Using Evidence-Based Practice in the Transition to Telepractice: Case Study of a Complexity-Based Speech Sound Intervention

Abstract

Purpose:

Speech-language pathologists (SLPs) are tasked with integrating the principles of evidence-based practice (EBP) to provide effective and efficient assessment and intervention services that best support clients and their families. As new research, technologies, and perspectives emerge, SLPs are required to adapt their clinical practices to meet these changes while maintaining high-quality evidence-based services. Through an illustrative case study, we aim to demonstrate the process of applying EBP principles – including research evidence, client and family perspectives, and clinical expertise – to a complexity-based speech sound intervention delivered via telepractice.

Conclusion:

Results of the case study suggest that utilizing the principles of EBP to transition an evidence-based complexity intervention to telepractice was successful. Additionally, the EBP framework provided opportunities for reflection and continued adaptation throughout the intervention. The process of applying an EBP framework to a quickly evolving clinical practice environment provides SLPs with essential tools that ensure their services meet the needs of the clients they serve.

Introduction

The field of speech-language pathology, along with many other health service professions, undergoes constant evolution in the wake of new technologies and research that continuously change our definitions of ‘best’ practice (Campbell & Goldstein 2022). The framework of evidence-based practice (EBP) involves the application of three distinct principles: research evidence, client and family perspectives, and clinical expertise. Within the EBP model, a practicing clinician integrates information from diverse sources, including external evidence, internal evidence, and evidence from client perspectives (Dollaghan, 2007). External evidence refers to the research evidence from scientific literature. Internal evidence is derived from clinical expertise and the data that speech-language pathologists (SLPs) collect and analyze throughout assessment and treatment. Client preferences are the individual values, perspectives, and priorities of individual clients and their family. As new research, technology, and perspectives emerge, EBP provides a structured, comprehensive method of collecting and assessing existing evidence that results in an informed clinical decision designed to best serve an individual client’s support needs (Gillam & Gillam, 2006). Ultimately, use of the EBP framework to integrate these dynamic sources of evidence has the potential to provide new opportunities for providing speech and language services.

Telepractice has been considered a viable delivery method for speech and language assessment and intervention for some time (McCullough, 2010), yet its use was not widespread among SLPs in private practice and public-school settings until the implementation of social distancing practices at the beginning of the COVID-19 pandemic (Hao et al., 2021). Available research has documented that telepractice is an effective service delivery model for speech-language pathology in many ways, including reliability of assessment measures (Manning et al., 2020; Raman et al., 2019; Sutherland et al., 2019), cost effectiveness (Little et al., 2018), and high caregiver engagement and motivation (Vismara et al., 2012). Telepractice also increases access to speech and language services for underserved communities or families who live in areas without sufficient numbers of SLPs to meet their needs (Akemoglu et al., 2020; Fitton et al., 2017; Waite et al., 2010). Despite evidence from several studies suggesting that telepractice is equally effective as in-person services (e.g., Coufal et al., 2018; Grogan-Johnson, 2013; Lee, 2018; Sutherland et al., 2019), there is limited research examining specific research-based speech sound interventions within the context of telepractice, creating a clinical practice gap between the service delivery models SLPs have access to and what the research has addressed thus far.

This research-to-clinical practice gap was highlighted at the onset of the COVID-19 pandemic, which necessitated a response to the sudden and unexpected shift in available therapeutic resources. SLPs were all but forced to transition their assessment and intervention practices to a telepractice service delivery model without compromising the efficacy and reliability of services (Aggarwal et al., 2020). Similarly, our research team, consisting of researchers, clinical faculty, and graduate student clinicians, was faced with adapting an in-person intervention study to telepractice. Due to the necessity of adhering to public health requirements, we made the informed decision to move forward with an adapted telepractice study through application of the three principles of the EBP framework – research evidence, client and family perspectives, and clinical expertise.

Purpose

The purpose of this Clinical Focus paper is to provide a real-world illustration of the process of applying the EBP framework. To that end, we detail the three individual principles of EBP: research evidence, client and family perspectives, and clinical expertise. Following each review is a discussion of how each principle was applied in a complexity-based speech sound intervention that required adaptation to telepractice (see Table 1). To facilitate the discussion of each EBP principle and its implementation, we first provide a brief description of the adapted intervention.

Table 1.

Applying the Principles of EBP to a Telepractice Complexity-Based Speech Sound Intervention

Principles of Evidence-Based Practice		Speech Sound Intervention Transition to Telepractice
Research-based evidence	Evidence is evaluated for a specific population. Evidence for an intervention approach is well-documented and meets the standards of high-quality experimental design.	Speech sound interventions support the acquisition of new speech sounds in children with speech sound disorders (SSD). The complexity approach is a method of treatment target selection that facilitates speech sound learning. This approach meets the standards of high-quality and credible experimental design, making it a strong candidate for use in a novel service delivery model such as telepractice.
Client/family perspectives	Clinicians provide services within the context of a family’s values, expectations, cultural background; a child’s individual support needs; and build positive collaborative relationships with core family members.	Clinicians consider the family’s environment, cultural background and familiarity with telepractice; access to technology; and the child’s individual strengths to determine optimal telepractice services.
Clinical expertise	Clinicians utilize their expertise to implement clinical outcome measures, individualize therapeutic strategies, and maximize treatment outcomes.	Clinicians may utilize the same or similar methods of data collection in a virtual space and individualize and adapt therapy strategies to telepractice to maximize treatment outcomes.

