complete picture of intervention effects. However, these should be interpreted with caution and in conjunction with visual analysis (Maggin et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Large confidence intervals indicate substantial variability within and across conditions. This is confirmed with visual analysis and is particularly true for Family 2, who had fewer data points and significant variability (especially in child behaviors). Overall, the individual differences noted across families support the use of individualized instructional adaptations when supporting family implementation of targeted intervention strategies. Our idiosyncratic findings are important and should not be discounted given the lack of functional relations. Publishing rigorous studies with complex or non-effects is crucial for developing a comprehensive understanding of evidence-based practices and preventing inflation of effect sizes in reviews and meta-analyses (Travers et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Our findings demonstrated that the FBSApp plus coaching was effective for some strategies across families, which might be important for guiding special education research, policy, and practice (Cook \u0026amp; Therrien, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section2\"\u003e\u003ch2\u003eTechnology-Based Interventions\u003c/h2\u003e\u003cp\u003eRecent studies have increasingly focused on leveraging mobile apps and other digital tools to support families and caregivers in implementing intervention strategies. Research indicates that these tools can provide accessible, cost-effective solutions that offer flexibility for families (Khetani et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Meadan \u0026amp; Daczewitz, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The use of real-time data collection and feedback mechanisms within these apps enhances their effectiveness (Barton et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) and allows interventions to be tailored to fit the unique needs and contexts of each family (Dunst et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), which is further supported by the current study. Accessible, technology-based interventions like the FBSApp might address service and support disparities faced by families from diverse racial, ethnic, and socioeconomic backgrounds (Guralnick, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Meadan \u0026amp; Daczewitz, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The COVID-19 pandemic has profoundly impacted early childhood education, highlighting the need for flexible, remote, and hybrid intervention models. Recent studies have explored the challenges and opportunities presented by the pandemic, underscoring the importance of developing resilient and adaptable support systems for families, such as the FBSApp (Cahill et al., 2021).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eThere are several important limitations to note. First, while Zoom allows for virtual support, it was not always convenient for families. Issues with zoom might have impacted our ability to build rapport with families, which should be examined in future research. Second, we decided to intervene for Family 1 despite decreasing trends in child CB, given the undesirable effects of extended baseline conditions.\u003c/p\u003e\u003cp\u003eThird, as expected, IOA was lower for variables that were free operant and required more inference-based decisions (e.g., prevent, teach, CB, and replacement behaviors; Yoder et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Free operant behaviors, which occur at any time and are not tied to specific antecedents or discrete responses, inherently introduce more opportunities for discrepancies between observers. This is particularly true when the behavior requires subjective judgment or when contextual factors are not explicitly observable, increasing the likelihood of differences in coding decisions (Kazdin, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Additionally, IOA was lower for low-rate behaviors, consistent with existing research showing that behaviors occurring infrequently present challenges for agreement due to their rarity and increased susceptibility to random error (Ledford \u0026amp; Gast, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). For example, a single discrepancy in coding a low-frequency behavior (e.g., observing one versus zero instances) can result in significant reductions in