Coaching via Telehealth: Caregiver-mediated Interventions for Young Children on the Waitlist for an Autism Diagnosis

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dc.contributor.advisorMachalicek, Wendy
dc.contributor.authorKunze, Megan
dc.date.accessioned2020-12-08T15:45:42Z
dc.date.available2020-12-08T15:45:42Z
dc.date.issued2020-12-08
dc.description.abstractThe average age for an autism diagnosis in the U.S. is 4-years-old (Hine et al., 2018), which is devastatingly late as caregivers often report initial concerns in their child’s development around 12-months-old and reliable autism diagnosis can be made by 18-months (Pierce et al., 2019). For children from under-resourced families in rural communities, the age of diagnosis is even later, around 5-years-old (Martinez et al., 2018). Early diagnosis of ASD provides toddlers access to medically necessary interventions beyond federally funded early intervention (Individuals with Disabilities Education Act, Part C, 2004) during a vital window of developmental opportunity (Warren et al., 2011). Late diagnosis often leads to under-served families despite economic status or geographic location. This study targeted ASD symptomology (i.e., higher-order restrictive and repetitive behaviors and interests; HO-RRBIs) in toddlers by pairing caregivers with an early interventionist via telehealth. Six mother-child dyads (four girls and two boys) whose child was (a) between 18 and 36-months-old, (b) demonstrated difficult levels of inflexible behaviors (i.e., HO- RRBIs), and (c) were on an ASD diagnostic waitlist were recruited from pediatrician offices and service districts throughout the Pacific Northwest and Texas. All families were considered under-served, under-resourced, or living in rural locations. In a concurrent multiple baseline design across participants, caregivers were coached to mediate early intervention to decrease inflexible and increase flexible child behaviors during play sessions through the use of four evidence-based applied behavior analytic strategies: modeling, prompting, differential reinforcement of appropriate behaviors, and response interruption and redirection. A visual analysis of the data combined with Tau-U revealed a strong basic effect between the intervention package and parent strategy use and child flexible and inflexible behavior. These findings were consistent except for one child participant whose results were a medium effect for flexible behaviors, yet a strong effect for inflexible behaviors. Standardized mean difference was beyond zero for all participants. All mothers rated their participation in the study as favorable. Results of distal and non-experimental outcomes are addressed. Implications for science and practice in early intervention for families whose children are at-risk for ASD are discussed.en_US
dc.identifier.urihttps://hdl.handle.net/1794/25887
dc.language.isoen_US
dc.publisherUniversity of Oregon
dc.rightsAll Rights Reserved.
dc.subjectapplied behavior analysisen_US
dc.subjectautism risken_US
dc.subjectearly intervnetionen_US
dc.subjectparent-mediated interventionen_US
dc.subjectrestricted and repetitive behaviorsen_US
dc.subjecttelehealthen_US
dc.titleCoaching via Telehealth: Caregiver-mediated Interventions for Young Children on the Waitlist for an Autism Diagnosis
dc.typeElectronic Thesis or Dissertation
thesis.degree.disciplineDepartment of Special Education and Clinical Sciences
thesis.degree.grantorUniversity of Oregon
thesis.degree.leveldoctoral
thesis.degree.namePh.D.

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