Telepractice Case Study

The case study presented here was originally conceptualized as an in-person intervention for an on-going speech sound intervention study (Combiths et al., 2022b; Potapova et al., 2022) using complexity-based target selection (see Gierut, 2007; Morrisette et al., 2006). In response to the COVID-19 pandemic and limitations on in-person research and intervention, we adapted a telepractice pilot in collaboration with the San Diego State University Speech-Language Clinic (SDSU-SLC). Herein, we describe this pilot as a case study following the principles of EBP. Participants were three children (ages 4;1, 4;11, and 5;1) enrolled in the SDSU-SLC for concerns with speech sound production. Parents reported no other oral-motor or hearing concerns, consistent with a functional speech sound disorder (SSD; Bernthal et al., 2022; Gierut, 1998). Each received a six-week complexity-based speech sound intervention via telepractice. For all assessment and intervention procedures, families used their own devices and Zoom, a video conferencing software that was compliant with the Health Insurance Portability and Accountability Act (HIPAA). Access to this technology was required by the SDSU-SLC and additional technological support was provided as needed over the course of the intervention. This study was approved by the SDSU Institutional Review Board. Participants’ parents provided informed consent for the study, and participants provided assent for each session.

Research Evidence

The EBP principle of research evidence establishes that interventions designed to support individuals of a specific population have a foundation of high-quality and credible evidence (Baker & McLeod, 2011a). Reliable research evidence demonstrated that intervention effects have been replicated across multiple studies (Dollaghan, 2007). High-quality evidence is obtained from research designs that limit subjective bias and include well-defined methods (Mullen, 2007). Evaluation of the limitations of research evidence based on any of the above factors is an important step in determining whether an intervention is appropriate for an individual client. In the following sections, we will describe and evaluate the evidence base for the complexity approach to target selection as well as strategies for speech sound intervention.

Complexity-Based Target Selection

Evidence from a large number of studies support a complexity-based phonological approach to target selection in speech sound intervention (Maggu et al., 2021). Gierut (2005) proposed that efficacious treatment for SSD may be considered through two distinct mechanisms: what to teach, and how to teach. The complexity approach is a method of determining what to teach a child with a SSD, such that a carefully selected treatment target will facilitate growth in a child’s phonological system in the most effective and efficient manner. This approach involves direct treatment on complex sound structures, such as consonant clusters, to facilitate widespread change in a child’s sound system (Barlow, 2004).

Replicability and reliability of treatment effects across multiple studies is a marker of high-quality research evidence. In support of the complexity-based target selection approach, a meta-analysis by Maggu et al. (2021) revealed that all included studies (n = 12) demonstrated effectiveness in improving treated complex sounds and untreated simple sounds. This effect has been replicated consistently over time (Gierut, et al., 1987, 1996; Gierut & Morrisette, 2012; Kamhi, 2006; Maggu et al., 2021; Powell et al., 1991; Rvachew & Nowak, 2001). Therefore, the research evidence suggests that the complexity-based approach is likely to effect positive change in clinical settings as well.

In a review of the evidence for the complexity approach, Baker and McLeod (2011a) found a total of 16 empirical studies met moderate levels of evidence quality in research design, designated by the authors as a controlled study without randomization, or quasi-experimental (e.g., multiple baseline design). Such designs provide adequate amounts of control over outside factors that could conflate results. Additionally, many of the studies reviewed by Baker and McLeod (2011a) were conducted with clinically relevant methods that more closely resemble a real-world clinical context rather than a sterile laboratory setting. The lack of environmental control of such research designs introduces confounding variables (i.e., differences across client experiences) that could limit overall positive effects of the complexity approach. However, the limitations of this type of research design is potentially superseded by their applicability in similar clinic or school settings in an effort to close the research-to-clinical practice gap (Douglas & Burshnic, 2019).

The complexity approach includes systematic target selection of a phonologically complex target sound, with each step clearly defined in the literature (Gierut, 2007; Storkel, 2018). Complex target selection is designed to promote widespread change across a child’s entire sound system. Evidence has shown that a linguistically complex target maximizes phonological change in a child’s sound system, suggesting that the complexity approach is not only effective, but may be more efficient than other intervention methods (Gierut, 1998). Sound target selection that maximizes phonological learning has been found to be most effective when based on the following criteria: treatment of sounds that children produced in error consistently (i.e., with low or 0% accuracy); application of implicational universals (i.e., sounds with more complex features generalize to less complex sounds); later-acquired sounds relative to the normative age of acquisition; and least knowledge, or non-stimulability, of a sound (Gierut, 2001; Miccio & Ingrisano, 2000; Powell et al., 1991). The steps involved in a complexity approach to target selection are presented in detail in Storkel (2018). Broadly, establishing appropriate complex sound targets for individual clients requires SLPs to adequately assess phoneme production accuracy, apply the previously stated criteria, and select an appropriate target (Combiths et al., 2022a; Storkel, 2018). In sum, the existing complexity-based target selection research evidence establishes a clear and well-defined method for clinicians to follow.