percentage agreement, as demonstrated in session 6 for Family 1: the primary coder recorded one instance of replacement behavior, while the secondary coder recorded none, resulting in 0% agreement. Such differences may disproportionately affect reliability metrics for low-rate behaviors compared to high-frequency behaviors, where single discrepancies have a smaller relative impact. To address these challenges, we graphed primary and secondary data on the same graph, allowing us to observe important differences across observers that were not readily captured by percentages of agreement alone (e.g., discrepancies in coding replacement behaviors). This method provides greater transparency and granularity in data interpretation, supplementing numeric IOA values with a visual representation of observer differences. Graphs displaying primary and secondary data are available via OpenScience Framework, supporting further exploration and replication of these findings.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eCBs are a major stressor for families and impact their quality of life. However, access to home-based supports is often difficult for families. We examined the use of a mobile technology\u0026mdash;the FBSApp\u0026mdash;that has strong potential to support families in using strategies that reduce their child\u0026rsquo;s CB and might be more accessible and efficient than other in person supports. Although we had idiosyncratic results and no functional relations, our data are promising. Our findings underscore the importance of individualized approaches and contribute to the broader discourse on individual intervention strategies that are family-centered and consider historical and immediate contexts. The rigor of our methodology ensures that our results are robust and reliable, providing a solid foundation for future research and potential replication studies. Overall, our study adds depth to the field by illustrating the complexity and individuality of educational experiences and interventions. Future research is needed to continue examining efficient ways to support families, including the use of the FBSApp and other mobile technologies (Buzhardt, \u0026amp; Meadan, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors participated in the research, wrote sections of the manuscript, and reviewed the final manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAdditional details regarding the participants, coding, and coaching procedures can be found on OpenScienceFramework (https://doi.org/10.17605/OSF.10/XK3GA).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAkemoglu, Y., Muharib, R., \u0026amp; Meadan, H. (2020). A systematic and quality review of parent-implemented language and communication interventions conducted via telepractice. \u003cem\u003eJournal of Behavioral Education\u003c/em\u003e, \u003cem\u003e29\u003c/em\u003e, 282-316.\u003c/li\u003e\n\u003cli\u003eAuthors. (2024). Xxxx. \u003cem\u003eManuscript under review. \u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eAuthors. (2024). Xxxx. \u003cem\u003eManuscript under review. \u003c/em\u003e\u003c/li\u003e\n\u003cli\u003eBarton, E. E. (2022). Family Behavior Support App (version 1.0.1) [Mobile app]. App Store. https://apps.apple.com/us/app/family-behavior-support-app/id1598406686 \u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eBarton, E. E., Reichow, B., Wolery, M., \u0026amp; Chen, C. (2020).\u003c/strong\u003e Technology-aided instruction and intervention for students with ASD: A meta-analysis. \u003cem\u003eJournal of Autism and Developmental Disorders, 50\u003c/em\u003e(1), 176-191. doi:10.1007/s10803-019-04260-8\u003c/li\u003e\n\u003cli\u003eBarton, E. E., Winchester, C., Velez, M. S., Todt, M., Locchetta, B. M., \u0026amp; Skiba, E. (2024). Field Testing the Family Behavior Support Mobile Application (FBSApp) During a Global Pandemic. \u003cem\u003eJournal of Autism and Developmental Disorders\u003c/em\u003e. https://doi.org/10.1007/s10803-024-06373-8 \u003c/li\u003e\n\u003cli\u003eBromley, J., Hare, D. J., Davison, K., \u0026amp; Emerson, E. (2004). Mothers supporting children with ASD: Social support, mental health status and satisfaction with services. \u003cem\u003eAutism: The International Journal of Research and Practice\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(4), 409\u0026ndash;423. \u003c/li\u003e\n\u003cli\u003eBuzhardt, J., \u0026amp; Meadan, H. (2022). Introduction to the special issue: A new era for remote early intervention and assessment. \u003cem\u003eJournal of Early Intervention\u003c/em\u003e, \u003cem\u003e44\u003c/em\u003e(2), 103-109.