The evidence base for the complexity approach is represented by quality single-subject research design, numerous replications, and well-defined methods and measures that lend support for applicability in a virtual service delivery environment (Baker & McLeod, 2011a; Maggu et al., 2021). Effectively, the process of appropriate target selection using the complexity approach may remain the same when delivered via telepractice, as stimulus items can be shown remotely, and a child’s production of sounds and movement of their articulators can still be assessed. The complexity approach also has the potential to be reliable in telepractice delivery, as sound targets available for intervention are not limited by the telepractice environment. Once the research evidence for the complexity approach has been collected and evaluated, clinicians may then begin speech sound intervention on the selected complex target sound. In the following section, we examine the research-based elements of effective speech sound interventions.

Strategies in Speech Sound Intervention

Intervention for SSDs aims to increase a child’s knowledge of their speech sound system. Within the EBP model, treatment target selection, or what to teach a child with a SSD, is supported by research evidence. Speech sound intervention strategies that detail how to teach a child a target sound are also supported by evidence. Intervention approaches for SSDs have an abundant and diverse research base (Baker & Mcleod, 2011a), and specific features related to a successful approach have been identified across most or all of them. Importantly, articulation of speech sounds through motor planning and execution and phonological knowledge of the underlying linguistic framework are interdependent mechanisms, and when used in conjunction can facilitate greater effectiveness and efficiency in learning of new speech sounds (Gierut, 2005). The research evidence for elements of best practice in providing speech sound intervention can be evaluated and implemented in conjunction with the complexity approach for target selection and are presented here (Baker et al., 2018).

The features of traditional treatment for SSDs include repeated practice across levels of linguistic complexity and production contexts, individualized feedback and cueing, motor learning of speech sounds, and intervention intensity, all of which are grounded in previous literature (Shriberg & Kwiatkowski, 1982). Repeated production attempts provide important practice and feedback opportunities for children with SSDs. Multiple forms of instruction, such as spoken, visual, tactile, and/or gestural cues that support the child’s production of the target sound can also be individualized. Feedback on the accuracy or performance of sound productions can be provided qualitatively by the clinician, with progression to self-monitoring by the child. Motor learning of new speech sounds is most effective when provided in three successive phases: articulatory placement instruction and production in isolation and at syllable-level, repeated practice of the target sound in randomized contexts across response length and cueing modality, and generalization to naturalistic, conversational opportunities (Skelton, 2004; Taps Richard, 2009). Finally, intervention intensity refers to the frequency, manner, and duration of sessions targeting a measurable goal (Baker, 2012).

As these research-based features of speech sound intervention are evaluated, it becomes clear that their carryover to telepractice should be considered in order for the intervention to be maximally effective. Modifications of in-person elicitation strategies may be needed to be used effectively with telepractice. However, such changes do not alter the fundamental qualities of these strategies, such as the ability to facilitate more accurate articulatory placement, phonological awareness, and frequent practice opportunities. Therefore, implications of high-quality research may be extended into telepractice. Indeed, Grogan-Johnson et al. (2013) found that SLPs used the same types of cues across in-person and telepractice service delivery models in a traditional, specific sound remediation approach with children in both groups making similar amounts of progress.

While it is important to acknowledge the differences in delivery for these clinical sound elicitation tools when provided via telepractice, their efficacy has the potential to remain consistent regardless of intervention modality. Overall, the complexity approach has several features that make its implementation via telepractice reliable and effective, including clear and detailed steps of assessment, well-documented evidence supporting the complexity approach as an effective intervention for SSDs, and ease of adaptation to digital assessment and intervention procedures. This research evidence will be discussed in the following section as it applies to the current telepractice case study.

Application of Research Evidence to the Telepractice Case Study

Based on the procedures outlined for the complexity approach (Storkel, 2018), each child’s sound system was assessed using a picture-based single-word elicitation probe, the Little PEEP (Barlow, 2012). The Little PEEP can be presented in a digital format, accessed for free at SLPath.com (Taps Richard, n.d.), and was presented in PowerPoint using the screenshare function over Zoom. Children were prompted to name each picture, and their productions were phonetically transcribed by the administering clinician and analyzed using Phon software (version 2.2; Rose & Hedlund, 2017). Throughout the assessment, it was important to ensure that the child’s face and articulators during production could be evaluated through proper positioning of the camera. Each family designated a personal device available to them (i.e., tablet, laptop, or desktop computer) for each session. Prior to the session, caregivers assisted with orienting the camera such that clinicians were able to reliably capture speech sound productions. Each participant was assessed two times (i.e., once with the full 300+ item probe, once with an individualized probe targeting speech sounds produced with low accuracy on the initial probe) to establish baseline levels of low-accuracy sounds. All three children were able to complete this task with minimal environmental support from their caregiver (e.g., verbal reminders to stay on task, occasional assistance with device positioning, etc.). Participant demographics and phonological performance prior to intervention are detailed in Table 2.

Table 2.

Participants’ Phonological Performance Prior to Intervention.

Participant	Age	PCC	Monitored Sounds	Monitored Sound Accuracy
Child 1	4;11	49.5%	k, g, θ, ð, s, z, ŋ, pl, pɹ, bɹ, kl, kɹ, gl, ɡɹ, fl, fɹ, vɹ, θɹ, sp, spl, spɹ, st, stɹ, sk, skɹ, skw, sl, sw, ps, bz, ts, js, θs, st, sj, mps, mz, nz, ŋks, lps, lts, lk, lks, lz, ɹts, ɹk, ɹs, ɹz, ɹʧ	23.2%
Child 2	4;1	58.6%	θ, ð , l, ɹ, pl, pɹ, bl, bɹ, tɹ, tw, dɹ, ɡɹ, fl, fɹ, vɹ, θɹ, sp, spl, spɹ, stɹ, sk, skɹ, skw, sm, sw, ʃɹ, θs, ld, lks, ɹs, ɹm	10.7%
Child 3	5;1	42.6%	θ, ð, s, ʧ, l, pl, pɹ, bl, bɹ, bj, tɹ, tw, dɹ, kl, kɹ, kw, ɡl, ɡɹ, fl, fɹ, vɹ, θɹ, sp, spl, spɹ, st, stɹ, sk, skɹ, skw, sm, sn, sl, sw, ʃɹ,ps, bz, ts, ks, fs, θs, st, sk, mp, mps, mz, nt, nd, ŋk, ŋks, lps, lts, ld, lks, lz, ɹt, ɹts, ɹd, ɹɡ	22.8%

Note: PCC = Percent consonants correct. Monitored sounds are consonants and consonant clusters that a child produced with less than 34% accuracy across two baseline sessions. Accuracy is calculated across all monitored sounds.

Individualized treatment targets (Table 3) were selected based on the principles of the complexity-based approach detailed previously. A total of six target words with the preselected target sound was presented as a representative picture within digital games (e.g., matching games, board games, bingo, etc.), and stories. Overall, implementing the target selection procedures outlined in the research evidence using a telepractice model required minimal adjustments that primarily reflected technology use and proficiency, rather than a need to deviate from the features relevant to the complexity approach itself.

Table 3.

Participants’ Individualized Treatment Sound Targets

Participant	Complex Sound Target	Example words	Productions per Session
			M	Range
Child 1	Word-final /-lz/	falls, pulls, yells	108	78—135
Child 2	Word-initial /spl-/	splice, splatter, splay	103	72—144
Child 3	Word-final /-ks/	packs, picks, knocks	107	67—159

The research evidence surrounding how to teach speech sounds (Gierut, 2005) were evaluated before and throughout the telepractice intervention. Emphasis on repeated production opportunities, receptive awareness activities, multimodal cues, and motor learning strategies facilitated learning of speech sounds through both articulatory and phonological mechanisms. Similar to the assessment and target selection processes, the telepractice environment only required presentation of these intervention strategies virtually without changes to their fundamental qualities. Treatment targets and materials were embedded within a variety of digital formats, using widely available presentation software as a simple method of providing visuals for sound target drills and drill play, self-feedback, motivational charts, and other materials. Embedding intervention stimuli within games and stories offered children frequent opportunities to become familiar with their target words, facilitated spontaneous productions during later sessions, and supported children with reaching a high number of target attempts in each session (Shriberg & Kwiatkowski, 1982). Table 3 lists each child’s individual sound target and examples of words used in intervention to practice their target.

All children received intervention intensity of three individual 35- to 45-minute sessions each week. Sessions were provided by a graduate student clinician, and supervised by an SLP licensed by the state of California and certified by the American Speech-Language-Hearing Association (ASHA). Treatment targets were elicited with a goal minimum of 100 times per session to ensure sufficient repetition for novel articulatory learning (Baker, 2012). While our research team began this intervention using a foundation of essential research-based elements of speech sound intervention, far more adjustments and adaptations were required based on individual client and family support needs due to the virtual environment. These adjustments and integration of client and family perspectives into the overall EBP process are discussed in the following section.