\u003c/li\u003e\n\u003cli\u003e\u0026Ccedil;elik, S., Tomris, G., \u0026amp; Tuna, D. M. (2022). The COVID-19 pandemic: Evaluation of the emergency remote parent training program based on at-home support for children with down syndrome. \u003cem\u003eChildren and Youth Services Review, 133, \u003c/em\u003e106325.\u003c/li\u003e\n\u003cli\u003eCook, B. G., \u0026amp; Therrien, W. J. (2017). Null effects and publication bias in special education research. \u003cem\u003eBehavioral Disorders\u003c/em\u003e, \u003cem\u003e42\u003c/em\u003e(4), 149-158.\u003c/li\u003e\n\u003cli\u003eChazin, K. T., Velez, M. S., \u0026amp; Ledford, J. R. (2022). Reducing escape without escape extinction: a systematic review and meta-analysis of escape-based interventions. \u003cem\u003eJournal of Behavioral Education, 31\u003c/em\u003e, 186-215.\u003c/li\u003e\n\u003cli\u003eDivision for Early Childhood. (2014). \u003cem\u003eDEC recommended practices in early intervention/early childhood special education 2014\u003c/em\u003e. http://ww.dec-sped.org/recommendedpractices\u003c/li\u003e\n\u003cli\u003eDoubet, S. L., \u0026amp; Ostrosky, M. M. (2015). The impact of challenging behavior on families: I don\u0026rsquo;t know what to do. \u003cem\u003eTopics in Early Childhood Special Education\u003c/em\u003e, \u003cem\u003e34\u003c/em\u003e(4), 223\u0026ndash;233. \u003c/li\u003e\n\u003cli\u003eDouglas, S. N., Kammes, R., \u0026amp; Nordquist, E. (2018). Online communication training for parents of children with autism spectrum disorder. \u003cem\u003eCommunication Disorders Quarterly\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(3), 415-425.\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eDunst, C. J., Trivette, C. M., \u0026amp; Hamby, D. W. (2019).\u003c/strong\u003e Meta-analysis of family-centered helpgiving practices research. \u003cem\u003eMental Retardation and Developmental Disabilities Research Reviews, 12\u003c/em\u003e(2), 110-119. doi:10.1002/mrdd.20120\u003c/li\u003e\n\u003cli\u003eFettig, A., \u0026amp; Barton, E. E. (2014). Functional assessment-based parent intervention to reduce children\u0026rsquo;s challenging behaviors: A literature review. \u003cem\u003eTopics in Early Childhood Special Education, 34\u003c/em\u003e, 49-61.\u003c/li\u003e\n\u003cli\u003eFixsen, D. L., Naoom, S. F., Blase, K. A., Friedman, R. M., \u0026amp; Wallace, F. (2005). \u003cem\u003eImplementation research: A synthesis of the literature\u003c/em\u003e. University of South Florida, Louis de la Parte Florida Mental Health Institute, National Implementation Research Network.\u003c/li\u003e\n\u003cli\u003eFox, L., Vaughn, B. J., Dunlap, G., \u0026amp; Bucy, M. (1997). Parent-professional partnership in behavioral support: a qualitative analysis of one family\u0026rsquo;s experience. \u003cem\u003eJournal of the Association for Persons with Severe Handicaps\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(4), 198\u0026ndash;207. \u003c/li\u003e\n\u003cli\u003eFrey, A. J., Small, J. W., Feil, E. G., Seeley, J. R., Walker, H. M., \u0026amp; Forness, S. (2015). First step to success: applications to preschoolers at risk. \u003cem\u003eEducation and Training in Autism and Developmental Disabilities\u003c/em\u003e, \u003cem\u003e50\u003c/em\u003e(4), 397\u0026ndash;407. \u003c/li\u003e\n\u003cli\u003eGast, D. L., Lloyd, B. P., \u0026amp; Ledford, J. R. (2018). Multiple baseline and multiple probe designs. In Ledford, J. R., \u0026amp; Gast, D. L. (Eds). \u003cem\u003eSingle case research methodology: Applications in special education and behavioral sciences\u003c/em\u003e (pp. 239-281). Routledge.\u003c/li\u003e\n\u003cli\u003eGerow, S., Hagan-Burke, S., Rispoli, M., Gregori, E., Mason, R., \u0026amp; Ninci, J. (2018). A review of parent-implemented functional communication training for children with ASD. \u003cem\u003eBehavior Modification\u003c/em\u003e, \u003cem\u003e42\u003c/em\u003e(3), 335-363. \u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eGuralnick, M. J. (2020).\u003c/strong\u003e Early intervention approaches to enhance the peer-related social competence of young children with developmental delays: A historical perspective. \u003cem\u003eInfants \u0026amp; Young Children, 33\u003c/em\u003e(4), 268-284. doi:10.1097/IYC.0000000000000169\u003c/li\u003e\n\u003cli\u003eHarbin, S. G., Choi, G., \u0026amp; Fettig, A. (2024). Reconceptualizing Family-Centered Partnerships in Parent-Implemented Interventions. \u003cem\u003eInfants \u0026amp; Young Children\u003c/em\u003e, \u003cem\u003e37\u003c/em\u003e(3), 256-269.