Client and Family Perspectives

The second principle in EBP, client and family perspectives, refers to consideration of the child and their primary caregivers’ individual values, priorities, expectations, and unique personal and cultural circumstances (ASHA (n.d.b)). The World Health Organization (WHO) designates environmental and personal factors as critical considerations for understanding the holistic context of an individual child’s disability, within the framework of the International Classification of Functioning, Disability and Health: Children and Youth version (ICF-CY; 2007). The ICF-CY specifies that understanding a child’s family and close community network, as well as their personal circumstances, are critical to developing successful intervention or support strategies for children with SSDs (Kearney et al., 2015, McLeod & McCormack, 2007). In addition, recent research has highlighted a need for outcome measures that capture social validity and caregiver perspectives of speech and language services (Olszewski & Rae, 2021; Fitton et al., 2017; Porter et al., 2020). Overall, successful implementation of this principle of EBP calls for SLPs to be trained in cultural competency and humility, engage in high-quality communication with caregivers, and individualize treatment practices to reflect family needs and circumstances.

Client and family considerations for telepractice are acknowledged and established by ASHA (n.d.b). Existing evidence points to the following key components: children demonstrate individual physical, cognitive, behavioral, and communication support needs and resources that should be considered when determining the appropriateness of telepractice for assessment and intervention (ASHA (n.d.a); Law et al., 2021). As it is used today, telepractice is often delivered in a client’s, student’s, or patient’s home environment. According to ASHA (n.d.a), telepractice is ideal when it ensures the “comfort, safety, confidentiality, and privacy of clients” and emphasizes the importance of selecting a location that is quiet with minimal visual distractions. The success of telepractice in the home is, therefore, impacted by a client’s access to a quiet, safe, private, and minimally distracting space. Access to a secure internet connection and personal device that supports the appropriate teleconferencing platform are additional factors related to a successful telepractice session.

In terms of technological access, according to the American Community Survey Report (U.S. Census Bureau, 2016), 89% of households in the United States own a personal computer (including smartphones) and 81% have an internet subscription, making telepractice a viable option for in-home use for many clients in the United States. Generally, a tablet, laptop, or desktop computer provides sufficient stability and image size to ensure a clear view of the clinician’s and child’s facial or gestural cues, as well as other visual or auditory digital materials provided over a teleconferencing platform. With education and on-call support, families have been shown to highly rate telepractice services even with some technical difficulties (Manning, et al., 2020).

Establishing a strong collaborative relationship between the clinician and caregiver is a recommended practice for service providers of children with communication disorders (Blue-Banning et al., 2004; Duchan & Kovarsky, 2011). According to Freckmann et al. (2017), clinicians report similar levels of rapport with their clients for both in-person and telepractice settings, indicating that telepractice does not decrease the ability of the clinician and caregiver to build a supportive partnership. Integrating a clinician’s expertise in speech-language pathology with a caregiver’s knowledge of their child yields important information for creating individualized care. Outcomes of these merged perspectives include identifying effective motivational and engagement strategies, providing more varied and individualized cues, and problem-solving various aspects of intervention.

Caregiver-based outcome measures that evaluate client and family perspectives provide clinicians with valuable data on how a child is achieving communication success in their daily life. One such measure for children with SSD is the Intelligibility in Context Scale (ICS; McLeod et al., 2012), in which caregivers rate their child’s functional intelligibility across multiple home-based listener contexts. Additionally, measures of intervention acceptability provide information on caregivers’ level of satisfaction with the procedures and clinical care they and their child received. Clinicians may use such measures to individualize care based on the delivery type and setting of provided services. This data allows clinicians to reliably adjust intervention methods, rapport-building strategies, and client education needs to best fit clients and their families. Overall, outcome measures that specifically evaluate client and family perspectives are important for understanding their experience with intervention and its impact on day-to-day life, a critical feature of evidence-based care.

The client and family perspectives principle calls for distinct awareness of the individual support needs and strengths that a client and their family can bring to the EBP process to ensure that all therapeutic services are maximally beneficial. Notably, integration of this principle also occurs alongside research evidence as literature around caregiver involvement and client characteristics expands. The emergence of caregiver-based outcome measures and family involvement frameworks will also serve to inform clinical expertise through new research, experiences, and sources of information.

Application of Client and Family Considerations to the Telepractice Case Study

The client and family considerations employed in the current case study were addressed prior to intervention and continued to evolve as clinicians built rapport with each child and their caregivers. The current case study evaluated client and family perspectives through informal conversation and feedback between clinician and caregiver. Caregivers were also provided with the ICS (McLeod et al., 2012) before and after intervention. All assessment and intervention sessions in the current case study were delivered virtually at a physical location of the family’s choosing. Engagement and motivation were supported individually by each child’s caregiver and clinician throughout the duration of each session. The research team provided our clients and families with additional individualized support for utilizing teleconferencing software, setting up optimal therapeutic environments, and ensuring that families felt comfortable with the procedures and supported in the telepractice intervention. Student clinicians collaborated with the child and their caregiver in creating session materials, including modifying games and activities for drill play. Adapting intervention strategies based on individual participant’s strengths and support needs increased overall rapport and motivation, creating more high-quality opportunities for each child to practice their target sound.

Within the telepractice model, for example, we used screen-sharing to show individualized virtual token boards or manual visual cues over video that set an appropriate pace for each child. These strategies served to maintain motivation and elicit the minimum goal number of productions for each session. At times, children experienced individual circumstances that led to intermittent attention, fatigue, decreased motivation, etc., that resulted in fewer productions in a session than the goal. However, average target sound productions remained above the goal minimum of 100 across all intervention sessions (refer to Table 3), providing meaningful opportunities for practice and meeting clinical goals for overall intervention intensity. We found that, similar to in-person delivery, switching between motivational activities and eliciting productions, as well as modifying individualized cues was mostly fast and effective using telepractice. When applicable, the online environment facilitated easy opportunities to follow each child’s lead in the moment with a preferred motivational activity, such as sharing a specific song or video. In addition, the research team found that appropriate camera angle and positioning and sufficient audio quality optimized virtual learning, which led to a more positive experience for both clinician and child.

In evaluation of client and family practices for the current case study within the EBP framework, our research team found that caregivers could be better supported with resources that provided information on creating optimal environments for their child’s sessions, such as visual handouts or discussing participation options before or after intervention sessions. Family-specific strategies were developed over time, with common themes emerging, including: providing the child with access to a physically supported sitting environment (preferably a table and chair), minimizing distractions (e.g., reducing environmental distractions, having the session in a separate room from the rest of the family, etc.), and communicating expectations of the session (e.g., creating a positive relationship to the child’s “work,” implementing a child-centered reward system, etc.). Any questions or concerns caregivers expressed about setting up the environment were addressed on an individual basis and occurred both during sessions and in follow-up communications after sessions. Ultimately, SLPs integrated client and family perspectives with available research evidence. The following section thus discusses features of clinical expertise that support this integration process as clinicians aim to provide the best possible individualized care.

Clinical Expertise

The third principle of EBP encompasses clinical expertise and expert opinion. This refers to clinicians’ experience-based knowledge, judgment, and critical reasoning developed through training and clinical practice (ASHA (n.d.b)). A clinician’s experience with appropriate evidence-based interventions, children with diverse behavioral profiles, and procedures for outcome measurement are important features of clinical expertise that serve to inform best practice (Baker & McLeod, 2011b). Clinical expertise is typically evaluated on an individual basis. Individual state licensing boards set minimum academic and clinical training standards for practicing SLPs, which vary greatly across the United States. Clinicians can separately apply for certification through the ASHA, a national association with its own training and continuing education requirements. Clinicians’ graduate training, years of experience in the field, and continuing education and/or supplementary training provide opportunities for further knowledge growth. Clinical expertise involves using expert knowledge to adapt research evidence to individual clients and service delivery environments, as well as determine appropriate outcome measures.

As the direct service provider, clinicians are tasked with using their expertise to integrate all of the external and internal (i.e., clinical assessment and progress monitoring data) evidence for a given treatment from beginning to end. Therefore, clinical expertise is a multi-step process that first involves generation of a PICO (patient, intervention, comparison, outcome) question. To answer this question, clinicians may then evaluate the external research evidence and internal evidence and integrate their findings to make the best clinical decision available.

In a real-world clinical context, adapting intervention strategies to better support clients includes continuous adjustment of cues and feedback methods to meet the support needs of an individual, as well as their strengths and difficulties in achieving a given task. Clinicians’ knowledge, resources, and expertise impact the overall positive potential for improved client and caregiver outcomes. Additional skills such as building rapport, embedding intervention techniques into functional contexts, and maintaining positive clinician-client communication practices also have a high impact on overall client and family outcomes (Ebert & Kohnert, 2010). As a key piece of the EBP triad, the weight of clinicians’ expertise should not be understated, but acknowledged as an important mediating factor in the overall success of an intervention. Clinicians are often faced with adjusting their strategy within a session based on a client’s evolving support needs and integrating research evidence for these considerations at a moment’s notice.

In addition to adapting sessions based on clinical experience and individual client profiles, clinicians may also use a variety of outcome measures to assess the validity and success of a research-based intervention for an individual client. Clinical outcome measures provide a more objective description of a client’s progress as a direct result of intervention. For SSDs, clinicians may use measures that include broad phonological generalization data, such as changes in percent consonants correct (PCC; Shriberg et al., 1997), increased accuracy of treated and untreated monitored sounds (following Combiths et al., 2019), or accuracy on the treated target sound. SLPs play an integral role in EBP implementation as they merge clinical expertise with research evidence to determine the most appropriate outcome measures that align with their client’s goals and best reflect their progress.