\u003c/li\u003e\n\u003cli\u003eJoachim, S., Sanders, M. R., \u0026amp; Turner, K. M. T. (2010). Reducing preschoolers\u0026rsquo; disruptive behavior in public with a brief parent discussion group. \u003cem\u003eChild Psychiatry and Human Development\u003c/em\u003e, \u003cem\u003e41\u003c/em\u003e(1), 47\u0026ndash;60. \u003c/li\u003e\n\u003cli\u003eKasprzak, C., Hurth, J., Rooney, R., Goode, S. E., Danaher, J. C., Whaley, K. T., Ringwalt, S. S., \u0026amp; Cate, D. (2012). States\u0026rsquo; accountability and progress in serving young children with disabilities. \u003cem\u003eTopics in Early Childhood Special Education, 32\u003c/em\u003e, 151-163. \u003c/li\u003e\n\u003cli\u003eKazdin, A. E. (2011). \u003cem\u003eSingle-case research designs: Methods for clinical and applied settings\u003c/em\u003e (2nd ed.). New York, NY: Oxford University Press.\u003c/li\u003e\n\u003cli\u003eKhetani, M. A., McManus, B. M., Arestad, K., Richardson, Z., Charlifue-Smith, R., Rosenberg, C., \u0026amp; Rigau, B. (2018). Technology-based functional assessment in early childhood intervention: a pilot study. \u003cem\u003ePilot and Feasibility Studies\u003c/em\u003e, \u003cem\u003e4\u003c/em\u003e, 1-9.\u003c/li\u003e\n\u003cli\u003eLedford, J. R., Lane, J. D., \u0026amp; Gast, D. L. (2018). Dependent variables, measurement, and reliability. In Ledford, J. R., \u0026amp; Gast, D. L. (Eds), \u003cem\u003eSingle Case Research Methodology: Applications in Special Education and Behavioral Sciences. \u003c/em\u003e(pp. 97\u0026ndash;131). Routledge.\u003c/li\u003e\n\u003cli\u003eLedford, J. R., \u0026amp; Gast, D. L. (2018). \u003cem\u003eSingle case research methodology: Applications in special education and behavioral sciences\u003c/em\u003e (3rd ed.). Routledge.\u003c/li\u003e\n\u003cli\u003eLucyshyn, J. M., Albin, R. W., Horner, R. H., Mann, J. C., Mann, J. A., \u0026amp; Wadsworth, G. (2007). Family implementation of positive behavior support for a child with autism: longitudinal, single-case, experimental, and descriptive replication. \u003cem\u003eJournal of Positive Behavior Interventions\u003c/em\u003e, \u003cem\u003e9\u003c/em\u003e(3), 131\u0026ndash;150. \u003c/li\u003e\n\u003cli\u003eMaggin, D. M., Cook, B. G., \u0026amp; Cook, L. (2019). Making sense of single-case design effect sizes. \u003cem\u003eLearning Disabilities Research \u0026amp; Practice, 34\u003c/em\u003e(3), 124-132. \u003c/li\u003e\n\u003cli\u003eMcDevitt, S. E. (2022). While quarantined: An online parent education and training model for families of children with autism in China. \u003cem\u003eResearch in Developmental Disabilities. \u003c/em\u003ehttps://doi.org/10.1016/j.ridd.2020.103851 \u003c/li\u003e\n\u003cli\u003eMeadan, H., \u0026amp; Daczewitz, M. E. (2015). Internet-based intervention training for parents of young children with disabilities: A promising service-delivery model. \u003cem\u003eEarly child development and care\u003c/em\u003e, \u003cem\u003e185\u003c/em\u003e(1), 155-169.\u003c/li\u003e\n\u003cli\u003eMeadan, H., Meyer, L. E., Snodgrass, M. R., \u0026amp; Halle, J. W. (2013). Coaching parents of young children with autism in rural areas using internet-based technologies. \u003cem\u003eRural Special Education Quarterly, 32\u003c/em\u003e(3), 3-10.\u003c/li\u003e\n\u003cli\u003eMeadan, H., Snodgrass, M. R., Meyer, L. E., Fisher, K. W., Chung, M. Y., \u0026amp; Halle, J. W. (2016). Internet-based parent-implemented intervention for young children with autism. \u003cem\u003eJournal of Early Intervention\u003c/em\u003e, \u003cem\u003e38\u003c/em\u003e(1), 3-23. \u003c/li\u003e\n\u003cli\u003eMiltenberger, R. G. (2012). Behavior skills training procedures. In R. G. Miltenberger (Ed.), \u003cem\u003eBehavior Modification: Principles and Procedures\u003c/em\u003e (pp.217-235). Wadsworth Publishing.\u003c/li\u003e\n\u003cli\u003eMoes, D. R., \u0026amp; Frea, W. D. (2002). Contextualized behavioral support in early intervention for children with autism and their families. \u003cem\u003eJournal of Autism and Developmental Disorders\u003c/em\u003e, \u003cem\u003e32\u003c/em\u003e(6), 519-533.