Application of Clinical Expertise in a Telepractice Case Study

The current case study employed clinical expertise in making critical decisions regarding feasible methods of implementation in the pre-intervention period as well as throughout the intervention as client rapport strengthened and support needs evolved. Treating student clinicians were supervised by licensed and ASHA-certified clinical faculty, who observed all telepractice sessions and provided direct feedback following each session. All students had a minimum of two semesters of graduate academic and clinical training at the start of the telepractice case study. Student clinicians were also required to attend weekly training meetings, led by a supervisor with clinical expertise in treating SSDs to review and provide feedback on intervention strategies. The telepractice setting facilitated use of more verbal and visual cues in comparison to tactile, and individualization of supportive cues occurred across all participants. For example, Child 1 received verbal cues to slow their rate of speech while producing the target word. Across sessions, Child 1 progressed to using the target word correctly within a phrase while self-evaluating their production accuracy. Child 2 benefited from verbal cues for their three-element consonant cluster /spl-/. For example, Child 2 learned to associate each phoneme with a preferred and highly motivating sound or word, such as “sss” for “snake”, “pirate,” and “lollipop.” For both Children 1 and 2, a caregiver was present during sessions to provide support in maintaining attention and problem solving as needed. Child 3 was able to maintain attention and motivation independently from caregiver support, but was provided a visual model for the correct production of the /-lz/ consonant cluster by their caregiver. Providing multimodal cues within the telepractice delivery setting required the most creativity and clinical problem-solving, given that treating clinicians had not yet had the experience of providing articulation cues virtually. Additional research and discussion of how best to elicit the target sounds continued over the course of the intervention, highlighting how clinical expertise intertwined with research evidence and client and family perspectives within the EBP framework. Through continuous communication and feedback with caregivers and the child, clinicians were able to effectively individualize their cues over telepractice to meet each child’s needs in ways that facilitated growth and change during every session. Overall, clinicians were able to continuously evaluate the research evidence (i.e., external evidence) with individual client and family characteristics. Following, clinical outcome data from the telepractice speech sound intervention are presented as internal evidence under the principle of clinical expertise.

Evaluating Intervention Outcomes

Progress monitoring and outcome data provide internal evidence that an intervention is effective and are an essential component of clinical expertise. The research team selected outcome measures based on clinical knowledge of descriptive phonological measures that capture overall change in a child’s sound system. Measures such as PCC and accuracy on monitored sounds before and after intervention provided data on the level of change for each participant. Progress as a result of the complexity-based speech sound intervention was measured and observed in each child’s sound system before and after intervention, providing clinical evidence that this approach via telepractice may be a reliable intervention for children with SSDs. Table 4 displays these measures for each participant at pre- and post- intervention time points.

Table 4.

Phonological Change from Pre- to Post- Intervention

Participant	Speech Sound Probe Accuracy (PCC)		Monitored Sounds Accuracy
	Pre	Post	Pre	Post
Child 1	49.5%	58.2%	23.2%	41.2%
Child 2	58.6%	61.1%	10.7%	17.5%
Child 3	42.6%	46.1%	22.8%	29.8%

Note: PCC = Percent consonants correct. Monitored sounds are consonants and consonant clusters that a child produced with less than 34% accuracy across two baseline sessions. Accuracy is calculated across all monitored sounds.

Results revealed that every participant increased their overall PCC on the speech sound probe in just six weeks of telepractice intervention with Child 1 demonstrating the greatest change. In addition, all participants increased accuracy for monitored sounds, indicating that learning occurred for sounds for which children had the least phonological knowledge (Powell et al., 1991). Accurately capturing this data for each participant was essential for determining the validity and effectiveness of our telepractice adaptation of the complexity-based speech sound intervention. In a clinical context, these measures would allow us to determine the next best step for each child within the EBP framework. The process for evaluating outcomes illustrates how clinical expertise must remain grounded in research evidence while growing into new and changing environments.

Conclusions from the Telepractice Case Study

The principles of EBP – research evidence, client and family perspectives, and clinical expertise – provide guidance on transitioning a traditionally in-person intervention to telepractice as research catches up to clinical practice realities. Adaptations can be considered ethical and efficacious when EBP principles are considered prior to providing services and continuously updated as services progress. In summary, the EBP framework was applied to the current case study in the following ways.

Research evidence was applied through external evaluation of the literature base for clinical intervention practices for children with SSDs. This principle of EBP was implemented by selecting the complexity-based speech sound intervention approach. This approach was applied through the selection of an individualized complex treatment target and clinical speech sound intervention strategies such as embedding the target sound in various linguistic contexts, multimodal cueing, and motor learning. Adherence to the complexity approach for target selection was maintained despite the required adaptations for telepractice. All children in the current case study successfully completed a full speech sound assessment virtually, thereby meeting requirements for establishing an appropriate complex sound target. Presentation of cues, learning materials, and intervention stimuli was also accessible in a virtual format, allowing clinicians to successfully adapt evidence-based clinical strategies to telepractice.

Client and family perspectives were evaluated through consideration of the child, their primary caregivers, and their family and community for individual support needs and personal or environmental considerations, specifically in the context of the child’s communication disorder/s (e.g., SSD). This principle of EBP was implemented in the current case study through continuous dialogue and feedback between clinicians and caregivers at each session, as well as practical adaptations for the telepractice model, such as coaching families in setting up optimal learning environments for their child.

Clinical expertise undergoes constant evolution as clinicians gain more knowledge, judgment, and critical reasoning skills across diverse clinical settings and populations. This principle of EBP was reflected in the telepractice case study as multi-faceted, encompassing clinical skills in adapting intervention strategies to individual children’s support needs as well as evaluating appropriate outcome measures related to progress as a result of intervention. This case study illustrates that clinical expertise cannot remain static as it becomes necessary to grow into new modalities, such as telepractice, to best meet the needs of the populations we serve. The field of speech-language pathology will continue to develop as new information and resources provide better practices for both SLPs and their clients. Together, with application of research evidence and considerations of individual client and family perspectives, it is within SLPs’ capacity to apply the principles of EBP to effectively transition an intervention to a service delivery model with limited evidence, in this case, telepractice.

Limitations and Future Directions

Given the special circumstances of developing this telepractice case study in response to an unexpected shift in service delivery due to the onset of the COVID-19 pandemic, there are limitations worth noting. First, intervention procedures originally designed for in-person implementation were adapted as the research team and clients/families adjusted to telepractice over the course of intervention.Therefore, using EBP principles to identify necessary resources and intervention adaptations before and during telepractice implementation could improve fidelity and consistency across participants.

A second limitation is that minimal information on client and family characteristics relevant to a telepractice setting was gathered, primarily as a result of the sudden shift in availability of in-person services. Additional measures such as a more thorough case history of each child and pre-assessment screening would be beneficial for future telepractice implementation. Such measures would provide important contextual information on a child’s abilities, motivating factors, and family support in a virtual environment. Pre-assessment screening using a caregiver interview could support clinicians in determining whether telepractice is an appropriate service delivery method or how it could be modified to best fit an individual’s needs. Finally, a survey of caregiver perceptions of telepractice prior to implementation would provide detailed information about how familiar caregivers are with the procedures, requirements, and effects of virtual therapy (Fitton et al., 2017).

Finally, the telepractice case study is limited somewhat in ecological and social validity. Social validity determines the significance of intervention procedures and outcomes as meaningful and relevant for individuals and their families (Olszewski & Rae, 2021; Wolff, 1979). Indeed, clinicians in the telepractice case study collaborated with caregivers throughout the intervention with the goal of creating a positive and effective session for each individual child. However, subjective measures evaluating caregivers’ perspectives were collected inconsistently following intervention. Caregiver- and family-reported measures serve to inform the client and family perspectives principle of EBP, making them a valuable clinical resource for increasing the social validity of interventions. For example, measures may include the aforementioned perceptions of intelligibility across listener contexts, or caregiver and child questionnaires regarding the child’s ability to access daily activities and social relationships in a variety of settings.

Functional outcome measures are important tools in evaluating the social validity of service delivery models, such as telepractice. For example, focused surveys with options for open- and closed- ended responses can be modified to provide information about families’ experience with telepractice, increasing clinical awareness of strategies that are successful and meaningful to the individual client. This has important implications for improving the cultural responsiveness and ecological validity of interventions, as clinical expertise continuously evolves to accommodate a changing service delivery landscape. As with research evidence, client and family perspectives are designed to be continuously appraised with clinical expertise in mind, ultimately shaping service procedures to maximize a client’s individual positive outcomes. In a later iteration of this intervention, caregivers were asked to complete a telepractice intervention satisfaction survey (adapted from Little et al., 2018). This measure was implemented upon reflection to increase our understanding of individual families’ perspectives on receiving this specific intervention via telepractice and to assess functional outcomes (Hustad, 2012).

As telepractice speech sound interventions are implemented in additional research or clinical settings, future directions may include applying EBP principles to design and implement an intervention specifically for telepractice delivery. Such a design would benefit from development of procedures and digital materials for virtual screening, assessment, and intervention, while allowing for real-time adaptations guided by the EBP framework. Pre-planning may enhance intervention fidelity, while more flexible characteristics maintained through EBP could contribute to increased overall outcomes and social validity. Additionally, a more direct comparison between service delivery models (i.e., telepractice versus in-person) of this complexity-based speech sound intervention may provide further evidence that the telepractice model is effective in improving outcomes for children with SSD.

Summary

Overall, this telepractice-based speech sound intervention was found to be advantageous in many ways, given the straightforward structure and expectations of intervention and the flexibility afforded to families in accessing telepractice from a time and place that works for them. Moving forward, the EBP framework may support the transition of research-based interventions to novel service delivery models not yet included in the literature. It also provides a construct for considering the effectiveness, efficiency, feasibility, and reliability of an intervention method in such a transition. Continuous evaluation of available technology and implementation methods still necessitates adherence to EBP. However, taking the time to strategically align with these principles serves to improve clinician and client experiences with speech and language services. The current case study illustrates how researchers and clinicians alike may implement the process of EBP to guide intervention adaptations to novel contexts, thereby mitigating the effects of an inherently imperfect design. The research evidence, client and family perspectives, and clinical expertise that optimally serve a client and their family constantly evolve as a function of new information and ever-changing environments and circumstances. In summary, this case study demonstrates that EBP is best used as a dynamic and interconnected process for implementing best practice, rather than a static tool.

Data Availability Statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request.