\u003c/li\u003e\n\u003cli\u003ePeters, S. Z., Brumbaugh, K. M., \u0026amp; Blackwell, A. (2023). The Effects of Virtual Caregiver Coaching in Antigua \u0026amp; Barbuda on the Implementation of EMT Language Support Strategies in Naturalistic Environments. \u003cem\u003eInternational Journal of Telerehabilitation\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(2), 1-14. doi: 10.5195/ijt.2023.6586\u003c/li\u003e\n\u003cli\u003ePustejovsky, J. E. (2018). Using response ratios for meta-analyzing single-case designs with behavioral outcomes. \u003cem\u003eJournal of School Psychology, 68,\u003c/em\u003e 99-112. \u003c/li\u003e\n\u003cli\u003ePustejovsky, J. E, Chen, M., \u0026amp; Swan, D. M. (2022). Single-case effect size calculator (Version 0.6.1). [Web application]. https://jepusto.shinyapps.io/SCD-effect-sizes/\u003c/li\u003e\n\u003cli\u003eSmith, B. J., \u0026amp; Fox, L. (2003). \u003cem\u003eSystems of Service Delivery: A Synthesis of Evidence Relevant to Young Children at Risk of or Who Have Challenging Behavior.\u003c/em\u003e University of South Florida Center for Evidence-Based Practice: Young Children with Challenging Behavior. \u003c/li\u003e\n\u003cli\u003eSquires, J., Bricker, D., \u0026amp; Twombly, E. (2015). \u003cem\u003eAges \u0026amp; Stages Questionnaires\u0026reg;: Social \u003c/em\u003e\u003cem\u003eEmotional, Second Edition (ASQ\u0026reg;:SE-2): A parent-completed child monitoring system for social-emotional behaviors.\u003c/em\u003e Brookes Publishing Co.\u003c/li\u003e\n\u003cli\u003eTapp, J. (2003). \u003cem\u003eProcoderDV.\u003c/em\u003e Vanderbilt Kennedy Center.\u003c/li\u003e\n\u003cli\u003eTravers, J. C., Cook, B. G., Therrien, W. J., \u0026amp; Coyne, M. D. (2016). Replication research and special education. \u003cem\u003eRemedial and Special Education\u003c/em\u003e, \u003cem\u003e37\u003c/em\u003e(4), 195-204.\u003c/li\u003e\n\u003cli\u003eU.S. Department of Commerce, Census Bureau. (2020, February). American Community Survey (ACS), 2018. \u003c/li\u003e\n\u003cli\u003eWahman, C. L., Fettig, A., \u0026amp; Zimmerman, K. (2023). Social and emotional intervention research as justice: A case for accountability. \u003cem\u003eRemedial and Special Education\u003c/em\u003e, \u003cem\u003e44\u003c/em\u003e(5), 423-438.\u003c/li\u003e\n\u003cli\u003eYoder, P. J., Lloyd, B. P., \u0026amp; Symons, F. J. (2018). \u003cem\u003eObservational Measurement of Behavior.\u003c/em\u003e Brookes Publishing Co.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-6940507/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6940507/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"We tested the Family Behavior Support application (FBSApp), a mobile app designed to support caregivers in their use of functional assessment-based intervention strategies to address their children’s challenging behaviors at home and support healthy social-emotional development. Two caregiver/child dyads participated in a single-case multiple baseline across behaviors (i.e., strategies) design. We used systematic, ongoing coaching via telehealth to support caregivers’ use of app-recommended intervention strategies in the context of a targeted home routine. Intervention resulted in increases in caregiver’s use of prevent and new response strategies, increases in child use of replacement behaviors, and decreases in child challenging behaviors. Functional relations were not identified due to a lack of change in one (i.e., Teach strategies) of three tiers for Family 1, and lack of sufficient experimental control due to withdrawal during the first tier for Family 2. Though we did not identify functional relations, our study is meaningful given we used a rigorous single case research design and had interesting, idiosyncratic results. These findings underscore the importance of individualized approaches and contribute to the broader discourse on personalized intervention strategies. Future research is needed to continue to examine efficient ways to support families in virtual settings.","manuscriptTitle":"The Effects of the Family Behavior Support Application (FBSApp) with Virtual, Strategy-Based Coaching on Caregiver and Child Behaviors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-05 12:25:24","doi":"10.21203/rs.3.rs-6940507/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"461f0ea5-796b-4bbf-9887-559d27550f7a","owner":[],"postedDate":"August 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-28T18:53:09+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-05 12:25:24","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6940507","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6940507","identity":"rs-6940507","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}